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Operations ManagementProcesses and Supply ChainsTHIRTEENTH EDITION

Lee J. Krajewski • Manoj K. Malhotra

GLOBAL EDITION

Operations ManagementPROCESSES AND SUPPLY CHAINS

Thirteenth Edition

Global Edition

LEE J. KRAJEWSKIProfessor Emeritus at

The Ohio State University and the University of Notre Dame

MANOJ K. MALHOTRACase Western Reserve University

Harlow, England • London • New York • Boston • San Francisco • Toronto • Sydney • Dubai • Singapore • Hong Kong Tokyo • Seoul • Taipei • New Delhi • Cape Town • Sao Paulo • Mexico City • Madrid • Amsterdam • Munich • Paris • Milan

A01_KRAJ9863_13_GE_FM.indd 1 18/05/21 6:27 PM

Please contact https://support.pearson.com/getsupport/s/contactsupport with any queries on this content. Acknowledgments of third-party content appear on the appropriate page within the text. Pearson Education Limited KAO Two KAO Park Hockham Way Harlow Essex CM17 9SR United Kingdom and Associated Companies throughout the world Visit us on the World Wide Web at: www.pearsonglobaleditions.com © Pearson Education Limited 2022 The rights of Lee J. Krajewski and Manoj K. Malhotra to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. Authorized adaptation from the United States edition, entitled Operations Management: Processes and Supply Chains, 13th edition, ISBN 978-0-136-86093-8, by Lee J. Krajewski and Manoj K. Malhotra, published by Pearson Education © 2022. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without either the prior written permission of the publisher or a license permitting restricted copying in the United Kingdom issued by the Copyright Licensing Agency Ltd, Saffron House, 6–10 Kirby Street, London EC1N 8TS. For information regarding permissions, request forms, and the appropriate contacts within the Pearson Education Global Rights and Permissions department, please visit www.pearsoned.com/permissions/. All trademarks used herein are the property of their respective owners. The use of any trademark in this text does not vest in the author or publisher any trademark ownership rights in such trademarks, nor does the use of such trademarks imply any affiliation with or endorsement of this book by such owners. This eBook is a standalone product and may or may not include all assets that were part of the print version. It also does not provide access to other Pearson digital products like Revel. The publisher reserves the right to remove any material in this eBook at any time. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN 10: 1-292-40986-X ISBN 13: 978-1-292-40986-3 eBook ISBN 13: 978-1-292-40994-8

Typeset in MeliorLTPro-Regular 9 by Integra Software Services Pvt. Ltd. eBook formatted by B2R Technologies Pvt. Ltd.

Dedicated with love to our families.

Judie KrajewskiChristine and Gary; Gabrielle

Selena and Jeff; AlexLori and Dan; Aubrey, Madeline, Amelia, and Marianna

Carrie and Jon; Jordanne, Alaina, and BradleyVirginia and JerryVirginia and Larry

Maya MalhotraJayne and Vivek

PoojaNeha

Santosh and Ramesh MalhotraIndra and Prem Malhotra; Neeti, Neil, Niam, and Nivin Ardeshna;

Deeksha Malhotra and Maniesh JoshiSadhana Malhotra

Leela and Mukund DabholkarAruna and Harsha Dabholkar; Aditee

Mangala and Pradeep Gandhi; Priya and Medha

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4

Brief Contents1 USING OPERATIONS TO CREATE VALUE 21SUPPLEMENT A DECISION MAKING 55

PART 1 Managing Processes 73

2 PROCESS STRATEGY AND ANALYSIS 733 QUALITY AND PERFORMANCE 1234 LEAN SYSTEMS 1635 CAPACITY PLANNING 197SUPPLEMENT B WAITING LINES 2216 CONSTRAINT MANAGEMENT 2397 PROJECT MANAGEMENT 273

PART 2 Managing Customer Demand 313

8 FORECASTING 3139 INVENTORY MANAGEMENT 357SUPPLEMENT C SPECIAL INVENTORY MODELS 40110 OPERATIONS PLANNING AND SCHEDULING 415SUPPLEMENT D LINEAR PROGRAMMING 45111 RESOURCE PLANNING 479

PART 3 Managing Supply Chains 529

12 SUPPLY CHAIN DESIGN 52913 SUPPLY CHAIN LOGISTICS NETWORKS 55714 SUPPLY CHAIN INTEGRATION 58915 SUPPLY CHAIN SUSTAINABILITY 629

Appendix NORMAL DISTRIBUTION 653

Selected References 654

Glossary 661

Name Index 671

Subject Index 675

ONLINE SUPPLEMENTS

SUPPLEMENT E SIMULATION E-1

SUPPLEMENT F FINANCIAL ANALYSIS F-1

SUPPLEMENT G ACCEPTANCE SAMPLING PLANS G-1

SUPPLEMENT H MEASURING OUTPUT RATES H-1

SUPPLEMENT I LEARNING CURVE ANALYSIS I-1

SUPPLEMENT J OPERATIONS SCHEDULING J-1

SUPPLEMENT K LAYOUT K-1

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5

Decision Trees 63Learning Objectives in Review 65 Key Equations 66 Key Terms 66 Solved Problems 66 Problems 68

PART 1 Managing Processes 73

2 PROCESS STRATEGY AND ANALYSIS 73

CVS Pharmacy 73

Process Structure in Services 77Customer-Contact Matrix 77Service Process Structuring 78

Process Structure in Manufacturing 78Product-Process Matrix 78Manufacturing Process Structuring 79Production and Inventory Strategies 80Layout 81

Process Strategy Decisions 81Customer Involvement 81Resource Flexibility 82Capital Intensity 83

Strategic Fit 84Decision Patterns for Service Processes 85Decision Patterns for Manufacturing

Processes 85Gaining Focus 86Managerial Practice 2.1 Plants-Within-a-Plant at Ford

Camacari 86

Strategies for Change 87Process Reengineering 88Process Improvement 88Managerial Challenge Marketing 88Process Analysis 89

Defining, Measuring, and Analyzing the Process 90Flowcharts 91Work Measurement Techniques 92Process Charts 95Data Analysis Tools 96

Redesigning and Managing Process Improvements 101

Questioning and Brainstorming 101Benchmarking 102Implementing 102

Learning Objectives in Review 104 Key Terms 105 Solved Problems 105 Discussion Questions 108 Problems 109 Active Model Exercise 116

Case Custom Molds, Inc. 117Case José’s Authentic Mexican Restaurant 119Video Case Process Strategy and Analysis at Cleveland

Clinic 120

ContentsPreface 11

1 USING OPERATIONS TO CREATE VALUE 21

Apple Inc. 21

Role of Operations in an Organization 23Historical Evolution and Perspectives 24

A Process View 24How Processes Work 25Nested Processes 25Service and Manufacturing Processes 25

A Supply Chain View 27Core Processes 27Support Processes 27Supply Chain Processes 28

Operations Strategy 28Corporate Strategy 29Market Analysis 31

Competitive Priorities and Capabilities 32Managerial Practice 1.1 Zara 33Order Winners and Qualifiers 34Using Competitive Priorities: An Airline Example 35Identifying Gaps Between Competitive Priorities and

Capabilities 35

Trends and Challenges in Operations Management 37Productivity Improvement 37Global Competition 38Ethical, Workforce Diversity, and Environmental

Issues 40

Fourth Industrial Revolution (Industry 4.0) 41The Internet of Things 42Additive Manufacturing 44

Developing Skills for Your Career 46Adding Value with Process Innovation 47

Learning Objectives in Review 48 Key Equations 49 Key Terms 49 Solved Problems 49 Discussion Questions 50 Problems 51

Case Chad’s Creative Concepts 53Video Case Using Operations to Create Value at Crayola 54

SUPPLEMENT A Decision Making 55Break-Even Analysis 55

Evaluating Services or Products 56Evaluating Processes 58

Preference Matrix 59Decision Theory 60

Decision Making Under Certainty 61Decision Making Under Uncertainty 61Decision Making Under Risk 63

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6 CONTENTS

Value Stream Mapping 180Current State Map 180Future State Map 184

Operational Benefits and Implementation Issues 186Organizational Considerations 186Process Considerations 186Inventory and Scheduling 187

Learning Objectives in Review 187 Key Equations 188Key Terms 188 Solved Problems 188 Discussion Questions 191Problems 191

Case Copper Kettle Catering 194Video Case Lean Systems at Autoliv 195

5 CAPACITY PLANNING 1973M 197

Planning Long-Term Capacity 199Measures of Capacity and Utilization 200Economies of Scale 200Diseconomies of Scale 201

Capacity Timing and Sizing Strategies 201Sizing Capacity Cushions 201Timing and Sizing Expansion 202Linking Capacity and Other Decisions 203Managerial Challenge Operations 204

A Systematic Approach to Long-Term Capacity Decisions 204

Step 1: Estimate Capacity Requirements 204Step 2: Identify Gaps 206Step 3: Develop Alternatives 206Step 4: Evaluate the Alternatives 207

Tools for Capacity Planning 208Managerial Practice 5.1 Capacity Planning at

PacifiCorp 208Waiting-Line Models 209Simulation 209Decision Trees 210

Learning Objectives in Review 210 Key Equations 211Key Terms 211 Solved Problems 211 Discussion Questions 213Problems 213Case Fitness Plus, Part A 219Video Case Gate Turnaround at Southwest Airlines 219

SUPPLEMENT B Waiting Lines 221Structure of Waiting-Line Problems 222

Customer Population 222The Service System 223Priority Rule 224Probability Distributions 225Arrival Distribution 225Service Time Distribution 225

Using Waiting-Line Models to Analyze Operations 226Single-Server Model 227Multiple-Server Model 229Little’s Law 230Finite-Source Model 231

Waiting Lines and Simulation 232SimQuick 232

3 QUALITY AND PERFORMANCE 123

Lego 123

Costs of Quality 125Prevention Costs 125Appraisal Costs 126Internal Failure Costs 126External Failure Costs 126Ethical Failure Costs 126

Total Quality Management and Six Sigma 127Total Quality Management 127Managerial Practice 3.1 Improving Quality Through

Employee Involvement at Santa Cruz Guitar Company 129Six Sigma 130

Acceptance Sampling 131Managerial Challenge Accounting 132

Statistical Process Control 132Variation of Outputs 133Control Charts 135Control Charts for Variables 136Control Charts for Attributes 140

Process Capability 143Defining Process Capability 143Using Continuous Improvement to Determine the

Capability of a Process 145

International Quality Documentation Standards and Awards 146

The ISO 9001:2015 Documentation Standards 146Malcolm Baldrige Performance Excellence Program 146

Systems Approach to Total Quality Management 147

Learning Objectives in Review 147 Key Equations 148 Key Terms 149 Solved Problems 149 Discussion Questions 152Problems 152 Active Model Exercise 160Experiential Learning 3.1 Statistical Process Control with a

Coin Catapult 160Video Case Quality at Axon 162

4 LEAN SYSTEMS 163Nike, Inc. 163

Continuous Improvement Using a Lean Systems Approach 166

Managerial Challenge Finance 166

Strategic Characteristics of Lean Systems 168Supply Chain Considerations in Lean Systems 168Process Considerations in Lean Systems 169Managerial Practice 4.1 Alcoa 171Toyota Production System 174

Designing Lean System Layouts 175One Worker, Multiple Machines 176Group Technology 176

The Kanban System 177General Operating Rules 178Determining the Number of Containers 178Other Kanban Signals 180

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CONTENTS 7

Learning Objectives in Review 296 Key Equations 297Key Terms 298 Solved Problems 298 Discussion Questions 302Problems 302 Active Model Exercise 310

Case The Pert Mustang 310Video Case Project Management at Choice Hotels

International 312

PART 2 Managing Customer Demand 313

8 FORECASTING 313Starbucks 313

Managing Demand 315Demand Patterns 315Demand Management Options 316

Key Decisions on Making Forecasts 318Deciding What to Forecast 318Choosing the Type of Forecasting Technique 318Managerial Challenge Information Technology 319

Forecast Error 319Cumulative Sum of Forecast Errors 319Dispersion of Forecast Errors 320Mean Absolute Percent Error 321Computer Support 322

Judgment Methods 322Causal Methods: Linear Regression 323Time-Series Methods 325

Naïve Forecast 325Horizontal Patterns: Estimating the Average 325Trend Patterns: Using Regression 328Seasonal Patterns: Using Seasonal Factors 330Criteria for Selecting Time-Series Methods 332

Big Data and the Forecasting Process 333Big Data 334Managerial Practice 8.1 Big Data and Health Care

Forecasting 335A Typical Forecasting Process 336

Learning Objectives in Review 338 Key Equations 339Key Terms 340 Solved Problems 340 Discussion Questions 344Problems 345Experiential Learning 8.1 Forecasting a Vital Energy

Statistic 353Case Yankee Fork and Hoe Company 354Video Case Forecasting and Supply Chain Management at

Deckers Outdoor Corporation 355

9 INVENTORY MANAGEMENT 357Ford’s Smart Inventory Management System (SIMS) 357

Inventory Trade-Offs 359Pressures for Small Inventories 360Pressures for Large Inventories 360Managerial Challenge Finance 361

Types of Inventory 362Accounting Inventories 362Operational Inventories 363

Inventory Reduction Tactics 365Cycle Inventory 365

Decision Areas for Management 233

Learning Objectives in Review 234 Key Equations 234Key Terms 235 Solved Problem 235 Problems 236

6 CONSTRAINT MANAGEMENT 239Microsoft Corporation 239

Managerial Challenge Marketing 241

The Theory of Constraints 242Key Principles of the TOC 243

Managing Bottlenecks in Service Processes 244Managing Bottlenecks in Manufacturing Processes 245

Identifying Bottlenecks 246Relieving Bottlenecks 247Managerial Practice 6.1 Theory of Constraints (TOC) and

Drum-Buffer-Rope (DBR) at Steelo Limited 248

Applying the Theory of Constraints to Product Mix Decisions 249Managing Constraints in Line Processes 251

Line Balancing 251Rebalancing the Assembly Line 255Managerial Considerations 256

Learning Objectives in Review 256 Key Equations 257Key Terms 257 Solved Problems 257 Discussion Questions 259Problems 259Experiential Learning 6.1 Min-Yo Garment Company 266Video Case Managing Constraints for Caregivers and Patients

at Cleveland Clinic During COVID-19 270

7 PROJECT MANAGEMENT 273Burj Khalifa 273

Defining and Organizing Projects 276Defining the Scope and Objectives of a Project 276Selecting the Project Manager and Team 277Recognizing Organizational Structure 277Managerial Challenge Marketing 278

Constructing Project Networks 278Defining the Work Breakdown Structure 278Diagramming the Network 280Managerial Practice 7.1 Cleveland Clinic 282

Developing the Project Schedule 283Critical Path 283Project Schedule 283Activity Slack 286

Analyzing Cost–Time Trade-Offs 286Cost to Crash 287Minimizing Costs 287

Assessing and Analyzing Risks 290Risk-Management Plans 290Statistical Analysis 291Analyzing Probabilities 292Near-Critical Paths 293Risk Caused by Changing Requirements: Scrum 294

Monitoring and Controlling Projects 295Monitoring Project Status 295Monitoring Project Resources 295Controlling Projects 296

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8 CONTENTS

Safety Stock Inventory 365Anticipation Inventory 365Pipeline Inventory 365

ABC Analysis 366Economic Order Quantity 367

Calculating the EOQ 368Managerial Insights from the EOQ 370

Continuous Review System 371Selecting the Reorder Point When Demand and Lead

Time Are Constant 371Selecting the Reorder Point When Demand Is

Variable and Lead Time Is Constant 372Selecting the Reorder Point When Both Demand and

Lead Time Are Variable 376Systems Based on the Q System 377Calculating Total Q System Costs 377Advantages of the Q System 378

Periodic Review System 378Selecting the Time Between Reviews 379Selecting the Target Inventory Level When Demand

Is Variable and Lead Time Is Constant 380Selecting the Target Inventory Level When Demand

and Lead Time Are Variable 381Calculating Total P System Costs 381Advantages of the P System 381Systems Based on the P System 382Managerial Practice 9.1 Inventory Management at

IKEA 382

Learning Objectives in Review 383 Key Equations 384 Key Terms 385 Solved Problems 386 Discussion Questions 390 Problems 391 Active Model Exercise 396Experiential Learning 9.1 Swift Electronic Supply, Inc. 397Case Parts Emporium 398Video Case Inventory Management at Crayola 400

SUPPLEMENT C Special Inventory Models 401Noninstantaneous Replenishment 401Quantity Discounts 404One-Period Decisions 406

Learning Objectives in Review 409 Key Equations 409 Key Term 409 Solved Problems 410 Problems 412

10 OPERATIONS PLANNING AND SCHEDULING 415

Cooper Tire and Rubber Company 415

Levels in Operations Planning and Scheduling 418Level 1: Sales and Operations Planning 418Level 2: Resource Planning 420Level 3: Scheduling 420

S&OP Supply Options 421Managerial Challenge Human Resources 422

S&OP Strategies 422Chase Strategy 422Level Strategy 422Constraints and Costs 423Sales and Operations Planning as a Process 423

Spreadsheets for Sales and Operations Planning 425Spreadsheets for a Manufacturer 425Spreadsheets for a Service Provider 426

Workforce and Workstation Scheduling 429Workforce Scheduling 429

Managerial Practice 10.1 Scheduling Major League Baseball Umpires 430

Job and Facility Scheduling 433Sequencing Jobs at a Workstation 434Software Support 436

Learning Objectives in Review 437 Key Terms 437 Solved Problems 438 Discussion Questions 441 Problems 441 Active Model Exercise 448

Case Memorial Hospital 448Video Case Sales and Operations Planning at Starwood 450

SUPPLEMENT D Linear Programming 451Characteristics of Linear Programming Models 451Formulating a Linear Programming Model 452Graphic Analysis 454

Plot the Constraints 454Identify the Feasible Region 456Plot the Objective Function Line 457Find the Visual Solution 458Find the Algebraic Solution 459Slack and Surplus Variables 460Sensitivity Analysis 460

Computer Analysis 461Simplex Method 461Computer Output 461

The Transportation Method 464Transportation Method for Sales and Operations

Planning 464

Learning Objectives in Review 468 Key Terms 468 Solved Problems 468 Discussion Questions 471 Problems 471

11 RESOURCE PLANNING 479Philips 479

Material Requirements Planning 481Dependent Demand 481Managerial Challenge Operations 483

Master Production Scheduling 483Developing a Master Production Schedule 484Available-to-Promise Quantities 486Freezing the MPS 487Reconciling the MPS with Sales and Operations

Plans 487

MRP Explosion 487Bill of Materials 487Inventory Record 489Planning Factors 491Outputs from MRP 494MRP and the Environment 497MRP, Core Processes, and Supply Chain

Linkages 498

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CONTENTS 9

Enterprise Resource Planning 499How ERP Systems Are Designed 499Managerial Practice 11.1 ERP Implementation at Valle

del Lili Foundation 500

Resource Planning for Service Providers 501Dependent Demand for Services 501Bill of Resources 502

Learning Objectives in Review 505 Key Terms 506 Solved Problems 506 Discussion Questions 511 Problems 512 Active Model Exercise 523

Case Wolverine, Inc. 524Video Case Resource Planning at Cleveland Clinic 527

PART 3 Managing Supply Chains 529

12 SUPPLY CHAIN DESIGN 529Amazon.com 529

Creating an Effective Supply Chain 531Managerial Challenge Operations 533

Measuring Supply Chain Performance 534Inventory Measures 534Financial Measures 536

Strategic Options for Supply Chain Design 537Efficient Supply Chains 537Responsive Supply Chains 538Designs for Efficient and Responsive Supply

Chains 539Autonomous Supply Chains 540

Mass Customization 541Competitive Advantages 542Supply Chain Design for Mass Customization 542

Outsourcing Processes 543Managerial Practice 12.1 Outsourcing in the Food

Delivery Business 543Outsourcing and Globalization 544Vertical Integration 545Make-or-Buy Decisions 546

Learning Objectives in Review 547 Key Equations 547 Key Terms 548 Solved Problem 548 Discussion Questions 549 Problems 549Experiential Learning 12.1 Sonic Distributors 552Case Brunswick Distribution, Inc. 553Video Case Supply Chain Design at Crayola 555

13 SUPPLY CHAIN LOGISTICSNETWORKS 557

Airbus SAS 557

Factors Affecting Location Decisions 560Dominant Factors in Manufacturing 560Dominant Factors in Services 562Managerial Challenge Human Resources 563

Load–Distance Method 563Distance Measures 564Calculating a Load–Distance Score 564Center of Gravity 565

Break-Even Analysis 567Transportation Method 569

Setting Up the Initial Tableau 569Dummy Plants or Warehouses 569Finding a Solution 570

Geographical Information Systems 571Using a GIS 571Managerial Practice 13.1 Fast-Food Site Selection

Using GIS 572The GIS Method for Locating Multiple

Facilities 573

Warehouse Strategy in Logistics Networks 573Inventory Placement 573Autonomous Warehouse Operations 574

A Systematic Location Selection Process 575

Learning Objectives in Review 576 Key Equations 577 Key Terms 577 Solved Problems 577 Discussion Questions 580 Problems 580 Active Model Exercise 586

Case R.U. Reddie for Location 586Video Case Continental Tire: Pursuing a Winning Plant

Decision 588

14 SUPPLY CHAIN INTEGRATION 589Oasis of the Seas 589

Supply Chain Disruptions 592Causes of Supply Chain Disruptions 592Supply Chain Dynamics 593Integrated Supply Chains 594Managerial Challenge Information Technology 595

Supply Chain Risk Management 596Operational Risks 596Managerial Practice 14.1 Coronavirus and the Supply

Chain: Where Is the Toilet Paper? 597Financial Risks 597Security Risks 598

Cloud Computing and Blockchains 600Cloud Computing 600Blockchains 601

New Service or Product Development Process 604Design 604Analysis 605Development 605Full Launch 605

Supplier Relationship Process 606Sourcing 606Design Collaboration 609Negotiation 609Buying 611Vendor-Managed Inventories 611Key Performance Measures for the Supplier

Relationship Process 612

Order Fulfillment Process 612Customer Demand Planning 612Supply Planning 612Production 612Logistics 613Key Performance Measures for the Order

Fulfillment Process 615

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10 CONTENTS

Customer Relationship Process 615Marketing 615Order Placement 616Customer Service 616Key Performance Measures for the Customer

Relationship Process 617

Learning Objectives in Review 617 Key Equations 618Key Terms 618 Solved Problems 618 Discussion Questions 620Problems 620

Case Wolf Motors 625Video Case Integrating the Supply Chain at Cleveland Clinic 626

15 SUPPLY CHAIN SUSTAINABILITY 629

Coca-Cola 629

The Three Elements of Supply Chain Sustainability 631Reverse Logistics 633

Supply Chain Design for Reverse Logistics 633Managerial Challenge Operations and Logistics 635

Energy Efficiency 635Transportation Distance 635Freight Density 638Transportation Mode 640

Disaster Relief Supply Chains 641Organizing for Disaster Relief 641Managing Disaster Relief Operations 642Managerial Practice 15.1 Using Drones in Disaster

Relief 643

Supply Chain Ethics 644Buyer–Supplier Relationships 644Facility Location 645Inventory Management 646

Managing Sustainable Supply Chains 646

Learning Objectives in Review 647 Key Equation 647Key Terms 647 Solved Problems 648 Discussion Questions 649Problems 649Video Case Supply Chain Sustainability at Clif Bar &

Company 651

Appendix NORMAL DISTRIBUTION 653

Selected References 654

Glossary 661

Name Index 671

Subject Index 675

Online SupplementsSupplement E SIMULATION E-1

Supplement F FINANCIAL ANALYSIS F-1

Supplement G ACCEPTANCE SAMPLING PLANS G-1

Supplement H MEASURING OUTPUT RATES H-1

Supplement I LEARNING CURVE ANALYSIS I-1

Supplement J OPERATIONS SCHEDULING J-1

Supplement K LAYOUT K-1

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11

It does not take a genius to know that the world, in particular the business world, is changing. Although the Twelfth Edition was successful at bringing current practice in operations manage-ment, in an easy-to-understand format, to a broad brush of business students, it became clear that much has happened since it was published. We began the Thirteenth Edition by obtaining feedback from instructors, reviewers, practicing managers, and students and diligently wove these inputs into the fabric of each chapter. However, before we could actually start the revision, the COVID-19 coronavirus pandemic struck the world. While it brought economic ruin to hundreds of millions of people worldwide, and death to many across the globe, it afforded an extraordinary opportunity to demonstrate how business operations can respond when an unexpected disaster presents itself. In the Thirteenth Edition you will see many examples of the effects of the corona-virus on business operations and how they were handled. We offer one final thought: If you are a business major taking operations management as a required course but you are not an operations major, we have made a special effort to show you how the principles of operations management will be useful to you regardless of your chosen career path.

New to This EditionVideo Cases—Cleveland Clinic In addition to the existing selection of real-world video cases throughout the text, this edition features the world-renowned Cleveland Clinic, headquartered in Cleveland, Ohio. Cleveland Clinic is a global-leading U.S.-based hospital group whose expertise is in specialized medical care. In addition to its 165-acre campus near downtown Cleveland, it has 11 regional hospitals throughout Northeast Ohio; 5 hospitals in Florida; a hospital in Abu Dhabi, UAE; and facilities in Las Vegas, Nevada, and Toronto, Canada. We have added four videos and cases that demonstrate the outstanding level of operations at Cleveland Clinic and how the coronavirus pandemic has affected them. You will first learn how Cleveland Clinic has addressed process-design challenges in Chapter 2, “Process Strategy and Analysis,” to set the stage. Then, in subsequent chapters, you will see managerial responses to operations issues related to managing constraints in Chapter 6, “Constraint Management,” planning for resources in Chapter 11, “Resource Planning,” and the coordination of supply chain activities and information flows throughout the organization in Chapter 14, “Supply Chain Integration.” It’s the first time we have woven a single organizational focus into the text. After reading the cases and watching the videos, we hope you will agree that such an emphasis provides the opportunity to really appreciate how broad the brush of operations management reaches in supporting the success of world-class organizations.

Chapter Opening Vignettes Each chapter opens with a real-world example of a company addressing the topic of that chapter. In this edition, we have introduced seven new vignettes highlighting the operations at Apple, Lego, Nike, 3M, Starbucks, Oasis of the Seas, and Coca-Cola, Inc.

New Technologies In the Thirteenth Edition, we have taken care to include the latest technologies being used to improve business operations. Here are some of those technologies you can look forward to:

▪▪ Fourth Industrial Revolution (Industry 4.0). Chapter 1, “Using Operations to Create Value,” describes Industry 4.0, which is the ongoing automation of traditional manufacturing and industrial practices using modern smart technology. The discussion categorizes the Industry 4.0 technologies into four groups: Smart Manufacturing, Smart Products, Smart Supply, and Base Technologies.

▪▪ Autonomous Supply Chains. Chapter 12, “Supply Chain Design,” dis-cusses the concept of autonomous supply chains, which is a digital transformation in which the latest in digital technology is used to facilitate and automate decision making up and down the supply chain and thereby transform the way supply chains operate.

Preface

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12 PREFACE

Detailed Chapter-by-Chapter ChangesWe have meticulously revised the text to enhance its readability and update all the references and business examples. Here are the major changes in each chapter.

Chapter 1: Using Operations to Create Value We added a new opening vignette featuring Apple that explains how its superior operations and supply chain capabilities are the reasons for its success. The 10 decision areas of operations management that Apple uses to maximize its operational efficiency and build strategic capabilities provide a nice entrée to the remainder of the text. We added a new section titled “Fourth Industrial Revolution (Industry 4.0),” which defines the four distinct categories of modern technologies: Smart Manufacturing, Smart Products, Smart Supply, and Base Technologies. We also put the Internet of Things (IoT) and additive manufacturing under this umbrella to make a succinct, but comprehensive, overview of modern technologies for improved operations. A new learning objective was added to cover this important material.

PART 1: Managing Processes The first part of the text lays the foundation for why a process view is critical for utilizing operations management as a strategic weapon by showing how to design and manage the internal processes in a firm, regardless of the functional area.

Chapter 2: Process Strategy and Analysis In addition to updating the opening vignette on CVS and the Managerial Practice on Ford Camacari, we added a Managerial Challenge focusing on the vice president of marketing and sales for Templeton’s Packaging Products Division, who must figure out why machine repair requests coming into her department from customers are

▪▪ Autonomous Warehouse Operations. Chapter 13, “Supply Chain Logistics Net-works,” addresses the use of automated guided vehicles, automated mobile robots, and aerial drones in warehouse operations.

▪▪ Blockchains. Chapter 14, “Supply Chain Integration,” defines the concept of block-chain, differentiates it from cloud computing, and shows an example of its use in sup-ply chains.

Managerial Challenges We believe that the principles of operations management are use-ful to managers of all disciplines. To demon-strate, we have added Managerial Challenges to each chapter, starting with Chapter 2, “Pro-cess Strategy and Analysis.” These challenges are realistic scenarios, based on extensive research, that describe meaningful opera-tions decision problems in which managers of various disciplines find themselves taking a leading role. The featured disciplines include accounting, finance, human resources, information systems, logistics, marketing, and opera-tions, and cover both manufacturing and service companies.

Managerial Practices It is important for the understanding of operations management to provide many examples of current practices. In this edition, we have added four new M a n a g e r i a l P r a c t i c e s , r a n g i n g f r o m t h e inventory system at IKEA to the shortage of toilet paper due to the coronavirus pandemic.

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PREFACE 13

experiencing lengthy delays. Finally, a new video case featuring the Cleveland Clinic shows how management used the Six Sigma Improvement Model to resolve a workflow problem involving skilled and licensed staff.

Chapter 3: Quality and Performance We added a new opening vignette describing the precise qual-ity standards of Lego, which produces 36 billion plastic bricks a year with a process that produces only 18 defects per million bricks. We also added a Managerial Challenge involving the corporate controller of Star Industries, who last year initiated a major overhaul of their payroll and customer billing processes and now has to determine if significant improvements were made. We updated the Managerial Practice on Santa Cruz Guitar Company and changed Figure 3.2 to be more consistent with the ISO 9001:2015 terminology.

Chapter 4: Lean Systems We moved this chapter, which was Chapter 6 in the Twelfth Edition, to next in line because the content and techniques strongly support the methods we describe in Chapter 3, “Quality and Performance.” We added a new opening vignette on Nike, Inc., that tells the engaging story of how Nike, Inc., applied the principles of lean systems to its factories and supply chain to become a leader in the industry. We updated the Managerial Practice on Alcoa and completely revamped the illustration of the Kanban system, including a new Figure 4.6 with multiple subparts, eliminating the two-card system and simplifying the discussion. Finally, we added a Managerial Challenge in which the VP of finance for Oak Grove Health System was given the assignment of figuring out how to combat the rising cost of patient care and declining revenues.

Chapter 5: Capacity Planning In keeping with the currency of the topics in the Thirteenth Edition, the new opening vignette on 3M shows how a top-notch company can cope with an unexpected capacity crunch brought on by the coronavirus pandemic. We also added a Managerial Challenge in which the facility manager for Tower Medical Center must determine how to cope with dramatically increased visits to the emergency department and a surge in surgery requests. The Managerial Practice on PacifiCorp was also updated.

Chapter 6: Constraint Management We created a new Managerial Practice on Steelo Limited that illustrates the application of the theory of constraints and the drum-buffer-rope system. A Managerial Challenge was also added that features the marketing manager at Schmidt Industries, who found out that his sales process was a bottleneck to the sales of the company’s winch product. Finally, we added a Video Case on constraint management at the Cleveland Clinic that shows how management analyzed and solved a personal protective equipment (PPE) bottleneck due to the COVID-19 virus pandemic.

Chapter 7: Project Management Cleveland Clinic, a main attraction of the Thirteenth Edition, is featured in a new Managerial Practice that discusses a project to build a new hospital in London, England. Also added to this chapter is a Managerial Challenge that involves the head of the marketing department for a large financial services firm who is tasked with overseeing a project within her department to design and implement a new process to deal with requests for creative ads, innovative communications, printed brochures, new web content, and continual sales support from units all over the company. Finally, we added a section addressing project risk caused by changing requirements. It describes an approach called scrum, which is an “Agile” project management framework that focuses on allowing teams to respond rapidly, efficiently, and effectively to change.

PART 2: Managing Customer Demand The second part of the text shows how to estimate customer demands and satisfy those demands through inventory management, operations planning and scheduling, and resource planning.

Chapter 8: Forecasting We begin this chapter with a new opening vignette describing how Starbucks uses big data for managing demands. We also added a Managerial Challenge featuring a recent information system graduate who was assigned the task of reviewing the forecasting system and software at Kramer Health Clinic because staffing levels of critical employees have been too low due to excessive forecast errors.

Chapter 9: Inventory Management The opening vignette on Ford’s Smart Inventory Management System was revised to include CarStory, which uses predictive analytics to determine how long used vehicles will remain on the lot. We added a new Managerial Practice describing how IKEA manages its large inventories at retail outlets. Finally, a Managerial Challenge presents a scenario in which the chief financial officer (CFO) of Medco, a manufacturer of medical technologies, is concerned about declining return on assets (ROA) and assigns his financial analyst in the corpo-rate office the task of reporting to him how inventory investment can be reduced without affecting the customers of Medco.

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14 PREFACE

Chapter 10: Operations Planning and Scheduling We updated the opening vignette on Cooper Tire and revised the Managerial Practice on umpire scheduling to include the 2019 World Series. We added a Managerial Challenge in which the director of human resources for Redwood Hotel, faced with staffing problems, must find a staffing plan that meets the hotel’s revenue targets.

Chapter 11: Resource Planning We updated the opening vignette on Philips and the Managerial Practice on Valle del Lili Foundation Hospital for recent events. We also added a Managerial Challenge in which the VP of manufacturing and her staff at Rennselar Industries, Inc., an original equipment manufacturer (OEM) of automotive parts, was tasked with recommending changes to the current master production scheduling process and resolving a problem in delivery performance. Finally, there is a new Video Case that reveals how Cleveland Clinic ensures that the required resources are available for the large number of complicated surgeries and procedures performed daily.

PART 3: Managing Supply Chains The third part of the text builds upon the tools for managing pro-cesses and customer demands at the level of the firm and provides the tools and perspectives to man-age the flows of materials, information, and funds between suppliers, the firm, and its customers.

Chapter 12: Supply Chain Design We added a Managerial Challenge in which the supply chain manager of Adorn, a leading manufacturer of women’s apparel, must analyze the supply chain to see how Adorn can get its products to market faster. We simplified the discussion of what a supply chain is by removing the distinction between service supply chains and manufacturing supply chains and instead focusing on the structure of a supply chain with its tiers of suppliers and distribution channels. Finally, we added a new section titled “Autonomous Supply Chains,” which describes the trend toward automating elements of supply chains and the advantages it can have.

Chapter 13: Supply Chain Logistics Networks We added a Managerial Challenge involving the director of human resources for EuroTran AG, a producer of transmissions, steering and axle systems, and driver assistance features for the automobile industry; this director was assigned to a committee analyzing the location for a new plant and finds that she must argue for the inclu-sion of key factors associated with labor climate and quality of life at the potential sites. We also added a major section titled “Warehouse Strategy in Logistics Networks,” in which we discuss inventory placement and autonomous warehouse operations, such as automated guided vehicles, autonomous mobile robots, and aerial drones.

Chapter 14: Supply Chain Integration This chapter underwent a major revision to drive home the importance of supply chain integration. The new opening vignette describes the Oasis of the Seas and the need for an integrated supply chain, especially when faced with unexpected disruptions such as the coronavirus pandemic. We added a Managerial Challenge in which the director of information technology for Crestview Food, Inc., whose stores were experiencing severe stock outages, had to devise a plan to facilitate information exchanges up and down the supply chain. We moved the section on additive manufacturing to Chapter 1, “Using Operations to Create Value,” and moved the section “Supply Chain Risk Management” to just after the section “Supply Chain Disruptions” to reinforce the tactics used to cope with disruptions in supply chains. We added a new Managerial Practice on the coronavirus and its effect on the supply of toilet paper. We also incorporated a major section titled “Cloud Computing and Blockchains,” which provides a thorough discussion of new technologies for integrating supply chains. The concept of a blockchain in a supply chain is explained with examples and two new figures. We discuss how it works, its benefits, and its uses. We also added a discussion question on cloud computing and blockchains. Finally, there is a new Video Case at Cleveland Clinic that shows the advantage of having an integrated supply chain to support the goal of a patient first enterprise in light of the COVID-19 pandemic.

Chapter 15: Supply Chain Sustainability A new opening vignette describes how Coca-Cola has worked on decreasing its water footprint in an industry that uses 69 percent of the world’s fresh-water supply. We also added a Managerial Challenge at Eagle Trucking Company, a transportation company serving the oil and gas, health care, and food industries, in which the CEO has tasked his vice presidents to devise a plan to reduce the company’s carbon footprint. We expanded the section on transportation mode to include a discussion of electric trucks.

Solving Teaching and Learning ChallengesMany students who take the introduction to operations management course have difficulty seeing the relevance of a process view of a business or the concepts of competitive priorities, throughput, and sustainability to their lives and their careers. Teaching can be a challenge when students are not motivated and get little reinforcement in what they have learned. We have found that students get motivated when they study concepts, techniques, and methods that are actually

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PREFACE 15

used in practice, and they get reinforcement when they can apply what they have learned. As for motivation, the Thirteenth Edition has four pillars:

Four Pillars of Motivational Learning

▪▪ Practical. This text is written from a managerial perspective. The Managerial Challenges show how students of any business major can find usefulness in the topics of this text. Further, there are many examples of problems typically experienced in practice and the decision tools used to analyze them. The explanations are intuitive and provide a basis for students to apply the concepts and techniques in practice.

▪▪ Current. The chapter opening vignettes, Managerial Practices, videos, and photos connect the topics covered in the text to present-day practice and issues.

▪▪ Comprehensive. The Thirteenth Edition covers all of the new and traditional topics manag-ers need to know to make their processes competitive weapons in a dynamic environment. Regardless of the functional area, processes are the means to get work done.

▪▪ Understandable. The Thirteenth Edition has numerous diagrams clearly showing the con-cepts or techniques being discussed. We took care to avoid unnecessary jargon. Key terms are defined in the margins of the paragraph where they are used, and key equations are listed at the end of the chapter. Further, each learning objective for a chapter is repeated at the end of the chapter with guidelines for review. All of these features are in the Thirteenth Edition to enhance clarity and make the text much more accessible to students of all majors.

As for reinforcement by applying what they have learned, the Thirteenth Edition provides ample opportunity for students to engage with the content.

Learning by Example

Many students struggle with quantitative problem solving. To help students who have difficulty, in the Thirteenth Edition each technique or interim calculation has an associated example problem in the chapter where it is discussed and a solved problem showing the entire technique for another problem at the end. In each case, the problem and all the steps toward solution are clearly demonstrated.

Developing Critical Problem-Solving Skills

Instructors can use the thought-provoking discus-sion questions in class to spark dialog of various issues and managerial situations. The problems are grouped under learning objectives to make it easier for instructors to assign problems that cover all objectives.

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16 PREFACE

Helping Students Apply Their Skills

Students can test their understanding of the con-tent using cases in two ways. First, the Thirteenth Edition has 14 video cases, 4 of which are new to this edition. Each video case has two parts: a written case describing a problem experienced by a real com-pany, along with several questions asking how the student might resolve the issue at hand, and a video showing the actual setting for the case and discussions with managers regarding the problem. Each format pro-vides a rich environment in which to discuss the topic of the chapter. The second way instructors can engage students is to use any of the 13 written cases in the text. These cases often provide data that students can use with techniques in the text to analyze and resolve an issue.

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PREFACE 17

Working in Teams and Gaining Valuable Decision-Making Experience

Perhaps the most engag-ing and fun activities in the Thirteenth Edition are the experiential learning and active model exercises. There are five time-tested experiential learning exer-cises that require students to form teams for work both in and out of class on exercises that involve them in team-based discussion questions and decisions. Two of these experiences are competitive decision simulations that often gen-erate intense interest in the students. In addition, there are 29 active model spreadsheets that require students to evaluate dif-ferent situations based on problem scenarios. These models are perfect for ask-ing “what if” questions and learning from the results. The Active Models assign-ments are supported by online tools that are avail-able to all students.

All told, the Thirteenth Edition has the elements to support student motivation and reinforce-ment and, along with a host of Instructor Resources, it solves most of the teaching and learning challenges involved in the introduction to operations management course.

Developing Employability SkillsFor students to succeed in a rapidly changing job market, they need to develop a variety of skills. We have identified seven critical skills that recruiters look for in students seeking a career in business. The matrix shows how major elements of the Thirteenth Edition map into those essential skills.

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18 PREFACE

Employability Skills in the 13e

Text Elements CommunicationCritical

Thinking Collaboration

Knowledge Application

and Analysis

Business Ethics

and Social Responsibility

Information Technology

Application and Computing Skills

Data Literacy

Active Model Exercises ✓ ✓ ✓

Cases ✓ ✓ ✓ ✓ ✓

Chapter Opening Vignettes ✓ ✓

Discussion Questions ✓ ✓

Experiential Learning ✓ ✓ ✓ ✓

Managerial Challenges ✓ ✓ ✓

Managerial Practices ✓ ✓

Numerical Examples ✓ ✓

OM Explorer and POM for Windows

Photo Illustrations ✓

Problems ✓ ✓ ✓ ✓

Solved Problems ✓ ✓

Additional Resources

Resources available to instructors and students at

www.pearsonglobal editions.com Features of the Resource

Online Supplements Supplement Sections E through K provide students and instructors with additional content on important topics such as Simulation, Financial Analysis, Acceptance Sampling, Measuring Output Rates, Learning Curve Analysis, Operations Scheduling, and Layout.

OM Explorer This text-specific software consists of Excel worksheets and includes tutors and solvers.

# Tutors provide coaching for more than 60 analytical techniques presented in the text. The tutors also provide additional examples for learning and practice.

# Solvers provide powerful general-purpose routines often encountered in prac-tice. These are great for experiential exercises and homework problems.

POM for Windows An easy-to-use software program that covers over 25 common OM techniques.

Active Models These 29 spreadsheets require students to evaluate different situations based on problem scenarios. They are excellent for doing “what-if” analyses.

SimQuick An Excel spreadsheet (with macros) for building simulation models of processes: waiting lines, supply chains, manufacturing facilities, and project scheduling. SimQuick is easy to learn, easy to use, and flexible in its modeling capability.

SmartDraw Draw diagrams, flowcharts, organization charts, and more in minutes with Smart-Draw’s diagram software. Thousands of included diagram templates and symbols.

Detailed information and additional resources are available at www.pearsonglobaleditions.com.

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PREFACE 19

Acknowledgments

No book is just the work of the authors. We greatly appreciate the assistance and valuable contri-butions by several people who made this edition possible. Thanks to Beverly Amer of Aspenleaf Productions for her efforts in filming and producing the new video segments for this edition. Special thanks are due to Howard Weiss of Temple University, whose expertise in upgrading the software for this book is greatly appreciated.

We would like to thank the people at Pearson, including Lynn Huddon, Manager of Content Strategy; Krista Mastroianni, Product Manager; and Yasmita Hota, Content Producer. We are also indebted to Kathy Smith, Project Manager, and Joanne Boehme, copyeditor at SPi Global. Without their hard work, dedication, and guidance, this book would not have been possible.

We want to give a special thank you to our colleague Larry Ritzman, who has been a coauthor of this text for 32 years. Much of the content, philosophy, and wisdom you see in this edition is due to his hard work. We can only hope that this and future editions of the text will carry on the legacy that he provided with his leadership. In addition, many colleagues at other colleges and universities provided valuable comments and suggestions for this and previous editions. In particular, we gratefully acknowledge Professor Giuliano Marodin at the Moore School of Business at the University of South Carolina and Professor R. L. Shankar at the Weatherhead School of Management for their valuable insights and contributions to the Thirteenth Edition. We also thank the reviewers who provided valuable suggestions and feedback that influenced this Thirteenth Edition: Katrice Malcom Branner, University of North Carolina at Charlotte; Philip Friedman, Concordia University Saint Paul; Navneet Jain, Maine Maritime Academy; Vicky Luo, University of Hartford; Jim Mirabella, Jacksonville University; Asil Oztekin, University of Massachusetts Lowell; Tammy Prater, Alabama State University; Matthew Reindorp, Drexel University; Keivan Sadeghzadeh, University of Massachusetts Dartmouth; Reza Sajjadi, University of Texas at Dallas; Len Samborowski, Nichols College; Hugh Scott, University of North Georgia; and Theresa A. Wells, University of Wisconsin–Eau Claire.

Finally, we thank our families for supporting us during this project, which involved multiple emails, teleconference calls, and long periods of seclusion amidst the coronavirus pandemic. Our wives, Judie and Maya, have provided the love, stability, and encouragement that sustained us while we transformed the Twelfth Edition into the Thirteenth.

Lee J. Krajewski

Manoj K. Malhotra

Global Edition AcknowledgmentsPearson would like to thank the following experts for their work on the Global Edition:

ContributorLakshmi Narasimhan Vedanthachari, Middlesex University London

ReviewersChristian Van Delft, HEC Paris Xin Ma, Monash UniversityAlka Nand, Monash University

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20

About the AuthorsLee J. Krajewski is Professor Emeritus at The Ohio State University and Professor Emeritus at the University of Notre Dame. While at The Ohio State University, he received the University Alumni Distinguished Teaching Award and the College of Business Outstanding Faculty Research Award. He initiated the Center for Excellence in Manufacturing Management and served as its director for four years. Lee also served as Acting Director of the Executive MBA Program, Chairperson of the Department of Management Sciences, and Academic Director of the MBA Program at The Ohio State University. At the University of Notre Dame, he held the William and Cassie Daley Chair in Management. In addition, he received the National President’s Award and the National Award of Merit of the American Production and Inventory Control Society (APICS). He served as president of the Decision Sciences

Institute and was elected a Fellow of the Decision Sciences Institute in 1988. He received the Distinguished Service Award in 2003. Lee has conducted seminars and consulted for firms such as Sany Corporation, Westinghouse Corporation, Franklin Chemical, and BancOhio.

Lee received his PhD from the University of Wisconsin. Over the years, he has designed and taught courses at both graduate and undergraduate levels on topics such as operations strategy, introduction to operations management, operations design, project management, and manufactur-ing planning and control systems.

Lee served as the editor of Decision Sciences, was the founding editor of the Journal of Operations Management, and has served on several editorial boards. Widely published himself, Lee has contributed numerous articles to such journals as Decision Sciences, Journal of Operations Management, Management Science, Production and Operations Management, International Journal of Production Research, Harvard Business Review, and Interfaces, to name just a few. He co-authored papers that won the Best Theoretical/Empirical Paper awards at three national Decision Sciences conferences. He also co-authored two papers that won the Stanley T. Hardy Award for the best paper in operations management. Lee’s areas of specialization include operations strategy, manufacturing planning and control systems, supply chain management, and master production scheduling.

Manoj K. Malhotra is the Dean and Albert J. Weatherhead III Professor of Management at the Weatherhead School of Management, Case Western Reserve University, and a member of the Leadership Cleveland class of 2019. Previously, he served as the Senior Associate Dean of Graduate Programs, Jeff B. Bates Professor, and Chairman of the Management Science Department at the Darla Moore School of Business, University of South Carolina (USC), Columbia. He also served from 2005 to 2017 as the founding director of the Center for Global Supply Chain and Process Management (GSCPM) at the Moore School. He earned an engineering undergraduate degree from the Indian Institute of Technology (IIT), Kanpur, India, in 1983, and a PhD in operations management from The Ohio State University

in 1990. He is a Fellow of the Decision Sciences Institute (DSI), Production and Operations Management Society (POMS), and the American Production and Inventory Management Society (APICS). Manoj has conducted seminars and consulted with firms such as Avaya, BMW, Continental, Cummins Turbo Technologies, Delta Air Lines, John Deere, Metso Paper, Palmetto Health, Sonoco, Verizon, Walmart, and Westinghouse-Toshiba, among others.

Apart from teaching operations management, supply chain management, and global business issues at USC, Manoj has also taught at the Terry School of Business, University of Georgia; Wirtschaftsuniversität Wien in Austria; and the Graduate School of Management at Macquarie University, Australia. His research has thematically focused on the deployment of flexible resources in manufacturing and service firms, on operations and supply chain strategy, and on the interface between operations management and other functional areas of business. His work on these and related issues has been published in the leading refereed journals of the field, such as Decision Sciences, European Journal of Operational Research, Interfaces, Journal of Operations Management, and Production and Operations Management. Manoj has been recognized for his pedagogical and scholarly contributions through several teaching and discipline-wide research awards. He was the recipient of the Michael J. Mungo Outstanding Graduate Teaching Award in 2006, the Carolina Trustee Professor Award in 2014, and the Breakthrough Leadership in Research Award in 2014 from the University of South Carolina. He has been the program chair for international conferences at both the Decision Sciences Institute (DSI) and Production and Operations Management Society (POMS). He also served as the president of POMS in 2017 and continues to serve as a senior editor for that journal.

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21

LEARNING OBJECTIVES After reading this chapter, you should be able to:

1USING OPERATIONS TO CREATE VALUE

Apple Inc.

1.1 Describe the role of operations in an organization and its historical evolution over time.

1.2 Describe the process view of operations in terms of inputs, processes, outputs, information flows, suppliers, and customers.

1.3 Describe the supply chain view of operations in terms of linkages between core and support processes.

1.4 Define an operations strategy and its linkage to corporate strategy and market analysis.

1.5 Identify nine competitive priorities used in operations strategy, and explain how a consistent pattern of decisions can develop organizational capabilities.

1.6 Identify the latest trends in operations management and understand how firms can address the challenges facing operations and supply chain managers in a firm.

1.7 Define the fourth industrial revolution (Industry 4.0) and understand how its embedded technologies and automation are transforming the practice of operations and supply chain management.

1.8 Understand how to develop skills for your career using this textbook.

The brand new Apple Store at Central World during the first day opening event, Bangkok, Thailand.

Apple Incorporated is the world’s largest multinational technology company: It has over 137,000 employees and 510 retail stores in 25 countries. Robust sales of consumer electronics, computer software, and online

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22 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

services have made it the most valued company in the world, with a market capitalization of $1.953 trillion as of August 12, 2020. Apple’s brand loyalty is legendary, with a cult-like following of customers who often stand in long lines to buy new products when they are launched. Even though its stellar reputation has been built on innovative designs and trendsetting new products like the iPhone, few realize that Apple’s distinctiveness and competitive superiority arise just as strongly, if not more so, from its outstanding manufacturing, operations, and supply chain management practices.

The 10 decision areas of operations management that Apple measures to maximize its operational efficiency and build strategic capabilities are (i) design of goods and services, (ii) quality management, (iii) process and capacity design, (iv) location strategy for stores, (v) layout design and strategy, (vi) job design and human resources, (vii) supply chain management, (viii) inventory management, (ix) scheduling, and (x) maintenance. A dedicated team of senior managers establish and implement a well-calibrated set of metrics that establish different standards, benchmarks, and criteria for productivity in different decision areas.

So, what drives Apple’s operational excellence? It is not any single decision area mentioned above that stands out in particular, but how well operations and supply chain decisions are intertwined into every other decision that the company makes in its fairly well-controlled ecosystem, ranging from product design to component sourcing, manufacturing, distribution, and retail store design and location. By focusing on a narrow product line, Apple can make each product in larger volumes and get quantity discounts from suppliers. By investing in advanced component material and manufacturing process technologies, coupled with a superior understanding of the markets, Apple can anticipate customer needs ahead of time and give customers what they want through innovative products that competitors cannot easily copy or reproduce.

Apple’s long-term investments in its processes, supply chains, and human resource practices also make it very resilient in managing its complex multinational supply chains. Even in the midst of the coronavirus pandemic, Foxconn, Apple’s contract manufacturer, was running night shifts at its iPhone factory in Zhengzhou, Henan Province, China. While it will not escape completely unscathed, Apple has built contingency plans and managed disruptions in its supply chains better than many of its competitors. Its launch of potential new products like iPhone 12, Apple TV, and an Apple Watch will not occur within the usual time frame of September 2020, but are on track to show up a few weeks later. Despite store closures and inventory shortages, Apple reported on July 30, 2020, that its revenue was the highest that the company has ever reported in its third quarter, up 11 percent year-over-year. And so the juggernaut continues, powered by its vaunted world-class skills and capabilities in operations and supply chain management.1

1Sources: Christine Rowland, “Apple Inc. Operations Management: 10 Decisions, Productivity,” Panmore Institute (February 19, 2019), http://panmore.com/apple-inc-operations-management-10-decisions-areas- productivity (August 10, 2020); Jonny Evans, “Apple’s Operations Teams Must Be Struggling to Pull Things Together,” Computerworld (March 2, 2020), https://www.computerworld.com/article/3530037/apples-operations-teams-must-be-struggling-to-pull-things-together.html (August 10, 2020); Kif Leswing, “Apple Posts Blowout Third Quarter, with Sales up 11% Despite Coronavirus Disruptions,” cnbc.com (July 30, 2020), https://www .cnbc.com/2020/07/30/apple-aapl-earnings-q3-2020.html (August 10, 2020); Marty Lativiere, “Operations: Apple’s Secret Sauce?” The Operations Room (November 4, 2011), https://operationsroom.wordpress.com/2011/11/04/operations-apples-secret-sauce/ (August 10, 2010); https://en.wikipedia.org/wiki/Apple_Inc. (August 10, 2020).

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 23

Operations management refers to the systematic design, direction, and control of pro-cesses that transform inputs into services and products for both internal and external customers. As exemplified by Apple, it can be a source of competitive advantage for firms in both service and manufacturing sectors.

This book deals with managing those fundamental activities and processes that organizations use to produce goods and services that people use every day. A process is any activity or group of activities that takes one or more inputs, transforms them, and provides one or more outputs for its customers. For organizational purposes, processes tend to be clustered together into opera-tions. An operation is a group of resources performing all or part of one or more processes. Processes can be linked together to form a supply chain, which is the interrelated series of pro-cesses within a firm and across different firms that produce a service or product to the satisfaction of customers.2 A firm can have multiple supply chains, which vary by the product or service provided. Supply chain management is the synchronization of a firm’s processes with those of its suppliers and customers to match the flow of materials, services, and information with cus-tomer demand. As we will learn throughout this book, all firms have processes and supply chains. Sound operational planning and design of these processes, along with internal and exter-nal coordination within its supply chain, can create wealth and value for a firm’s diverse stakeholders.

Role of Operations in an OrganizationBroadly speaking, operations and supply chain management underlie all departments and functions in a business. Whether you aspire to manage a department or a particular process within it, or you just want to understand how the process you are a part of fits into the overall fabric of the business, you need to understand the principles of operations and supply chain management.

Operations serve as an excellent career path to upper management positions in many orga-nizations. The reason is that operations managers are responsible for key decisions that affect the success of the organization. In manufacturing firms, the head of operations usually holds the title chief operations officer (COO) or vice president of manufacturing (or of production or operations). The corresponding title in a service organization might be COO or vice president (or director) of operations. Reporting to the head of operations are the managers of departments such as customer service, production and inventory control, and quality assurance.

Figure 1.1 shows operations as one of the key functions within an organization. The circular relationships that are shown highlight the importance of the coordination among the three main-line functions of any business: (1) operations, (2) marketing, and (3) finance. Each function is unique and has its own knowledge and skill areas, primary responsibilities, processes, and deci-sion domains. From an external perspective, finance generates resources, capital, and funds from investors and sales of its goods and services in the marketplace. Based on business strategy, the finance and operations functions then decide how to invest these resources and convert them into physical assets and material inputs. Operations subsequently transforms these material and ser-vice inputs into product and service outputs. These outputs must match the characteristics that can be sold in the selected markets by marketing. Marketing is responsible for producing sales revenue of the outputs, which become returns to investors and capital for supporting operations. Functions such as accounting, information systems, human resources, and engineering make the firm complete by providing essential information, services, and other managerial support.

These relationships provide direction for the business as a whole and are aligned to the same strategic intent. It is important to understand the entire circle, and not just the individual functional areas. How well these functions work together determines the effectiveness of the organization. Functions should be integrated and should pursue a common strategy. Success depends on how well they are able to do so. No part of this circle can be dismissed or minimized without loss of effectiveness, and regardless of how departments and functions are individually managed; they are always linked together through processes. Thus, a firm competes not only by offering new services and products, creative marketing, and skillful finance but also through its unique competencies in operations and sound management of core processes.

operations management

The systematic design, direction, and control of processes that transform inputs into services and products for internal, as well as external, customers.

2The terms supply chain and value chain are sometimes used interchangeably.

process

Any activity or group of activities that takes one or more inputs, transforms them, and provides one or more outputs for its customers.

operation

A group of resources performing all or part of one or more processes.

supply chain

An interrelated series of processes within and across firms that pro-duces a service or product to the satisfaction of customers.

supply chain management

The synchronization of a firm’s processes with those of its sup-pliers and customers to match the flow of materials, services, and information with customer demand.

▼ FIGURE 1.1Integration Between Different Functional Areas of a Business

FinanceAcquires financial

resources and capitalfor inputs

OperationsTranslates

materials andservices into

outputs

MarketingGenerates sales

of outputs

Support Functions• Accounting• Information Systems• Human Resources• Engineering

SalesRevenue

Material &Service Inputs

Product &Service Outputs

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24 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Historical Evolution and PerspectivesThe history of modern operations and supply chain management is rich and over 200 years old, even though its practice has been around in one form or another for centuries. James Watt invented the steam engine in 1785. The subsequent establish-ment of railroads facilitated efficient movement of goods throughout Europe, and eventually even in distant colonies such as India. With the invention of the cotton gin in 1794, Eli Whitney introduced the concept of interchangeable parts. It revolution-ized the art of machine-based manufacturing and, coupled with the invention of the steam engine, led to the great industrial revolution in England and the rest of Europe. The textile industry was one of the earliest industries to be mechanized. The industrial revolution gradually spread to the United States and the rest of the world in the 19th century and was accompanied by such great innovations as the internal combustion engine, steam-powered ships, metallurgy of iron making, large-scale production of chemicals, and invention of machine tools, among others. The foundations of modern manufacturing and technological breakthroughs were also inspired

by the creation of a mechanical computer by Charles Babbage in the early part of the 19th cen-tury. He also pioneered the concept of division of labor, which laid the foundation for scientific management of operations and supply chain management that was further improved upon by Frederick Taylor in 1911.

Three other landmark events from the 20th century define the history of operations and sup-ply chain management. First is the invention of the assembly line for the Model T car by Henry Ford in 1909. The era of mass production was born, in which complex products like automobiles could be manufactured in large numbers at affordable prices through repetitive manufacturing. Second, Alfred Sloan in the 1930s introduced the idea of strategic planning for achieving product proliferation and variety, with the newly founded General Motors Corporation offering “a car for every purse and purpose.” Finally, with the publication of the Toyota Production System book in Japanese in 1978, Taiichi Ohno laid the groundwork for removing wasteful activities from an organization, a concept that we explore further in this book while learning about lean systems.

The recent history of operations and supply chains over the past three decades has been steeped in technological advances. The 1980s were characterized by wide availability of computer-aided design (CAD), computer-aided manufacturing (CAM), and automation. Information technology applications started playing an increasingly important role in the 1990s and started connecting the firm with its extended enterprise through Enterprise Resource Planning Systems and outsourced technology hosting for supply chain solutions. Service organizations like Amazon, Federal Express, United Parcel Service (UPS), and Walmart also became sophisticated users of information technology in operations, logistics, and management of supply chains. The new millennium has seen an acceleration of this trend, along with an increased focus on modern smart technologies, sustainability and the natural environment. We cover all these ideas and topical areas in greater detail throughout this book.

A Process ViewYou might wonder why we begin by looking at processes rather than at departments or even the firm. The reason is that a process view of the firm provides a much more relevant picture of the way firms actually work. Departments typically have their own set of objectives, a set of resources with capabilities to achieve those objectives, and managers and employees responsible for perfor-mance. Some processes, such as billing, may be so specific that they are contained wholly within a single department, such as accounting.

The concept of a process, however, can be much broader. A process can have its own set of objectives, involve a workflow that cuts across departmental boundaries, and require resources from several departments. You will see examples throughout this text of companies that discov-ered how to use their processes to gain a competitive advantage. You will notice that the key to success in many organizations is a keen understanding of how their processes work, since an organization is only as effective as its processes. Therefore, operations management is relevant and important for all students, regardless of major, because all departments have processes that must be managed effectively to gain a competitive advantage.

The Ford Motor Company, founded in 1903, produced about 1 million Model T’s in 1921 alone.

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 25

How Processes WorkFigure 1.2 shows how processes work in an organization. Any process has inputs and outputs. Inputs can include a combi-nation of human resources (workers and managers), capital (equipment and facilities), purchased materials and services, land, and energy. The numbered circles represent operations through which services, products, or customers pass and where processes are performed. The arrows represent flows and can cross because one job or customer can have different requirements (and thus a different flow pattern) than the next job or customer.

Processes provide outputs to customers. These outputs may often be services (that can take the form of information) or tangible products. Every process and every person in an organization has customers. Some are external customers, who may be end users or intermediaries (e.g., manufacturers, financial institutions, or retailers) buying the firm’s finished services or products. Others are internal customers, who may be employees in the firm whose process inputs are actually the outputs of earlier processes man-aged within the firm. Either way, processes must be managed with the customer in mind.

In a similar fashion, every process and every person in an organization relies on suppliers. External suppliers may be other businesses or individuals who provide the resources, services, products, and materials for the firm’s short-term and long-term needs. Processes also have internal suppliers, who may be employees or processes that supply important information or materials.

Inputs and outputs vary depending on the service or product provided. For example, inputs at a jewelry store include merchandise, the store building, registers, the jeweler, and customers; outputs to external customers are services and sold merchandise. Inputs to a factory manufactur-ing blue jeans include denim, machines, the plant, workers, managers, and services provided by outside consultants; outputs are clothing and supporting services. The fundamental role of inputs, processes, and customer outputs holds true for processes at all organizations.

Figure 1.2 can represent a whole firm, a department, a small group, or even a single indi-vidual. Each one has inputs and uses processes at various operations to provide outputs. The dashed lines represent two special types of input: participation by customers and information on performance from both internal and external sources. Participation by customers occurs not only when they receive outputs but also when they take an active part in the processes, such as when students participate in a class discussion. Information on performance includes internal reports on customer service or inventory levels and external information from market research, government reports, or telephone calls from suppliers. Managers need all types of information to manage processes most effectively.

Nested ProcessesProcesses can be broken down into subprocesses, which in turn can be broken down further into still more subprocesses. We refer to this concept of a process within a process as a nested process. It may be helpful to separate one part of a process from another for several reasons. One person or one department may be unable to perform all parts of the process, or different parts of the process may require different skills. Some parts of the process may be designed for routine work, whereas other parts may be geared for customized work. The concept of nested processes is illustrated in greater detail in Chapter 2, “Process Strategy and Analysis,” where we reinforce the need to understand and improve activities within a business and each process’s inputs and outputs.

Service and Manufacturing ProcessesTwo major types of processes are (1) service and (2) manufacturing. Service processes pervade the business world and have a prominent place in our discussion of operations management. Manufacturing processes are also important; without them the products we enjoy as part of our daily lives would not exist. In addition, manufacturing gives rise to service opportunities.

Differences Why do we distinguish between service and manufacturing processes? The answer lies at the heart of the design of competitive processes. While Figure 1.3 shows several distinctions between service and manufacturing processes along a continuum, the two key differences that we discuss in detail are (1) the nature of their output and (2) the degree of customer contact. In general, manufacturing processes also have longer response times, they are more capital intensive, and their quality can be measured more easily than those of service processes.

external customers

A customer who is either an end user or an intermediary (e.g., manufacturers, financial institutions, or retailers) buying the firm’s finished services or products.

internal customers

One or more employees or processes that rely on inputs from other employees or processes to perform their work.

external suppliers

The businesses or individuals who provide the resources, services, products, and materials for the firm’s short-term and long-term needs.

internal suppliers

The employees or processes that supply important information or materials to a firm’s processes.

nested process

The concept of a process within a process.

▲ FIGURE 1.2Processes and Operations

External environment

Internal and externalcustomers

Processes andoperations

2

1

4

3

5

Information onperformance

Outputs• Goods• Services

Inputs• Workers• Managers• Equipment• Facilities• Materials• Land• Energy

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26 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Manufacturing processes convert materials into goods that have a physical form we call products. For example, an assembly line produces a 370 Z sports car, and a tailor produces an outfit for the rack of an upscale clothing store. The transformation processes change the materials on one or more of the following dimensions:

1. Physical properties

2. Shape

3. Size (e.g., length, breadth, and height of a rectan-gular block of wood)

4. Surface finish

5. Joining parts and materials

The outputs from manufacturing processes can be produced, stored, and transported in anticipation of future demand.

If a process does not change the properties of materials on at least one of these five dimen-sions, it is considered a service (or nonmanufacturing) process. Service processes tend to produce intangible, perishable outputs. For example, the output from the auto loan process of a bank would be a car loan, and an output of the order fulfillment process of the U.S. Postal Service is the delivery of your letter. The outputs of service processes typically cannot be held in a finished goods inventory to insulate the process from erratic customer demands.

A second key difference between service processes and manufacturing processes is degree of customer contact. Service processes tend to have a higher degree of customer contact. Customers may take an active role in the process itself, as in the case of shopping in a supermarket, or

they may be in close contact with the service provider to communicate specific needs, as in the case of a medical clinic. Manufacturing processes tend to have less customer contact. For example, washing machines are ultimately produced to meet retail forecasts. The process requires little information from the ultimate consumers (you and me), except indirectly through market surveys and market focus groups. Even though the distinction between service and manufacturing processes on the basis of customer contact is not perfect, the important point is that managers must recognize the degree of customer contact required when designing processes.

Similarities At the level of the firm, service providers do not just offer services and manufacturers do not just offer prod-ucts. Patrons of a restaurant expect good service and good food. A customer purchasing a new computer expects a good prod-uct as well as a good warranty, maintenance, replacement, and financial services.

Further, even though service processes do not keep finished goods inventories, they do inventory their inputs. For example, hospitals keep inventories of medical sup-plies and materials needed for day-to-day operations. Some manufacturing processes, in contrast, do not inventory their outputs because they are too costly. Such would be the case with low-volume customized products (e.g., tailored suits) or products with short shelf lives (e.g., daily newspapers).

When you look at what is being done at the process level, it is much easier to see whether the process is pro-viding a service or manufacturing a product. However, this clarity is lost when the whole company is classified as either a manufacturer or a service provider because it often performs both types of processes. For example, the process of cooking a hamburger at a McDonald’s is a manufacturing process because it changes the material’s physical properties (dimension 1), as is the process of assembling the hamburger with the bun (dimension 5). However, most of the other processes visible or invisible to McDonald’s customers are service processes. You can debate whether to call the whole McDonald’s organiza-tion a service provider or a manufacturer, whereas clas-sifications at the process level are much less ambiguous.

▲ FIGURE 1.3Continuum of Characteristics of Manufacturing and Service Processes

• Physical, durable output• Output can be inventoried• Low customer contact• Long response time• Capital intensive• Quality easily measured

More like amanufacturing

process

• Intangible, perishable output• Output cannot be inventoried• High customer contact• Short response time• Labor intensive• Quality not easily measured

More likea serviceprocess

(a) A manufacturing process showing workers on a production line in a factory. (b) A service process showing a hospitable cheerful server helping customers with the menu and taking their orders in a restaurant.

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 27

A Supply Chain ViewMost services or products are produced through a series of interrelated business activities. Each activity in a process should add value to the preceding activities; waste and unnecessary cost should be eliminated. Our process view of a firm is helpful for understanding how services or products are produced and why cross-functional coordination is important, but it does not shed any light on the strategic benefits of the processes. The missing strategic insight is that processes must add value for customers throughout the supply chain. The concept of supply chains rein-forces the link between processes and performance, which includes a firm’s internal processes as well as those of its external customers and suppliers. It also focuses attention on the two main types of processes in the supply chain, namely, (1) core processes and (2) support processes. Figure 1.4 shows the links between the core and support processes in a firm and a firm’s external customers and suppliers within its supply chain.

Core ProcessesA core process is a set of activities that delivers value to external customers. Managers of these processes and their employees interact with external customers and build relationships with them, develop new services and products, interact with external suppliers, and produce the service or product for the external customer. Examples include a hotel’s reservation handling, a new car design for an auto manufacturer, or Web-based purchasing for an online retailer like Amazon.com. Of course, each of the core processes has nested processes within it.

In this text we focus on four core processes:

1. Supplier Relationship Process. Employees in the supplier relationship process select the suppliers of services, materials, and information and facilitate the timely and efficient flow of these items into the firm. Working effectively with suppliers can add significant value to the services or products of the firm. For example, negotiating fair prices, scheduling on-time deliveries, and gaining ideas and insights from critical suppliers are just a few of the ways to create value.

2. New Service/Product Development Process. Employees in the new service/product development process design and develop new services or products. The services or products may be developed to external customer specifications or conceived from inputs received from the market in general.

3. Order Fulfillment Process. The order fulfillment process includes the activities required to produce and deliver the service or product to the external customer.

4. Customer Relationship Process, sometimes referred to as customer relationship management. Employees involved in the customer relationship process identify, attract, and build relation-ships with external customers and facilitate the placement of orders by customers. Traditional functions, such as marketing and sales, may be a part of this process.

core process

A set of activities that delivers value to external customers.

supplier relationship process

A process that selects the sup-pliers of services, materials, and information and facilitates the timely and efficient flow of these items into the firm.

new service/product development process

A process that designs and develops new services or prod-ucts from inputs received from external customer specifications or from the market in general through the customer relationship process.

order fulfillment process

A process that includes the activities required to produce and deliver the service or product to the external customer.

customer relationship process

A process that identifies, attracts, and builds relationships with external customers and facili-tates the placement of orders by customers, sometimes referred to as customer relationship management.

◀ FIGURE 1.4Supply Chain Linkages Showing Work and Information Flows

External customersEx

tern

al s

uppl

iers

Support Processes

Supplierrelationshipprocess

Newservice/productdevelopment

Customerrelationshipprocess

Orderfulfillmentprocess

Support ProcessesA support process provides vital resources and inputs to the core processes and is essential to the management of the business. Processes as such are not just in operations but are found in account-ing, finance, human resources, management information systems, and marketing. The human resources function in an organization provides many support processes, such as recruiting and hiring workers who are needed at different levels of the organization, training the workers for skills and knowledge needed to properly execute their assigned responsibilities, and establishing incen-tive and compensation plans that reward employees for their performance. The legal department

support process

A process that provides vital resources and inputs to the core processes and therefore is essential to the management of the business.

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28 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Activity-based costing Employee benefits Help desks

Asset management Employee compensation IT networks

Billing budget Employee development Payroll

Complaint handling Employee recruiting Records management

Credit management Employee training Research and development

Customer satisfaction Engineering Sales

Data warehousing Environment Security management

Data mining External communications Waste management

Disaster recovery Finance Warranty

TABLE 1.1 | ILLUSTRATIVE BUSINESS PROCESSES OUTSIDE OPERATIONS

Process Description Process Description

Outsourcing Exploring available suppliers for the best options to perform processes in terms of price, quality, delivery time, and environ-mental issues

Customer Service

Providing information to answer questions or resolve problems using automated information services as well as voice- to-voice contact with customers

Warehousing Receiving shipments from suppliers, verifying quality, placing in inventory, and reporting receipt for inventory records

Logistics Selecting transportation mode (train, ship, truck, airplane, or pipeline), scheduling both inbound and outbound shipments, and providing intermediate inventory storage

Sourcing Selecting, certifying, and evaluating suppliers and managing supplier contracts

Cross-docking

Packing of products of incoming shipments so they can be easily sorted more econom-ically at intermediate warehouses for out-going shipments to their final destination

TABLE 1.2 | SUPPLY CHAIN PROCESS EXAMPLES

All of these support processes must be managed to create as much value for the firm and its customers as possible, and are therefore vital to the execution of core processes highlighted in Figure 1.4. Managers of these processes must understand that they cut across the organization, regardless of whether the firm is organized along functional, product, regional, or process lines.

Supply Chain ProcessesSupply chain processes are business processes that have external customers or suppliers. Table 1.2 illustrates some common supply chain processes.

These supply chain processes should be documented and analyzed for improvement, exam-ined for quality improvement and control, and assessed in terms of capacity and bottlenecks. Supply chain processes will be only as good as the processes within the organization that have only internal suppliers and customers. Each process in the chain, from suppliers to customers, must be designed and managed to add value to the work performed.

supply chain processes

Business processes that have external customers or suppliers.

puts in place support processes ensuring that the firm is in compliance with the rules and regula-tions under which the business operates. The accounting function supports processes that track how the firm’s financial resources are being created and allocated over time, while the information systems function is responsible for the movement and processing of data and information needed to make business decisions. Organizational structure throughout the many diverse industries varies, but for the most part, all organizations perform similar business processes. Table 1.1 lists a sample of them that are outside the operations area.

Operations StrategyOperations strategy specifies the means by which operations implements corporate strategy and helps to build a customer-driven firm. It links long-term and short-term operations decisions to corporate strategy and develops the capabilities the firm needs to be competitive. It is at the heart of managing processes and supply chains. A firm’s internal processes are only building blocks:

operations strategy

The means by which operations implements the firm’s corporate strategy and helps to build a customer-driven firm.

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 29

They need to be organized to ultimately be effective in a competitive environment. Operations strategy is the linchpin that brings these processes together to form supply chains that extend beyond the walls of the firm, encompassing suppliers as well as customers. Since customers con-stantly desire change, the firm’s operations strategy must be driven by the needs of its customers.

Developing a customer-driven operations strategy is a process that begins with corporate strat-egy, which, as shown in Figure 1.5, coordinates the firm’s overall goals with its core processes. It determines the markets the firm will serve and the responses the firm will make to changes in the environment. It provides the resources to develop the firm’s core competencies and core processes, and it identifies the strategy the firm will employ in international markets. Based on corporate strategy, a market analysis categorizes the firm’s customers, identifies their needs, and assesses competitors’ strengths. This information is used to develop competitive priorities. These priorities help managers develop the services or products and the processes needed to be competitive in the marketplace. Competitive priorities are important to the design of existing as well as new services or products, the processes that will deliver them, and the operations strategy that will develop the firm’s capabilities to fulfill them. Developing a firm’s operations strategy is a continuous process because the firm’s capabilities to meet the competitive priorities must be periodically checked, and any gaps in performance must be addressed in the operations strategy.

Corporate StrategyCorporate strategy provides an overall direction that serves as the framework for carrying out all the organization’s functions. It specifies the business or businesses the company will pursue, isolates new opportunities and threats in the environment, and identifies growth objectives.

◀ FIGURE 1.5Connection Between Corporate Strategy and Key Operations Management Decisions

Yes

No

PerformanceGap?

Corporate Strategy• Environmental scanning• Core competencies• Core processes• Global strategies Market Analysis

• Market segmentation• Needs assessment

Competitive Priorities• Cost• Quality• Time• Flexibility

New Service/Product Development• Design• Analysis• Development• Full launch

Decisions• Managing processes• Managing supply chains

Operations Strategy

Competitive Capabilities• Current• Needed• Planned

Developing a corporate strategy involves four considerations: (1) environmental scanning: monitoring and adjusting to changes in the business environment, (2) identifying and develop-ing the firm’s core competencies, (3) developing the firm’s core processes, and (4) developing the firm’s global strategies.

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30 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Environmental Scanning The external business environment in which a firm competes changes continually, and an organization needs to adapt to those changes. Adaptation begins with envi-ronmental scanning, the process by which managers monitor trends in the environment (e.g., the industry, the marketplace, and society) for potential opportunities or threats. A crucial reason for environmental scanning is to stay ahead of the competition. Competitors may be gaining an edge by broadening service or product lines, improving quality, or lowering costs. New entrants into the market or competitors that offer substitutes for a firm’s service or product may threaten continued profitability. Other important environmental concerns include economic trends, tech-nological changes, political conditions, social changes (i.e., attitudes toward work), and the avail-ability of vital resources. For example, car manufacturers recognize that dwindling oil reserves will eventually require alternative fuels for their cars. Consequently, they have designed prototype cars that use hydrogen or electric power as supplements to gasoline as a fuel.

Developing Core Competencies Good managerial skill alone cannot overcome environmental changes. Firms succeed by taking advantage of what they do particularly well—that is, the organi-zation’s unique strengths. Core competencies are the unique resources and strengths that an orga-nization’s management considers when formulating strategy. They reflect the collective learning of the organization, especially in how to coordinate processes and integrate technologies. These competencies include the following:

1. Workforce. A well-trained and flexible workforce allows organizations to respond to market needs in a timely fashion. This competency is particularly important in service organizations, where customers come in direct contact with employees.

2. Facilities. Having well-located facilities (offices, stores, and plants) is a primary advantage because of the long lead time needed to build new ones. In addition, flexible facilities that can handle a variety of services or products at different levels of volume provide a competi-tive advantage.

3. Market and Financial Know-How. An organization that can easily attract capital from stock sales, market and distribute its services or products, or differentiate them from similar services or products on the market has a competitive edge.

4. Systems and Technology. Organizations with exper-tise in information systems have an edge in industries that are data intensive, such as banking. Particularly advantageous is expertise in Internet technologies and applications, such as business-to-consumer and business-to-business systems. Having the patents on a new technology is also a big advantage.

Developing Core Processes A firm’s core competencies should drive its core processes: customer relationship, new service or product development, order fulfillment, and supplier relationship. Many companies have all four pro-cesses, whereas others focus on a subset of them to better match their core competencies, since they find it difficult to be good at all four processes and still be competitive. For instance, in the credit card business within the bank-ing industry, some companies primarily specialize in find-ing customers and maintaining relationships with them. American Airlines’ credit card program reaches out and achieves a special affinity with customers through its mar-keting database. In contrast, specialized credit card compa-nies, such as Capital One, focus on service innovation by creating new features and pricing programs. Finally, many companies are taking over the order fulfillment process by managing the processing of credit card transactions and call centers. The important point is that every firm must evaluate its core competencies and choose to focus on those processes that provide it the greatest competitive strength.

Developing Global Strategies Identifying opportunities and threats today requires a global perspective. A global strategy may include buying foreign services or parts, com-bating threats from foreign competitors, or planning ways to enter markets beyond traditional national boundaries. Although warding off threats from global competitors is

core competencies

The unique resources and strengths that an organization’s management considers when formulating strategy.

lead time

The elapsed time between the receipt of a customer order and filling it.

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Capital One Financial Corp. is a U.S.-based bank holding company specializing in credit cards, home loans, auto loans, banking, and savings products.

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 31

necessary, firms should also actively seek to penetrate foreign markets. Two effective global strate-gies are (1) strategic alliances and (2) locating abroad.

One way for a firm to open foreign markets is to create a strategic alliance. A strategic alliance is an agreement with another firm in which each firm maintains its autonomy, while gaining new opportunities. It may take one of two forms. One form of strategic alliance is the collaborative effort, which often arises when one firm has core competencies that another needs but is unwilling (or unable) to duplicate. Such arrangements commonly arise out of buyer–supplier relationships. Another form of strategic alliance is technology licensing in which one company licenses its ser-vice or production methods to another. Licenses may be used to gain access to foreign markets. Such access to foreign and domestic markets can also be gained through forming a joint venture, in which two companies typically pool resources to create a separate business entity. A joint venture is typically more involved and longer lasting than a strategic alliance.

Another way to enter global markets is to locate operations in a foreign country. However, managers must recognize that what works well in their home country might not work well elsewhere. The economic and political environment or customers’ needs may be significantly different. For example, the family-owned chain Jollibee Foods Corporation became the dominant fast-food chain in the Philippines by catering to a local preference for sweet and spicy flavors, which it incorporates into its fried chicken, spaghetti, and burgers. Jollibee’s strengths are its creative marketing programs and an understanding of local tastes; it claims that its burger is similar to the one a Filipino would cook at home. McDonald’s responded by introducing its own Filipino-style spicy burger, but competition is stiff. This example shows that to be suc-cessful, corporate strategies must recognize customs, preferences, and economic conditions in other countries.

Locating abroad is a key decision in the design of supply chains because it affects the flow of materials, information, and employees in support of the firm’s core processes. Chapter 12, “Supply Chain Design,” and Chapter 13, “Supply Chain Logistic Networks,” offer more in-depth discussion of these other implications.

Market AnalysisOne key to successfully formulating a customer-driven operations strategy for both service and manufacturing firms is to understand what the customer wants and how to provide it. A market analysis first divides the firm’s customers into market segments and then identifies the needs of each segment. In this section, we examine the process of market analysis, and we define and discuss the concepts of market segmentation and needs assessment.

Market Segmentation Market segmentation is the process of identifying groups of customers with enough in common to warrant the design and provision of services or products that the group wants and needs. To identify market segments, the analyst must determine the characteristics that clearly differentiate each segment. The company can then develop a sound marketing program and an effective operating strategy to support it. For instance, The Gap, Inc., a major provider of casual clothes, targets teenagers and young adults, while the parents or guardians of infants to 12-year-olds are the primary targets for its GapKids stores. At one time, managers thought of customers as a homogeneous mass market but now realize that two customers may use the same product for different reasons. Identifying the key factors in each market segment is the starting point in devising a customer-driven operations strategy.

Needs Assessment The second step in market analysis is to make a needs assessment, which identifies the needs of each segment and assesses how well competitors are addressing those needs. Each market segment’s needs can be related to the service or product and its supply chain. Market needs should include both the tangible and intangible attributes and features of products and services that a customer desires. Market needs may be grouped as follows:

▪▪ Service or Product Needs. Attributes of the service or product, such as price, quality, and degree of customization.

▪▪ Delivery System Needs. Attributes of the processes and the supporting systems, and resources needed to deliver the service or product, such as availability, convenience, courtesy, safety, accuracy, reliability, delivery speed, and delivery dependability.

▪▪ Volume Needs. Attributes of the demand for the service or product, such as high or low vol-ume, degree of variability in volume, and degree of predictability in volume.

▪▪ Other Needs. Other attributes, such as reputation and number of years in business, after-sale technical support, ability to invest in international financial markets, and competent legal services.

Once it makes this assessment, the firm can incorporate the needs of customers into the design of the service or product and the supply chain that must deliver it. We further discuss these new service and product development-related issues in Chapter 14, “Supply Chain Integration.”

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32 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Competitive Priorities and CapabilitiesA customer-driven operations strategy requires a cross-functional effort by all areas of the firm to understand the needs of the firm’s external customers and to specify the operating capabilities the firm requires to outperform its competitors. Such a strategy also addresses the needs of internal customers because the overall performance of the firm depends upon the performance of its core and supporting processes, which must be coordinated to provide the overall desirable outcome for the external customer.

Competitive priorities are the critical operational dimensions a process or supply chain must possess to satisfy internal or external customers, both now and in the future. Competitive priorities are planned for processes and the supply chain created from them. They must be pres-ent to maintain or build market share or to allow other internal processes to be successful. Not all competitive priorities are critical for a given process; management selects those that are most important. Competitive capabilities are the cost, quality, time, and flexibility dimensions that a process or supply chain actually possesses and is able to deliver. When the capability falls short of the priority attached to it, management must find ways to either close the gap or revise the priority.

We focus on nine broad competitive priorities that fall into the four capability groups of cost, quality, time, and flexibility. Table 1.3 provides definitions and examples of these competitive priorities, as well as how firms achieve them at the process level.

competitive priorities

The critical dimensions that a process or supply chain must possess to satisfy its internal or external customers, both now and in the future.

competitive capabilities

The cost, quality, time, and flex-ibility dimensions that a process or supply chain actually pos-sesses and is able to deliver.

Cost Definition Processes Considerations Example

1. Low-cost operations

Delivering a service or a prod-uct at the lowest possible cost to the satisfaction of external or internal customers of the process or supply chain

To reduce costs, processes must be designed and oper-ated to make them efficient, using rigorous process analysis that addresses workforce, methods, scrap or rework, overhead, and other factors, such as investments in new automated facilities or technologies to lower the cost per unit of the service or product.

Costco achieves low costs by design-ing all processes for efficiency, stacking products on pallets in warehouse-type stores, and negotiating aggressively with their suppliers. Costco can provide low prices to its customers because they have designed operations for low cost.

Quality

2. Top quality Delivering an outstanding ser-vice or product

To deliver top quality, a service process may require a high level of customer contact, and high levels of helpful-ness, courtesy, and availability of servers. It may require superior product features, close tolerances, and greater durability from a manufacturing process.

Rolex is known globally for creating pre-cision timepieces.

3. Consistent quality

Producing services or prod-ucts that meet design specifi-cations on a consistent basis

Processes must be designed and monitored to reduce errors, prevent defects, and achieve similar outcomes over time, regardless of the “level” of quality.

McDonald’s standardizes work meth-ods, staff training processes, and pro-curement of raw materials to achieve the same consistent product and process quality from one store to the next.

Time

4. Delivery speed Quickly filling a customer’s order

Design processes to reduce lead time (elapsed time between the receipt of a customer order and filling it) through keeping backup capacity cushions, storing inventory, and using premier transportation options.

Netflix engineered its customer relation-ship, order fulfillment, and supplier rela-tionship processes to create an integrated Web-based system that allows its cus-tomers to watch multiple episodes of a TV program or movies in rapid succession.

5. On-time delivery Meeting delivery-time prom-ises

Along with processes that reduce lead time, planning processes (forecasting, appointments, order promising, scheduling, and capacity planning) are used to increase percent of customer orders shipped when promised (95% is often a typical goal).

United Parcel Service (UPS) uses its expertise in logistics and warehousing processes to deliver a very large volume of shipments on-time across the globe.

6. Development speed

Quickly introducing a new service or a product

Processes aim to achieve cross-functional integration and involvement of critical external suppliers in the ser-vice or product development process.

Zara is known for its ability to bring fash-ionable clothing designs from the runway to market quickly.

TABLE 1.3 | DEFINITIONS, PROCESS CONSIDERATIONS, AND EXAMPLES OF COMPETITIVE PRIORITIES

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At times, management may emphasize a cluster of competitive priorities together. For example, many companies focus on the com-petitive priorities of delivery speed and devel-opment speed for their processes, a strategy called time-based competition. To implement the strategy, managers carefully define the steps and time needed to deliver a service or produce a product and then critically analyze each step to determine whether they can save time without hurting quality. Zara is an exam-ple of a firm that follows time-based competi-tion. Managerial Practice 1.1 illustrates how Zara used development speed and quick deliv-ery time to carve out a unique and profitable niche for itself in the fast-fashion industry.

To link to corporate strategy, management assigns selected competitive priorities to each process (and the supply chains created from them) that are consistent with the needs of external as well as internal customers. Competitive priorities may change over time. For example, consider a high-volume standardized product, such as color ink-jet desktop printers. In the early stages of the ramp-up period when the printers had just entered the mass market, the manufacturing processes required consistent quality, delivery speed, and volume flexibility. In the later stages of the ramp-up when demand was high, the competitive priorities became low-cost operations, consistent quality, and on-time delivery. Competitive priorities must change and evolve over time along with changing business conditions and customer preferences.

time-based competition

A strategy that focuses on the competitive priorities of delivery speed and development speed.

Flexibility Definition Processes Considerations Example

7. Customization Satisfying the unique needs of each customer by changing service or product designs

Processes with a customization strategy typically have low volume, close customer contact, and an ability to reconfig-ure processes to meet diverse types of customer needs.

Ritz Carlton customizes services to indi-vidual guest preferences.

8. Variety Handling a wide assortment of services or products efficiently

Processes supporting variety must be capable of larger volumes than processes supporting customization. Ser-vices or products are not necessarily unique to specific customers and may have repetitive demands.

Amazon.com uses information technology and streamlined customer relationship and order fulfillment processes to reliably deliver a vast variety of items to its customers.

9. Volume flexibility Accelerating or decelerat-ing the rate of production of services or products quickly to handle large fluctuations in demand

Processes must be designed for excess capacity and excess inventory to handle demand fluctuations that can vary in cycles from days to months. This priority could also be met with a strategy that adjusts capacity without accumulation of inventory or excess capacity.

The United States Post Office (USPS) can have severe demand peak fluctua-tions at large postal facilities where pro-cesses are flexibly designed for receiving, sorting, and dispatching mail to numer-ous branch locations.

M A N A G E R I A L PRACTICE Zara

Zara is a clothing and accessories company that was founded in Galicia, Spain, in 1975. With 2,259 stores located worldwide in 96 countries, Zara has emerged as a leader in the fashion industry that is known for tough operations challenges. The product life cycle is extremely short and hard to forecast. Retailers chronically suffer from steep price discounts for remaining inventory (markdowns) and stockouts. For some retailers, the estimated costs of markdowns can be as high as 33 percent of sales. However, a new trend known as fast fashion is changing the way these fashion brands operate. The Spanish fast-fashion leader Zara is proving to be a tough competition for

U.S. retailers such as Abercrombie & Fitch, American Eagle Outfitters, and Aeropostale. Compared to the 50 to 70 percent average markdown cost of fashion retailers, Zara’s markdowns are only around 15 percent. Fast-fashion companies like Zara focus on competitive priorities of product development speed, which allows them to respond quickly to changing consumer trends without inflating costs. For example, Zara’s Spanish company headquarters, in the small industrial city of Arteixo, took 5 days to design the prototype of a loose-fitting winter coat. Design ideas and market insights were collected from discussions with store managers. Next, pattern makers, cutters, and

1.1

Netflix, an American media-services provider headquartered in Los Gatos, California, USA, has proven to be a major source of entertainment during the coronavirus pandemic due to its rapidly delivered video-on-demand streaming service.

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Order Winners and QualifiersCompetitive priorities focus on what operations can do to help a firm be more competitive and are in response to what the market wants. Another useful way to examine a firm’s ability to be suc-cessful in the marketplace is to identify the order winners and order qualifiers. An order winner is a criterion that customers use to differentiate the services or products of one firm from those of another. Order winners can include price (which is supported by low-cost operations) and other dimensions of quality, time, and flexibility. However, order winners also include criteria not directly related to the firm’s operations, such as after-sale support (Are maintenance service contracts available? Is there a return policy?); technical support (What help do I get if something goes wrong? How knowledgeable are the technicians?); and reputation (How long has this com-pany been in business? Have other customers been satisfied with the service or product?). It may take good performance on a subset of the order-winner criteria, cutting across operational as well as nonoperational criteria, to make a sale.

Order winners are derived from the considerations customers use when deciding which firm to purchase a service or product from in a given market segment. Sometimes customers demand a certain level of demonstrated performance before even contemplating a service or product. Minimal level required from a set of criteria for a firm to do business in a particular market segment is called an order qualifier. Fulfilling the order qualifier will not ensure competitive success; it will only position the firm to compete in the market. From an operations perspective, understand-ing which competitive priorities are order qualifiers and which ones are order winners is important for the investments made in the design and management of processes and supply chains.

Figure 1.6 shows how order winners and qualifiers are related to achieving the competitive priorities of a firm. If a minimum threshold level is not met for an order-qualifying dimension (con-sistent quality, for example) by a firm, then it would get disqualified from even being considered further by its customers. For example, there is a level of quality consistency that is minimally toler-able by customers in the auto industry. When the subcompact car Yugo built by Zastava Corporation could not sustain the minimal level of quality, consistency, and reliability expected by customers, it had to exit the U.S. car market in 1991 despite offering very low prices (order winner) of under $4,000. However, once the firm qualifies by attaining consistent quality beyond the threshold, it

order winner

A criterion customers use to differentiate the services or products of one firm from those of another.

order qualifier

Minimal level required from a set of criteria for a firm to do business in a particular market segment.

First, Zara has all nonvalue-adding activities eliminated from its pro-cesses. Every creative decision is made quickly in an open workspace at Zara’s headquarters. Designers and sales staff hold impromptu communications with Zara store managers around the world, who are often flown in to consult, view a few mockups, and provide additional design ideas. There are no formal meet-ings in this entire process. Second, most other retailers maintain sophisticated distribution networks, which increase the chance of losing track of inventories. In contrast, Zara relies on a centralized distribution system where 60 percent of the production takes place in Spain and nearby countries, and which in turn improves inventory accuracy. Rather than partnering with Asian subcontrac-tors, Zara has built 14 highly automated Spanish factories that produce “gray goods,” the foundations of their final products. These gray goods are then sent to Zara’s partner network of more than 300 small shops in Portugal and Galicia for finishing. This final step is done after Zara becomes confident about the upcoming fashion trends and demand. Zara can also quickly ramp up manu-facturing for popular products and get items to their stores in a matter of days.

The estimated financial benefit of fast fashion to reduce markdowns and stockouts adds up to a profit increase of as much as 28 percent. Zara is four times more profitable than most of its competitors, which is achieved through lower inventory costs. Over the past couple of decades, fashion brands have aggressively experimented with various sourcing and distribution strategies to cut costs and inventories. Zara has been very successful by focusing on what customers want, and how to meet their needs by rapidly developing and bringing new products to the market rather than just empha-sizing inward-looking cost savings in parts of their supply chain. With these efforts paying off, Zara’s parent company Inditex has now become the world’s largest clothing retailer.3

3Sources: Steve Denning, “How Agile and Zara Are Transforming the US Fashion Industry,” Forbes (March 13, 2015); Greg Petro, “The Future of Fashion Retailing: The Zara Approach,” Forbes (Oct. 25, 2012); Patricia Kowsmann, “Fast Fashion: How a Zara Coat Went from Design to Fifth Avenue in 25 Days,” Wall Street Journal (Dec. 6, 2016); https://en.wikipedia.org/wiki/Zara_(retailer), (August 11, 2020).

tailors worked 13 days to produce 8,000 coats. Ironing, labeling, tagging, and quality inspection took another 6 days. The finished coats were trucked in to Zara’s logistics center and exported through the Barcelona airport. The next day, the clothes were displayed at Fifth Avenue stores and sold for $189. Now, Zara introduces new products twice per week to its 1,670 stores around the world. Moreover, it takes only 10 to 15 days from the design to sales. How is Zara able to achieve such surprising results?

Zara store at Singapore Changi Airport, which is the primary civilian airport for Singapore and one of the largest transportation hubs in Southeast Asia.

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may only gain additional sales at a very low rate by investing further in improving that order-qualifying dimension. In contrast, for an order-winning dimension (i.e., low price driven by low-cost operations), a firm can reasonably expect to gain appre-ciably greater sales and market share by continuously lowering its prices as long as the order qualifier (i.e., consis-tent quality) is being adequately met. Toyota Corolla and Honda Civic have successfully followed this route in the marketplace to become leaders in their target market segment.

Order winners and qualifiers are often used in competitive bidding. For example, before a buyer considers a bid, suppliers may be required to document their ability to pro-vide consistent quality as measured by adherence to the design specifications for the service or com-ponent they are supplying (order qualifier). Once qualified, the supplier may eventually be selected by the buyer on the basis of low prices (order winner) and the reputation of the supplier (order winner).

Using Competitive Priorities: An Airline ExampleTo gain a better understanding of how com-panies use competitive priorities, let us look at a major airline. We will consider two mar-ket segments: (1) first-class passengers and (2) coach passengers. Core services for both mar-ket segments are ticketing and seat selection, baggage handling, and transportation to the customer’s destination. The peripheral ser-vices are quite different across the two mar-ket segments. First-class passengers require separate airport lounges; preferred treatment during check-in, boarding, and deplaning; more comfortable seats; better meals and bev-erages; more personal attention (cabin atten-dants who refer to customers by name); more frequent service from attendants; high levels of courtesy; and low volumes of passengers (adding to the feeling of being special). Coach passengers are satisfied with standardized services (no surprises), courteous flight atten-dants, and low prices. Both market segments expect the airline to hold to its schedule. Consequently, we can say that the competitive priorities for the first-class segment are top quality and on-time delivery, whereas the competitive priorities for the coach segment are low-cost operations, consistent quality, and on-time delivery.

The airline knows what its collective capabilities must be as a firm, but how does that get communicated to each of its core processes? Let us focus on the four core processes: (1) customer relationship, (2) new service or product development, (3) order fulfillment, and (4) supplier rela-tionship. Competitive priorities are assigned to each core process to achieve the service required to provide complete customer satisfaction. Table 1.4 shows some possible assignments just to give you an idea of how this works.

Identifying Gaps Between Competitive Priorities and CapabilitiesOperations strategy translates service or product plans and competitive priorities for each market segment into decisions affecting the supply chains that support those market segments. Even if it is not formally stated, the current operations strategy for any firm is really the pattern of decisions that have been made for its processes and supply chains. As we have previously seen in Figure 1.5, corporate strategy provides the umbrella for key operations management decisions that contribute to the development of the firm’s ability to compete successfully in the marketplace. Once manag-ers determine the competitive priorities for a process, it is necessary to assess the competitive capabilities of the process. Any gap between a competitive priority and the capability to achieve that competitive priority must be closed by an effective operations strategy.

▲ FIGURE 1.6Relationship of Order Winners and Order Qualifiers to Competitive Priorities

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Sale

s ($

)

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s ($

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Achievement of competitive priority Achievement of competitive priority

Threshold

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Developing capabilities and closing gaps is the thrust of operations strategy. To demonstrate how this works, suppose the management of a bank’s credit card division decides to embark on a marketing campaign to significantly increase its business, while keeping costs low. A key process in this division is billing and payments. The division receives credit transactions from the mer-chants, pays the merchants, assembles and sends the bills to the credit card holders, and processes payments. The new marketing effort is expected to significantly increase the volume of bills and payments. In assessing the capabilities, the process must have to serve the bank’s customers and to meet the challenges of the new market campaign; management assigns the following competi-tive priorities for the billing and payments process:

▪▪ Low-Cost Operations. It is important to maintain low costs in the processing of the bills because profit margins are tight.

▪▪ Consistent Quality. The process must consistently produce bills, make payments to the mer-chants, and record payments from the credit card holders accurately.

▪▪ Delivery Speed. Merchants want to be paid for the credit purchases quickly.▪▪ Volume Flexibility. The marketing campaign is expected to generate many more transactions

in a shorter period of time.

Management assumed that customers would avoid doing business with a bank that could not produce accurate bills or payments. Consequently, consistent quality is an order qualifier for this process.

CORE PROCESSES

Priority Supplier Relationship New Service Development Order Fulfillment Customer Relationship

Low-Cost Operations Costs of acquiring inputs must be kept to a minimum to allow for competitive pricing.

Airlines compete on price and must keep operating costs in check.

Top Quality New services must be carefully designed because the future of the airline industry depends on them.

High-quality meal and bev-erage service delivered by experienced cabin attendants ensures that the service provided to first-class passen-gers is kept top notch.

High levels of customer con-tact and lounge service for the first-class passengers.

Consistent Quality Quality of the inputs must adhere to the required speci-fications. In addition, informa-tion provided to suppliers must be accurate.

Once the quality level is set, it is important to achieve it every time.

The information and service must be error free.

Delivery Speed Customers want immediate information regarding flight schedules and other ticketing information.

On-Time Delivery Inputs must be delivered to tight schedules.

The airline strives to arrive at destinations on schedule; oth-erwise, passengers might miss connections to other flights.

Development Speed It is important to get to the market fast to preempt the competition.

Customization The process must be able to create unique services.

Variety Many different inputs must be acquired, including main-tenance items, meals, and beverages.

Maintenance operations are required for a variety of air-craft models.

The process must be capable of handling the service needs of all market segments and promotional programs.

Volume Flexibility The process must be able to handle variations in supply quantities efficiently.

TABLE 1.4 | COMPETITIVE PRIORITIES ACROSS DIFFERENT CORE PROCESSES FOR AN AIRLINE

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Is the billing and payment process up to the competitive challenge? Table 1.5 shows how to match capabilities to priorities and uncover any gaps in the credit card division’s operations strategy. The procedure for assessing an operations strategy begins with identifying good measures for each priority. The more quantitative the measures are, the better. Data are gathered for each measure to determine the current capabilities of the process. Gaps are identified by comparing each capability to management’s target values for the measures, and unacceptable gaps are closed by appropriate actions.

The credit card division shows significant gaps in the process’s capability for low-cost opera-tions. Management’s remedy is to redesign the process in ways that reduce costs but will not impair the other competitive priorities. Likewise, for volume flexibility, management realized that a high level of utilization is not conducive for processing quick surges in volumes while maintaining delivery speed. The recommended actions will help build a capability for meeting more volatile demands.

Trends and Challenges in Operations ManagementSeveral trends are currently having a great impact on operations management: productivity improvement; global competition; and ethical, workforce diversity, and environmental issues. In this section, we look at these trends and their challenges for operations managers.

Productivity ImprovementProductivity is a basic measure of performance for economies, industries, firms, and processes. Improving productivity is a major trend in operations management because all firms face pres-sures to improve their processes and supply chains so as to compete with their domestic and foreign competitors. Productivity is the value of outputs (services and products) produced divided by the values of input resources (wages, cost of equipment, etc.) used:

Productivity =Output

Input

Manufacturing employment peaked at just below 20 million in mid-1979, and shrank by nearly 8 million from 1979 to 2011.4 However, the manufacturing productivity in the United States has climbed steadily, as more manufacturing capacity and output has been achieved effi-ciently with a leaner workforce. It is interesting and even surprising to compare productivity improvements in the service and manufacturing sectors. In the United States, employment in the service sector has grown rapidly, outstripping the manufacturing sector. It now employs about 90 percent of the workforce. But service-sector productivity gains have been much lower. If productivity growth in the service sector stagnates, so does the overall standard of living regard-less of which part of the world you live in. Other major industrial countries, such as Japan and Germany, are experiencing the same problem. Yet signs of improvement are appearing. The surge of investment across national boundaries can stimulate productivity gains by exposing firms to

productivity

The value of outputs (services and products) produced divided by the values of input resources (wages, costs of equipment, etc.).

4Paul Wiseman, “Despite China’s Might, US Factories Maintain Edge,” The State and The Associated Press (January 31, 2011).

Competitive Priority Measure Capability Gap Action

Low-cost operations ▪▪ Cost per billing statement▪▪ Weekly postage

▪▪ $0.0813▪▪ $17,000

▪▪ Target is $0.06▪▪ Target is $14,000

▪▪ Eliminate microfilming and storage of billing statements

▪▪ Develop Web-based process for posting bills

Consistent quality ▪▪ Percent errors in bill information

▪▪ Percent errors in posting payments

▪▪ 90%▪▪ 74%

▪▪ Acceptable▪▪ Acceptable

▪▪ No action▪▪ No action

Delivery speed ▪▪ Lead time to process merchant payments

▪▪ 48 hours ▪▪ Acceptable ▪▪ No action

Volume flexibility ▪▪ Utilization ▪▪ 98% ▪▪ Too high to support rapid increase in volumes

▪▪ Acquire temporary employees▪▪ Improve work methods

TABLE 1.5 | OPERATIONS STRATEGY ASSESSMENT OF THE BILLING AND PAYMENT PROCESS

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greater competition. Increased investment in information technology by service providers also increases productivity.

Measuring Productivity As a manager, how do you measure the productivity of your processes? Many measures are available. For example, value of output can be measured by what the customer pays or simply by the number of units produced or customers served. The value of inputs can be judged by their cost or simply by the number of hours worked.

Managers usually pick several reasonable measures and monitor trends to spot areas needing improvement. For example, a manager at an insurance firm might measure office productivity as the number of insurance policies processed per employee per week. A manager at a carpet company might measure the productivity of installers as the number of square yards of carpet installed per hour. Both measures reflect labor productivity, which is an index of the output per person or per hour worked. Similar measures may be used for machine productivity, where the denominator is the number of machines. Accounting for several inputs simultaneously is also possible. Multifactor productivity is an index of the output provided by more than one of the resources used in production; it may be the value of the output divided by the sum of labor, materials, and overhead costs. Example 1.1 shows how to calculate the labor productivity and multifactor productivity measures.

Productivity CalculationsEXAMPLE 1.1

Calculate the productivity for the following operations:

a. Three employees process 600 insurance policies in a week. They work 8 hours per day, 5 days per week.

b. A team of workers makes 400 units of a product, which is sold in the market for $10 each. The accounting department reports that for this job the actual costs are $400 for labor, $1,000 for materials, and $300 for overhead.

SOLUTION

a. Labor productivity =Policies processed

Employee hours

=600 policies

(3 employees)(40 hours/employee)= 5 policies/hour

b. Multifactor productivity =Value of output

Labor cost + Materials cost + Overhead cost

=(400 units)($10/unit)

$400 + $1,000 + $300=

$4,000$1,700

= 2.35

DECISION POINTWe want multifactor productivity to be as high as possible. These measures must be compared with performance levels in prior periods and with future goals. If they do not live up to expectations, the pro-cess should be investigated for improvement opportunities.

Online ResourceTutor 1.1 in OM Explorer provides a new example for calculating productivity.

The Role of Management The way processes are managed plays a key role in productivity improvement. Managers must examine productivity from the level of the supply chain because it is the collective performance of individual processes that makes the difference. The challenge is to increase the value of output relative to the cost of input. If processes can generate more output or output of better quality using the same amount of input, productivity increases. If they can maintain the same level of output while reducing the use of resources, productivity also increases.

Global CompetitionMost businesses realize that, to prosper, they must view customers, suppliers, facility locations, and competitors in global terms. Firms have found that they can increase their market penetra-tion by locating their production facilities in foreign countries because it gives them a local presence that reduces customer aversion to buying imports. Globalization also allows firms to balance cash flows from other regions of the world when economic conditions are less robust in the home country. Sonoco, a $5-billion-a-year industrial and consumer packaging company in Hartsville, South Carolina, has nearly 19,900 employees in 335 locations worldwide spread

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across 33 countries.5 These global operations resulted in international sales and income growth even as domestic sales were stumbling during 2007. How did Sonoco do it?6 Locating operations in countries with favorable tax laws is one reason. Lower tax rates in Italy and Canada helped in pad-ding the earnings margin. Another reason was a weak dollar, whereby a $46 million boost came from turning foreign currencies into dollars as Sonoco exported such items as snack bag packaging, and tubes and cores used to hold tape and textiles, to operations it owned in foreign countries. The exchange rate difference was more than enough to counter the added expense of increased raw materi-als, shipping, and energy costs in the United States.

Most products today are composites of materi-als and services from all over the world. Your t-shirt is sewn in Honduras from cloth cut in the United States. Sitting in a Cineplex theater (Canadian), you munch a Nestle’s Crunch bar (Swiss) while watching a Columbia Pictures movie (Japanese). Five develop-ments spurred the need for sound global strategies: (1) improved transportation and communications technologies; (2) loosened regulations on financial institutions; (3) increased demand for imported ser-vices and goods; (4) reduced import quotas and other international trade barriers due to the formation of regional trading blocks, such as the European Union (EU) and the United States–Mexico–Canada Agreement (USMCA); and (5) comparative cost advantages.

Comparative Cost Advantages China and India have traditionally been the sources for low-cost, but skilled, labor, even though the cost advantage is diminishing as these countries become economically stronger. In the late 1990s, companies manufactured products in China to grab a foothold in a huge market, or to get cheap labor to produce low-tech products despite doubts about the quality of the workforce and poor roads and rail systems. Today, however, China’s new factories, such as those in the Pudong industrial zone in Shanghai, produce a wide variety of products that are sold overseas in the United States and other regions of the world. U.S. manufacturers have increas-ingly abandoned low profit margin sectors like con-sumer electronics, shoes, and toys to emerging nations such as China and Indonesia. Instead, they are focusing on making expensive goods like computer chips, advanced machinery, and health care products that are complex and require specialized labor.

Foreign companies have opened tens of thousands of new facilities in China over the past decade. A major reason is the so-called “landed cost” of the product, or the cost of getting the product to the ultimate consumer. If a firm is interested in selling products in Southeast Asia, it may be less expen-sive to use Chinese labor and suppliers, ship major components to China, and then deliver the final product to customers in China and Southeast Asia, than it is to produce the product at home with Chinese components and then ship the completed product to Southeast Asia. The same argument on landed costs may sometimes make it cheaper for U.S.-based firms to locate facilities here, especially if the major markets for the product are in the United States and transportation costs are high.

Alternatively, it may be less expensive to import products made abroad if labor is a significant component of product costs. Many goods the United States imports from China now come from foreign-owned companies with operations there. These companies include cell phone makers such as Apple, and nearly all of the big footwear and clothing brands. Many more major manu-facturers are there as well. The implications for competition are enormous. Companies that do not have operations in China are finding it difficult to compete on the basis of low prices with companies that do. Instead, they must focus on speed and small production runs.

5https://en.wikipedia.org/wiki/Sonoco (August 7, 2020).6Ben Werner, “Sonoco Holding Its Own,” The State (February 7, 2008); http://www.sonoco.com, 2008.

Sonoco is a global supplier of innovative packaging solutions, including packages for Chips Ahoy cookies, M&M’s, Pringles Potato Crisps, flexible brick packs for coffee, and many other products.

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What China is to manufacturing, India is to service. As with the manufacturing companies, the cost of labor is a key factor. Indian software companies have grown sophisticated in their applications and offer a big advantage in cost. The computer services industry is also affected. Back-office operations are affected for the same reason. Many firms are using Indian companies for accounting and bookkeeping, research and development, preparing tax returns, and process-ing insurance claims. Many tech companies, such as Intel and Microsoft, are opening significant research and development (R&D) operations in India.

Disadvantages of Globalization Of course, operations in other countries can have disadvantages. A firm may have to relinquish proprietary technology if it turns over some of its component manufacturing to offshore suppliers or if suppliers need the firm’s technology to achieve desired

quality and cost goals. Political risks may also be involved. Each nation can exercise its sov-ereignty over the people and property within its borders. The extreme case is nationaliza-tion, in which a government may take over a firm’s assets without paying compensation. Exxon and other large multinational oil firms are scaling back operations in Venezuela due to nationalization concerns. Further, a firm may actually alienate customers back home if jobs are lost to offshore operations.

Employee skills may be lower in foreign countries, requiring additional training time. South Korean firms moved much of their sports shoe production to low-wage Indonesia and China, but they still manufacture hiking shoes and inline roller skates in South Korea because of the greater skills required. In addi-tion, when a firm’s operations are scattered globally, customer response times can be lon-ger. We discuss these issues in more depth in Chapter 12, “Supply Chain Design,” because they should be considered when making deci-sions about outsourcing. Coordinating compo-nents from a wide array of suppliers can be challenging. In addition, catastrophic events, such as the earthquake in Japan in 2011 or the

coronavirus pandemic crisis in 2020, can affect production and operations globally because inter-connected supply chains can spread disruptions rapidly across international borders.

Strong global competition affects industries everywhere. For example, U.S. manufacturers of steel, appliances, household durable goods, machinery, and chemicals have seen their market share decline in both domestic and international markets. With the value of world trade in com-mercial services now in trillions of dollars per year, banking, data processing, airlines, and con-sulting services are beginning to face many of the same international pressures. Regional trading blocs, such as EU and USMCA, further change the competitive landscape in both services and manufacturing. Regardless of which area of the world you live in, the challenge is to produce services or products that can compete in a global market and to design the processes that can make it happen.

Ethical, Workforce Diversity, and Environmental IssuesBusinesses face more ethical quandaries than ever before, intensified by an increasing global presence and rapid technological change. As companies locate new operations and acquire more suppliers and customers in other countries, potential ethical dilemmas arise when business is conducted by different rules. Some countries are more sensitive than others about conflicts of interest, bribery, discrimination against minorities and women, minimum-wage levels, and unsafe workplaces. Managers must decide whether to design and operate processes that do more than just meet local standards. In addition, technological change brings debates about data protection and customer privacy. In an electronic world, businesses are geographically far from their customers, so a reputation of trust is paramount.

In the past, many people viewed environmental problems, such as toxic waste, poisoned drinking water, poor air quality, and climate change as quality-of-life issues; now, many people and businesses see them as survival issues. The automobile industry has seen innovation in elec-tric and hybrid cars in response to environmental concerns and economic benefits arising from using less expensive fuels. Industrial nations face a particular burden because their combined

A firefighter walks around rubble near a burning factory damaged by an earthquake and tsu-nami in Sendai, northeastern Japan, on March 13, 2011. The impact of the earthquake was particularly acute on industries that rely on batteries, LCD panels, automotive sensors, and cutting-edge electronic component and parts sourced from Japan.

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populations consume proportionally much larger resources. Just seven nations, including China, the United States, and India, produce almost half of all greenhouse gases. China and India have added to that total carbon footprint because of their vast economic and manufac-turing expansion over the past decade.

Apart from government initiatives, large multinational companies have a responsibility as well for creating environmentally con-scious practices, and can do so profitably. For instance, Timberland, which is a division of the VF Corporation, has over 110 stores in China because of strong demand for its boots, shoes, clothes, and outdoor gear in that coun-try. It highlights its environmental credentials and corporate social responsibility through investments such as the reforestation efforts in northern China’s Horqin Desert. About 1700 acres of trees had been planted by 2015, along with efforts to improve production of vegeta-bles in the Horqin region by about 4% between 2001 and 2010.7 Timberland hopes to increase its footprint globally by environmentally differentiating itself from the competition. We discuss environmental issues in greater detail in Chapter 15, “Supply Chain Sustainability.”

The challenge is clear: Issues of ethics, workforce diversity, and the environment are becom-ing part of every manager’s job. When designing and operating processes, managers should con-sider integrity, respect for the individual, and customer satisfaction along with more conventional performance measures such as productivity, quality, cost, and profit.

As we learn next, the fourth industrial revolution is providing several technology-driven solutions to meeting the trending challenges in operations management, while also radically transforming the practice of operations and supply chain management.

Fourth Industrial Revolution (Industry 4.0)Accelerating change in the form of information technology, e-commerce, robotics, and the Internet is dramatically affecting the design of new services and products as well as a firm’s sales, order fulfillment, and purchasing processes. The first industrial revolution occurred between 1760 and 1840, and introduced the use of water and steam-powered machines and tools instead of hand-powered ones. The second industrial revolution, which lasted from 1870 to the start of World War I in 1914, was marked by great productivity increases that were spurred by technological advances in railroads and electricity-driven production lines replacing human labor, which caused an increase in unemployment. The third industrial revolution started after World War II and ushered in the digital age with an extensive use of computers in production processes. The fourth industrial revolution (Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology. Communications on a large scale between virtually connected smart machines that can monitor themselves to diagnose and solve problems without human intervention can lead to a tremendous increase in productivity at lowered costs.8

The term Industry 4.0 was first used at a Hannover fair in Germany in 2011, and it represents the fourth industrial revolution. Many believe that the technologies developed recently will allow companies to enter a new computerized era of manufacturing and managing large systems that were too complex to integrate, monitor, and control before the advent of Industry 4.0. Many new technologies can be associated with Industry 4.0, and they can be categorized in different ways. We use an adapted framework of Frank et al. (2019)9 to categorize the Industry 4.0 technologies into four groups: Smart Manufacturing, Smart Products, Smart Supply, and Base Technologies.

▪▪ Smart Manufacturing Technologies help a company’s internal operations to become more efficient and can serve to increase virtual integration, augment virtualization, enhance

7https://footwearnews.com/2015/focus/athletic-outdoor/timberland-tree-planting-china-horqin-desert-145781/#!#:~:text=Timberland%27s%20efforts%20have%20resulted%20in%20more%20than%201%2C700,1%2C700%20acres%20being%20planted%20in%20China%27s%20Horqin%20Desert (August 7, 2020).8https://en.wikipedia.org/wiki/Fourth_Industrial_Revolution (August 7, 2020).

fourth industrial revolution (Industry 4.0)

The ongoing automation of traditional manufacturing and industrial practices using modern smart technology.

9A. G. Frank, L. S. Dalenogare, and N. F. Ayala. (2019). Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. International Journal of Production Economics, 210, 15–26.

Entrance to Timberland store at a shopping mall in Shenzhen, China.

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worldwide by 2025, generating an economic impact of $4 to $7 trillion every year.13 Imagine the enormity of the data collected and the potential effect on our lives and the operations of compa-nies and civic infrastructure. Although this tremendous growth of IoT has raised security and privacy concerns, its impact on our everyday lives is unmistakable and includes applications in diverse industries and contexts, such as manufacturing, agriculture, military, health care, smart homes, smart cities, communications, transportation, and energy management, to mention a few.

Operations Management Applications While the IoT is growing exponentially, here are some examples of how it affects the field of operations management today.

▪▪ Product design and development. Sensors imbedded in a product can transmit real-time data on its use that can be helpful in the design of new products. New designs can ward off problems customers are having with the current model. In some cases when the product has a user interface capability, actual fixes to problems can be downloaded to the product via the Internet.

▪▪ Health care. Devices implanted in patients can monitor blood pressure and heart rates and trigger emergency services if necessary. The response time for emergencies, a competitive priority for hospitals, can be greatly reduced with these devices.

▪▪ Preventive maintenance. Sensor data can be used to determine when a machine part is wear-ing out and should be replaced before it actually fails. Machine failure, which is always unscheduled, is more expensive than performing maintenance when the machine is not being used.

▪▪ Inventory management. Sensors or cam-eras can be installed in inventory storage bins to measure the amount of inventory. These devices can actually trigger an order for more inventory when needed.

▪▪ Logistics. The movement of personnel and materials is an important aspect of a firm’s operations. Real-time rerouting, autonomous (self-driving) vehicles, and using the Internet to track containers and packages are but a few of the applications of IoT in logistics.

▪▪ City management. Transportation is one of the largest areas of application of IoT in cities. For example, with the use of track-ing data of public transit systems from IoT devices, the commute time of passengers can be reduced by improved schedules that reduce the buffer time in their itiner-ary. Traffic-light management can improve drive times through the city in real time. IoT smart meters can signal electrical distribution problems, water leaks, and dangerous levels of air pollu-tion. Songdo, South Korea, is the first fully equipped and wired smart city. Computers are built into the buildings and the streets. Nearly everything in the city will stream data to a bank of computers that will be monitored and analyzed with little or no human intervention.14

Given these examples, and those you can imagine coming in the not-too-distant future, you might be thinking that the IoT will make operations management obsolete. Not so fast! The IoT generates huge amounts of data, often referred to as “big data.” (See Chapter 8, “Forecasting,” for more details on big data.) That data must be organized and analyzed to be of any use. Firms use high-powered analytical models to sift through the data and make sense of it, resulting in a format that managers can use for decision making. In some cases, the data are fed in real time back to the IoT sensor for a programmed decision, as in the inventory management example.

12 For a complete discussion of the IoT, see James Manyika, Michael Chui, Peter Bisson, Jonathan Woetzel, Richard Dobbs, Jacques Bughin, and Dan Aharon, “The Internet of Things: Mapping the Value Beyond the Hype,” McKinsey Global Institute (June 2015).

13https://techjury.net/blog/internet-of-things-statistics/ (August 7, 2020).14“Internet of Things,” https://en.wikipedia.org/wiki/Internet_of_things (November 17, 2016); Songdo IBD, songdoibd.com (Dec. 10, 2016); https://en.wikipedia.org/wiki/Songdo_International_Business_District (August 10, 2020).

automation, improve product traceability, and facilitate efficient energy management. Manufacturing execution systems (MES) are computerized systems used in manufacturing to track and document the transformation of raw materials into finished goods and optimize their production output.10 Sensors and programmable logic controllers can collect real-time data about equipment, and then MES can be used to monitor if production is being executed according to the plan in real time.

Smart Manufacturing Technologies rely heavily on artificial intelligence (AI), which is a constellation of technologies, from machine learning to natural language processing, that allows machines to sense, comprehend, act, and learn.11 AI is the machine counterpart of the natural intelligence displayed by human beings. Robots with AI can work in repeatable and ergonomically unfriendly tasks, and learn more quickly to adapt to producing new products. In addition, Collaborative Robots can be integrated with operators to increase overall quality and productivity. Other technologies can enhance an operator’s productivity and reduce workplace injuries, such as exoskeletons that can help workers in lifting products and/or tools by reducing the stress and pressure on their arms and/or knees. Additive manufacturing, such as 3D printing of digital models, allows companies to achieve a very high level of cus-tomization, although the production volume is not high. Other technologies such as virtual reality and/or augmented reality have a variety of different applications, such as helping in product development to visualize products before they are physically produced, and as a training tool to simulate a variety of working conditions and situations.

▪▪ Smart Products Technologies are front-end technologies that embed digital capabilities in products themselves. For example, sensors can be used to monitor how products are perform-ing in the field, and digital remote interfaces can be used to connect those products to their manufacturer. In addition, artificial intelligence with analytical algorithms based on predic-tive diagnostics can have optimization functions to enhance product performance. In practice, some cars, electrical equipment, and appliances already have those capabilities, which allow the user and/or service technicians to monitor product performance in real time.

▪▪ Smart Supply Technologies relate to supporting the digital integration of a company with its suppliers, customers, and internal operations in real time. Digital platforms with suppliers increase the visibility of inventory, distribution centers, demand, and scheduled deliveries. Systems integration with customers is key to sustaining on-time delivery of products with minimum inventory. Blockchains are an example of a Smart Supply Technology that is cov-ered in greater detail in Chapter 14, “Supply Chain Integration.”

▪▪ Base Technologies are needed to support the application of the other Smart technologies. These technologies create the interconnectivity and make it possible for other technologies to work. For example, the Internet of Things (IoT) represents the integration of sensors and computers in an Internet environment through wireless communication; cloud computing services enable an on-demand network of a shared pool of computing resources; big data gathers a large amount of results and information from the interaction of these systems; and data analytics, based on sophisticated statistical and machine learning methods, can be used to improve the performance of the product, decision-making processes, production processes, and/or product performance.

Due to their relevance, widespread use, and impact across a wide spectrum of industries and settings, from this vast set we highlight and discuss two specific technologies next.

The Internet of ThingsIt is common to see pedestrians on a busy street or shoppers in a mall accessing the Internet on their handheld devices. For these people, it is important to be “connected.” What if “things” were as connected as humans? If you think that idea is from a science fiction novel, you are wrong. The Internet of Things (IoT) is the interconnectivity of objects, embedded with software, sensors, and actuators that enable these objects to collect and exchange data over a network without requiring human intervention. For example, in the IoT, a “thing” can be a person with a heart transplant monitor, a sensor in an automobile that sends real-time operating information to the manufacturer, or Wi-Fi–enabled remote monitoring devices to control such items as home lighting, heating, kitchen, and security systems.12 It is estimated that there will be more than 64 billion IoT devices

10 https://en.wikipedia.org/wiki/Manufacturing_execution_system (August 12, 2020).11 www.accenture.com/ai-insights (August 12, 2020).

manufacturing execution systems (MES)

Computerized systems used in manufacturing to track and docu-ment the transformation of raw materials to finished goods and optimize their production output.

artificial intelligence (AI)

A constellation of technologies, from machine learning to natural language processing, that allows machines to sense, comprehend, act, and learn.

Internet of Things (IoT)

The interconnectivity of objects, embedded with software, sen-sors, and actuators that enable these objects to collect and exchange data over a net-work without requiring human intervention.

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worldwide by 2025, generating an economic impact of $4 to $7 trillion every year.13 Imagine the enormity of the data collected and the potential effect on our lives and the operations of compa-nies and civic infrastructure. Although this tremendous growth of IoT has raised security and privacy concerns, its impact on our everyday lives is unmistakable and includes applications in diverse industries and contexts, such as manufacturing, agriculture, military, health care, smart homes, smart cities, communications, transportation, and energy management, to mention a few.

Operations Management Applications While the IoT is growing exponentially, here are some examples of how it affects the field of operations management today.

▪▪ Product design and development. Sensors imbedded in a product can transmit real-time data on its use that can be helpful in the design of new products. New designs can ward off problems customers are having with the current model. In some cases when the product has a user interface capability, actual fixes to problems can be downloaded to the product via the Internet.

▪▪ Health care. Devices implanted in patients can monitor blood pressure and heart rates and trigger emergency services if necessary. The response time for emergencies, a competitive priority for hospitals, can be greatly reduced with these devices.

▪▪ Preventive maintenance. Sensor data can be used to determine when a machine part is wear-ing out and should be replaced before it actually fails. Machine failure, which is always unscheduled, is more expensive than performing maintenance when the machine is not being used.

▪▪ Inventory management. Sensors or cam-eras can be installed in inventory storage bins to measure the amount of inventory. These devices can actually trigger an order for more inventory when needed.

▪▪ Logistics. The movement of personnel and materials is an important aspect of a firm’s operations. Real-time rerouting, autonomous (self-driving) vehicles, and using the Internet to track containers and packages are but a few of the applications of IoT in logistics.

▪▪ City management. Transportation is one of the largest areas of application of IoT in cities. For example, with the use of track-ing data of public transit systems from IoT devices, the commute time of passengers can be reduced by improved schedules that reduce the buffer time in their itiner-ary. Traffic-light management can improve drive times through the city in real time. IoT smart meters can signal electrical distribution problems, water leaks, and dangerous levels of air pollu-tion. Songdo, South Korea, is the first fully equipped and wired smart city. Computers are built into the buildings and the streets. Nearly everything in the city will stream data to a bank of computers that will be monitored and analyzed with little or no human intervention.14

Given these examples, and those you can imagine coming in the not-too-distant future, you might be thinking that the IoT will make operations management obsolete. Not so fast! The IoT generates huge amounts of data, often referred to as “big data.” (See Chapter 8, “Forecasting,” for more details on big data.) That data must be organized and analyzed to be of any use. Firms use high-powered analytical models to sift through the data and make sense of it, resulting in a format that managers can use for decision making. In some cases, the data are fed in real time back to the IoT sensor for a programmed decision, as in the inventory management example.

12 For a complete discussion of the IoT, see James Manyika, Michael Chui, Peter Bisson, Jonathan Woetzel, Richard Dobbs, Jacques Bughin, and Dan Aharon, “The Internet of Things: Mapping the Value Beyond the Hype,” McKinsey Global Institute (June 2015).

13https://techjury.net/blog/internet-of-things-statistics/ (August 7, 2020).14“Internet of Things,” https://en.wikipedia.org/wiki/Internet_of_things (November 17, 2016); Songdo IBD, songdoibd.com (Dec. 10, 2016); https://en.wikipedia.org/wiki/Songdo_International_Business_District (August 10, 2020).

An employee demonstrates connecting to the Internet on a Samsung Electronics Co. Family Hub fridge freezer, inside the Smart Home section at a John Lewis Plc department store in London, United Kingdom, on Friday, April 8, 2016. The increasing integration of connected devices—what is commonly referred to as the Internet of things, or IoT—promises enormous benefits for consumers and businesses.

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In other cases, monitoring and accumulating data from a process may take months and ultimately result in a change to the process itself. Regardless, operations managers are very much involved.

Concerns and Barriers Does the Internet of Things pose challenges for operations managers? Absolutely. If the IoT is to have extensive use, several concerns must be addressed.

▪▪ Technology. The cost of the basic hardware such as sensors, tracking identifiers, batteries, and storage must continue to drop. In addition, the bandwidth needed to support the intercon-nectivity of billions of devices must increase.

▪▪ Privacy. The amount of private data accessed and transmitted by IoT devices causes concerns of privacy. Does the manufacturer of an implant device have rights to the data collected by the device so as to improve future versions of it? Some sort of legal understanding of ownership rights needs to be in place for each application.

▪▪ Security. With billions of devices creating and transmitting data there is a real concern for the security of those data. The problem is only exacerbated as new IoT devices are introduced to the market.

▪▪ Organizational roles. Operations management and information technology, traditionally two separate functional areas, will have to become more aligned with the advent of IoT. Actuators and sensors provide operating data that not only aid decision making but also affect the business metrics used to evaluate operating performance. It behooves operations managers to learn the capabilities of the IoT.

The Internet of Things is certainly a trend that affects operations and supply chain man-agement in a major way. Whether it is an opportunity or a challenge depends upon how it is embraced. Keep in mind, however, that the IoT, as complicated and pervasive as it is, is only a Base Technology and an enabler for the decision-making tools available to operations managers.

The key is knowing what to do when address-ing various operating problems as they arise. That is the purpose of this text.

Additive ManufacturingRecognizing Smart Manufacturing Technolo-gies and incorporating them into the fabric of a firm’s operations and supply chains are keys to the future success of a firm. One such disrup-tive technology, a major part of Industry 4.0, is additive manufacturing (AM), which is a term used to describe the technologies that build three-dimensional (3D) objects by adding layers of material such as plastic, metal, or concrete. Also known as 3D printing, AM involves com-puters, 3D modeling software, 3D printing machine equipment, and layering material. Once a 3D design is provided using computer-aided design (CAD), the printing equipment lays down successive layers of liquid, powder, sheet material, and so on, to fabricate a 3D object. While AM was mostly used to build pro-totypes during the product development phase,

it is now moving beyond its previous boundaries by playing an integral game-changing role in manufacturing firms’ supply chains.

Operations and Supply Chain Implications of AM Additive manufacturing adoption cases show the potential benefits of AM in terms of improving various supply chain performance outcomes. Moreover, AM can even motivate new business models by decentralizing the production pro-cess.15 The benefits of AM include:

▪▪ Reduced material inputs. Traditionally, the cost of material input required for production was related to the product’s design complexity. AM may help firms overcome the trade-off between cost and complexity. For example, Lockheed Martin was able to reduce the required material inputs for producing a highly complex aerospace component by using AM. The component, which previously required 33 pounds of metal to create a 1-pound component, was reduced to nearly 1 pound of metal. Scrap that occurs in the form of removed material

additive manufacturing (AM)

The technologies that build 3D objects by adding layers of material such as plastic, metal, or concrete.

15M. Kelly, J. Crane, and C. Haley. (2015). 3D Opportunity for the Supply Chain: Additive Manufacturing Delivers. Westlake, TX: Deloitte University Press.

3D Printers making protective visors in a town hall in Paris.

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is also reduced, contributing to a reduction in waste and environmental sustainability. Lockheed Martin was also able to reduce the weight of a satellite, which reduced the size of the rocket and the amount of fuel needed to launch it. A larger payload could now be carried using the same size rocket and fuel, which is significant because the rocket is one of the most expensive parts of a mission.16

▪▪ Simplified production. AM helps firms eliminate intermediary processes of parts production and subassemblies because separate pieces can be manufactured as single objects. This allows manufacturers to achieve reductions in labor, tooling, and work-in-process inventory holding costs. A research study from Italy showed that AM helped LED manufacturers drastically reduce the time to market for a new product.17 The common practice of launching a new LED product involves showcasing them at design fairs, selecting internal components, running technical tests, and designing the appropriate packaging that, in total, may take from 6 months to several years. Because AM does not require molds, and setting up production for small production volumes is very quick once the 3D printer has been programmed, manufacturers can quickly test various design alternatives via rapid prototyping and send finalized designs to their mass production facilities.

▪▪ Although reducing or eliminating assembly resources may simplify production, it does carry significant implications for supply chain networks: The skill of labor required to produce a part often influences where that part can be produced and still remain economically competi-tive. With higher-skilled AM labor needed, countries with lower wage and skill levels could become less attractive locations for production facilities.

▪▪ Production and supply chain flexibility. AM can contribute to production flexibility by being able to reduce the time and resources necessary to design and develop new products, or even change input materials with ease during production. As a result, firms can react more rap-idly to changing market preferences, shorten lead times in the supply chain, and reduce the required levels of finished goods inventory. For example, a luxury car manufacturer has used AM in developing air manifolds for a V8 engine. By being able to produce multiple design iterations quickly through rapid prototyping, the new product development cycle was shrunk by 50 percent, from 12 months to 6 months.

AM can also be used to offer highly customized products. Product customization poten-tially yields an increase in customers’ perceived product value, and thus, a higher willingness to pay. Firms can enhance the perceived product value by increasing the customers’ involve-ment in the production process by allowing them to co-design a product. As an example, Twikit.com offers customized medals and trophies built via AM.18 Using AM, Blizzard enter-tainment was able to provide customized character figurines based on customer preferences.

▪▪ Decentralized, distributed production networks. Distributed production on demand, or on-demand production in distributed locations, represents a scenario in which customers can fabricate objects at or near the point of use. In this regard, AM supports the strategies of postponement  (see Chapter 12, “Supply Chain Design”) and forward inventory place-ment (see Chapter 13, “Supply Chain Logistic Networks”). This significantly reduces the inventories required to support customer availability expectations, reduces lead time, and reduces dependency on forecast accuracy for low-volume products. When this scenario is taken to the extreme, distributed AM production networks may even partially eliminate the need for seller-controlled means of production. Consumers could purchase access to designs and produce goods at home or at other production-capable locations. For example, UPS is expanding its third-party logistics service to offer on-demand AM services in 60 UPS stores and a dedicated facility, called Fast Radius, that provides 3D printing, computerized numeri-cal control machinery (CNC), and rapid injection molding services for industrial companies. In conjunction with the software company SAP, customers’ orders will be seamlessly routed to the nearest UPS AM facility for production and delivery. The on-demand network will benefit customers of all sizes who need the capabilities of 3D printing and do not have the necessary resources to do the job. Mass adoption of a distributed production model such as this could have far-reaching effects on global trading, as AM technology could enable countries that have traditionally been dependent on imported goods to reduce their reliance on foreign production. The potential for on-demand AM is boundless. NASA is experiment-ing with using AM to produce required parts on the International Space Station, while the U.S. Navy is investigating the use of AM to produce spare parts while at sea.

16See http://www.lockheedmartin.com/us/news/features/2014/additive-manufacturing.html for more details.17P. S. Perez, M. Levi, and V. Folli. (2014). A Study of Additive Manufacturing Applied to the Design and Production of LED Luminaires. Milan, Italy: Politecnico Di Milano.18C. Weller, R. Kleer, and F. T. Piller. (2015). Economic Implications of 3D Printing: Market Structure Models in Light of Additive Manufacturing Revisited. International Journal of Production Economics, 164, 43–56.

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Enablers of Adopting AM Regardless of the varying AM usages, the people and technology that help capture the value in AM typically require a mix of enabling elements and processes:19

▪▪ Talent/Workforce. The more sophisticated the application of AM becomes, the greater is the need for new competencies, skills, talent infrastructure, and workforce planning. Many manufacturers rely on CAD programs in designing AM parts. The original CAD programs were not built to consider the unique features of AM to build parts with complex internal structures. The industry is still undergoing the pains of transition to a disruptive technology and, until a fully integrated CAD for AM emerges, firms will experience a shortage of AM specialized designers.

The absence of clear guidelines for procedures and design know-how is also making it difficult to obtain the required workforce skills and optimize product designs. The International Standardization Organization (ISO) and the American Society for Testing and Materials (ASTM) are the two main institutions that have established technical committees and published AM standards. The published guidelines are still limited, and additional guidelines on reporting and testing procedures will be added in the future.

▪▪ Intellectual property rights. AM also poses severe risks to the intellectual property rights with respect to safeguarding product designs. Stringent checks and balances need to be in place to protect intellectual property. As copying product designs via digitalized 3D blueprints is even easier than before, managing digital security and protecting intellectual property will become critically important.

▪▪ Quality assurance. Validating the quality and consistency of AM production is currently the greatest challenge in using AM to produce more sophisticated, high-valued parts. While this is less of a challenge for parts requiring lower conformance and functionality, it is still an essential component of any AM production solution. Parts may lack resistance to environ-mental influences and fail with exposure to high-stress conditions. Moreover, process vari-ability may still be high, making reproducibility a challenge. There is a need for establishing global quality and testing standards for AM.

▪▪ Process. Deploying AM can affect the entire workflow of an organization. Modifying exist-ing processes and activities helps ensure that AM is deployed to its full potential. Currently, available materials and the choice of colors and surface finishes are quite limited. Moreover, the build space of AM machines sets a physical limit to product dimensions. As the produc-tion process is constrained by AM specifications, there is a need for further development of improved open-space designs for AM machines.

Additive manufacturing is not the first, nor will it be the last, technology that will require changes to the four core processes of a supply chain. Regardless of the disruption, successful operations and supply chain managers focus on optimizing the performance of these core processes, which is the focus of this textbook.

Developing Skills for Your CareerYou can develop skills for your career by understanding how firms can meet their current and future challenges through a better design of operating processes and supply chains. This textbook will help you achieve that goal and become an effective manager even if your major lies in a func-tional area of business other than operations and supply chain management. Each chapter has a Managerial Challenge, which is a realistic problem scenario affecting various functional areas, in which the principles of operations management expressed in the chapter can be useful. Further, the trends and challenges we identified earlier represent opportunities to improve existing pro-cesses and supply chains or to create new, innovative ones, regardless of the functional area. The management of processes and supply chains goes beyond designing them; it requires the ability to ensure they achieve their goals and maximize their competitiveness in the markets they serve. We share this philosophy of operations management, as illustrated in Figure 1.7. To assist you in your learning, we use this figure at the start of each chapter to show how the topic of the chapter fits into our philosophy of operations management. In addition, this text also contains several chapter supplements that can be accessed through online resources.

Figure 1.7 shows that all effective operations decisions follow from a sound operations strategy. Consequently, our text has three major parts: “Part 1: Managing Processes,” “Part 2: Managing Customer Demand,” and “Part 3: Managing Supply Chains.” The flow of topics reflects our approach of first understanding how a firm’s operations can help provide a solid foundation for competitiveness, before tackling the essential process design decisions that will support its strategies. Each part begins with a strategy discussion to support the decisions in that part. Once it

19K. Marchese, R. Gorham, J. Joyce, B. Sniderman, and M. Passaretti. (2017). 3D Opportunity for Business Capabilities. Westlake, TX: Deloitte University Press.

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is clear how firms design and improve processes, we explain how they implement those designs to satisfactorily meet customer demand. Finally, we examine the design and operation of supply chains that link processes, whether they are internal or external to the firm. The performance of the supply chains determines the firm’s outcomes, which include the services or products the firm produces, the financial results, and feedback from the firm’s customers.  These outcomes, which are considered in the firm’s strategic plan, are discussed throughout this text.

Part 1: Managing Processes In Part 1, we focus on analyzing processes and how they can be improved to meet the goals of the operations strategy. We begin by addressing the strategic aspects of process design and then present a six-step systematic approach to process analysis. Each chapter in this part deals with some aspect of that approach. We discuss the tools that help manag-ers analyze processes, and we reveal the methods firms use to measure process performance and quality. These methods provide the foundation for programs such as Six Sigma and total quality man-agement. Making processes “lean” by eliminating activities that do not add value while improving those that do add value are also key decisions in the redesign of processes. We also look at long-term capacity planning of firms, as well as shorter-term tactical decisions aimed at better identification and management of system constraints and bottlenecks. The activities involved in managing processes are essential for providing significant benefits to the firm. Effective manage-ment of its processes can allow a firm to reduce its costs and also increase customer satisfaction.

The concluding chapter of Part 1 is a discussion of the methods and tools of project manage-ment. Project management is an effective approach to implementing operations strategy through the introduction of new services or products as well as any changes to a firm’s processes or sup-ply chains.

Part 2: Managing Customer Demand The focus of this part of the book is on effectively forecasting and managing customer demand. Therefore, we begin by taking a look at forecasting methods and their accuracy, followed by managing inventory such that enough is kept on hand for satisfying customer demand but without tying up excessive resources in it. We follow that with chapters focused on two key planning activities for effective operations: (1) operations planning and sched-uling, and (2) resource planning. Together, these planning activities allow for the creation of goods and services that would meet customer demand in a cost-effective fashion.

Part 3: Managing Supply Chains The focus of Part 3 is on supply chains involving processes both internal and external to the firm and the tools that enhance their execution. We follow that with understanding how the design of supply chains and major strategic decisions, such as outsourcing and locating facilities, affect performance. We also look at new technologies and contemporary issues surrounding supply chain integration and the impact of supply chains on the environment.

Later chapters deal with a variety of subjects: process analysis, including methods used in programs such as Six Sigma and total quality management and those used in making lean processes; managing processes, essential for providing significant benefits to the firm by reduc-ing costs and increasing customer satisfaction; effectively forecasting and managing customer demand, including the use of inventory management and planning activities; and managing sup-ply chains, which involves using processes both internal and external to the firm and incorporat-ing new technologies.

Adding Value with Process InnovationOf great importance is that the effective operation of a firm and its supply chain is as vital as the design and implementation of its processes. Skilled managers in this field inherently understand that process innovation can make a big difference even in a low-growth industry. Examining pro-cesses from the perspective of the value they add is an important part of a successful manager’s agenda, as is gaining an understanding of how core processes and related supply chains are linked to their competitive priorities, markets, and the operations strategy of a firm. Who says operations management does not make a difference?

▲ FIGURE 1.7Managing Processes, Customer Demand, and Supply Chains

Using Operations to Create Value

Managing Customer DemandForecasting

Inventory ManagementOperations Planning and Scheduling

Resource Planning

Managing Supply ChainsSupply Chain Design

Supply Chain Logistics NetworksSupply Chain Integration

Supply Chain Sustainability

Managing Processes

Process Strategy and AnalysisQuality and Performance

Lean SystemsCapacity Planning

Constraint ManagementProject Management

Part 1Managing Processes

Designing andoperating processes in

the firm

Part 2Managing Customer

DemandForecasting demands

and developinginventory plans andoperating schedules

Part 3Managing Supply

ChainsDesigning an integratedand sustainable supply

chain of connectedprocesses between firms

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In the long run, all management decisions should reflect corporate strategy. To that end, regardless of the functional area, all managers either directly use the principles of operations management or are directly influenced by them. Processes can be found throughout the organization, from the boardroom to the billing department, and this text is all about managing those processes. At the strategic level, new capabilities must be developed and existing capabilities must be maintained to best serve the firm’s external customers. Managers of all disciplines must design new processes that have strategic implications. They are also deeply involved in the development, organization, and operation of supply chains that link external suppliers and external customers to the firm’s internal processes, as the Managerial Challenges in each chapter show.

Plans, policies, and actions should be linked to all functional areas to sup-port the firm’s overall goals and objectives. Taking a process view of a firm facilitates these links. Regardless of whether you aspire to be an operations manager, or you just want to use the principles of operations management to become a more effective manager, remember that effective management of peo-ple, capital, information, and materials is critical to the success of any process and any supply chain.

As you study operations management, keep two principles in mind:

1. Each part of an organization, not just the operations function, must design and operate processes that are part of a supply chain and deal with quality, technology, and staffing issues.

2. Each function of an organization has its own identity and yet is connected with operations through shared processes.

Great strategic decisions lead nowhere if the tactical decisions that support them are wrong. Remember: All managers are involved in tactical decisions, including process improvement and performance measurement, managing and planning projects, generating production and staffing plans, managing inven-tories, and scheduling resources. You will find numerous examples of these decisions, and the implications of making them, throughout this text. You will also learn about the decision-making tools practicing managers use to recognize and define the problem and then choose the best solution. The topics in this text will help you meet operations challenges and achieve operational innovation regardless of your chosen career path.

Through operational innovations that add value to its products and catchy promotional advertise-ments, Progressive Insurance has been able to achieve amazing growth in a low-growth industry. Here, Stephanie Courtney, who plays the charac-ter Flo in commercials for Progressive Insurance, waves to a friend after throwing out a pitch before a baseball game between the Kansas City Royals and Cleveland Indians, in Cleveland, Ohio.

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources

1.1 Describe the role of opera-tions in an organization and its historical evolution over time.

The section “Role of Operations in an Organization” shows how different functional areas of business come together to create value for a firm.

1.2 Describe the process view of operations in terms of inputs, processes, outputs, information flows, suppli-ers, and customers.

See the section “A Process View,” which focuses on how nested and other processes work. Understand the key differences between manufacturing and service processes. Review Figure 1.2 for the important inputs, outputs, and information flows associated with any process.

1.3 Describe the supply chain view of operations in terms of linkages between core and support processes.

Review Figure 1.4 for the important supply chain linkage and infor-mation flows.

1.4 Define an operations strat-egy and its linkage to cor-porate strategy and market analysis.

See the section “Operations Strategy” and subsection “Corporate Strategy” and review Figure 1.5.

1.5 Identify nine competitive priorities used in operations strategy, and explain how a consistent pattern of deci-sions can develop organiza-tional capabilities.

The section “Competitive Priorities and Capabilities” discusses the important concept of order winners and qualifiers. Review Table 1.3 for important illustrations and examples of how leading edge firms implemented different competitive priorities to create a unique positioning in the marketplace. Review Table 1.5, which provides a nice illustrative example of how firms must identify gaps in their competitive priorities and build capabilities through related process and operational changes.

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 49

Learning Objective Guidelines for Review Online Resources

1.6 Identify the latest trends in operations management and understand how firms can address the challenges facing operations and sup-ply chain managers in a firm.

The section “Trends and Challenges in Operations Manage-ment” describes the pressures and challenges that managers face in achieving productivity improvements, enhancing sustain-ability, and maintaining workforce diversity in the face of global competition.

OM Explorer Tutor: Productivity MeasuresActive Model Exercise: Productivity

1.7 Define the fourth industrial revolution (Industry 4.0) and understand how its embed-ded technologies and auto-mation are transforming the practice of operations and supply chain management.

The section “Fourth Industrial Revolution (Industry 4.0)” lays out a framework of new technologies that constitute the fourth industrial revolution, and how they can be managed to improve processes and supply chains. Also review the subsections “The Internet of Things” and “Additive Manufacturing.”

1.8 Understand how to develop skills for your career using this textbook.

The section “Developing Skills for Your Career” lays out the foun-dations of this textbook, and how the content of each chapter can help you develop core understanding about managing processes and supply chains. Also review the subsection “Adding Value with Process Innovation.”

Key EquationsTrends and Challenges in Operations Management 1. Productivity is the ratio of output to input:

Productivity =Output

Input

Key Termsadditive manufacturing (AM) 44artificial intelligence (AI) 42competitive capabilities 32competitive priorities 32core competencies 30core process 27customer relationship process 27external customers 25external suppliers 25fourth industrial revolution

(Industry 4.0) 41internal customers 25

internal suppliers 25Internet of Things (IoT) 42lead time 30manufacturing execution systems

(MES) 42nested process 25new service/product development

process 27operation 23operations management 23operations strategy 28order fulfillment process 27

order qualifier 34order winner 34process 23productivity 37supplier relationship process 27supply chain 23supply chain management 23supply chain processes 28support process 27time-based competition 33

Solved Problem 1Student tuition at Boehring University is $150 per semester credit hour. The state supplements school revenue by $100 per semester credit hour. Average class size for a typical 3-credit course is 50 students. Labor costs are $4,000 per class, materials costs are $20 per student per class, and overhead costs are $25,000 per class.

a. What is the multifactor productivity ratio for this course process?b. If instructors work an average of 14 hours per week for 16 weeks for each 3-credit class of

50 students, what is the labor productivity ratio?

SOLUTION

a. Multifactor productivity is the ratio of the value of output to the value of input resources.

Value of output = a 50 studentsclass

b a 3 credit hoursstudents

b a$150 tuition + $100 state support

credit hourb

= $37,500/class

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50 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Value of inputs = Labor + Materials + Overhead

= $4,000 + ($20/student * 50 students/class) + $25,000

= $30,000/class

Multi factorproctivity

=Output

Input=

$37,500/class$30,000/class

= 1.25

b. Labor productivity is the ratio of the value of output to labor hours. The value of output is the same as in part (a), or $37,500/class, so

Labor hours of input = a 14 hoursweek

b a 16 weeksclass

b = 224 hours/class

Labor productivity =Output

Input=

$37,500/class224 hours/class

= $167.41/hour

Solved Problem 2Natalie Attire makes fashionable garments. During a particular week, employees worked 360 hours to produce a batch of 132 garments, of which 52 were “seconds” (meaning that they were flawed). Seconds are sold for $90 each at Attire’s Factory Outlet Store. The remaining 80 garments are sold to retail distribution at $200 each. What is the labor productivity ratio of this manufacturing process?

SOLUTION

Value of output = (52 defective * $90/defective) + (80 garments * $200/garment) = $20,680

Labor hours of input = 360 hours

Labor productivity =Output

Input=

$20,680360 hours

= $57.44 in sales per hour

Discussion Questions1. Consider your last (or current) job, internship, or

volunteer experience.

a. What activities did you perform?

b. Who were your customers (internal and external), and how did you interact with them?

c. How could you measure the customer value you were adding by performing your activities?

d. Was your position in accounting, finance, human resources, management information systems, market-ing, operations, or other? Explain.

2. Anglo American plc is a multinational mining company with its headquarters in South Africa. It is the world’s larg-est producer of platinum as well as a major producer of diamond, copper, nickel, and coal. What should be the focus of Anglo American’s operations strategy, and what are its competitive priorities?

3. A local hospital declares that it is committed to pro-vide care to patients arriving at the emergency unit in less than 15 minutes and that it will never turn away patients who need to be hospitalized for further medical care. What implications does this commitment have for strategic operations management decisions (i.e., deci-sions relating to capacity and workforce)?

4. FedEx built its business on quick, dependable delivery of items being shipped by air from one business to another.

Its early advantages included global tracking of shipments using Web technology. The advancement of Internet technology enabled competitors to become much more sophisticated in order tracking. In addition, the advent of Web-based businesses put pressure on increased ground transportation deliveries. Explain how this change in the environment has affected FedEx’s operations strategy, especially relative to UPS, which has a strong hold on the business-to-consumer ground delivery business.

5. Suppose that you were conducting a market analysis for a new textbook about technology management. What would you need to know to identify a market segment? How would you make a needs assessment? What should be the collection of services and products?

6. Although all nine of the competitive priorities discussed in this chapter are relevant to a company’s success in the marketplace, explain why a company should not necessarily try to excel in all of them. What determines the choice of the competitive priorities that a company should emphasize for its key processes?

7. Choosing which processes are core to a firm’s competi-tive position is a key strategic decision. For example, Nike, a popular sports shoe company, focuses on the customer relationship, new product development, and supplier relationship processes and leaves the order fulfillment process to others. Allen Edmonds, a top-quality shoe company, considers all four processes to be

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 51

core processes. What considerations would you make in determining which processes should be core to your manufacturing company?

8. A local fast-food restaurant processes several customer orders at once. Service clerks cross paths, sometimes nearly colliding, while they trace different paths to fill customer orders. If customers order a special combination of toppings on their hamburgers, they must wait quite some time while the special order is cooked. How would you modify the restaurant’s operations to achieve com-petitive advantage? Because demand surges at lunchtime, volume flexibility is a competitive priority in the fast-food business. How would you achieve volume flexibility?

9. Kathryn Shoemaker established Grandmother’s Chicken Restaurant in Middlesburg 5 years ago. It features a unique recipe for chicken, “just like grandmother used to make.” The facility is homey, with relaxed and friendly service. Business has been good during the past 2 years, for both lunch and dinner. Customers normally wait about 15 minutes to be served, although complaints about service delays have increased recently. Shoemaker is currently considering whether to expand the cur-rent facility or open a similar restaurant in neighboring Uniontown, which has been growing rapidly.

a. What types of strategic plans must Shoemaker make?

b. What environmental forces could be at work in Middles-burg and Uniontown that Shoemaker should consider?

c. What are the possible distinctive competencies of Grandmother’s?

10. Wild West, Inc., is a regional telephone company that inherited nearly 100,000 employees and 50,000 retirees

from AT&T. Wild West has a new mission: to diversify. It calls for a 10-year effort to enter the financial services, real estate, cable TV, home shopping, entertainment, and cellular communication services markets—and to compete with other telephone companies. Wild West plans to pro-vide cellular and fiber-optic communications services in markets with established competitors, such as the United Kingdom, and in markets with essentially no competition, such as Russia and former Eastern Bloc countries.

a. What types of strategic plans must Wild West make? Is the “do-nothing” option viable? If Wild West’s mis-sion appears too broad, which businesses would you trim first?

b. What environmental forces could be at work that Wild West should consider?

c. What are the possible core competencies of Wild West? What weaknesses should it avoid or mitigate?

11. You are designing a grocery delivery business. Via the Internet, your company will offer staples and frozen foods in a large metropolitan area and then deliver them within a customer-defined window of time. You plan to partner with two major food stores in the area. What should be your competitive priorities and what capabilities do you want to develop in your core and support processes?

12. Under what conditions would you recommend a small manufacturer of consumer electrical goods to acquire additive manufacturing (AM) capabilities for producing some of the components needed for the manufacturing process, instead of sourcing them from external suppliers? How would these considerations change if the firm grows over time and production volumes increase dramatically?

The OM Explorer, POM for Windows, and Active Model soft-ware is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how to do

the calculations by hand. At the least, the software provides a check on your calculations. When calculations are particularly complex and the goal is interpreting the results in making deci-sions, the software entirely replaces the manual calculations.

Problems

Trends and Challenges in Operations Management 1. (Refer to Solved Problem 1.) Coach Bjourn Toulouse led the

Big Red Herrings to several disappointing football seasons. Only better recruiting will return the Big Red Herrings to winning form. Because of the current state of the program, Boehring University fans are unlikely to support increases in the $192 season ticket price. Improved recruitment will increase overhead costs to $30,000 per class section from the current $25,000 per class section. The university’s budget plan is to cover recruitment costs by increasing the average class size to 75 students. Labor costs will increase to $6,500 per 3-credit course. Material costs will be about $25 per student for each 3-credit course. Tuition will be $200 per semester credit, which is supplemented by state support of $100 per semester credit.

a. What is the multifactor productivity ratio? Compared to the result obtained in Solved Problem 1, did pro-ductivity increase or decrease for the course process?

b. If instructors work an average of 20 hours per week for 16 weeks for each 3-credit class of 75 students, what is the labor productivity ratio?

2. Suds and Duds Laundry washed and pressed the following numbers of dress shirts per week.

Week Work Crew Total Hours Shirts

1 Sud and Dud 24 68

2 Sud and Jud 46 130

3 Sud, Dud, and Jud 62 152

4 Sud, Dud, and Jud 51 125

5 Dud and Jud 45 131

a. Calculate the labor productivity ratio for each week.

b. Explain the labor productivity pattern exhibited by the data.

3. White Tiger Electronics produces CD players using an automated assembly line process. The standard cost of CD players is $150 per unit (labor, $30; materials, $70; and overhead, $50). The sales price is $300 per unit.

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52 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

a. To achieve a 10 percent multifactor productivity improvement by reducing materials costs only, by what percentage must these costs be reduced?

b. To achieve a 10 percent multifactor productivity improvement by reducing labor costs only, by what percentage must these costs be reduced?

c. To achieve a 10 percent multifactor productivity improvement by reducing overhead costs only, by what percentage must these costs be reduced?

4. At Symtecks, the output of a specific process is valued at $100 per unit. The cost of labor is $50 per hour including benefits. The accounting department provided the follow-ing information about the process for the past four weeks:

Week 1 Week 2 Week 3 Week 4

Units Produced 1,124 1,310 1,092 981

Labor ($) 12,735 14,842 10,603 9,526

Materials ($) 21,041 24,523 20,442 18,364

Overhead ($) 8,992 10,480 8,736 7,848

a. Use the multifactor productivity ratio to see whether recent process improvements had any effect and, if so, when the effect was noticeable.

b. Has labor productivity changed? Use the labor pro-ductivity ratio to support your answer.

5. Alyssa’s Custom Cakes currently sells 5 birthday, 2 wedding, and 3 specialty cakes each month for $50, $150, and $100 each, respectively. The cost of labor is $50 per hour including benefits. It takes 90 minutes to produce a birthday cake, 240 minutes to produce a wed-ding cake, and 60 minutes to produce a specialty cake. Alyssa’s current multifactor productivity ratio is 1.25.

a. Use the multifactor productivity ratio provided to calculate the average cost of the cakes produced.

b. Calculate Alyssa’s labor productivity ratio in dollars per hour for each type of cake.

c. Based solely on the labor productivity ratio, which cake should Alyssa try to sell the most?

d. Based on your answer in part (a), is there a type of cake Alyssa should stop selling?

6. The Big Black Bird Company (BBBC) has a large order for special plastic-lined military uniforms to be used in an urgent military operation. Working the normal two shifts of 40 hours each per week, the BBBC production process usually produces 2,500 uniforms per week at a standard cost of $120 each. Seventy employees work the first shift and 30 employees work the second. The con-tract price is $200 per uniform. Because of the urgent need, BBBC is authorized to use around-the-clock pro-duction, 6 days per week. When each of the two shifts works 72 hours per week, production increases to 4,000 uniforms per week but at a cost of $144 each.

a. Did the multifactor productivity ratio increase, decrease, or remain the same? If it changed, by what percentage did it change?

b. Did the labor productivity ratio increase, decrease, or remain the same? If it changed, by what percentage did it change?

c. Did weekly profits increase, decrease, or remain the same?

7. Thomas Cope, located in Bolton, England, is a manufac-turer of stainless steel exhaust hoods used in industrial kitchens. The firm works 20 days a month, and each employee works an average of 8 hours per day. To keep costs down, Thomas Cope employs labor with limited experience. This causes quality issues, and every day 10 percent of the production is scrapped. Each exhaust hood sells for £125. Labor is paid at £15/hour, materi-als cost per exhaust hood is £40, and overhead cost is £3,500. The firm currently has 250 employees.

a. Calculate the labor and multifactor productivity ratios.

b. To improve the firm’s multifactor productivity, Thomas Cope has three choices 1) increase 20 percent sales by reducing the sales price by 10 percent, 2) improve quality by hiring skilled labor at £20 per hour resulting in no defects, or 3) reduce material costs by 10 percent. Which option has the greatest impact on the multifactor productivity measure?

8. Mariah Enterprises makes a variety of consumer elec-tronic products. Its camera manufacturing plant is considering choosing between two different processes, named Alpha and Beta, which can be used to make two component parts A and B. To make the correct decision, the managers would like to compare the labor and multi-factor productivity of process Alpha with that of process Beta. The value of process output for component A and B are $175 and $140 per unit, respectively. The correspond-ing overhead costs are $6,000 and $5,000, respectively.

PROCESS ALPHA PROCESS BETA

Product A B A B

Output (units) 50 60 30 80

Labor ($) $1,200 $1,400 $1,000 $2,000

Materials ($) $2,500 $3,000 $1,400 $3,500

a. Which process, Alpha or Beta, is more productive?

b. What conclusions can you draw from your analysis?

9. Akiko, a mobile Vegan café, in London sells wraps, bowls, and burgers. It employs two sandwich artists to assemble the wraps as per customer requests. The café’s current daily labor cost is £160, the equipment cost is £175, and the overhead cost is £125. Daily demands, along with selling price and material costs per beverage, are given here:

Wraps Bowls Burgers

Number of units sold

250 300 100

Price per item £4 £5.50 £6.00

Materials (£) £0.90 £1.40 £1.75

Jimmy Riverside, the manager at Akiko, would like to understand how adding waffles and ice-cream will alter the café’s productivity. His market research shows that waffles and ice-cream will attract both American and European tourists. Assuming that the new equipment is purchased before these are added to the menu, Jimmy has developed new average daily demand and cost projections. The new equipment cost is £350, and the overhead cost is £100. Modified daily

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USING OPERATIONS TO CREATE VALUE CHAPTER 1 53

demands, as well as selling price and material costs per units for the new product lines, are given here:

Wraps Bowls BurgersWaffles and Ice-cream

Number of units sold

250 300 100 90

Price per item £4 £5.50 £6.00 £4.50

Material (£) £0.90 £1.40 £1.75 £1.50

a. Calculate the change in labor and multifactor pro-ductivity if waffles and ice-cream are added to the menu.

b. If everything else remains unchanged, how many units of waffles and ice-cream would have to be sold to ensure that the multifactor productivity remains at its current level?

◀ ACTIVE MODEL 1.1Labor Productivity Using Data from Example 1.1

Active Model ExerciseThis Active Model is available online. It allows you to evaluate the important elements of labor productivity.

Microsoft® Windows® and Microsoft Office® are registered trademarks of the Microsoft Corporation in the United States and other countries. This book is not sponsored or endorsed by or affiliated with the Microsoft Corporation.

QUESTIONS

1. If the insurance company can process 60 (10 percent) more policies per week, by what percentage will the productivity measure rise?

2. Suppose the 8-hour day includes a 45-minute lunch. What is the revised productivity measure, excluding lunch?

3. If an employee is hired, what will be the weekly num-ber of policies processed if the productivity of five poli-cies per hour is maintained?

4. Suppose that, during the summer, the company works for only 4 days per week. What will be the weekly num-ber of policies processed if the productivity of five poli-cies per hour is maintained?

CASE Chad’s Creative Concepts

Chad’s Creative Concepts designs and manufactures wood furniture. Founded by Chad Thomas on the banks of Lake Erie in Sandusky, Ohio, the com-pany began by producing custom-made wooden furniture for vacation cabins located along the coast of Lake Erie and on nearby Kelly’s Island and Bass Island. Being an “outdoors” type himself, Thomas originally wanted to bring “a bit of the outdoors” inside. Chad’s Creative Concepts developed a solid reputation for creative designs and high-quality workmanship. Sales eventu-ally encompassed the entire Great Lakes region. Along with growth came additional opportunities.

Traditionally, the company focused entirely on custom-made furniture, with the customer specifying the kind of wood from which the piece would be made. As the company’s reputation grew and sales increased, the sales force began selling some of the more popular pieces to retail furniture outlets. This move into retail outlets led Chad’s Creative Concepts into the production of a more standard line of furniture. Buyers of this line were much more price sensitive and imposed more stringent delivery requirements than did clients for the custom line. Custom-designed furniture, however, continued to dominate sales, accounting for 60 percent of volume and 75 percent of dollar sales.

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54 CHAPTER 1 USING OPERATIONS TO CREATE VALUE

Currently, the company operates a single manufacturing process in Sandusky, where both custom furniture and standard furniture are manufactured. The equipment is mainly general purpose in nature to provide the flexibility needed for producing custom pieces of furniture. The layout puts together saws in one section of the facility, lathes in another, and so on. The quality of the finished product reflects the quality of the wood chosen and the craftsmanship of indi-vidual workers. Both custom and standard furniture compete for processing time on the same equipment by the same craftspeople.

During the past few months, sales of the standard line steadily increased, leading to more regular scheduling of this product line. However, when sched-uling trade-offs had to be made, custom furniture was always given priority because of its higher sales and profit margins. Thus, scheduled lots of standard furniture pieces were left sitting around the plant in various stages of completion.

As he reviews the progress of Chad’s Creative Concepts, Thomas is pleased to note that the company has grown. Sales of custom furniture remain strong, and sales of standard pieces are steadily increasing. However, finance and accounting indicate that profits are not what they should be. Costs associ-ated with the standard line are rising. Dollars are being tied up in inventory,

both in raw materials and work-in-process. Expensive public warehouse space has to be rented to accommodate the inventory volume. Thomas also is con-cerned with increased lead times for both custom and standard orders, which are causing longer promised delivery times. Capacity is being pushed, and no space is left in the plant for expansion. Thomas begins a careful assessment of the overall impact that the new standard line is having on his manufactur-ing process.

QUESTIONS1. What types of decisions must Chad Thomas make daily for his com-

pany’s operations to run effectively? Over the long run?2. How did sales and marketing affect operations when the company began

to sell standard pieces to retail outlets?3. How has the move to producing standard furniture affected the com-

pany’s financial structure?4. What might Chad Thomas have done differently to avoid some of the

problems he now faces?20

20Source: This case was prepared by Dr. Brooke Saladin, Wake Forest University, as a basis for classroom discussion. Copyright © Brooke Saladin. Reprinted by permission.

VIDEO CASE Using Operations to Create Value at Crayola

Operations processes are at the heart of Crayola, the Easton, Pennsylvania, maker of crayons, markers, and paints loved by children of all ages around the world. Since 1903, the company has been taking wax, dyes, and other raw materials and turning them into a colorful array of products sold through an extensive network of distributors and retailers such as Walmart and Target stores. Each day, the company produces 13 million crayons, 2 million markers, 500,000 jars of paint, 170,000 pounds of modeling compounds, and 22,000 Silly Putty© eggs from its three manufacturing plants.

Crayola derives much of its own inspiration and creativity by asking, “What would a kid do?”—especially when focusing on innovation. Not that kids have the knowledge to create complex systems and operational processes. Rather, the question leads to creative solutions by freeing employees to think about the company’s competitive priorities in new ways. In the supply chain, the company maintains five “pillars” of operational leadership. These pillars focus attention on differentiating the company on (1) innovation, (2) sustainabil-ity, (3) agility and resilience, (4) cost, and (5) quality and ethical responsibility.

The company has a history of innovation. They were the first to introduce an art education program called Dream-Makers into the nation’s elementary schools. Washable markers and crayons also were firsts for the industry and continue to be best-sellers for the company. Recently, the language on crayon paper packaging changed to include three languages—French, English, and Spanish—instead of one. This change alone saved $400,000 in paper and printing costs, since the packaging could now be used across multiple markets.

In the area of sustainability, Crayola built a solar farm on a 20-acre site adjacent to its manufacturing plant in Easton. The farm produces enough energy to completely run the plant as well as the headquarters building nearby. The 850 million colored pencils produced each year only use reforested wood, with one tree planted for every tree harvested. Sourcing for paraffin wax used in crayons recently moved from Louisiana to western Pennsylvania, saving 5,000 barrels of oil annually related to wax transportation. All plastic components are made with recycled plastics. And any excess wax from the production of cray-ons is reintroduced into the manufacturing process so no waste is produced.

The company is aggressively pursuing new markets outside the United States. China’s market of children ages 0 to 14 is larger than all the other global markets combined, with more than half the world’s child population. Yet only 14 percent of the company’s total sales come from international markets. So, particular attention is being devoted to growing the company’s manufacturing and distribution presences there. As you can imagine, this means operations manag-ers must think about how to grow the current supply chain beyond the boundaries of existing domestic and international borders if additional expansion is to occur.

QUESTIONS1. Map Crayola’s five pillars of operational leadership to the competitive

priorities in Table 1.3.2. Create an assessment of Crayola’s competitive priorities as it relates to

their plans to expand to Asia.3. Which of the competitive priorities might present the biggest challenge

to Crayola as it expands internationally?

Crayola, headquartered in Pennsylvania, has become a leader in its industry by focusing on operational excellence and innovation.

Pear

son

Educ

atio

n

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55

A.1 Explain break-even analysis, using both the graphic and algebraic approaches.

A.2 Define and construct a preference matrix.

SUPPLEMENT

Operations managers make many decisions as they manage processes and sup-ply chains. Although the specifics of each situation vary, decision making generally involves the same basic steps: (1) recognize and clearly define the problem, (2) collect the informa-tion needed to analyze possible alternatives, and (3) choose and implement the most feasible alternative.

Sometimes, hard thinking in a quiet room is sufficient. At other times, interacting with oth-ers or using more formal procedures are needed. Here, we present four such formal procedures: break-even analysis, the preference matrix, decision theory, and the decision tree.

▪▪ Break-even analysis helps the manager identify how much change in volume or demand is necessary before a second alternative becomes better than the first alternative.

▪▪ The preference matrix helps a manager deal with multiple criteria that cannot be evaluated with a single measure of merit, such as total profit or cost.

▪▪ Decision theory helps the manager choose the best alternative when outcomes are uncertain.▪▪ A decision tree helps the manager when decisions are made sequentially—when today’s best

decision depends on tomorrow’s decisions and events.

Break-Even AnalysisTo evaluate an idea for a new service or product, or to assess the performance of an existing one, determining the volume of sales at which the service or product breaks even is useful. The break-even quantity is the volume at which total revenues equal total costs. Use of this technique is known as break-even analysis. Break-even analysis can also be used to compare processes by finding the volume at which two different processes have equal total costs.

break-even analysis

The use of the break-even quantity; it can be used to com-pare processes by finding the volume at which two different processes have equal total costs.

break-even quantity

The volume at which total revenues equal total costs.

A DECISION MAKING

LEARNING OBJECTIVES After reading this supplement, you should be able to:

A.3 Explain how decision theory can be used to make deci-sions under conditions of certainty, uncertainty, and risk.

A.4 Describe how to draw and analyze a decision tree.

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56 PART 1 MANAGING PROCESSES

Evaluating Services or ProductsWe begin with the first purpose: to evaluate the profit poten-tial of a new or existing service or product. This technique helps the manager answer questions, such as the following:

▪▪ Is the predicted sales volume of the service or product sufficient to break even (neither earning a profit nor sustaining a loss)?

▪▪ How low must the variable cost per unit be to break even, based on current prices and sales forecasts?

▪▪ How low must the fixed cost be to break even?▪▪ How do price levels affect the break-even volume?

Break-even analysis is based on the assumption that all costs related to the production of a specific service or prod-uct can be divided into two categories: (1) variable costs and (2) fixed costs.

The variable cost, c, is the portion of the total cost that varies directly with volume of output: costs per unit for materials, labor, and usually some fraction of overhead. If we

let Q equal the number of customers served or units produced per year, total variable cost = cQ. The fixed cost, F, is the portion of the total cost that remains constant regardless of changes in levels of output: the annual cost of renting or buying new equipment and facilities (including depreciation, interest, taxes, and insurance); salaries; utilities; and portions of the sales or adver-tising budget. Thus, the total cost of producing a service or good equals fixed costs plus variable costs multiplied by volume, or

Total cost = F + cQ

The variable cost per unit is assumed to be the same no matter how small or large Q is, and thus, total cost is linear. If we assume that all units produced are sold, total annual revenues equal revenue per unit sold, p, multiplied by the quantity sold, or

Total revenue = pQ

If we set total revenue equal to total cost, we get the break-even quantity point as

pQ = F + cQ

(p – c)Q = F

Q =F

p – c

We can also find this break-even quantity graphically. Because both costs and revenues are linear relationships, the break-even quantity is where the total revenue line crosses the total cost line.

Break-even analysis cannot tell a manager whether to pursue a new service or product idea or drop an existing line. The technique can only show what is likely to happen for various fore-casts of costs and sales volumes. To evaluate a variety of “what-if” questions, we use an approach called sensitivity analysis, a technique for systematically changing parameters in a model to determine the effects of such changes. The concept can be applied later to other techniques, such as linear programming. Here we assess the sensitivity of total profit to different pricing strategies, sales volume forecasts, or cost estimates.

variable cost

The portion of the total cost that varies directly with volume of output.

fixed cost

The portion of the total cost that remains constant regardless of changes in levels of output.

sensitivity analysis

A technique for systematically changing parameters in a model to determine the effects of such changes.

Finding the Break-Even QuantityEXAMPLE A.1

A hospital is considering a new procedure to be offered at $200 per patient. The fixed cost per year would be $100,000, with total variable costs of $100 per patient. What is the break-even quantity for this service? Use both algebraic and graphic approaches to get the answer.

SOLUTIONThe formula for the break-even quantity yields

Q =F

p – c=

100,000200 – 100

= 1,000 patients

Online ResourcesActive Model A.1 provides additional insight on this break-even example and its extensions with four “what-if” questions.

Tutor A.1 in OM Explorer provides a new example to practice break-even analysis.

A manager is doing some hard thinking and analysis on his computer before reaching a final decision.

Syda

Pro

duct

ions

/Shu

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DECISION MAKING SUPPLEMENT A 57

To solve graphically, we plot two lines: one for costs and one for revenues. Two points determine a line, so we begin by calculating costs and revenues for two different output levels. The following table shows the results for Q = 0 and Q = 2,000. We selected zero as the first point because of the ease of plotting total revenue (0) and total cost (F). However, we could have used any two reasonably spaced output levels.

Quantity (patients) (Q )Total Annual Cost ($)

(100,000 + 100Q )Total Annual Revenue

($) (200Q )

0 100,000 0

2,000 300,000 400,000

Spiro

view

Inc/

Shut

ters

tock

▲ FIGURE A.1 Graphic Approach to Break-Even Analysis

0

100

500

200

300

400

1,000 1,500 2,000

Dol

lars

(in

thou

sand

s)

Patients (Q )

(2,000, 400)

(2,000, 300)

Total annual costs

Break-even quantity

Fixed costs

Total annual revenues

Loss

Profits

We can now draw the cost line through points (0, 100,000) and (2,000, 300,000). The revenue line goes between (0, 0) and (2,000, 400,000). As Figure A.1 indicates, these two lines intersect at 1,000 patients, the break-even quantity.

DECISION POINTManagement expects the number of patients needing the new procedure will exceed the 1,000-patient break-even quantity but first wants to learn how sensitive the decision is to demand levels before mak-ing a final choice.

Sensitivity Analysis of Sales ForecastsEXAMPLE A.2

If the most pessimistic sales forecast for the proposed service in Figure A.1 were 1,500 patients, what would be the procedure’s total contribution to profit and overhead per year?

SOLUTIONThe graph shows that even the pessimistic forecast lies above the break-even volume, which is encour-aging. The procedure’s total contribution, found by subtracting total costs from total revenues, is

pQ – (F + cQ) = 200(1,500) – [100,000 + 100(1,500)] = $50,000

DECISION POINTEven with the pessimistic forecast, the new procedure contributes $50,000 per year. After evaluating the proposal with the present value method (see online Supplement F), management added the new procedure to the hospital’s services.

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58 PART 1 MANAGING PROCESSES

Evaluating ProcessesOften, choices must be made between two processes or between an internal process and buying services or materials on the outside. In such cases, we assume that the decision does not affect revenues. The manager must study all the costs and advantages of each approach. Rather than find the quantity at which total costs equal total revenues, the analyst finds the quantity for which the total costs for two alternatives are equal. For the make-or-buy decision, it is the quantity for which the total “buy” cost equals the total “make” cost. Let Fb equal the fixed cost (per year) of the buy option, Fm equal the fixed cost of the make option, cb equal the variable cost (per unit) of the buy option, and cm equal the variable cost of the make option. Thus, the total cost to buy is Fb + cbQ and the total cost to make is Fm + cmQ. To find the break-even quantity, we set the two cost functions equal and solve for Q :

Fb + cbQ = Fm + cmQ

Q =Fm – Fbcb – cm

The make option should be considered, ignoring qualitative factors, only if its variable costs are lower than those of the buy option. The reason is that the fixed costs for making the service or product are typically higher than the fixed costs for buying. Under these circumstances, the buy option is better if production volumes are less than the break-even quantity. Beyond that quantity, the make option becomes better. Chapter 12, “Supply Chain Design,” brings out other considerations when making make-or-buy decisions.

Break-Even Analysis for Make-or-Buy DecisionsEXAMPLE A.3

The manager of a fast-food restaurant featuring hamburgers is adding salads to the menu. For each of the two new options, the price to the customer will be the same. The make option is to install a salad bar stocked with vegetables, fruits, and toppings and let the customer assemble the salad. The salad bar would have to be leased and a part-time employee hired. The manager estimates the fixed costs at $12,000 and variable costs totaling $1.50 per salad. The buy option is to have preassembled salads avail-able for sale. They would be purchased from a local supplier at $2.00 per salad. Offering preassembled

FIGURE A.2 ▶Break-Even Analysis Solver of OM Explorer for Example A.3

$05,0000

$90,000

10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

$80,000

$70,000

$60,000

$50,000

$40,000

$30,000

$20,000

$10,000

Quantity (Q )

(38,400, 79,200)

(38,400, 69,600)

Break-even quantity

Fixed costs (F)Variable costs (c)

Expected demand

Break-even quantityDecision: Process 1

Cost of Process 1Cost of Process 2

$12,000$1.50

25,000

19,200.0

$2,400$2.00

Process 1 Process 2

salads would require installation and operation of additional refrigeration, with an annual fixed cost of $2,400. The man-ager expects to sell 25,000 salads per year.

What is the make-or-buy quantity?

SOLUTIONThe formula for the break-even quantity yields the following:

Q =Fm – Fbcb – cm

=12,000 – 2,400

2.0 – 1.5= 19,200 salads

Figure A.2 shows the solution from OM Explorer’s Break-Even Analysis Solver. The break-even quantity is 19,200 salads. As the 25,000-salad sales forecast exceeds this amount, the make option is preferred. Only if the res-taurant expected to sell fewer than 19,200 salads would the buy option be better.

DECISION POINTManagement chose the make option after considering other qualitative factors, such as customer prefer-ences and demand uncertainty. A deciding factor was that the 25,000-salad sales forecast is well above the 19,200-salad break-even quantity.

Online ResourcesActive Model A.2 provides additional insight on this make-or-buy example and its extensions.

Tutor A.2 in OM Explorer provides a new example to practice break-even analysis on make-or-buy decisions.

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DECISION MAKING SUPPLEMENT A 59

Preference MatrixDecisions often must be made in situations where multiple criteria cannot be naturally merged into a single measure (such as dollars). For example, a manager deciding in which of two cities to locate a new plant would have to consider such unquantifiable factors as quality of life, worker attitudes toward work, and community reception in the two cities. These important factors cannot be ignored. A preference matrix is a table that allows the manager to rate an alternative according to several performance criteria. The criteria can be scored on any scale, such as from 1 (worst possible) to 10 (best possible) or from 0 to 1, as long as the same scale is applied to all the alternatives being compared. Each score is weighted according to its perceived importance, with the total of these weights typically equaling 100. The total score is the sum of the weighted scores (weight * score) for all the criteria. The manager can compare the scores for alternatives against one another or against a predetermined threshold. We use the preference matrix technique extensively in this text to address decisions where there are qualitative, as well as quantitative, factors to consider.

preference matrix

A table that allows the manager to rate an alternative according to several performance criteria.

salads would require installation and operation of additional refrigeration, with an annual fixed cost of $2,400. The man-ager expects to sell 25,000 salads per year.

What is the make-or-buy quantity?

SOLUTIONThe formula for the break-even quantity yields the following:

Q =Fm – Fbcb – cm

=12,000 – 2,400

2.0 – 1.5= 19,200 salads

Figure A.2 shows the solution from OM Explorer’s Break-Even Analysis Solver. The break-even quantity is 19,200 salads. As the 25,000-salad sales forecast exceeds this amount, the make option is preferred. Only if the res-taurant expected to sell fewer than 19,200 salads would the buy option be better.

DECISION POINTManagement chose the make option after considering other qualitative factors, such as customer prefer-ences and demand uncertainty. A deciding factor was that the 25,000-salad sales forecast is well above the 19,200-salad break-even quantity.

Online ResourcesActive Model A.2 provides additional insight on this make-or-buy example and its extensions.

Tutor A.2 in OM Explorer provides a new example to practice break-even analysis on make-or-buy decisions.

A drive-through only restaurant that does not have seating capacity will have lower fixed costs than a full-service restaurant, and therefore will need a lower number of customers to reach the break-even point.

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Evaluating an Alternative with a Preference MatrixEXAMPLE A.4

The following table shows the performance criteria, weights, and scores (1 = worst, 10 = best) for a new product: a thermal storage air conditioner. If management wants to introduce just one new product and the highest total score of any of the other product ideas is 800, should the firm pursue making the air conditioner?

Performance Criterion Weight (A ) Score (B ) Weighted Score (A * B )

Market potential 30 8 240

Unit profit margin 20 10 200

Operations compatibility 20 6 120

Competitive advantage 15 10 150

Investment requirement 10 2 20

Project risk 5 4 20

Weighted score = 750

Online ResourceTutor A.3 in OM Explorer provides a new example to practice with preference matrixes.

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60 PART 1 MANAGING PROCESSES

Not all managers are comfortable with the preference matrix technique. It requires the manager to state criteria weights before examining the alternatives, although the proper weights may not be readily apparent. Perhaps only after seeing the scores for several alterna-tives can the manager decide what is important and what is not. Because a low score on one criterion can be compensated for or overridden by high scores on others, the preference matrix method also may cause managers to ignore important signals. In Example A.4, the investment required for the thermal storage air conditioner might exceed the firm’s financial capability. In that case, the manager should not even be considering the alternative no matter how high its score.

Decision TheoryDecision theory is a general approach to decision making when the outcomes associated with alternatives are often in doubt. It helps operations managers with decisions on process, capacity, location, and inventory because such decisions are about an uncertain future. Decision theory can also be used by managers in other functional areas. With decision theory, a manager makes choices using the following process:

1. List the feasible alternatives. One alternative that should always be considered as a basis for reference is to do nothing. A basic assumption is that the number of alternatives is finite. For example, in deciding where to locate a new retail store in a certain part of the city, a manager could theoretically consider every grid coordinate on the city’s map. Realistically, however, the manager must narrow the number of choices to a reasonable number.

2. List the events (sometimes called chance events or states of nature) that have an impact on the outcome of the choice but are not under the manager’s control. For example, the demand experienced by the new facility could be low or high, depending not only on whether the location is convenient to many customers but also on what the competition does and general retail trends. Then, group events into reasonable categories. For example, suppose that the average number of sales per day could be anywhere from 1 to 500. Rather than have 500 events, the manager could represent demand with just three events: 100 sales/day, 300 sales/day, or 500 sales/day. The events must be mutually exclusive and collectively exhaustive, meaning that they do not overlap and that they cover all eventualities.

3. Calculate the payoff for each alternative in each event. Typically, the payoff is total profit or total cost. These payoffs can be entered into a payoff table, which shows the amount for each alternative if each possible event occurs. For three alternatives and four events, the table would have 12 payoffs (3 * 4). If significant distortions will occur if the time value of money is not recognized, the payoffs should be expressed as present values or internal rates of return (see online Supplement F). For multiple criteria with important qualitative factors, use the weighted scores of a preference matrix approach as the payoffs.

decision theory

A general approach to decision making when the outcomes asso-ciated with alternatives are often in doubt.

payoff table

A table that shows the amount for each alternative if each possible event occurs.

SOLUTIONBecause the sum of the weighted scores is 750, it falls short of the score of 800 for another product. This result is confirmed by the output from OM Explorer’s Preference Matrix Solver in Figure A.3.

FIGURE A.3 ▶Preference Matrix Solver for Example A.4

Insert a Criterion Add a Criterion Remove a Criterion

Market potentialUnit profit marginOperations compatabilityCompetitive advantageInvestment requirementProject risk

30202015105

Weight (A)8

106

1024

Score (B)2402001201502020

Final Weighted Score 750

Weighted Score (A x B)

DECISION POINTManagement should drop the thermal storage air-conditioner idea. Another new product idea is better, con-sidering the multiple criteria, and that management only wanted to introduce one new product at the time.

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DECISION MAKING SUPPLEMENT A 61

4. Estimate the likelihood of each event, using past data, executive opinion, or other forecasting methods. Express it as a probability, making sure that the probabilities sum to 1.0. Develop probability estimates from past data if the past is considered a good indicator of the future.

5. Select a decision rule to evaluate the alternatives, such as choosing the alternative with the lowest expected cost. The rule chosen depends on the amount of information the manager has on the event probabilities and the manager’s attitudes toward risk.

Using this process, we examine decisions under three different situations: certainty, uncer-tainty, and risk.

Decision Making Under CertaintyThe simplest situation is when the manager knows which event will occur. Here the decision rule is to pick the alternative with the best payoff for the known event. The best alternative is the highest payoff if the payoffs are expressed as profits. If the payoffs are expressed as costs, the best alternative is the lowest payoff.

Decisions Under CertaintyEXAMPLE A.5

A manager is deciding whether to build a small or a large facility. Much depends on the future demand that the facility must serve, and demand may be small or large. The manager knows with certainty the payoffs that will result under each alternative, shown in the following payoff table. The payoffs (in $000) are the present values of future revenues minus costs for each alternative in each event.

POSSIBLE FUTURE DEMAND

Alternative Low High

Small facility 200 270

Large facility 160 800

Do nothing 0 0

What is the best choice if future demand will be low?

SOLUTIONIn this example, the best choice is the one with the highest payoff. If the manager knows that future demand will be low, the company should build a small facility and enjoy a payoff of $200,000. The larger facility has a payoff of only $160,000. The “do nothing” alternative is dominated by the other alternatives; that is, the outcome of one alternative is no better than the outcome of another alternative for each event. Because the “do nothing” alternative is dominated, the manager does not consider it further.

DECISION POINTIf management really knows future demand, it would build the small facility if demand will be low and the large facility if demand will be high. If demand is uncertain, it should consider other decision rules. Ies

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Decision Making Under UncertaintyHere, we assume that the manager can list the possible events but cannot estimate their probabili-ties. Perhaps, a lack of prior experience makes it difficult for the firm to estimate probabilities. In such a situation, the manager can use one of four decision rules:

1. Maximin. Choose the alternative that is the “best of the worst.” This rule is for the pessimist, who anticipates the “worst case” for each alternative.

2. Maximax. Choose the alternative that is the “best of the best.” This rule is for the optimist, who has high expectations and prefers to “go for broke.”

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62 PART 1 MANAGING PROCESSES

3. Laplace. Choose the alternative with the best weighted payoff. To find the weighted payoff, give equal importance (or, alternatively, equal probability) to each event. If there are n events, the importance (or probability) of each is 1/n, so they add up to 1.0. This rule is for the realist.

4. Minimax Regret. Choose the alternative with the best “worst regret.” Calculate a table of regrets (or opportunity losses), in which the rows represent the alternatives and the columns represent the events. A regret is the difference between a given payoff and the best payoff in the same column. For an event, it shows how much is lost by picking an alternative to the one that is best for this event. The regret can be lost profit or increased cost, depending on the situation.

Decisions Under UncertaintyEXAMPLE A.6

Reconsider the payoff matrix in Example A.5. What is the best alternative for each decision rule?

SOLUTION

a. Maximin. An alternative’s worst payoff is the lowest number in its row of the payoff matrix because the payoffs are profits. The worst payoffs ($000) are

Alternative Worst Payoff

Small facility 200

Large facility 160

The best of these worst numbers is $200,000, so the pessimist would build a small facility.

b. Maximax. An alternative’s best payoff ($000) is the highest number in its row of the payoff matrix, or

Alternative Best Payoff

Small facility 270

Large facility 800

The best of these best numbers is $800,000, so the optimist would build a large facility.

c. Laplace. With two events, we assign each a probability of 0.5. Thus, the weighted payoffs ($000) are

Alternative Weighted Payoff

Small facility 0.5(200) + 0.5(270) = 235

Large facility 0.5(160) + 0.5(800) = 480

The best of these weighted payoffs is $480,000, so the realist would build a large facility.

d. Minimax Regret. If demand turns out to be low, the best alternative is a small facility and its regret is 0 (or 200 – 200). If a large facility is built when demand turns out to be low, the regret is 40 (or 200 – 160).

REGRET

Alternative Low Demand High Demand Maximum Regret

Small facility 200 – 200 = 0 800 – 270 = 530 530

Large facility 200 – 160 = 40 800 – 800 = 0 40

The column on the right shows the worst regret for each alternative. To minimize the maximum regret, pick a large facility. The biggest regret is associated with having only a small facility and high demand.

DECISION POINTThe pessimist would choose the small facility. The realist, optimist, and manager choosing to minimize the maximum regret would build the large facility.

Online ResourceTutor A.4 in OM Explorer provides a new example to make decisions under uncertainty.

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DECISION MAKING SUPPLEMENT A 63

Decision Making Under RiskHere we assume that the manager can list the events and estimate their probabilities. The manager has less information than with decision making under certainty, but more information than with decision making under uncertainty. For this intermediate situation, the expected value decision rule is widely used (both in practice and in this book). The expected value for an alternative is found by weighting each payoff with its associated probability and then adding the weighted payoff scores. The alternative with the best expected value (highest for profits and lowest for costs) is chosen.

This rule is much like the Laplace decision rule, except that the events are no longer assumed to be equally likely (or equally important). The expected value is what the average payoff would be if the decision could be repeated time after time. Of course, the expected value decision rule can result in a bad outcome if the wrong event occurs. However, it gives the best results if applied consistently over a long period of time. The rule should not be used if the manager is inclined to avoid risk.

Decisions Under RiskEXAMPLE A.7

Reconsider the payoff matrix in Example A.5. For the expected value decision rule, which is the best alternative if the probability of small demand is estimated to be 0.4 and the probability of large demand is estimated to be 0.6?

SOLUTIONThe expected value for each alternative is as follows:

Alternative Expected Value

Small facility 0.4(200) + 0.6(270) = 242

Large facility 0.4(160) + 0.6(800) = 544

DECISION POINTManagement would choose a large facility if it used this expected value decision rule because it provides the best long-term results if consistently applied over time.

Online ResourceTutor A.5 in OM Explorer provides a new example to make decisions under risk.

Decision TreesThe decision tree method is a general approach to a wide range of processes and supply chain decisions, such as product planning, process analysis, process capacity, and location. It is particu-larly valuable for evaluating different capacity expansion alternatives when demand is uncertain and sequential decisions are involved. For example, a company may expand a facility in 2015 only to discover in 2018 that demand is much higher than forecasted. In that case, a second decision may be necessary to determine whether to expand again or build a second facility.

A decision tree is a schematic model of alternatives available to the decision maker along with their possible consequences. The name derives from the treelike appearance of the model. It consists of a number of square nodes, representing decision points, which are left by branches (which should be read from left to right), representing the alterna-tives. Branches leaving circular, or chance, nodes represent the events. The probability of each chance event, P(E), is shown above each branch. The prob-abilities for all branches leaving a chance node must sum to 1.0. The conditional payoff, which is the pay-off for each possible alternative–event combination, is shown at the end of each combination. Payoffs are given only at the outset, before the analysis begins, for the end points of each alternative–event combi-nation. In Figure A.4, for example, payoff 1 is the financial outcome the manager expects if alternative 1 is chosen and then chance event 1 occurs.

No payoff can be associated yet with any branches farther to the left, such as alternative 1 as a whole because it is followed by a chance event and is not an end point. Payoffs often are expressed as the present value of net profits. If revenues are not affected by the decision, the payoff is expressed as net costs.

decision tree

A schematic model of alterna-tives available to the decision maker, along with their possible consequences.

Possible 2nd decision

1stdecision

= Event node

= Decision node

Alternative 2

Altern

ative

1

1

E3 [P (E3)]

E2 [P (E2)]

E3 [P (E3)]

E2 [P (E2)]

E1 [P (E1)]

Ei = Event iP(Ei ) = Probability of event i

E 1 [P (

E 1)]

Payoff 8

Payoff 7

Payoff 6Alternative 5

Alternative 4

Alternative 3

Payoff 5

Payoff 4

Payoff 3

Payoff 2

Payoff 1

2

▼ FIGURE A.4A Decision Tree Model

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64 PART 1 MANAGING PROCESSES

After drawing a decision tree, we solve it by working from right to left, calculating the expected payoff for each node as follows:

1. For an event node, we multiply the payoff of each event branch by the event’s probability. We add these products to get the event node’s expected payoff.

2. For a decision node, we pick the alternative that has the best expected payoff. If an alternative leads to an event node, its payoff is equal to that node’s expected payoff (already calculated). We “saw off,” or “prune,” the other branches not chosen by marking two short lines through them. The decision node’s expected payoff is the one associated with the single remaining unpruned branch. We continue this process until the leftmost decision node is reached. The unpruned branch extending from it is the best alternative to pursue. If multistage decisions are involved, we must await subsequent events before deciding what to do next. If new prob-ability or payoff estimates are obtained, we repeat the process.

Various software applications are available for drawing decision trees. PowerPoint can be used to draw decision trees, although it does not have the capability to analyze the decision tree. More extensive capabilities, in addition to POM for Windows, are found with SmartDraw (http://www.smartdraw.com), PrecisionTree decision analysis from Palisade Corporation (http:// www.palisade.com), and TreePlan (http://www.treeplan.com/treeplan.htm).

EXAMPLE A.8 Analyzing a Decision Tree

A retailer must decide whether to build a small or a large facility at a new location. Demand at the location can be either low or high, with probabilities estimated to be 0.4 and 0.6, respectively. If a small facility is built and demand proves to be high, the manager may choose not to expand (payoff = $223,000) or to expand (payoff = $270,000). If a small facility is built and demand is low, there is no reason to expand and the payoff is $200,000. If a large facility is built and demand proves to be low, the choice is to do

nothing ($40,000) or to stimulate demand through local advertising. The response to advertising may be either modest or sizeable, with their probabilities estimated to be 0.3 and 0.7, respectively. If it is modest, the payoff is estimated to be only $20,000; the payoff grows to $220,000 if the response is sizeable. Finally, if a large facil-ity is built and demand turns out to be high, the payoff is $800,000.

Draw a decision tree. Then analyze it to determine the expected payoff for each decision and event node. Which alternative—building a small facility or building a large facility—has the higher expected payoff?

SOLUTIONThe decision tree in Figure A.5 shows the event probability and the payoff for each of the seven alternative-event combinations. The first decision is whether to build a small or a large facility. Its node is shown first, to the left, because it is the decision

the retailer must make now. The second decision node—whether to expand at a later date—is reached only if a small facility is built and demand turns out to be high. Finally, the third decision point—whether to advertise—is reached only if the retailer builds a large facility and demand turns out to be low.

Analysis of the decision tree begins with calculation of the expected payoffs from right to left, shown on Figure A.5 beneath the appropriate event and decision nodes.

1. For the event node dealing with advertising, the expected payoff is 160, or the sum of each event’s payoff weighted by its probability [0.3(20) + 0.7(220)].

2. The expected payoff for decision node 3 is 160 because Advertise (160) is better than Do nothing (40). Prune the Do nothing alternative.

3. The payoff for decision node 2 is 270 because Expand (270) is better than Do not expand (223). Prune Do not expand.

4. The expected payoff for the event node dealing with demand, assuming that a small facility is built, is 242 [or 0.4(200) + 0.6(270)].

Online ResourceActive Model A.3 provides additional insight on this decision tree example and its extensions.

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DECISION MAKING SUPPLEMENT A 65

5. The expected payoff for the event node dealing with demand, assuming that a large facility is built, is 544 [or 0.4(160) + 0.6(800)].

6. The expected payoff for decision node 1 is 544 because the large facility’s expected payoff is larg-est. Prune Small facility.

DECISION POINTThe retailer should build the large facility. This initial decision is the only one made now. Subsequent decisions are made after learning whether demand actually is low or high.

◀ FIGURE A.5Decision Tree for Retailer (in $000)

Large facility

Small

facility

2

3

1

High demand [0.6]

Low demand [0.4]

Low de

mand

[0.4]

High demand[0.6]

$200

$223

$270

$20

$220

$40

$160

$800

Do not expand

Expand

Do nothing

Advertise

$544

$544

$160

$270

Modest response [0.3]

Sizable response [0.7]

$242

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources

A.1 Explain break-even analy-sis, using both the graphic and algebraic approaches.

The section “Break-Even Analysis” covers this analysis. Example A.1 and Solved Problem 1 demonstrate both approaches. Example A.3 shows its use in evaluating different processes.

Active Model Exercises: A.1: Break-Even Analysis; A.2: Make-or-Buy DecisionOM Explorer Solver: Break-Even AnalysisOM Explorer Tutors: A.1: Break-Even Analysis; Evaluating Services and Products; A.2: Break-Even Analysis; Evaluating ProcessesPOM for Windows: Break-Even Analysis; Cost-Volume Analysis

A.2 Define and construct a preference matrix.

See the section “Preference Matrix” for making decisions involv-ing unquantifiable factors, where some factors are rated more important than others. Example A.4 and Solved Problem 2 demon-strate the calculations.

OM Explorer Solver: Preference MatrixOM Explorer Tutor: A3: Preference MatrixPOM for Windows: Preference Matrix

A.3 Explain how decision the-ory can be used to make decisions under conditions of certainty, uncertainty, and risk.

The section “Decision Theory” begins with the construction of a payoff table that shows the payoff for each feasible alternative and each event. See the table in Example A.5. In addition, the sec-tions “Decision Making Under Uncertainty” and “Decision Making Under Risk” cover these decision rules for when the outcomes associated with alternatives are in doubt. Examples A.6 and A.7 demonstrate how these rules work and so does Solved Problem 3.

OM Explorer Solver: Decision TheoryOM Explorer Tutors: A.4: Decisions Under Uncertainty; A.5: Decisions Under Risk; A.6: Location Decisions Under UncertaintyPOM for Windows: Decision Tables

A.4 Describe how to draw and analyze a decision tree.

The section “Decision Trees” shows how to draw and analyze decision trees where several alternatives are available over time. Example A.8 and Solved Problem 4 show how to work back from right to left, pruning as you go, until the best alternative is found for decision node 1.

Active Model Exercise: A.3: Decision TreePOM for Windows: Decision Trees (graphical)

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66 PART 1 MANAGING PROCESSES

Key EquationsBreak-Even Analysis

1. Break-even quantity: Q =F

p – c

2. Evaluating processes, make-or-buy indifference quantity: Q =Fm – Fbcb – cm

Key Termsbreak-even analysis 55break-even quantity 55decision theory 60

decision tree 63fixed cost 56payoff table 60

preference matrix 59sensitivity analysis 56variable cost 56

Solved Problem 1The owner of a small manufacturing business has patented a new device for washing dishes and cleaning dirty kitchen sinks. Before trying to commercialize the device and add it to his or her existing product line, the owner wants reasonable assurance of success. Variable costs are estimated at $7 per unit produced and sold. Fixed costs are about $56,000 per year.

a. If the selling price is set at $25, how many units must be produced and sold to break even? Use both algebraic and graphic approaches.

b. Forecasted sales for the first year are 10,000 units if the price is reduced to $15. With this pricing strategy, what would be the product’s total contribution to profits in the first year?

SOLUTION

a. Beginning with the algebraic approach, we get

Q =F

p – c=

56,00025 – 7

= 3,111 units

FIGURE A.6 ▶

0

50

1

$77.7

3.1

2 3 4 5 6 7 8

100

150

200

250

Dol

lars

(in

thou

sand

s)

Units (in thousands)

Break-even quantity

Total costs

Total revenues

Using the graphic approach, shown in Figure A.6, we first draw two lines:

Total revenue = 25Q Total cost = 56,000 + 7Q

The two lines intersect at Q = 3,111 units, the break-even quantity.

b. Total profit contribution = Total revenue – Total cost = pQ – (F + cQ) = 15(10,000) – [56,000 + 7(10,000)] = $24,000

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DECISION MAKING SUPPLEMENT A 67

Solved Problem 2Herron Company is screening three new product ideas: A, B, and C. Resource constraints allow only one of them to be commercialized. The performance criteria and ratings, on a scale of 1 (worst) to 10 (best), are shown in the following table. The Herron managers give equal weights to the performance criteria. Which is the best alternative, as indicated by the preference matrix method?

RATING

Performance Criterion Product A Product B Product C

1. Demand uncertainty and project risk 3 9 2

2. Similarity to present products 7 8 6

3. Expected return on investment (ROI) 10 4 8

4. Compatibility with current manufacturing process 4 7 6

5. Competitive advantage 4 6 5

SOLUTION

Each of the five criteria receives a weight of 1/5 or 0.20.

Product Calculation Total Score

A (0.20 * 3) + (0.20 * 7) + (0.20 * 10) + (0.20 * 4) + (0.20 * 4) = 5.6

B (0 * 9) + (0.20 * 8) + (0.20 * 4) + (0.20 * 7) + (0.20 * 6) = 6.8

C (0.20 * 2) + (0.20 * 6) + (0.20 * 8) + (0.20 * 6) + (0.20 * 5) = 5.4

The best choice is Product B. Products A and C are well behind in terms of total weighted score.

Solved Problem 3Adele Weiss manages the campus flower shop. Flowers must be ordered three days in advance from her supplier in Mexico. Although Valentine’s Day is fast approaching, sales are almost entirely last-minute, impulse purchases. Advance sales are so small that Weiss has no way to estimate the probability of low (25 dozen), medium (60 dozen), or high (130 dozen) demand for red roses on the big day. She buys roses for $15 per dozen and sells them for $40 per dozen. Con-struct a payoff table. Which decision is indicated by each of the following decision criteria?

a. Maximin

b. Maximax

c. Laplace

d. Minimax regret

SOLUTION

The payoff table for this problem is

DEMAND FOR RED ROSES

Alternative Low (25 dozen) Medium (60 dozen) High (130 dozen)

Order 25 dozen $625 $625 $625

Order 60 dozen $100 $1,500 $1,500

Order 130 dozen ($950) $450 $3,250

Do nothing $0 $0 $0

a. Under the maximin criteria, Weiss should order 25 dozen, because if demand is low, Weiss’s profits are $625, the best of the worst payoffs.

b. Under the maximax criteria, Weiss should order 130 dozen. The greatest possible payoff, $3,250, is associated with the largest order.

Online ResourceTutor A.6 in OM Explorer examines decisions under uncertainty for a location example.

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68 PART 1 MANAGING PROCESSES

Solved Problem 4White Valley Ski Resort is planning the ski lift operation for its new ski resort. Management is trying to determine whether one or two lifts will be necessary; each lift can accommodate 250 people per day. Skiing normally occurs in the 14-week period from December to April, during which the lift will operate 7 days per week. The first lift will operate at 90 percent capacity if economic conditions are bad, the probability of which is believed to be about a 0.3. During normal times the first lift will be utilized at 100 percent capacity, and the excess crowd will provide 50 percent utilization of the second lift. The probability of normal times is 0.5. Finally, if times are really good, the probability of which is 0.2, the utilization of the second lift will increase to 90 percent. The equivalent annual cost of installing a new lift, recognizing the time value of money and the lift’s economic life, is $50,000. The annual cost of installing two lifts is only $90,000 if both are purchased at the same time. If used at all, each lift costs $200,000 to operate, no matter how low or high its utilization rate. Lift tickets cost $20 per customer per day.

Should the resort purchase one lift or two?

SOLUTION

The decision tree is shown in Figure A.7. The payoff ($000) for each alternative-event branch is shown in the following table. The total revenues from one lift operating at 100 percent capacity are $490,000 (or 250 customers * 98 days * $20/customer@day).

Alternative Economic Condition Payoff Calculation (Revenue – Cost)

One lift Bad times 0.9(490) – (50 + 200) = 191

Normal times 1.0(490) – (50 + 200) = 240

Good times 1.0(490) – (50 + 200) = 240

Two lifts Bad times 0.9(490) – (90 + 200) = 151

Normal times 1.5(490) – (90 + 400) = 245

Good times 1.9(490) – (90 + 400) = 441

FIGURE A.7 ▶

$256.0

One lift $225.3

$256.0

$441

$245

$151

$240

$191

$240

Bad times [0.3]

Two lifts

Good times [0.2]

Normal times [0.5]

Good times [0.2]

Normal times [0.5]

Bad times [0.3]

The OM Explorer, POM for Windows, and Active Model soft-ware is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how

to do the calculations by hand. At the least, the software pro-vides a check on your calculations. When calculations are particularly complex and the goal is interpreting the results in making decisions, the software entirely replaces the manual calculations.

Problems

c. Under the Laplace criteria, Weiss should order 60 dozen. Equally weighted payoffs for ordering 25, 60, and 130 dozen are about $625, $1,033, and $917, respectively.

d. Under the minimax regret criteria, Weiss should order 130 dozen. The maximum regret of ordering 25 dozen occurs if demand is high: $3,250 – $625 = 2,625. The maximum regret of ordering 60 dozen occurs if demand is high: $3,250 – 1,500 = 1,750. The maximum regret of ordering 130 dozen occurs if demand is low: $625 – ( – $950) = $1,575.

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DECISION MAKING SUPPLEMENT A 69

1. Mary Williams, owner of Williams Products, is evalu-ating whether to introduce a new product line. After thinking through the production process and the costs of raw materials and new equipment, Williams estimates the variable costs of each unit produced and sold at $6 and the fixed costs per year at $60,000.

a. If the selling price is set at $18 each, how many units must be produced and sold for Williams to break even? Use both graphic and algebraic approaches to get your answer.

b. Williams forecasts sales of 10,000 units for the first year if the selling price is set at $14 each. What would be the total contribution to profits from this new product during the first year?

c. If the selling price is set at $12.50, Williams forecasts that first-year sales would increase to 15,000 units. Which pricing strategy ($14.00 or $12.50) would result in the greater total contribution to profits?

d. What other considerations would be crucial to the final decision about making and marketing the new product?

2. A product at the Jennings Company enjoyed reasonable sales volumes, but its contributions to profits were dis-appointing. Last year, 17,500 units were produced and sold. The selling price is $22 per unit, the variable cost is $18 per unit, and the fixed cost is $80,000.

a. What is the break-even quantity for this product? Use both graphic and algebraic approaches to get your answer.

b. If sales were not expected to increase, by how much would Jennings have to reduce its variable cost to break even?

c. Jennings believes that a $1 reduction in price will increase sales by 50 percent. Is this enough for Jen-nings to break even? If not, by how much would sales have to increase?

d. Jennings is considering ways to either stimulate sales volume or decrease variable cost. Management believes that either sales can be increased by 30 percent or that variable cost can be reduced to 85 percent of its cur-rent level. Which alternative leads to higher contribu-tions to profits, assuming that each is equally costly to implement? (Hint: Calculate profits for both alterna-tives and identify the one having the greatest profits.)

e. What is the percent change in the per-unit profit con-tribution generated by each alternative in part (d)?

3. An interactive television service that costs $10 per month to provide can be sold on the information high-way for $15 per client per month. If a service area includes a potential of 15,000 customers, what is the most a company could spend on annual fixed costs to acquire and maintain the equipment?

4. A restaurant is considering adding fresh brook trout to its menu. Customers would have the choice of catching their own trout from a simulated mountain stream or simply asking the waiter to net the trout for them. Oper-ating the stream would require $10,600 in fixed costs per year. Variable costs are estimated to be $6.70 per trout. The firm wants to break even if 800 trout dinners are sold per year. What should be the price of the new item?

5. Spartan Castings must implement a manufacturing pro-cess that reduces the amount of particulates emitted into

the atmosphere. Two processes have been identified that provide the same level of particulate reduction. The first process is expected to incur $350,000 of fixed cost and add $50 of variable cost to each casting Spartan pro-duces. The second process has fixed costs of $150,000 and adds $90 of variable cost per casting.

a. What is the break-even quantity beyond which the first process is more attractive?

b. What is the difference in total cost if the quantity pro-duced is 10,000?

6. A news clipping service is considering moderniza-tion. Rather than manually clipping and photocopy-ing articles of interest and mailing them to its clients, employees electronically input stories from most widely circulated publications into a database. Each new issue is searched for key words, such as a client’s company name, competitors’ names, type of business, and the company’s products, services, and officers. When matches occur, affected clients are instantly notified via an online network. If the story is of interest, it is elec-tronically transmitted, so the client often has the story and can prepare comments for follow-up interviews before the publication hits the street. The manual pro-cess has fixed costs of $400,000 per year and variable costs of $6.20 per clipping mailed. The price charged the client is $8.00 per clipping. The computerized process has fixed costs of $1,300,000 per year and variable costs of $2.25 per story electronically transmitted to the client.

a. If the same price is charged for either process, what is the annual volume beyond which the automated pro-cess is more attractive?

b. The present volume of business is 225,000 clippings per year. Many of the clippings sent with the current process are not of interest to the client or are multiple copies of the same story appearing in several publi-cations. The news clipping service believes that by improving service and by lowering the price to $4.00 per story, modernization will increase volume to 900,000 stories transmitted per year. Should the clip-ping service modernize?

c. If the forecasted increase in business is too optimis-tic, at what volume will the new process (with the $4.00 price) break even?

7. Hahn Manufacturing purchases a key component of one of its products from a local supplier. The current purchase price is $1,500 per unit. Efforts to standardize parts suc-ceeded to the point that this same component can now be used in five different products. Annual component usage should increase from 150 to 750 units. Management won-ders whether it is time to make the component in-house rather than to continue buying it from the supplier. Fixed costs would increase by about $40,000 per year for the new equipment and tooling needed. The cost of raw mate-rials and variable overhead would be about $1,100 per unit, and labor costs would be $300 per unit produced.

a. Should Hahn make rather than buy?

b. What is the break-even quantity?

c. What other considerations might be important?

8. Techno Corporation is currently manufacturing an item at variable costs of $5 per unit. Annual fixed costs of manufacturing this item are $140,000. The current

Break-Even Analysis

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70 PART 1 MANAGING PROCESSES

12. The Forsite Company is screening three ideas for new services. Resource constraints allow only one idea to be commercialized at the present time. The following esti-mates have been made for the five performance criteria that management believes to be most important:

RATING

Performance Criterion Service A Service B Service C

Capital equipment investment required

0.6 0.8 0.3

Expected return on investment (ROI)

0.7 0.3 0.9

Compatibility with current workforce skills

0.4 0.7 0.5

Competitive advantage 1.0 0.4 0.6

Compatibility with EPA requirements

0.2 1.0 0.5

a. Calculate a total weighted score for each alternative. Use a preference matrix and assume equal weights for each performance criterion. Which alternative is best? Worst?

b. Suppose that the expected ROI is given twice the weight assigned to each of the remaining criteria. (The sum of weights should remain the same as in part [a].) Does this modification affect the ranking of the three potential services?

13. You are in charge of analyzing five new suppliers of an important raw material and have been given the informa-tion shown in the table (1 = worst, 10 = best). Man-agement has decided that criteria 2 and 3 are equally important and that criteria 1 and 4 are each four times as

important as criterion 2. No more than two new suppliers are required, but each new vendor must exceed a total score of 70 percent of the maximum total points to be considered.

RATING

Performance Criterion

Vendor A

Vendor B

Vendor C

Vendor D

Vendor E

Quality of raw material 8 7 3 6 9

Environmental impact 3 8 4 7 7

Responsiveness to order changes

9 5 7 6 5

Cost of raw material 7 6 9 2 7

a. Which new vendors do you recommend?

b. Would your decision change if the criteria were con-sidered equally important?

14. Accel Express, Inc., collected the following information on where to locate a warehouse (1 = poor, 10 = excellent):

LOCATION SCORE

Location Factor Factor Weight A B

Construction costs 10 8 5

Utilities available 10 7 7

Business services 10 4 7

Real estate cost 20 7 4

Quality of life 20 4 8

Transportation 30 7 6

selling price of the item is $10 per unit, and the annual sales volume is 30,000 units.

a. Techno can substantially improve the item’s quality by installing new equipment at additional annual fixed costs of $60,000. Variable costs per unit would increase by $1, but, as more of the better-quality product could be sold, the annual volume would increase to 50,000 units. Should Techno buy the new equipment and maintain the current price of the item? Why or why not?

b. Alternatively, Techno could increase the selling price to $11 per unit. However, the annual sales volume would be limited to 45,000 units. Should Techno buy the new equipment and raise the price of the item? Why or why not?

9. The Tri-County Generation and Transmission Association is a nonprofit cooperative organization that provides electrical service to rural customers. Based on a faulty long-range demand forecast, Tri-County overbuilt its generation and distribution system. Tri-County now has much more capacity than it needs to serve its customers. Fixed costs, mostly debt service on investment in plant and equipment, are $82.5 million per year. Variable costs, mostly fossil fuel costs, are $25 per megawatt-hour (MWh, or million watts of power used for 1 hour). The new person in charge of demand forecasting prepared a short-range forecast for

use in next year’s budgeting process. That forecast calls for Tri-County customers to consume 1 million MWh of energy next year.

a. How much will Tri-County need to charge its cus-tomers per MWh to break even next year?

b. The Tri-County customers balk at that price and con-serve electrical energy. Only 95 percent of forecasted demand materializes. What is the resulting surplus or loss for this nonprofit organization?

10. Earthquake, drought, fire, economic famine, flood, and a pestilence of TV court reporters have caused an exo-dus from the City of Angels to Boulder, Colorado. The sudden increase in demand is straining the capacity of Boulder’s electrical system. Boulder’s alternatives have been reduced to buying 150,000 MWh of electric power from Tri-County G&T at a price of $75 per MWh, or refurbishing and recommissioning the abandoned Pearl Street Power Station in downtown Boulder. Fixed costs of that project are $10 million per year, and variable costs would be $35 per MWh. Should Boulder build or buy?

11. Tri-County G&T sells 150,000 MWh per year of electrical power to Boulder at $75 per MWh, has fixed costs of $82.5 million per year, and has variable costs of $25 per MWh. If Tri-County has 1,000,000 MWh of demand from its customers (other than Boulder), what will Tri-County have to charge to break even?

Preference Matrix

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DECISION MAKING SUPPLEMENT A 71

Decision Theory

a. Which location, A or B, should be chosen on the basis of the total weighted score?

b. If the factors were weighted equally, would the choice change?

15. Janice Gould of Krebs Consulting is in the process of making a recommendation to a client regarding the corporate-wide purchase of an analytical software plat-form. She has made the following estimates on manage-ment’s most important performance criteria and has rated three software packages across these criteria.

RATING

Performance CriterionFactor Weight

Software A

Software B

Software C

Functionality 25 9 8 9

Vendor reliability 10 7 5 9

RATING

Performance CriterionFactor Weight

Software A

Software B

Software C

Compatibility with current systems

20 6 8 6

Maintenance and support 10 5 5 8

Total cost 25 4 8 5

Speed of implementation 10 8 4 7

a. Which software platform would you recommend?

b. Assume that the client has a change of mind and now argues that the maintenance and support criterion is already accounted for by the total cost criterion. Fur-ther, the client asks Ms. Gould to drop maintenance and support and add its factor weight to total cost. Will this client request alter the recommendation?

16. Build-Rite Construction has received favorable publicity from guest appearances on a public TV home improve-ment program. Public TV programming decisions seem to be unpredictable, so Build-Rite cannot estimate the prob-ability of continued benefits from its relationship with the show. Demand for home improvements next year may be either low or high. But Build-Rite must decide now whether to hire more employees, do nothing, or develop subcontracts with other home improvement contractors. Build-Rite has developed the following payoff table:

DEMAND FOR HOME IMPROVEMENTS

Alternative Low Moderate High

Hire ($250,000) $100,000 $625,000

Subcontract $100,000 $150,000 $415,000

Do nothing $50,000 $80,000 $300,000

Which alternative is best, according to each of the follow-ing decision criteria?

a. Maximin

b. Maximax

c. Laplace

d. Minimax regret

17. Robert Ragsdale is trying to decide if he should pur-chase repair and replacement insurance on a new laptop computer that he is planning to purchase. The policy costs $400.00 at the time of purchase, and over the next 3 years will replace the laptop if it is stolen or repair it if it is broken. The following table contains the total costs of this decision.

AlternativeComputer Is Stolen

Computer Breaks

Computer Neither Breaks Nor Is Stolen

Buy the Insurance $2,900.00 $2,900.00 $2,900.00

Do Not Buy the Insurance $5,000.00 $3,100.00 $2,500.00

Which alternative is best, according to each of the follow-ing decision criteria?

a. Maximin

b. Maximax

c. Laplace

d. Minimax regret

18. Benjamin Moses, chief engineer of Offshore Chemicals, Inc., must decide whether to build a new processing facility based on an experimental technology. If the new facility works, the company will realize a net profit of $20 million. If the new facility fails, the company will lose $10 million. Benjamin’s best guess is that there is a 40 percent chance that the new facility will work.

What decision should Benjamin Moses make?

19. A manager is trying to decide whether to build a small, medium, or large facility. Demand can be low, average, or high, with the estimated probabilities being 0.25, 0.40, and 0.35, respectively.

A small facility is expected to earn an after-tax net present value of just $18,000 if demand is low. If demand is average, the small facility is expected to earn $75,000; it can be increased to medium size to earn a net present value of $60,000. If demand is high, the small facility is expected to earn $75,000 and can be expanded to medium size to earn $60,000 or to large size to earn $125,000.

A medium-sized facility is expected to lose an esti-mated $25,000 if demand is low and earn $140,000 if demand is average. If demand is high, the medium-sized facility is expected to earn a net present value of $150,000; it can be expanded to a large size for a net payoff of $145,000.

If a large facility is built and demand is high, earnings are expected to be $220,000. If demand is average for the large facility, the present value is expected to be $125,000; if demand is low, the facility is expected to lose $60,000.

Which alternative is best, according to each of the following decision criterion?

a. Maximin

b. Maximax

c. Minimax regret

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72 PART 1 MANAGING PROCESSES

Decision Trees20. Draw a decision tree for the three options described in

Problem 19. What should management do to achieve the highest expected payoff?

21. The owner of Pearl Automotive Dealers is trying to decide whether to expand his current facility. If he expands and customer demand turns weak, there is a chance he could lease part of his newly constructed facility to another dealer. If he doesn’t expand and strong demand occurs, he could attempt to lease another facility across town. Analyze the decision tree in Figure A.8. What is the best set of decisions and the expected payoff?

▲ FIGURE A.8

Lease New Facility

Do Not Lease New Facility

Property Is NotLeased (80%)

Propert

y is

Leased

(20%)

Propert

y Is

Leased

(20%)

Lease New Facility

Expa

ndFa

cility

Do Not Expand

Facility

Do Not Lease New Facility

Property Is NotLeased (80%)

$2,000,000

Stron

g Prod

uct D

eman

d (50

%)

Strong Product

Demand (50%)

Weak ProductDemand (30%)

Weak Product Demand (30%)

Average

Product

Demand

(20%)

Average Product Demand (20%)

$1,200,000 $400,000

$100,000

$200,000$1,800,000

$1,200,000

$1,300,000

$900,000

$400,000

1

2

3

22. Analyze the decision tree in Figure A.9. What is the expected payoff for the best alternative? First, be sure to infer the missing probabilities.

▲ FIGURE A.9

[0.2]

2

Alternative 2

Alternat

ive 1

1

3

$24

[0.3]

[0.5]

[0.4]

[0.3]

[0.4]

[0.5]

$20

$26

$30

$20

$25

$18

$20

$30

$15

23. A manager is trying to decide whether to buy one machine or two. If only one is purchased and demand proves to be excessive, the second machine can be purchased later. Some sales will be lost, however, because the lead time for producing this type of machine is 6 months. In addition, the cost per machine will be lower if both are purchased at the same time. The probability of low demand is estimated to be 0.20. The after-tax net present value of the benefits from purchasing the two machines together is $90,000 if demand is low and $180,000 if demand is high.

If one machine is purchased and demand is low, the net present value is $120,000. If demand is high, the manager has three options. Doing nothing has a net present value of $120,000; subcontracting, $160,000; and buying the second machine, $140,000.

a. Draw a decision tree for this problem.

b. How many machines should the company buy initially? What is the expected payoff for this alternative?

24. A manufacturing plant has reached full capacity. The company must build a second plant—either small or large—at a nearby location. The demand is likely to be high or low. The probability of low demand is 0.3. If demand is low, the large plant has a present value of $5 million and the small plant, a present value of $8 million. If demand is high, the large plant pays off with a present value of $18 million, and the small plant with a present value of only $10 million. However, the small plant can be expanded later if demand proves to be high for a present value of $14 million.

a. Draw a decision tree for this problem.

b. What should management do to achieve the highest expected payoff?

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73

2.4 Discuss how process decisions should strategically fit together.

2.5 Compare and contrast the two commonly used strategies for change, and understand a systematic way to analyze and improve processes.

2.6 Discuss how to define, measure, and analyze processes.2.7 Identify the commonly used approaches for effectively

improving and controlling processes.

2.1 Understand the process structure in services and how to position a service process on the customer-contact matrix.

2.2 Understand the process structure in manufacturing and how to position a manufacturing process on the product-process matrix.

2.3 Explain the major process strategy decisions and their implications for operations.

LEARNING OBJECTIVES After reading this chapter, you should be able to:

PROCESS STRATEGY AND ANALYSIS

PART 1 Managing Processes

2

People walk by a CVS pharmacy on 3rd Avenue in Manhattan.Ro

man

Tira

spol

sky/

Shut

ters

tock

CVS Pharmacy

CVS Pharmacy is the largest pharmacy chain in the United States, with over 9,600 locations and 2015 revenues exceeding US$150 billion. Owned by CVS Health, it was originally opened as the Consumer

Value Store (CVS) in Lowell, Massachusetts, in 1963. By 2002, CVS had become one of America’s largest retail drugstores. While it sells a wide

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74 PART 1 MANAGING PROCESSES

assortment of merchandise including cosmetic products, greeting cards, and convenience foods among others, over two-thirds of its revenue is generated by the pharmacies. CVS also operates 1,100 MinuteClinic medical clinics and Diabetes Care Centers, which are staffed by nurse practitioners and physician assistants specializing in family health care. In response to the pandemic crisis in 2020, CVS Health partnered with the state of New York and also ramped up its testing capacity across the United States to nearly 1.5 million COVID-19 tests per month.

Despite a rapid growth and expansion in business, customer satisfaction in the pharmacies was declining because of increasing service failures in its order fulfillment process. This was an important issue because it increased the waiting time for customers and stressed employees working at the pickup stations. CVS deployed a task force team to identify the root causes behind the poor service and develop a set of process improvement strategies. The team found out that because they were not tracking the refill limits in the information system, customers would not find out whether they would get their refills until their next pickup visit. In addition, the drug utilization review system—which alerts potential threats arising from using the wrong drug or over-prescription and halts the order fulfillment based on the patient’s medication records and possible drug interactions that might take place—did not function flawlessly. While pharmacists were capable of resolving 90 percent of these problem cases through a follow-up review, the remaining 10 percent of the alerts required contacting a doctor, which would delay the prescription fulfillment. The automated insurance checking system also caused problems. When customers changed their insurers or jobs, or if there were typos in the script, the employee would have to contact the customer, insurer, or sometimes even the doctor to verify the information. CVS would still fill the prescription even when the insurance issue had not been resolved; however, the customer had to pay full price at the time of pickup. In addition to process failures and congestions within the store, there were also other factors that led to frustration at the customers’ end. For example, patients living with complex illnesses such as rheumatoid arthritis often faced difficulties in getting their medications via in-store visits. Walking into the store was not a pleasant experience for these patients, and to make matters worse, the pharmacy often did not have the required specialty drugs in storage.

After a thorough assessment, CVS implemented a number of changes to the existing process. Issues with the existing in-store order fulfillment process were addressed by reorganizing process flows. For example, CVS moved the data entry process to the beginning of order drop-off to make sure that all the information is acquired while the customer is still present. Next, CVS bundled all quality-related processes together into a quality assurance step to ensure that the pharmacists focused on the customers’ safety and getting the correct drug at the right dosage into the packaging. This step also included the drug utilization review. CVS also implemented visualization technology to enhance visibility of the current orders and pending tasks. An online “virtual queue” allowed workers at the pharmacy station to prioritize their work and focus their efforts on tasks that were congesting the waiting line. Finally, CVS launched an initiative called “Specialty Connect” to provide simpler ordering and delivery options to specialty

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 75

drug customers. Through this program, customers can place orders online to skip the line, or have medications delivered by mail. Patients could also consult a centralized group of clinical and insurance experts for assistance.

Implementing these process changes was not an easy task. CVS had to present the results of the task force team study, including interviews, analyses, observations, and videos, to the pharmacy supervisors to persuade them to adopt the recommendations. Diffusion of best practices relied on a network of pharmacy supervisors who would travel around their districts and initiate improvement projects. As a result, the customer satisfaction on waiting times improved and the overall satisfaction was greatly enhanced. This improvement in customer satisfaction resulted in increased pharmacy contributions to revenue and decreased customer complaints. Also, since its launch, Specialty Connect has served approximately 75,000 patients, with 97 percent reporting satisfaction with the program. Understanding and improving their core customer-facing service processes paid big dividends for CVS.1

In Chapter 1, we learned how firms create value by properly aligning their operationsstrategy with the competitive priorities and capabilities that they emphasize in the marketplace. In Part 1 of the book, we focus on managing internal processes of the firm, including the design and analysis of these processes (Chapter 2, “Process Strategy and Analysis”), measurement of process quality  (Chapter 3, “Quality and Performance”), understanding how elimination of waste can make processes more lean and efficient (Chapter 4, “Lean Systems”), management of process capacity and its constraints within different types of organizations (Chapter 5 “Capacity Planning,” and Chapter 6, Constraint Management,” respectively), and managing projects (Chapter 7, “Project Management”).

Processes involve the use of an organization’s resources to provide something of value and are perhaps the least understood and managed aspect of a business. No service can be provided and no product can be made without a process, and no process can exist without at least one service or product. Even with talented and motivated people, a firm cannot gain competitive advantage with faulty processes. Process decisions as such are strategic in nature. As we saw in Chapter 1, they should further a company’s long-term competitive goals. In making process deci-sions, managers focus on controlling such competi-tive priorities as quality, flexibility, time, and cost. As exemplified by CVS Pharmacy, process manage-ment is an ongoing activity, with the same princi-ples applying to both first-time and redesign choices. Many different choices are available in selecting human resources, equipment, outsourced services, materials, work flows, and methods that transform inputs into outputs. Another choice is which processes are to be done in-house and which processes are to be outsourced—that is, done out-side the firm and purchased as materials and ser-vices. This decision helps to define the supply chain, and is covered more fully in subsequent chapters.

In this chapter, we focus on process strategy, which specifies the pattern of decisions made in managing processes so that the processes will achieve their competitive priorities, as well as process analysis, which is the documentation and detailed understanding of how work is performed

1Sources: A. F. McAfee, “Pharmacy Service Improvement at CVS,” Harvard Business School (2006); C. Cramer, “CVS Caremark Hosts Grand Opening of State-of-the-Art Mail Service Pharmacy and Customer Center,” Dow Jones Newswires (2013); K. Sheridan, “CVS Revamps to Meet Specialty Medicine Needs,” InformationWeek (2015); https://en.wikipedia.org/wiki/CVS_Pharmacy (August 3, 2020).

process strategy

The pattern of decisions made in managing processes so that they will achieve their competitive priorities.

process analysis

The documentation and detailed understanding of how work is performed and how it can be redesigned.

Using Operations to Create Value

Part 1

Managing Processes

Designing andoperating processes inthe firm

Managing Supply Chains

Forecasting demands anddeveloping inventory plansand operating schedules

Designing an integrated andsustainable supply chain of

connected processes between firms

Managing Customer Demand

Managing Processes

Project Management

Process Strategy and AnalysisQuality and Performance

Lean SystemsCapacity Planning

Constraint Management

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76 PART 1 MANAGING PROCESSES

and how it can be redesigned. Process deci-sions directly affect the process itself and indirectly the services and the products that it provides. All parts of an organization, as well as external suppliers and customers across the supply chain, need to be involved to ensure that processes are providing the most value to their internal and external customers.

Process strategy guides a variety of pro-cess decisions, and in turn is guided by opera-tions strategy and the organization’s ability to obtain the resources necessary to support them. We begin by defining four basic process decisions: (1) process structure, (2) customer involvement, (3) resource flexibility, and (4) capital intensity. We discuss these deci-sions for both service and manufacturing pro-cesses. We pay particular attention to ways in which these decisions fit together, depending on factors such as competitive priorities, cus-tomer contact, and volume, which in turn lead to two basic change strategies for analyzing and modifying processes: (1) process reengineer-ing and (2) process improvement. Both these approaches need process analysis to identify and implement changes.

Three principles concerning process strat-egy are particularly important:

1. The key to successful process decisions is to make choices that fit the situation and thatmake sense together. They should not work at cross purposes, with one process optimizedat the expense of other processes. A more effective process is one that matches key processcharacteristics and has a close strategic fit.

2. Although this section of the text focuses on individual processes, they are the building blocksthat eventually create the firm’s whole supply chain. The cumulative effect on customersatisfaction and competitive advantage is huge.

3. Whether processes in the supply chain are performed internally or by outside suppliers andcustomers, management must pay particular attention to the interfaces between processes.Dealing with these interfaces underscores the need for cross-functional coordination.

Whether dealing with processes for offices, service providers, or manufacturers, operationsmanagers must consider four common process decisions. Figure 2.1 shows that they are all impor-tant steps toward an effective process design. These four decisions are best understood at the process or subprocess level rather than at the firm level.

▪▪ Process structure determines the process type relative to the kinds of resources needed, how resources are partitioned between them, and their key characteristics. A layout is the physical arrangement of operations (or departments) relative to each other.

▪▪ Customer involvement reflects the ways in which customers become part of the process and the extent of their participation.

▪▪ Resource flexibility is the ease with which employees and equipment can handle a wide variety of products, output levels, duties, and functions.

▪▪ Capital intensity is the mix of equipment and human skills in a process. The greater the cost of equipment relative to the cost of labor, the greater is the capital intensity.

The concepts that we develop around these four decisions establish a framework within which we can address the appropriate process design in every situation. We establish the patterns of choices that create a good fit between the four decisions. For example, if you walk through a manufacturing facility where materials flow smoothly from one workstation to the next (which we will define later to be a line process), you would be tempted to conclude that all processes should be line processes. They seem so efficient and organized. However, con-verting to a line process would be a big mistake if volumes are low and the products made are customized. Resources must be more flexible to handle a variety of products in such a situation. The result is a more disorganized appearance with jobs crisscrossing in many dif-ferent directions depending on the product being made. Despite appearances, this process is the best choice.

process structure

The process type relative to the kinds of resources needed, how resources are partitioned between them, and their key characteristics.

layout

The physical arrangement of operations (or departments) relative to each other.

customer involvement

The ways in which customers become part of the process and the extent of their participation.

resource flexibility

The ease with which employees and equipment can handle a wide variety of products, output levels, duties, and functions.

capital intensity

The mix of equipment and human skills in a process.

▲ FIGURE 2.1Major Decisions for Effective Processes

Layout• Block plan• Detailed layout

Process Structure• Customer-contact position

(services)• Product-process position

(manufacturing)

Capital Intensity• Low automation• High automation

Resource Flexibility• Specialized• Enlarged

Strategies for Change• Process reengineering• Process improvement

Customer Involvement• Low involvement• High involvement

Effective ProcessDesign

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 77

Process Structure in ServicesOne of the first decisions a manager makes in designing a well-functioning process is to choose a process type that best achieves the competitive priorities for that process. Strategies for designing processes can be quite different, depending on whether a service is being provided or a product is being manufactured. We begin with service processes, given their huge implication for workforce resources in industrialized countries.

A process strategy that gets customers in and out of a fast-food restaurant quickly would not be the right process strategy for a five-star restaurant, where customers seek a leisurely dining experience. To gain insights, we must start at the process level and recognize key contextual vari-ables associated with the process. A good process strategy for a service process depends first and foremost on the type and amount of customer contact. Customer contact is the extent to which the customer is present, is actively involved, and receives personal attention during the service process. Face-to-face interaction, sometimes called a moment of truth or service encounter, brings the customer and service providers together. At that time, customer attitudes about the quality of the service provided are shaped. Table 2.1 shows several dimen-sions of customer contact. Many levels are possible on each of the five dimensions. Also, some parts of a process can have low contact and other parts of a process can have high contact.

Customer-Contact MatrixThe customer-contact matrix, shown in Figure 2.2, brings together three elements: (1) the degree of customer contact, (2) customiza-tion, and (3) process characteristics. The matrix is the starting point for evaluating and improving a process.

Customer Contact and Customization The horizontal dimension of the matrix represents the service provided to the customer in terms of customer contact and competitive priorities. A key com-petitive priority is how much customization is needed. Positions on the left side of the matrix represent high customer contact and highly customized services. The customer is more likely to be present and active. The process is more likely to be visible to the customer, who receives more personal attention. The right side of the matrix represents low customer contact, passive involve-ment, less personalized attention, and a process out of the customer’s sight.

Process Divergence and Flow The vertical dimension of the customer-contact matrix deals with two characteristics of the process itself: (1) process divergence and (2) flow. Each process can be analyzed on these two dimensions.

customer contact

The extent to which the customer is present, is actively involved, and receives personal attention during the service process.

Dimension High Contact Low Contact

Physical presence Present Absent

What is processed People Possessions or information

Contact intensity Active, visible Passive, out of sight

Personal attention Personal Impersonal

Method of delivery Face to face Regular mail or email

TABLE 2.1 | DIMENSIONS OF CUSTOMER CONTACT INSERVICE PROCESSES

◀ FIGURE 2.2Customer-Contact Matrix for Service Processes

ProcessCharacteristics

Hybrid office

Back office

(3)Low interaction withcustomers, standardizedservices

(2)Some interaction with customers, standard services with some options

(1) High interaction with customers, highly customized service

Front office

(1)Flexible flows withindividualized processes

(2)Flexible flows withsome dominantpaths, with someexceptions as to howwork performed

(3)Line flows, routinework performed thesame with all customers

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78 PART 1 MANAGING PROCESSES

Process divergence is the extent to which the process is highly customized with considerable latitude as to how its tasks are performed. If the process changes with each customer, virtually every performance of the service is unique. Examples of highly divergent service processes where many steps in them change with each customer are found in consulting, law, and architecture. A service with low divergence, in contrast, is repetitive and standardized. The work is performed exactly the same with all customers and tends to be less complex. Certain hotel services and telephone services are highly standardized to ensure uniformity.

When divergence is considerable, the work flow tends to be more flexible. A flexible flow means that the customers, materials, or information moves in diverse ways, with the path of one customer or job often crisscrossing the path that the next one takes. Each one can follow a carefully preplanned path, even though the first impression is one of disorganized, jumbled flows. Such an appearance goes naturally with high process divergence. A line flow means that the customers, materials, or information moves linearly from one operation to the next, according to a fixed sequence. When diversity is low and the process standardized, line flows are a natural consequence.

Service Process StructuringFigure 2.2 shows several desirable positions in the matrix that effectively connect the service product with the process. The manager has three process structures, which form a continuum, to choose from: (1) front office, (2) hybrid office, and (3) back office. It is unlikely that a process can be a top performer if a process lies too far from one of these diagonal positions, occupying instead one of the extreme positions represented by the light blue triangles in the matrix (refer to Figure 2.2). Such posi-tions represent too much of a disconnect between the service provided and process characteristics.

Front Office A front-office process has high customer contact where the service provider inter-acts directly with the internal or external customer. Because of the customization of the service and variety of service options, many of the steps in it have considerable divergence. Work flows are flexible, and they vary from one customer to the next. The high-contact service process tends to be adapted or tailored to each customer.

Hybrid Office A hybrid office tends to be in the middle of the five dimensions in Table 2.1, or perhaps high on some contact measures and low on others. A hybrid-office process has moder-ate levels of customer contact and standard services, with some options available from which the customer chooses. The work flow progresses from one workstation to the next, with some dominant paths apparent.

Back Office A back-office process has low customer contact and little service customization. The work is standardized and routine, with line flows from one service provider to the next until the service is completed. Preparing the monthly client fund balance reports in the financial ser-vices industry is a good example. It has low customer contact, low divergence, and a line flow.

Process Structure in ManufacturingMany processes at a manufacturing firm are actually services to internal or external customers, and so the previous discussion on services applies to them. Similarly, manufacturing processes can be found in service firms. Clarity comes when view-ing work at the process level, rather than the organizational level. Here we focus instead on the manufacturing processes. Because of the differences between ser-vice and manufacturing processes, we need a different view on process structure.

Product-Process MatrixThe product-process matrix (Figure 2.3) brings together three elements: (1) volume, (2) product customization, and (3) process characteristics. It synchronizes the prod-uct to be manufactured with the manufac-turing process itself.

A good strategy for a manufacturing process depends first and foremost on

process divergence

The extent to which the process is highly customized with considerable latitude as to how its tasks are performed.

flexible flow

The customers, materials, or information moves in diverse ways, with the path of one customer or job often crisscrossing the path that the next one takes.

line flow

The customers, materials, or information moves linearly from one operation to the next, according to a fixed sequence.

front office

A process with high customer contact where the service provider interacts directly with the internal or external customer.

hybrid office

A process with moderate levels of customer contact and standard services with some options available.

back office

A process with low customer contact and little service customization.

A financial consultant discusses options with a couple at their home. This process scores high on customer contact, because the customers are present, take an active part in creating the service, receive personal attention, and have a face-to-face meeting.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 79

volume. Customer contact, a primary feature of the customer-contact matrix for services, normally is not a consideration for manufacturing processes (although it is a factor for the many service processes throughout manufacturing firms). For many manufacturing pro-cesses, high product customization means lower vol-umes for many of the steps in the process. The vertical dimension of the product-process matrix deals with the same two characteristics in the customer-contact matrix: process divergence and flow. Each manu-facturing process should be analyzed on these two dimensions, just as was done for a service process.

Manufacturing Process StructuringFigure 2.3 shows several desirable positions (often called process choices) in the product-process matrix that effectively connect the manufactured product with the process. Process choice is the way of struc-turing the process by organizing resources around the process or organizing them around the products. Organizing around the process means, for example, that all milling machines are grouped together and process all products or parts needing that kind of transformation. Organizing around the product means bringing together all the different human resources and equipment needed for a specific product and dedicating them to producing just that product. The manager has four process choices, which form a continuum, to choose from: (1) job process, (2) batch process, (3) line process, and (4) continuous-flow process. As with the customer-contact matrix, it is unlikely that a manufacturing process can be a top performer if its position is too far from the diagonal. The fundamental message in Figure 2.3 is that the best choice for a manufacturing process depends on the volume and degree of customization required of the process. The process choice might apply to an entire manufacturing process or just one subprocess nested within it.

process choice

A way of structuring the process by organizing resources around the process or organizing them around the products.

Line flows at a Five Guys Burgers and Fries location in Brooklyn, New York showing production of hamburgers and fries on an assembly line.

▼ FIGURE 2.3Product-Process Matrix for Manufacturing Processes

(1)Customized process, with flexible and unique sequenceof tasks

(2)Disconnected line flows, moderately repetitive work

(3)Connected line, highly repetitive work

(4)Continuous flows

(1)Low-volumeproducts, made to customer order

(2)Multiple products, with low to moderate volume

(3)Few major products,higher volume

(4)High volume, highstandardization, commodity products

Jobprocess

Small batchprocess

Large batchprocess

Batch processes

Lineprocess

Continuous-flow process

Process Characteristics

Less customization and higher volume

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80 PART 1 MANAGING PROCESSES

Job Process A job process creates the flexibility needed to produce a wide variety of products in sig-nificant quantities, with considerable divergence in the steps performed. Customization is high and vol-ume for any one product is low. The workforce and equipment are flexible to handle considerable task divergence. Companies choosing job processes often bid for work. Typically, they make products to order and do not produce them ahead of time. Each new order is handled as a single unit—that is, as a job. Examples are machining a metal casting for a cus-tomized order or producing customized cabinets.

With a job process, all equipment and workers capable of certain types of work are positioned together. Because customization is high and most jobs have a different sequence of steps, this process choice creates flexible flows through the operations rather than a line flow.

Batch Process The batch process is by far the most common process choice found in practice, leading to terms such as small batch or large batch to fur-ther distinguish one process choice from another.

A batch process differs from the job process with respect to volume, variety, and quantity. The primary difference is that volumes are higher because the same or similar products or parts going into them are produced repeatedly. Some of the components going into the final product may be processed in advance. Production lots are handled in larger quantities (or batches) than they are with job processes. A batch of one product (or component part going into it or perhaps other prod-ucts) is processed, and then production is switched to the next one. Eventually, the first product is produced again. A batch process has average or moderate volumes, but process divergence is still too great to warrant dedicating a separate process for each product. The process flow is flexible, but more dominant paths emerge than at a job process, and some segments of the process have a line flow. Examples of a batch process are making standard components that feed an assembly line or some processes that manufacture capital equipment.

Line Process A line process lies between the batch and continuous processes on the continuum; volumes are high and products are standardized, which allows resources to be organized around particular products. Divergence is minimal in the process or line flows, and little inventory is held between the processing steps. Each step performs the same process over and over, with little variability in the products manufactured. Production and material handling equipment is special-ized. Products created by a line process include the assembly of computers, automobiles, appli-ances, and toys.

Standard products are produced in advance of their need and held in inventory so that they are ready when a customer places an order. Product variety is possible by careful control of the addition of standard options to the main product.

Continuous-Flow Process A continuous-flow process is the extreme end of high-volume stan-dardized production, with rigid line flows. Process divergence is negligible. Its name derives from the way materials move through the process. Usually, one primary material (such as a liquid, a gas, or a powder) moves without stopping through the process. A continuous-flow process differs from a line process in one important respect: Materials (be they undifferentiated or discrete) flow through the process without stopping until the whole batch is finished. The time span can be several shifts or even several months. Examples of a continuous-flow process are petroleum refin-ing; chemical processes; paper manufacturing; and processes making steel, soft drinks, and food.

Production and Inventory StrategiesStrategies for manufacturing processes differ from those in services not only because of low customer contact and involvement but also because of the ability to use inventories not only as purchased materials but also in the form of subassemblies or finished products. As we learned in Chapter 1, there are clearly exceptions to this rule, as Avis has an inventory of autos to rent, and FedEx has an inventory of in-process parcels. Design-to-order, make-to-order, assemble-to-order, and make-to-stock strategies are four approaches to inventory that should be coordinated with process choice.

Design-to-Order Strategy A firm uses a design-to-order strategy when it can design new products that do not currently exist, and then manufacture them to meet unique customer specifications. Typically a job process is employed to create a highly customized product, such as a designer pair of shoes for a particular client.

job process

A process with the flexibility needed to produce a wide variety of products in significant quantities, with considerable divergence in the steps performed.

batch process

A process that differs from the job process with respect to volume, variety, and quantity.

line process

A process that lies between the batch and continuous processes on the continuum; volumes are high and products are standardized, which allows resources to be organized around particular products.

continuous-flow process

The extreme end of high-volume standardized production and rigid line flows, with production not starting and stopping for long time intervals.

design-to-order strategy

A strategy that involves designing new products that do not currently exist, and then manufacturing them to meet unique customer specifications.

A job shop manufacturing floor, with workers in different areas of the shop processing different operations for creating a product.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 81

Make-to-Order Strategy Manufacturers that make products to customer specifications in low vol-umes tend to use the make-to-order strategy, coupling it with job or small batch processes. Even though the product is based on a standard design, it is a more complex process than assembling a final product from standard components. This strategy provides a high degree of customization and typically uses job or small batch processes. The processes have high divergence. Specialized medical equipment, castings, and expensive homes are suited to the make-to-order strategy.

Assemble-to-Order Strategy The assemble-to-order strategy is an approach to producing a wide variety of products from relatively few subassemblies and components after the customer orders are received. Typical competitive priorities are variety and fast delivery times. The assemble-to-order strategy often involves a line process for assembly and a batch process for fabrication. Because they are devoted to manufacturing standardized components and subassemblies in high volumes, the fabrication processes focus on creating appropriate amounts of component invento-ries for the assembly processes. Once the specific order from the customer is received, the assem-bly processes create the product from standardized components and subassemblies produced by the fabrication processes.

Stocking finished products would be economically prohibitive because the numerous pos-sible options make forecasting relatively inaccurate. Thus, the principle of postponement is applied, whereby the final activities in the provision of a product are delayed until the orders are received. The assemble-to-order strategy is also linked to mass customization, where highly diver-gent processes generate a wide variety of customized products at reasonably low costs.  Both postponement and mass customization are covered more fully in Chapter 12, “Supply Chain Design.”

Make-to-Stock Strategy Manufacturing firms that hold items in stock for immediate delivery, thereby minimizing customer delivery times, use a make-to-stock strategy. This strategy is fea-sible for standardized products with high volumes and reasonably accurate forecasts. It is the inventory strategy of choice for line or continuous-flow processes. Examples of products produced with a make-to-stock strategy include garden tools, electronic components, soft drinks, and chemicals.

Combining a line process with the make-to-stock strategy is sometimes called mass production. It is what the popular press commonly envisions as the classical manufacturing process, because the environment is stable and predictable, with workers repeating narrowly defined tasks with low divergence.

LayoutSelecting process structures for the various processes housed in a facility is a strategic decision, but must be followed by a more tactical decision—creating a layout. A layout is the physical arrangement of operations (or departments) created from the various processes and puts them in tangible form. For organizational purposes, processes tend to be clustered together into operations or departments. An operation is a group of human and capital resources performing all or part of one or more processes. For example, an operation could be several customer service representa-tives in a customer reception area; a group of machines and workers producing cell phones; or a marketing department. Regardless of how processes are grouped together organizationally, many of them cut across departmental boundaries. The flows across departmental lines could be informa-tional, services, or products. Process structures that create more flows across departmental lines, as with job or batch processes, are the most challenging layout problems. Supplement K, “Layout,” provides a more in-depth analysis of how to gather information and develop detailed layout plans.

Process Strategy DecisionsHaving covered process structure decisions in both service and manufacturing organizations, we turn our attention now to the other three major process strategy decisions shown in Figure 2.1— customer involvement, resource flexibility, and capital intensity.

Customer InvolvementCustomer involvement reflects the ways in which customers become part of the process and the extent of their participation. It is especially important for many service processes, particularly if customer contact is (or should be) high.

Possible Advantages The advantages of a more customer-focused process might increase the net value to the customer. Some customers seek active participation in and control over the ser-vice process, particularly if they will enjoy savings in both price and time. The manager must assess whether advantages outweigh disadvantages, judging them in terms of the competitive priorities and customer satisfaction. More customer involvement can mean better quality, faster

make-to-order strategy

A strategy used by manufacturers that make products to customer specifications in low volumes.

assemble-to-order strategy

A strategy for producing a wide variety of products from relatively few subassemblies and components after the customer orders are received.

postponement

The strategy of delaying final activities in the provision of a product until the orders are received.

mass customization

The strategy that uses highly divergent processes to generate a wide variety of customized products at reasonably low costs.

make-to-stock strategy

A strategy that involves holding items in stock for immediate delivery, thereby minimizing customer delivery times.

mass production

A term sometimes used in the popular press for a line process that uses the make-to-stock strategy.

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82 PART 1 MANAGING PROCESSES

delivery,  greater flexibility, and even lower cost. Self- service is the choice of many retailers, such as gasoline stations, supermarkets, and bank services. Manufacturers of products (such as toys, bicycles, and furniture) may also prefer to let the customer perform the final assem-bly  because product, shipping, and inventory costs fre-quently are lower. In fact, IKEA Furniture Company’s business model is based on customers being actively involved in its processes.

Customer involvement can also help coordinate across the supply chain  (see Chapter 14, “Supply Chain Integration”). Emerging technologies allow companies to engage in an active dialogue with customers and make them partners in creating value and forecasting future demand. Suppliers to automobile companies can be close collaborators in the process of developing new vehicles and are no longer passive providers of materials and services. The same is true for distributors. Walmart does more than

just distribute Procter & Gamble’s products: It shares daily sales information and works with Procter & Gamble in managing inventories and warehousing operations.

Possible Disadvantages Customer involvement is not always a good idea. In some cases, giving the customer more active contact in a service process will just be disruptive, making the process less efficient. Managing the timing and volume of customer demands becomes more challenging if the customer is physically present and expects prompt delivery. Exposing the facilities and employees to the customer can have important quality implications (favorable or unfavorable). Such changes make interpersonal skills a prerequisite to the service provider’s job, but higher skill levels come at a cost. It also might mean having many smaller decentralized facilities closer to the various customer concentration areas if the customer comes to the service providers.

Resource FlexibilityJust as managers must account for customer contact when making customer involvement deci-sions, so must they account for process divergence and diverse process flows when making resource flexibility decisions in Figure 2.1. For example, high task divergence and flexible process flows require more flexibility of the process’s resources—its employees, facilities, and equipment. Employees need to perform a broad range of duties, and equipment must be general purpose. Otherwise, resource utilization will be too low for economical operations.

Workforce Operations managers must decide whether to have a flexible workforce. Members of a flexible workforce are capable of doing many tasks, either at their own workstations or as they move from one workstation to another. However, such flexibility often comes at a cost, requiring greater skills and thus more training and education. Nevertheless, benefits can be large: Worker flexibility can be one of the best ways to achieve reliable customer service and alleviate capacity bottlenecks. Resource flexibility helps to absorb the feast-or-famine workloads in individual

operations that are caused by low-volume production, divergent tasks, flexible flows, and fluid scheduling.

The type of workforce required also depends on the need for volume flexibility. When conditions allow for a smooth, steady rate of output, the likely choice is a permanent workforce that expects regular full-time employment. If the process is subject to hourly, daily, or seasonal peaks and valleys in demand, the use of part-time or temporary employees to supplement a smaller core of full-time employees may be the best solution. However, this approach may not be practical if knowledge and skill requirements are too high for a temporary worker to grasp quickly.

Equipment Low volumes mean that process designers should select flexible, general-purpose equipment. Figure 2.4 illustrates this relationship by showing the total cost lines for two different types of equipment that can be chosen for a pro-cess. Each line represents the total annual cost of the process at different volume levels. It is the sum of fixed costs and variable costs  (see Supplement A, “Decision Making”). When volumes are low (because

Online ResourceTutor 2.1 in OM Explorer demonstrates how to do break-even analysis for equipment selection.

flexible workforce

A workforce whose members are capable of doing many tasks, either at their own workstations or as they move from one workstation to another.

Customers use the Create Your Taste self-ordering kiosk in the McDonald’s on the 2500 block of Ogden Avenue in Downers Grove, Ill. It allows customers to directly place their order including the toppings, size, and sides.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 83

customization is high), process 1 is the better choice. It calls for inexpensive general-purpose equipment, which keeps investment in equipment low and makes fixed costs (F1) small. Its variable unit cost is high, which gives its total cost line a relatively steep slope. Process 1 does the job, but not at peak efficiency.

Conversely, process 2 is the better choice when volumes are high and customization is low. Its advantage is low variable unit cost, as reflected in the flatter total cost line. This efficiency is possible when customization is low because the equipment can be designed for a narrow range of products or tasks. Its disadvantage is high equipment investment and, thus, high fixed costs (F2). When annual volume produced is high enough, spreading these fixed costs over more units produced, the advantage of low variable costs more than compen-sates for the high fixed costs.

The break-even quantity in Figure 2.4 is the quantity at which the total costs for the two alternatives are equal. At quantities beyond this point, the cost of process 1 exceeds that of process 2. Unless the firm expects to sell more than the break-even amount, which is unlikely with high customization and low volume, the capital investment of process 2 is not warranted.

Capital IntensityCapital intensity is the mix of equipment and human skills in the process; the greater the cost of equipment relative to the cost of labor, the greater is the capital intensity. As the capabilities of technology increase and its costs decrease, managers face an ever-widening range of choices, from operations utilizing very little automation to those requiring task-specific equipment and little human intervention. Automation is a system, process, or piece of equipment that is self-acting and self-regulating. Although automation is often thought to be necessary to gain competitive advantage, it has both advantages and disadvantages. Thus, the automa-tion decision requires careful examination.

Automating Manufacturing Processes Substituting labor-saving capital equipment and technology for labor has been a classic way of improving productivity and quality consistency in manufacturing processes. If invest-ment costs are large, automation works best when volume is high, because more customization typically means reduced volume. Gillette, for example, spent $750 million on the production lines and robotics that gave it a capac-ity to make 1.2 billion razor cartridges a year. The equip-ment is complicated and expensive. Only with such high volumes could this line process produce the product at a price low enough that consumers could afford to buy it.

One big disadvantage of capital intensity can be the prohibitive investment cost for low-volume operations (see Figure 2.4). Generally, capital-intensive opera-tions must have high utilization to be justifiable. Also, automation does not always align with a company’s competitive priorities. If a firm offers a unique prod-uct or high-quality service, competitive priorities may indicate the need for hand labor and individual atten-tion rather than new technology. A case in point is the downstream processes in Gillette’s supply chain that package and store the razor cartridges. It customizes the packaging for different regions of the world, so that volumes for any one type of package are much lower. As a result of the low volumes, Gillette does not use expensive automation for these processes. In fact, it out-sources them. It produces razor cartridges to stock using highly automated processes and then packages them in customized fashion at remote locations on demand.

automation

A system, process, or piece of equipment that is self-acting and self-regulating.

▲ FIGURE 2.4Relationship Between Process Costs and Product Volume

Units per year (Q )

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Break-even quantity

Process 2: Special-purpose equipment

Process 1: General-purpose equipment

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R.R. Donnelly has been able to achieve flexible automation by receiving books digitally and preparing them to go on press electronically. This allows the company to put books on press more quickly and print smaller, more manageable quantities in a single print run.

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Manufacturers use two types of automation: (1) fixed and (2) flexible (or programmable). Particularly appropriate for line and continuous-flow process choices, fixed automation produces one type of part or product in a fixed sequence of simple operations. Operations managers favor fixed automation when demand volumes are high, product designs are stable, and product life cycles are long. These conditions compensate for the process’s two primary drawbacks: (1) large initial investment cost and (2) relative inflexibility. However, fixed automation maximizes effi-ciency and yields the lowest variable cost per unit if volumes are high.

Flexible (or programmable) automation can be changed easily to handle various products. The ability to reprogram machines is useful for both low- and high-customization processes. In the case of high customization, a machine that makes a variety of products in small batches can be programmed to alternate between products. When a machine has been dedicated to a particular product or family of products, as in the case of low customization and a line flow, and the product is at the end of its life cycle, the machine can simply be reprogrammed with a new sequence of tasks for a new product. An industrial robot, which is a versatile, computer-controlled machine programmed to perform various tasks, is a classic example of flexible automation. These “steel-collar” workers operate independently of human control. A robot’s arm has up to six standard movements. The robot’s “hand” can be changed to perform different tasks, such as materials handling, assembly, and testing. Machine learning and artificial intelligence technologies allow machines to learn from observed rules, as well as screening and sorting algorithms in detecting product defects and abusive customers, or even functioning as automated secretaries.

Automating Service Processes Using capital inputs as a labor-saving device is also possible for service processes. In educational services, for example, long-distance learning technology now can supplement or even replace the traditional classroom experience by using books, computers, web-sites, and videos as facilitating goods that go with the service. Justifying technology need not be limited to cost reduction. Sometimes, it can actually allow more task divergence by making available a wide menu of choices to the customer. It can also improve quality by being more consistent.

The need for volume to justify expensive automation is just as valid for service processes as for manufacturing processes. Increasing the volume lowers the cost per dollar of sales. Volume is essential for many capital-intensive processes in the transportation, communications, and utili-ties industries.

Economies of Scope If capital intensity is high, resource flexibility usually is low. In certain types of manufacturing operations, such as machining and assembly, programmable automation breaks this inverse relationship between resource flexibility and capital intensity. It makes possible both high capital intensity and high resource flexibility, creating economies of scope. Economies of scope reflect the ability to produce multiple products more cheaply in combination than separately. In such situations, two conflicting competitive priorities—customization and low price—become more compatible. However, taking advantage of economies of scope requires that a family of parts or products have enough collective volume to utilize equipment fully. Another enabler of economies of scope is additive manufacturing, which refers to three-dimensional (3D) printing technology. It allows firms to react to a wider variety of demands without incurring additional cost. Changes in designs or added complexity due to customized customer specifications can be incorporated by simply tweaking the 3D blueprint of the product. Simply by acquiring such additive manufacturing

capabilities  as described in Chapter 1, “Using Operations to Create Value,” firms are able to achieve substantial economies of scope.

Economies of scope also apply to service pro-cesses. Consider, for example, Disney, whose managers used the Internet to reap the benefits of economies of scope. They aggressively linked their Internet processes with one another and with other parts of Disney. A flexible technology that handles many services together can be less expen-sive than handling each one separately, particu-larly when the markets are not too volatile.

Strategic FitThe manager should understand how the four major process decisions tie together, so as to spot ways of improving poorly designed processes. The choices should fit the situation and each other. When the fit is more strategic, the process will be more effective. We examine services and manu-facturing processes, looking for ways to test for strategic fit.

fixed automation

A manufacturing process that produces one type of part or product in a fixed sequence of simple operations.

flexible (or programmable) automation

A manufacturing process that can be changed easily to handle various products.

industrial robot

Versatile, computer-controlled machine programmed to perform various tasks.

economies of scope

Economies that reflect the ability to produce multiple products more cheaply in combination than separately.

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Decision Patterns for Service ProcessesAfter analyzing a process and determining its position on the customer-contact matrix in Figure 2.2, it may be apparent that it is improperly positioned, either too far to the left or right, or too far to the top or bottom. Opportunities for improvement become apparent. Perhaps, more customiza-tion and customer contact is needed than the process currently provides. Perhaps, instead, the process is too divergent, with unnecessarily flexible flows. Reducing divergence might reduce costs and improve productivity.

The process should reflect its desired competitive priorities. Front offices generally empha-size top quality and customization, whereas back offices are more likely to emphasize low-cost operation, consistent quality, and on-time delivery. The process structure selected then points the way to appropriate choices on customer involvement, resource flexibility, and capital intensity. High customer contact at a front-office service process means:

1. Process Structure. The customer (internal or external) is present, actively involved, and receives personal attention. These conditions create processes with high divergence and flexible process flows.

2. Customer Involvement. When customer contact is high, customers are more likely to become part of the process. The service created for each customer is unique.

3. Resource Flexibility. High process divergence and flexible process flows fit with more flex-ibility from the process’s resources—its workforce, facilities, and equipment.

4. Capital Intensity. When volume is higher, automation and capital intensity are more likely. Even though higher volume is usually assumed in the back office, it is just as likely to be in the front office for financial services. Information technology is a major type of automation at many service processes, which brings together both resource flexibility and automation.

Of course, this list provides general tendencies rather than rigid prescriptions. Exceptions can be found, but these relationships provide a way of understanding how service process decisions can be linked coherently.

Decision Patterns for Manufacturing ProcessesJust as a service process can be repositioned in the customer-contact matrix, a manufacturing process can also be moved in the product-process matrix. Changes can be made either in the horizontal direction of Figure 2.3 by changing the degree of customization and volume, or they can be moved in the vertical direction by changing process divergence. Competitive priorities must be considered when translating strategy into spe-cific manufacturing processes. Figure 2.5 shows some usual tendencies found in practice. Job and small batch processes are usual choices if top quality, on-time deliv-ery, and flexibility (customization, variety, and volume flexibility) are given primary emphasis. Large batch, line, and continuous-flow processes match up with an emphasis on low-cost operations, consistent quality, and delivery speed.

The production and inventory strategy should also be chosen to be consistent with the competitive priorities emphasized. As shown in Figure 2.5, the design-to-order strategy is consistent with top quality, customization, and variety. The focus is on meeting the unique needs of the customers by specifically designing a variety of products according to the customer speci-fications. The make-to-order strategy matches up with flexibility (particularly customization) and top qual-ity. Because delivery speed is more difficult, meeting due dates and on-time delivery get the emphasis on the time dimension. The assemble-to-order strategy allows delivery speed and flexibility (particularly variety) to be achieved, whereas the make-to-stock strategy is the usual choice if delivery speed and low-cost operations are emphasized. Keeping an item in stock ensures quick delivery because it is generally available when needed, without delays in producing it. High volumes open up opportunities to reduce costs.

The process structure selected once again points the way to appropriate choices on customer involvement,

▼ FIGURE 2.5Links of Competitive Priorities with Manufacturing Strategy

Top quality, on-time delivery,and flexibility

(a) Links with Process Choice

Job process orsmall batch process

Low-cost operations, consistentquality, and delivery speed

Large batch, line, orcontinuous-flow process

Competitive Priorities Process Choice

Top quality, on-time delivery,and flexibility

Make-to-order

Delivery speed and variety Assemble-to-order

Top quality, customization,and variety

Design-to-order

(b) Links with Production and Inventory Strategy

Low-cost operation and delivery speed

Make-to-stock

Competitive Priorities Production and Inventory Strategy

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86 PART 1 MANAGING PROCESSES

resource flexibility, and capital intensity. High volumes per part type at a manufacturing process typically mean:

1. Process Structure. High volumes, combined with a standard product, make a line flow possible. It is just the opposite where a job process produces to specific customer orders.

2. Customer Involvement. Customer involvement is not a factor in most manufacturing processes, except for choices made on product variety and customization. Less discretion is allowed with line or continuous-flow processes to avoid the unpredictable demands required by custom-ized orders.

3. Resource Flexibility. When volumes are high and process divergence is low, flexibility is not needed to utilize resources effectively, and specialization can lead to more efficient processes.

4. Capital Intensity. High volumes justify the large fixed costs of an effi-cient operation.

Gaining FocusIn the past, new services or products often were added to a facility in the name of better utilizing fixed costs and keeping everything under the same roof. The result was a jumble of competitive priorities, process structures, and technologies. In the effort to do everything, nothing was done well. A process that aims to achieve low cost and efficiency should not be mixed with a process that needs to be flexible and offer a large product variety. Focus means choosing one or the other, but not both simultaneously in the same facility.

Focus by Process Segments A facility’s operations often can be neither characterized nor actually designed for one set of competitive priorities and one process choice. At a services facility, some parts of the process might seem like a front office and other parts like a back office. Such arrangements can be effective, provided that sufficient focus is given to each process by the management segmenting them into separate operations that are rela-tively autonomous.

Plants within plants (PWPs) are different operations within a facility with individualized competitive priorities, processes, and workforces under the same roof. Boundaries for PWPs may be established by physically

separating subunits or simply by revising organizational relationships. At each PWP, customization, capital intensity volume, and other relationships are crucial and must be complementary. The advantages of PWPs are fewer layers of management, greater ability to rely on team problem solving, and shorter lines of communication between departments. As illustrated in Managerial Practice 2.1, Ford Corporation has adopted a PWP-focused strategy at its highly successful Camacari plant in Brazil, where several suppliers produce parts under the same roof as the original manufacturer.

plants within plants (PWPs)

Different operations within a facility with individualized competitive pri-orities, processes, and workforces under the same roof.

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MANAGERIAL PRACTICE Plants-Within-a-Plant at Ford Camacari

Ford Motor Company is a global automotive company with manufacturing operations located worldwide, including Brazil, Canada, China, Mexico, United Kingdom, and United States, among many others. Its Ford do Brasil subsidiary was established in 1919, and underwent several transfor-mations in its ownership structure and range of manufacturing and assembly operations over the past hundred years. In Bahia, Camacari, a city in the rural northeast region of Brazil, Ford has invested over $4 billion to build one of the most advanced automobile factories in the world. Ford Ecosport Mini SUV and the Ford Fiesta models for the Brazilian market and other developing countries are manufactured here. The Camacari plant, which opened in 2001, is more automated than several of Ford’s facilities in the United States, with more robots here than in many U.S. plants. Ford Camacari is also one of the most flexible factories in the world, capable of producing five different vehicle platforms at the same time on the same line. Ford owns the land and buildings, and all employees on the site are registered on a single human resource system.

However, the real revolution at Camacari lies in the close integration of Ford suppliers in the assembly process, while retaining individual processes and workforces for each supplier. The idea is to involve suppliers right from the vehicle’s design stage to the final assembly. By locating the suppli-ers within the vehicle’s manufacturing facility, the respective modules are manufactured and delivered to the main assembly line, with little logistics involved. While Ford controls the final assembly process, 21 component suppliers and 4 service providers are located on the site. Eight additional component suppliers are located offsite, but in close vicinity. Of the 21 component suppliers, 10 are in the final assembly area, which forms the “plants-within-a-plant” (PWP) configuration. They are Faurecia (door module), Visteon (cockpit), Pelzer (soft trim), Interim (headliner), Lear (seats), Mapri-Textron (fasteners), Valeo (front-end module), Benteler (suspension), ArvinMeritor (exhaust), and Pireli (tire assembly). Each supplier manages its own production processes and line settings on the site, and maintains its own

2.1

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Focused Service Operations Service industries also implement the concepts of focus and PWPs. Specialty retailers opened stores with smaller, more accessible spaces. These focused facilities generally chipped away at the business of large department stores. Using the same philosophy, some department stores now focus on specific customers or products. Remodeled stores create the effect of many small boutiques under one roof.

Focused Factories Hewlett-Packard, Rolls-Royce, Japan’s Ricoh and Mitsubishi, and Britain’s Imperial Chemical Industries PLC are some of the firms that created focused factories, splitting large plants that produced all the company’s products into several specialized smaller plants. The theory is that narrowing the range of demands on a facility will lead to better performance because management can concentrate on fewer tasks and lead a workforce toward a single goal.

Strategies for ChangeThe four major process decisions represent broad, strategic issues and define the nature of the pro-cesses a firm needs to compete effectively. However, decisions that are made must be translated into actual process designs or redesigns. There are two different but complementary philosophies for process design and change: (1) process reengineering and (2) process improvement. Process analysis, supported by the tools described later, is needed regardless of whether reengineering or process improvement is attempted. An individual or a whole team examines the process and looks for ways to streamline tasks, eliminate whole processes entirely, cut expensive materials or services, improve the environment, or make jobs safer. By comprehensively analyzing the process, one must find the ways to trim costs and delays and to improve customer satisfaction.

focused factories

The result of a firm’s splitting large plants that produced all the company’s products into several specialized smaller plants.

competitive priorities. Although these suppliers are not responsible for the final assembly, some of them carry out quality check measures beyond the boundaries of their embedded plants. This additional step ensures that the difference in competitive priorities and processes do not hinder the quality and seamless flow of production in the entire plant.

The workforce at Camacari is also different in a number of ways. The entire plant employs approximately 9,000 workers, including the suppliers. Because the majority do not have any prior industrial work experience, they undergo a 900-hour training program. This collective training program enhances the cohesiveness among employees and facilitates a culture of

collaboration and joint problem solving. Unlike many U.S. auto plants, where workers’ responsibilities are strictly limited to specific job classifications, workers are encouraged to learn as many skills as possible, which allows the plant to be flexible.

By having such a plant, Ford is able to have module suppliers commit to the success of the whole product because they get paid when the product is approved and functionally accepted. The suppliers would have to prioritize resolving delivery or quality issues with Ford, which eventually improves the final quality. When there is a problem with a part, it is simple to track down the source and work with the related supplier to correct it. Due to closer communication and knowledge transfer between companies and employees, Ford is experiencing faster learning curves and cross fertilization of practices in the workforce. Ford can shorten the development times and launch times for new products, and quickly ramp up production volumes because of the increased collaboration and involvement of suppliers. The reduced inventory and logistics costs more than compensate for the high interest rates charged for credit in Brazil.

However, this approach may have some disadvantages as well. Salary negotiations may align toward the entire plant’s standards, reducing margin for the suppliers. Decision making can take longer for some issues, such as labor union negotiations, which require agreement of all the partners. Managing organizational culture is also not an easy task. This may complicate the startup of the factory, because of the mix of various management styles and company cultures the suppliers may bring into the plant. Finally, it increases the organizational inertia, because change is less likely to happen with suppliers embedded within the plant. When a module faces technical improvements, there is a risk that it might not be compatible with other modules, and it may require Ford to a change a supplier.

Overall, focused operations along with flexibility and close supplier involvement make the Camacari plant one of the most innovative ones among Ford’s worldwide network of facilities. The Camacari plant is an example of how the PWP concept can be established beyond a single firm’s boundary and create a closely integrated production facility that incorporates the ben-efits of collaborative problem solving at the interorganizational level.2

2Sources: B. G. Hoffman, “Ford’s Test Bed: Brazil’s Camacari Plant Is Model for the Future, The Detroit News (2007); M. Sako, “Outsourcing of Tasks and Outsourcing of Assets: Evidence from Automotive Supplier Parks in Brazil. Platforms, Markets and Innovation (2009), 251; https://en.wikipedia.org/wiki/Ford_Brasil (August 3, 2020).

Ford Motor Company assembly workers work on the assembly line of the Ford Fiesta and Ecosport vehicles at a plant in Camacari, in the northeastern Brazilian state of Bahia. Ford invested US $1.2 billion at the Camacari’s factory and created a unique environment that consolidates production line with their direct suppliers’ own facilities where the models are made for the Brazilian market and exported to other development countries as well.

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88 PART 1 MANAGING PROCESSES

Process ReengineeringReengineering is the fundamental rethinking and radical redesign of processes to improve perfor-mance dramatically in terms of cost, quality, service, and speed. Process reengineering is about reinvention rather than incremental improvement. It is strong medicine and not always needed or successful. Pain, in the form of layoffs and large cash outflows for investments in information technology, almost always accompanies massive change. However, reengineering processes can have big payoffs. Table 2.2 lists the key elements of the overall approach.

Element Description

Critical processes The emphasis of reengineering should be on core business processes. Normal process-improvement activities can be continued with the other processes.

Strong leadership Senior executives must provide strong leadership for reengineering to be successful. Otherwise, cynicism, resistance (“we tried that before”), and boundaries between departments can block radical changes.

Cross-functional teams A team, consisting of members from each functional area affected by the process change, is charged with carrying out a reengineering project. Self-managing teams and employee empowerment are the rule rather than the exception.

Information technology Information technology is a primary enabler of process engineering. Most reengineering projects design processes around information flows, such as customer order fulfillment.

Clean-slate philosophy Reengineering requires a “clean-slate” philosophy—that is, starting with the way the customer wants to deal with the company. To ensure a customer orientation, teams begin with internal and external customer objectives for the process.

Process analysis Despite the clean-slate philosophy, a reengineering team must understand things about the current process: what it does, how well it performs, and what factors affect it. The team must look at every procedure involved in the process throughout the organization.

TABLE 2.2 | KEY ELEMENTS OF REENGINEERING

Reengineering has led to many successes and will continue to do so. However, it is not simple or easily done, nor is it appropriate for all processes or all organizations. The best understanding of a process, and how to improve it, often lies with the people who perform the work each day, not with cross-functional teams or top management.

Process ImprovementProcess improvement is the systematic study of the activities and flows of each process to improve it. Its purpose is to “learn the numbers,” understand the process, and dig out the details. Once a process is really understood, it can be improved. The relentless pressure to provide better quality at a lower price means that companies must continually review all aspects of their operations. Process improvement goes on, whether or not a process is reengineered. There is always a better way. Most processes can be improved if someone thinks of a way and implements it effectively. Indeed, companies will either adapt processes to the changing needs of customers or cease to exist. Long-term success comes from managers and employees who really understand their busi-nesses. But all too often, highly publicized efforts that seem to offer quick-fix solutions fail to live up to expectations over the long haul, be they programs for conceptualizing a business vision, conducting culture transformation campaigns, or providing leadership training.

As the following Managerial Challenge illustrates, analyzing and improving processes are not limited to just the core operations of a firm, but can readily extend to other functional areas like marketing, finance, engineering, and accounting as well.

reengineering

The fundamental rethinking and radical redesign of processes to improve performance dramatically in terms of cost, quality, service, and speed.

process improvement

The systematic study of the activ-ities and flows of each process to improve it.

M A N A G E R I A L CHALLENGE

Templeton, Inc. is a packaging products manufacturing company with diversified operations in over two dozen countries scattered around the globe. Apart from supplying packaging raw materials, it also customizes the design and installation of machines that help the client firms uniquely package their products. The sales and marketing team at Templeton prides itself in its ability to develop deep client relationships by taking a life cycle approach to the sales and repair of its products. This approach assures customers that Templeton will service or repair any of its machines throughout their economic lives in a timely fashion. When packaging machines malfunction, repair orders are generated and sent to the sales and marketing team,

Marketing

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Process AnalysisProcess analysis is the documentation and detailed understanding of how work is performed and how it can be redesigned. Looking at the strategic issues can help identify opportunities for improvement. Do gaps exist between a process’s competitive priorities and its current competitive capabilities, as was found for the assessment of operations strategy at a credit card division in Chapter 1, “Using Operations to Create Value”? Do multiple measures of cost, top quality, quality consistency, delivery speed, and on-time delivery meet or exceed expectations? Is there a good strategic fit in the process? If the process provides a service, does its position on the customer-contact matrix (see Figure 2.2) seem appropriate? How does the degree of customer contact match up with process structure, customer involvement, resource flexibility, and capital intensity? Similar questions should be asked about manufacturing processes regarding the strategic fit between process choice, volume, and product customization.

Process analysis begins with identifying and defining a new opportunity for improvement and ends with implementing and controlling a revised process, and which we capture through the Six Sigma Process Improvement Model. Other approaches to process improvement are statistical process control and process capability analysis, discussed in Chapter 3, “Quality and Performance,” and value stream mapping, discussed in Chapter 4, “Lean Systems.” We avoid overlap by covering each technique just once, while bringing out the essence of the approach covered in each chapter. The chapters do have a shared goal: better processes.

Six Sigma Process Improvement Model Figure 2.6 shows the Six Sigma Process Improvement Model, a five-step procedure that leads to improvements in process performance. This model can be applied to projects involving incremental improvements to processes or to projects requiring major changes, including a redesign of an existing process or the development of a new process.

The following steps constitute the model:

▪▪ Define. The scope and boundaries of the process to be analyzed are first established. Is it a broad process that stretches across the whole organization, involving many steps and many employees, or is it a more narrowly bracketed nested subprocess that is just part of one per-son’s job? A process’s scope can be too narrow or too broad. For example, a broadly defined process that outstrips the resources available, sometimes called “trying to boil the ocean,” is doomed because it will increase employee frustration without producing any results.

which then arranges for the inoperative module to be sent to Templeton’s internal division responsible for processing these orders. The facility, after an initial diagnosis of the problem, will either repair the malfunctioning assembly or send the client a new one. The company has a standard turnaround time of 25 calendar days or less for fulfilling these customer requests.

Lucy Solano, the vice president of marketing and sales for Templeton’s Packaging Products Division, noticed the steadily increasing customer complaints about repair orders being delayed and affecting production. A quick check revealed that more than 65% of the orders over the past quarter had been delayed beyond 25 days, with 35% of orders still not being filled after 2 months. Alarmed by these statistics, Lucy shared this customer data with Peter Jamison, the plant manager of the repair facility in Virginia, in the United States, which handled all such requests worldwide. They agreed to meet in person at the plant the following Monday.

Peter broadly described to Lucy the plant operations at their initial meeting. She was, however, overwhelmed when she toured the plant. She examined the computerized customer-order log and was dismayed to see the time lag between her department getting the order request, arranging for the delivery of the module for repair, and the actual time Peter’s facility received the module. Much of the 25-day repair window was consumed by this process. This put the repair process in an expedite mode much of the time. The shop floor itself was cluttered with several different customer repair orders being worked upon simultaneously at many workstations. The staging area for the shipment of fixed machine assemblies was likewise busy. Lucy quickly realized that to truly analyze and improve the process in her department and at the plant, she would need to understand what happens to a typical customer order when it is received in the sales department, when and how the order and the malfunctioning module transition to the repair facility and the shop floor, how long it takes to complete, how long it waits in the shipping department, and what occurs in the processing of the paperwork to close out the order and get it delivered directly to the client site. A process analysis had not been done at the Virginia facility for well over a decade. Topics covered next in this chapter will be helpful to Lucy and Peter as they embark upon their quest of systematically improving the repair order-taking and completion process at Templeton, and once again meeting the customer service promises made by their sales and marketing team.

▼ FIGURE 2.6Six Sigma Process Improvement Model

Define

Measure

Analyze

Improve

Control

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The resources that management assigns to improving or reengineering a process should match the scope of the process. Once scope is established, determine the characteristics of the pro-cess’s output that are critical to customer satisfaction and identify any gaps between these characteristics and the process’s capabilities. Get a picture of the current process by docu-menting it using techniques outlined in this chapter.

▪▪ Measure. It is important to have good performance measures to evaluate a process for clues on how to improve it. Metrics are performance measures for the process and the steps within it. A good place to start is with competitive priorities, but they need to be specific. The analyst creates multiple measures of quality, customer satisfaction, time to perform each step or the whole process, cost, errors, safety, environmental measures, on-time delivery, flexibility, and the like. Once the metrics are identified, it is time to collect information on how the process is currently performing on each one. Measurement can be rough-cut estimates or quite exten-sive. It is important to quantify the work the process does that affects the gap. Select what to measure, identify data sources, and prepare a data collection plan.

▪▪ Analyze. Use the data on measures to perform process analysis to determine where improvements are necessary. A careful analysis of the process and its performance on the selected metrics should uncover disconnects, or gaps, between actual and desired performance. Illogical, missing, or extraneous steps can cause performance gaps. They can also be caused by metrics that reinforce the silo mentality of individual departments when the process spans across several departments. The analyst or design team should dig deep to find the root causes of performance gaps. For instance, techniques for analyzing wait times and delays can provide important information  (see Supplement B, “Waiting Lines” and online Supplement E, “Simulation”). Whether or not major redesign is necessary, establish procedures to make the desired outcome routine.

▪▪ Improve. Using analytical and creative thinking, the design team generates a long list of ideas for improvements. These ideas are then sifted and analyzed. Ideas that are justifiable, where benefits outweigh costs, are reflected in a new process design that can meet the new performance objectives. The new design should be documented “as proposed.” Combining the new process design with the documentation of the current process gives the analysts clear before-and-after pictures. The new documentation should make clear how the revised process will work and the performance expected for the various metrics used. Implement the changes.

▪▪ Control. After the implementation, monitor the process to make sure that high performance levels are maintained. Once again, data analysis tools can be used to control the process. Implementation is more than developing a plan and carrying it out. Many processes have been redesigned effectively, but never get implemented. People resist change: “We have always done it that way” or “We tried that before.” Widespread participation in process analysis is essential, not only because of the work involved but also because it builds commitment. It is much easier to implement something that is partly your own idea. In addition, special expertise may be needed, such as for developing software. New jobs and skills may be needed, involving training and investments in new technology. Implementation and control brings to life the steps needed to bring the redesigned process online. Management or the steering committee must make sure that the implementation project goes according to schedule.

Successful users have found that it is essential to rigorously follow the steps in the Six Sigma Improvement Model, which is sometimes referred to as the DMAIC process (whose name comes from using the first letter of each step in the model). To accomplish the goals of Six Sigma, employees must be trained in the “whys” and the “how-tos” of process performance and what it means to customers, both internal and external. Successful firms using Six Sigma develop a cadre of internal teachers who then are responsible for teaching and assisting teams involved in a process-improvement project. These teachers have different titles depending on their experience and level of achievement. Green Belts devote part of their time to teaching and helping teams with their projects and the rest of their time to their normally assigned duties. Black Belts are full-time teachers and leaders of teams involved in Six Sigma projects. Finally, Master Black Belts are full-time teachers who review and mentor “Black Belts.”

We dive a little deeper into the first three phases of the DMAIC process next, while elaborat-ing on the Improve and Control phase in Chapter 3, “Quality and Performance.”

Defining, Measuring, and Analyzing the ProcessThe Six Sigma Process Improvement Model starts with first defining and understanding the current state of the existing process. This step is needed before data can be collected to measure key attributes of the process, and then analyze that data to improve, design, and control a newly designed future state process.

Three major techniques for effectively defining and measuring processes are (1) flowcharts, (2) work measurement techniques, and (3) process charts. They allow you to “lift the lid and peer

metrics

Performance measures that are established for a process and the steps within it.

Green Belt

Employees who have achieved the first level of training in a Six Sigma program and spend part of their time teaching and helping teams with their projects.

Black Belt

Employees who have reached the highest level of training in a Six Sigma program and spend all of their time teaching and leading teams involved in Six Sigma projects.

Master Black Belt

Full-time teachers and mentors to several Black Belts.

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inside” to see how an organization does its work. You can see how a process operates, at any level of detail, and how well it is performing. Trying to create one of these charts might even reveal a lack of any established process. It may not be a pretty picture, but it is how work actually gets done. Techniques for defining the process lend themselves to finding performance gaps, generating ideas for process improvements, and documenting the look of a redesigned process.

FlowchartsA flowchart traces the flow of information, custom-ers, equipment, or materials through the various steps of a process. Flowcharts are also known as flow diagrams, process maps, relationship maps, or blueprints. Flowcharts have no precise format and typically are drawn with boxes (with a brief descrip-tion of the step inside), and with lines and arrows to show sequencing. The rectangle (n) shape is the usual choice for a box, although other shapes ( , ,

, , or ) can differentiate between different types of steps (e.g., operation, delay, storage, and inspection). Colors and shading can also call attention to different types of steps, such as those particularly high on process divergence. Divergence is also communicated when an outgoing arrow from a step splits into two or more arrows that lead to different boxes. Although many rep-resentations are acceptable, there must be agreement on the conventions used. They can be given as a key somewhere in the flowchart, and/or described in accompanying text. It is also important to communicate what (e.g., information, customer order, customer, and materials) is being tracked.

You can create flowcharts with several programs. Microsoft PowerPoint offers many different formatting choices for flowcharts (see the Flowchart submenu under AutoShapes). Other powerful software packages for flowcharting and drawing diagrams (such as organization charts and deci-sion trees) are SmartDraw (www.smartdraw.com), Microsoft Visio (www.microsoft.com/office/visio), and Micrografx (www.micrografx.com). Often, free downloads are available at such sites on a trial basis.

Flowcharts can be created for several levels in the organization. For example, at the strategic level, they could show the core processes and their linkages (as in Figure 1.4). At this level, the flowcharts do not have much detail; however, they give a bird’s-eye view of the overall business. Just identifying a core process is often helpful. However, in this chapter, we focus at the process level, where we get into the details of the process being analyzed. Many steps may have subpro-cesses nested within them. Rather than representing everything in one flowchart, an overview of the whole process can first be created. Subsequently flowcharts can be developed to flesh out nested processes. This nesting approach often becomes a practical necessity because only so much detail can be shown in any single flowchart.

Swim Lane Flowchart One of the most commonly used forms of a flowchart is the swim lane flowchart. It is a visual representation that groups functional areas responsible for different subprocesses into lanes. It is most appropriate when the business process spans several department boundaries, and where parallel lines similar to lanes in a swimming pool separate each department or a functional area. Swim lanes are labeled according to the functional groups they represent and can be arranged either horizontally or vertically.

The swim lane flowchart in Figure 2.7 illustrates the order placement and acceptance process at a manufacturing company. The process starts when an order is generated by a customer and ends when the order is actually rejected, modified, or approved by the company in consultation with the customer. All functions contributing to this process are included in the flowchart. The columns represent different departments or functional areas, and the steps appear in the depart-ment column where they are performed. The customer is also shown as one of the column head-ings. This approach shows the handoffs from one department to another when the outgoing arrow from a step goes to another column. Special dotted-line arrows are one way to show handoffs. Handoffs are points where cross-functional coordination is at particular risk due to the silo men-tality. Misunderstandings, backlogs, and errors are more likely at these points.

Figure 2.7 illustrates one other feature. The diamond shape (◊) represents a yes/no decision or outcome, such as the results of an inspection or recognition of different kinds of customer requirements. In Figure 2.7, the diamond represents three yes/no decision points within finance, and one each within sales and operations. These yes/no decision points are more likely to appear when a process is high in divergence.

flowchart

A diagram that traces the flow of information, customers, equipment, or materials through the various steps of a process.

swim lane flowchart

A visual representation that groups functional areas responsible for different subprocesses into lanes. It is most appropriate when the business process spans several department boundaries.

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Designer presenting a flow chart during a meeting. The use of flowcharts can help in documenting and evaluating processes.

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92 PART 1 MANAGING PROCESSES

Swim lane flowcharts allow the process analyst and managers to look at the horizontal orga-nization rather than the vertical organization and departmental boundaries implied by a typi-cal organizational chart. Swim lane flowcharts show how organizations produce their outputs through cross-functional work processes and allow the design team to see all the critical interfaces between functions and departments.

Service Blueprint A service blueprint is a special flowchart of a service process that shows which steps have high customer contact. It uses a dotted line of visibility to identify which steps are visible to the customer (and thus are more of a front-office process) and those that are not (back-office process). Of course, visibility is just one aspect of customer contact, and it may not adequately capture how actively the customer is involved or how much personal attention is required. A service blueprint can use colors, shading, or box shapes, instead of the lines of vis-ibility, to show the extent and type of customer contact. Another approach to service blueprinting is to tag each step with a number, and then have an accompanying table that describes in detail the customer contact for each numbered step. There is no one “right way” to create a flow chart or service blueprint.

Work Measurement TechniquesProcess definition would not be complete without estimates of the average time each step in the process would take. Time estimates are needed not just for process-improvement efforts but for capacity planning, constraint management, performance appraisal, and scheduling. Estimating task times can be as simple as making a reasoned guess, asking a knowledgeable person, or tak-ing notes while observing the process. More extensive studies involve collecting data for several weeks, consulting cost accounting data, or checking data recorded in information systems.

Formal techniques that rely on the judgment of skilled observers are also available: (1) the time study method, (2) the elemental standard data method, (3) the predetermined data method, and (4) work sampling. A fifth method, (5) learning curve analysis, is particularly appropriate when a new product or process is introduced and the time per unit produced has not yet stabi-lized. The method chosen depends on the purpose of the data, process type (job, batch, or line), and degree of product customization. A more comprehensive treatment of these techniques is provided in online Supplement H, “Measuring Output Rates” and online Supplement I, “Learn-ing Curve Analysis.”

service blueprint

A special flowchart of a service process that shows which steps have high customer contact.

▲ FIGURE 2.7Swim Lane Flowchart of the Order-Filling Process Showing Handoffs between DepartmentsSource: D. Kroenke, Using MIS, 4th ed., © 2012. Reprinted and electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 93

Time Study Method Time study uses a trained analyst to perform four basic steps in setting a time standard for a job or process: (1) selecting the work elements (steps in a flowchart or pro-cess chart) within the process to be studied, (2) timing the elements, (3) determining the sample size, and (4) setting the final standard. It is essentially the average time observed, adjusted for normal effort and making an allowance for breaks, unavoidable delays, and the like. The analyst records time spent on each element of the process being studied using a stopwatch, and records the time spent on each element for several repetitions. The analyst assigns a performance rating for each element to adjust for normal effort. Some elements may be performed faster or slower than normal, in the analyst’s judgment. The allowance is expressed as a proportion or percent of the total normal time.

Elemental Standard Data Method Another method is needed when products or services are highly customized, job processes prevail, and process divergence is great. Elemental standard data is a database of standards compiled by a firm’s analysts for basic elements that they can draw on later to estimate the time required for a particular job. This approach works well when work ele-ments within certain jobs are similar to those in other jobs. Sometimes, the time required for a work element depends on variable characteristics of the jobs, such as the amount of metal to be deposited for a welding process. In such cases, an equation that relates these characteristics to the time required is also stored in the database. Another method, such as time study or past records, still must be used to compile the normal times (before the allowance is added) stored in the database.

time study

A work measurement method using a trained analyst to perform four basic steps in setting a time standard for a job or process: selecting the work elements (or nested processes) within the process to be studied, timing the elements, determining the sample size, and setting the final standard.

elemental standard data

A database of standards compiled by a firm’s analysts for basic elements that they can draw on later to estimate the time required for a particular job, which is most appropriate when products or services are highly customized, job processes prevail, and process divergence is great.

Time Study of Watch Assembly ProcessEXAMPLE 2.1

A process at a watch assembly plant has been changed. The pro-cess is divided into three work elements. A time study has been performed with the following results. The time standard for the pro-cess previously was 14.5 minutes. Based on the new time study, should the time standard be revised?

SOLUTIONThe new time study had an initial sample of four observations, with the results shown in the following table. The performance rating factor (RF) is shown for each element (to adjust for normal effort), and the allowance for the whole process is 18 percent of the total normal time.

Obs 1 Obs 2 Obs 3 Obs 4Average

(min) RFNormal Time

Element 1 2.60 2.34 3.12 2.86 2.730 1.0 2.730

Element 2 4.94 4.78 5.10 4.68 4.875 1.1 5.363

Element 3 2.18 1.98 2.13 2.25 2.135 0.9 1.922

Total Normal Time = 10.015 minutes

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Workers seen on a watch assembly line at the Jaeger-LeCoultre factory in Le Sentier, Switzerland.

The normal time for an element in the table is its average time, multiplied by the RF. The total normal time for the whole process is the sum of the normal times for the three elements, or 10.015 minutes. To get the standard time (ST) for the process, just add in the allowance, or

ST = 10.015(1 + 0.18) = 11.82 minutes/watch

DECISION POINTThe time to assemble a watch appears to have decreased considerably. However, based on the pre-cision that management wants, the analyst decided to increase the sample size before setting a new standard. Online Supplement H, “Measuring Output Rates,” gives more information on determining the number of additional observations needed.

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94 PART 1 MANAGING PROCESSES

Predetermined Data Method The predetermined data method divides each work element even more, into a series of micromotions that make up the element. The analyst then consults a published database that contains the normal times for the full array of possible micromotions. A process’s normal time can then be calculated as the sum of the times given in the database for the elements performed in the process. This approach makes most sense for highly repetitive processes with little process divergence and line flows. The micromotions (such as reach, move, or apply pressure) are very detailed.

Work Sampling Method Work sampling estimates the proportion of time spent by people or machines on different activities, based on observations randomized over time. Examples of these activities include working on a service or product, doing paperwork, waiting for instructions, waiting for maintenance, or being idle. Such data can then be used to assess a process’s productiv-ity, estimate the allowances needed to set standards for other work measurement methods, and spot areas for process improvement. It is best used when the processes are highly divergent with flexible flows. Figure 2.8 shows the input data and numerical results for 1 week of observations. It shows an idle time of 23.81 percent for the week and also reports that 237 more observations are needed to achieve the confidence and precision levels required with the input data. How these conclusions are reached is explained in online Supplement H, “Measuring Output Rates.”

predetermined data method

A database approach that divides each work element into a series of micromotions that make up the element. The analyst then consults a published database that contains the normal times for the full array of possible micromotions.

▲ FIGURE 2.8Work Sampling Study of Admission Clerk at Health Clinic Using OM Explorer’s Time Study Solver

(a) Input Data and Numerical Results (b) Idle Time and Observations Required

◀ FIGURE 2.9Learning Curve with 80% Learning Rate Using OM Explorer’s Learning Curves Solver

Learning Curve Analysis The time estimation techniques just covered assume that the process is stable. If the process is revised, then just repeat the method for the revised process after it stabilizes. Learning curve analysis, in contrast, takes into account that learning takes place on an ongoing basis, such as when new products or services are introduced frequently. With instruction and repetition, workers learn to perform jobs more efficiently, process improvements are identified, and better admin-istration methods are created. These learning effects can be anticipated with a learning curve, a line that displays the relationship between processing time and the cumulative quantity of a product or service produced. The time required to produce a unit or create a service decreases as more units or customers are processed. The learning curve for a process depends on the rate of learning and the actual or estimated time for the first unit processed. Figure 2.9 demonstrates the learning curve assuming an 80 percent learning rate, with the first unit taking 120,000 hours and the cumulative average time for the first 10 units produced. The learning rate deals with each doubling of the output total. The time for the second unit is 80 percent of the first (or 120,000 * .80 = 96,000 hours), the time for the fourth unit is 80 percent of the second unit (or 96,000 * .80 = 76,800 hours), and so on. Finding the time estimate for a unit that is not an exact doubling (such as the fifth unit), and also the cumulative average time for the first 10 units, is explained in online Supplement I, “Learning Curve Analysis.”

work sampling

A process that estimates the proportion of time spent by people or machines on different activities, based on observations randomized over time.

learning curve

A line that displays the relationship between processing time and the cumulative quantity of a product or service produced.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 95

Process ChartsA process chart is an organized way of documenting all the activities performed by a person or group of people at a workstation, with a customer, or working with certain materials. It analyzes a process using a table, and provides information about each step in the process. In contrast to flowcharts, swim lane flowcharts, and service blueprints, it requires the time estimates (see work measurement techniques covered in the last section). Often it is used to drill down to the job level for an individual person, a team, or a focused nested process. It can have many formats. Here, we group the type of activities for a typical process into five categories:

▪▪ Operation. Changes, creates, or adds something. Drilling a hole and serving a customer are examples of operations.

▪▪ Transportation. Moves the study’s subject from one place to another (sometimes called mate-rials handling). The subject can be a person, a material, a tool, or a piece of equipment. A customer walking from one end of a counter to the other, a crane hoisting a steel beam to a location, and a conveyor carrying a partially completed product from one workstation to the next are examples of transportation. It could also be the shipment of a finished product to the customer or a warehouse.

▪▪ Inspection. Checks or verifies something but does not change it. Getting customer feedback, checking for blemishes on a surface, weighing a product, and taking a temperature reading are examples of inspections.

▪▪ Delay. Occurs when the subject is held up awaiting further action. Time spent waiting for a server; time spent waiting for materials or equipment; cleanup time; and time that workers, machines, or workstations are idle because they have no work to complete are examples of delays.

▪▪ Storage. Occurs when something is put away until a later time. Supplies unloaded and placed in a storeroom as inventory, equipment put away after use, and papers put in a file cabinet are examples of storage.

Depending on the situation, other categories can be used. For example, subcontracting for outside services might be a category, temporary storage and permanent storage, or environmental waste might be three separate categories. Choosing the right category for each activity requires taking the perspective of the subject charted. A delay for the equipment could be inspection or transportation for the operator.

To complete a chart for a new process, the analyst must identify each step performed. If the process is an existing one, the analyst can actually observe the steps and categorize each step according to the subject being studied. The analyst then records the distance traveled and the time taken to perform each step. After recording all the activities and steps, the analyst summa-rizes the steps, times, and distances data. Figure 2.10 shows a process chart prepared using OM Explorer’s Process Chart Solver. It is for a patient with a twisted ankle being treated at a hospital. The process begins at the entrance and ends with the patient exiting after picking up a prescription.

After a process is charted, the analyst sometimes estimates the annual cost of the entire process. It becomes a benchmark against which other methods for performing the process can be evaluated. Annual labor cost can be estimated by finding the product of (1) time in hours to perform the process each time, (2) variable costs per hour, and (3) number of times the process is performed each year, or

Annuallabor cost

= ¢ Time to performthe process in hours

≤¢Variable costsper hour

≤¢Number of times processis performed per year

≤For example, if the average time to serve a customer is 4 hours, the variable cost is

$25 per hour, and 40 customers are served per year, then the labor cost is $4,000 per year (or 4 hr/customer * $25/hr * 40 customers/yr).

In the case of the patient in Figure 2.10, this conversion would not be necessary, with total patient time being sufficient. What is being tracked is the patient’s time, not the time and costs of the service providers.

You can design your own process chart spreadsheets to bring out issues that are particu-larly important for the process you are analyzing, such as categories for customer contact, process divergence, and the like. You can also track performance measures other than time and distance traveled, such as error rates. In addition, you can also create a different version of the process chart spreadsheet that examines processes much as done with flowcharts, except now in the form of a table. The columns that categorize the activity type could be replaced by one or more columns reporting different metrics of interest, rather than trying to fit them into a flowchart. Although it might not look as elegant, it could be just as informative—and easier to create.

process chart

An organized way of documenting all the activities performed by a person or group of people, at a workstation, with a customer, or on materials.

Online ResourceTutor 2.2 in OM Explorer provides a new example to practice creating process charts.

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96 PART 1 MANAGING PROCESSES

Data Analysis ToolsMetrics and performance information complete the docu-mentation of a process. The specific metrics analysts choose depends on the process being analyzed and on the competi-tive priorities. Good starting points are the per-unit processing time and cost at each step, and the time elapsed from begin-ning to end of the process. Capacity utilization, environmental issues, and customer (or job) waiting times reveal where in the process delays are most likely to occur. Customer satisfaction measures, error rates, and scrap rates identify possible qual-ity problems. We introduce many such metrics in subsequent chapters. Only when these subsequent chapters are understood do we really complete our discussion of process analysis.

Metrics can be displayed in various ways. Sometimes, they can be added directly on the flowchart or process chart. When the number of metrics gets unwieldy, another approach is to create a supporting table for the chart. Its rows are the steps in the flow-chart, swim lane flowchart, service blueprint, or process chart. The columns are the current performance, goals, and performance gaps for various metrics. Various tools are available to help you understand the causes of these performance gaps and problems.3 Here we present six tools: (1) checklists, (2) histograms and bar charts, (3) Pareto charts, (4) scatter diagrams, (5) cause-and-effect diagrams, and (6) graphs. Many of them were developed initially

to analyze quality issues, but they apply equally well to process analysis in general.

Checklists Data collection through the use of a checklist is often the first step in the analysis of a metric. A checklist is a form used to record the frequency of occurrence of certain process failures. A process failure is any performance shortfall, such as error, delay, environmental waste, rework, and the like. The characteristics may be measurable on a continuous scale (e.g., weight,

3Several of these tools, particularly Pareto charts and cause-and-effect diagrams, are closely affiliated with Chapter 3, “Quality and Performance.” We introduce them here because they apply to process failures in general and not just to quality rejects.

checklist

A form used to record the frequency of occurrence of certain process failures.

process failure

Any performance shortfall, such as error, delay, environmental waste, rework, and the like.

Insert Step

Summary

ActivityNumberof Steps

Time(min)

Distance(ft)

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Subject:

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Ending:

Emergency room admission

Ankle injury patient

Enter emergency room

Leave hospitalOperation

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Enter emergency room, approach patient windowSit down and fill out patient historyNurse escorts patient to ER triage roomNurse inspects injuryReturn to waiting roomWait for available bedGo to ER bedWait for doctorDoctor inspects injury and questions patientNurse takes patient to radiologyTechnician x-rays patientReturn to bed in ERWait for doctor to returnDoctor provides diagnosis and adviceReturn to emergency entrance areaCheck outWalk to pharmacyPick up prescriptionLeave the building

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0.5010.000.753.000.751.001.004.005.002.003.002.003.002.001.004.002.004.001.00

FIGURE 2.10 ▶Process Chart for Emergency Room Admission

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The leader of a design team presents several charts that document a process in their office that they are analyzing. He is identifying several areas of substandard performance across a range of different metrics. The next step will be to redesign the process. The flipchart on the right will be quite useful in generating rapid fire ideas from the team on how the process might be improved.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 97

customer satisfaction on a 1 to 7 scale, unit cost, scrap loss percentage, time, or length) or on a yes/no basis (e.g., customer complaint, posting error, paint discoloration, or inattentive servers).

Histograms and Bar Charts Data from a checklist often can be presented succinctly and clearly with histograms or bar charts. A histogram summarizes data measured on a continuous scale, showing the frequency distribution of some process failure (in statistical terms, the central tendency and dispersion of the data). Often the mean of the data is indicated on the histogram. A bar chart (Figure 2.11) is a series of bars representing the frequency of occurrence of data characteristics measured on a yes/no basis. The bar height indicates the number of times a particular process failure was observed.

Pareto Charts When managers discover several process problems that need to be addressed, they have to decide which should be attacked first. Vilfredo Pareto, a 19th-century Italian scientist whose statistical work focused on inequalities in data, proposed that most of an “activity” is caused by relatively few of its factors. In a restaurant-quality problem, the activity could be cus-tomer complaints and the factor could be “discourteous server.” For a manufacturer, the activity could be product defects and the factor could be “missing part.” Pareto’s concept, called the 80–20 rule, is that 80 percent of the activity is caused by 20 percent of the factors. By concentrating on the 20 percent of the factors (the “vital few”), managers can attack 80 percent of the process failure problems. Of course, the exact percentages vary with each situation, but inevitably relatively few factors cause most of the performance shortfalls.

The few vital factors can be identified with a Pareto chart, a bar chart on which the factors are plotted along the horizontal axis in decreasing order of frequency (Figure 2.12). The chart has two vertical axes, the one on the left showing frequency (as in a histogram) and the one on the right showing the cumulative percentage of frequency. The cumulative frequency curve identifies the few vital factors that warrant immediate managerial attention.

histogram

A summarization of data measured on a continuous scale, showing the frequency distribution of some process failure (in statisti-cal terms, the central tendency and dispersion of the data).

bar chart

A series of bars representing the frequency of occurrence of data characteristics measured on a yes/no basis.

Pareto chart

A bar chart on which factors are plotted along the horizontal axis in decreasing order of frequency.

Pareto Chart for a RestaurantEXAMPLE 2.2

The manager of a neighborhood restaurant is concerned about the lower numbers of customers patron-izing his eatery. Complaints have been rising, and he would like to find out what issues to address and present the findings in a way his employees can understand.

SOLUTIONThe manager surveyed his customers over several weeks and collected the following data:

Online ResourcesActive Model 2.1 provides additional insights on this Pareto chart example and its extensions.

Tutor 2.3 in OM Explorer provides a new example on creating Pareto charts.

Figure 2.11 is a bar chart and Figure 2.12 is a Pareto chart, both created with OM Explorer’s Bar, Pareto, and Line Charts Solver. They present the data in a way that shows which complaints are more prev-alent (the vital few). You can reformat these charts for any yes/no metrics by unprotecting the spreadsheet and then making your revisions. Another approach is to create your own spreadsheets from scratch. More advanced software with point-and-click inter-faces include Minitab (https://www.minitab.com/en-us/), SAS (https://www.sas.com/en_us/home.html), and Microsoft Visio (https://www.microsoft.com/en-us/.).

DECISION POINTIt was clear to the manager (and all employees) which com-plaints, if rectified, would cover most of the process fail-ure problems in the restaurant. First, slow service will be addressed by training the existing staff, adding another server, and improving the food preparation process. Remov-ing some decorative furniture from the dining area and spac-ing the tables better will solve the problem with cramped tables. The Pareto chart shows that these two problems, if rectified, will account for almost 70 percent of the complaints.

Complaint Frequency

Discourteous server 12

Slow service 42

Cold dinner 5

Cramped tables 20

Atmosphere 10

People having lunch in packed restaurants on a hot day.

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98 PART 1 MANAGING PROCESSES

Scatter Diagrams Sometimes managers suspect that a certain factor is causing a particular pro-cess failure. A scatter diagram, which is a plot of two variables showing whether they are related, can be used to verify or negate the suspicion. Each point on the scatter diagram represents one data observation. For example, the manager of a castings shop may suspect that casting defects are a function of the diameter of the casting. A scatter diagram could be constructed by plotting the number of defective castings found for each diameter of casting produced. After the diagram is completed, any relationship between diameter and number of process failures will be clear.

Cause-and-Effect Diagrams An important aspect of process analysis is linking each metric to the inputs, methods, and process steps that build a particular attribute into the service or product. One way to identify a design problem is to develop a cause-and-effect diagram that relates a key performance problem to its potential causes. First developed by Kaoru Ishikawa, the diagram helps management trace disconnects directly to the operations involved. Processes that have no bearing on a particular problem are not shown on the diagram.

The cause-and-effect diagram sometimes is called a fishbone diagram. The main performance gap is labeled as the fish’s “head,” the major categories of potential causes as structural “bones,” and the likely specific causes as “ribs.” When constructing and using a cause-and-effect diagram, an analyst identifies all the major categories of potential causes for the problem. These might be personnel, machines, materials, and processes. For each major category, the analyst lists all the likely causes of the performance gap. Under personnel might be listed “lack of training,” “poor communication,” and “absenteeism.” Creative thinking helps the analyst identify and properly classify all suspected causes. The analyst then systematically investigates the causes listed on the diagram for each major category, updating the chart as new causes become apparent. The process of constructing a cause-and-effect diagram calls management and worker attention to the primary factors affecting process failures. Example 2.3 demonstrates the use of a cause-and-effect diagram by a firm manufacturing air conditioners.

scatter diagram

A plot of two variables showing whether they are related.

cause-and-effect diagram

A diagram that relates a key performance problem to its potential causes.

FIGURE 2.12 ▶Pareto Chart

0Slow

serviceCramped

tablesDiscourteous

serverAtmosphere

(42 + 20)

89x 100% = 69.7%

Colddinner

Failure Name

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25201510

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0.0%

Analysis of Inadequate Production of HeadersEXAMPLE 2.3

A process improvement team is working to improve the production output of Johnson Manufacturing’s header cell. Johnson manufactures a key component, headers, used in commercial air conditioners. A header is part of the circulatory system of a commercial air conditioner that moves coolant between various components such as the evaporator coil and the condenser coil. Currently, the header production

FIGURE 2.11 ▶Bar Chart

0Discourteous

serverSlow

serviceCold

dinner

Failure Name

Crampedtables

Atmosphere

Failu

res

10

20

30

4045

5

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35

45

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 99

cell is scheduled separately from the main work in the plant. Often, individual headers are not sequenced to match the product they go into on the final assembly line in a timely fashion, and so the product can sit in queue waiting for a header.

SOLUTIONAs a first step, the team conducted extensive onsite observations across the six processing steps within the cell, followed by the transport of the finished header to the air conditioner assembly area for instal-lation into an air conditioner unit. The six processing steps included:

1. Cut copper pipes to the appropriate length.

2. Punch vent and stub holes into the copper log.

3. Weld a steel supply valve onto the top of the copper log.

4. Braze end caps and vent plugs to the copper log.

5. Braze stub tubes into each stub hole in the copper log.

6. Add plastic end caps to protect the newly created header.

To analyze all the possible causes of the problem, the team constructed a cause-and-effect diagram (Figure 2.13). The main problem, inadequate header production, is the head of the diagram. The team brainstormed all possible causes, and together they identified several major categories: management, labor, method, measurement, machine, and materials—or the 6 Ms. Several suspected causes were identified for each major category.

◀ FIGURE 2.13Cause-and-Effect Diagram for Inadequate Header Production

InadequateHeader

Production

Method LaborManagement

Materials Machine Measurement

Suboptimal schedulingof headers

Excessive batching

90% rework level atthe Weld

Cell layout not fullyoptimized

Operators not givenspecific job requirements

Operators take breaksat the same time

Raw materials stockedon the cell floor

Material clutterthroughout thewhole cell

UnderutilizedRobotic weld

Too many headers inqueue before Braze 2

Frequent machinebreakdowns specificallyat the Weld

Frequent changes inheader priority

Information not clearlycommunicated from theheader cell to management

Confusion caused byunlabeled headers

Setup time increases causedby differences in headersgeometry

DECISION POINTThe improvement team noted several immediate issues that were slowing down production of headers. These issues included operators batching individual jobs (method branch) into groups to save walking time, which was further exacerbated by the availability of raw materials stocked on the shop floor (materials branch) and the lack of specific job requirement (management branch). Further, there were many instances of indi-vidual tasks not being done correctly, and thus having to be redone—such as the 90 percent rework rate at weld (method branch). The next step in this process improvement was to eliminate the raw material on the floor, improve quality at the weld machine, and move each header individually using a header-specific cart.

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100 PART 1 MANAGING PROCESSES

Graphs Visualizing data in user-friendly ways can greatly enhance process analysis. Graphs represent data in a variety of pictorial formats, such as line charts and pie charts. Line charts repre-sent data sequentially with data points connected by line segments to highlight trends in the data. Line charts are used in control charts (see Chapter 3, “Quality and Performance”) and forecasting (see Chapter 8, “Forecasting”). Pie charts represent process factors as slices of a pie; the size of each slice is in proportion to the number of occurrences of the factor. Pie charts are useful for showing data from a group of factors that can be represented as percentages totaling 100 percent.

Each of the tools for improving quality may be used independently, but their power is greatest when they are used together. In solving a process-related problem, managers often must act as detectives, sifting data to clarify the issues involved and deducing the causes. We call this process data snooping. Example 2.4 demonstrates how the tools for improving quality can be used for data snooping.

graphs

Representations of data in a variety of pictorial forms, such as line charts and pie charts.

▲ FIGURE 2.14Application of the Tools for Improving Quality

Materials

Other

People

Process

Out of specification

Not available

Communication

Absenteeism

Training

Wrong setup

Machine speed

Machine maintenance

Schedule changes

Humidity

Broken fiber board

50

40

30

20

10

0

100

80

60

40

20

0

Num

ber

of F

ailu

res

Cum

ulat

ive

Perc

enta

ge

C

D

A B

Step 2. Pareto Chart

20

15

10

5

0

Num

ber

of B

roke

n Fi

ber

Boa

rds

Shift

Step 3. Cause-and-Effect Diagram Step 4. Bar Chart

Headliner failures

Total

4

3

36

7

Total 50

TallyProcess failure

A. Tears in fabric

B. Discolored fabric

C. Broken fiber board

D. Ragged edges

Step 1. Checklist

Process Failure

First Second Third

Identifying Causes of Poor Headliner Process FailuresEXAMPLE 2.4

The Wellington Fiber Board Company produces headliners, the fiberglass components that form the inner roof of passenger cars. Management wanted to identify which process failures were most prevalent and to find the cause.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 101

A simulation model goes one step further than static data analysis tools, because it can show how the process dynamically changes over time. Process simulation is the act of reproducing the behavior of a process, using a model that describes each step. Once the process is modeled, the analyst can make changes in the model to measure the impact on certain metrics, such as response time, waiting lines, resource utilization, and the like. To learn more about how simulation works, see online Supplement E, “Simulation.”

Redesigning and Managing Process ImprovementsA doctor pinpoints an illness after a thorough examination of the patient, and then the doctor recommends treatments based on the diagnosis; so it is with processes. After a process is defined, metrics data are collected, and disconnects are identified, the process analyst or design team puts together a set of changes that will improve the process. At this step, people directly involved in the process are brought in to get their ideas and inputs.

Questioning and BrainstormingSometimes, ideas for reengineering or improving a process become apparent after defining the process and carefully examining the areas of substandard performance, handoffs between depart-ments, and steps where customer contact is high. Example 2.4 illustrated how such documenta-tion pointed to a better way of handling the fiber boards through better training. In other cases, the better solution is less evident. Ideas can be uncovered (because there is always a better way) by asking six questions about each step in the process, and a final series of questions about the process as a whole:

1. What is being done?

2. When is it being done?

3. Who is doing it?

4. Where is it being done?

5. How is it being done?

6. How well does it do on the various metrics of importance?

Answers to these questions are challenged by asking still another series of questions. Why is the process even being done? Why is it being done where it is being done? Why is it being done when it is being done?

Creativity can also be stimulated by brainstorming, letting a group of people knowledgeable about the process propose ideas for change by saying whatever comes to mind. A facilitator records the ideas on a flipchart, so that all can see. Participants are discouraged from evaluating any of the ideas generated during the session. The purpose is to encourage creativity and to get as many ideas as possible, no matter how far-fetched the ideas may seem. The participants of a brainstorming session need not be limited to the design team as long as they have seen or worked with the process. For instance, Baptist Memorial Hospital in Memphis, Tennessee, holds “huddle meetings” at least three times a day seeking out process improvements. The meetings bring together the hospital’s

process simulationThe act of reproducing the behavior of a process, using a model that describes each step.

brainstorming

Letting a group of people, knowledgeable about the process, propose ideas for change by saying whatever comes to mind.

SOLUTIONFigure 2.14 shows the sequential application of several tools for improving quality.

Step 1. A checklist of different types of process failures was constructed from last month’s production records.

Step 2. A Pareto chart prepared from the checklist data indicated that broken fiber board accounted for 72 percent of the process failures.

Step 3. A cause-and-effect diagram for broken fiber board identified several potential causes for the problem. The one strongly suspected by the manager was employee training.

Step 4. The manager reorganized the production reports into a bar chart according to shift, because the personnel on the three shifts had varied amounts of experience.

DECISION POINTThe bar chart indicated that the second shift, with the least experienced workforce, had most of the process failures. Further investigation revealed that workers were not using proper procedures for stack-ing the fiber boards after the press operation, which caused cracking and chipping. The manager set up additional training sessions focused on board handling. Although the second shift was not responsible for all the process failures, finding the source of many of the failures enabled the manager to improve the performance of her operations.

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102 PART 1 MANAGING PROCESSES

house supervisor, housekeeping supervisor, and key nurses. Improvements have been dramatic, and resulted in it being ranked among the top five hospitals in Tennessee.

A growing number of big companies are also taking advantage of the Internet and specially designed software to run brainstorming sessions that allow people at far-flung locations to “meet” online and hash out solutions to particular problems. The technology lets employees see, and build on, one another’s ideas, so that one person’s seed of a notion can grow into a practical plan.

After the brainstorming session is over, the design team moves into the “get real” phase: They evaluate the different ideas. The team identifies the changes that give the best payoffs for process redesign. The redesign could involve issues of capacity, technology, or even location, all of which are discussed in more detail in the following chapters.

The redesigned process is defined once again, this time as the “after” view of the process. Expected payoffs are carefully estimated, along with risks. For changes involving investments, the time value of money must be considered (see online Supplement F, “Financial Analysis”). The impact on people (skills, degree of change, training requirements, and resistance to change) must also be factored into the evaluation of the new design.

BenchmarkingBenchmarking can be another valuable source for process redesign. Benchmarking is a systematic procedure that measures a firm’s processes, services, and products against those of industry lead-ers. Companies use benchmarking to better understand how outstanding companies do things so that they can improve their own processes.

Benchmarking focuses on setting quantitative goals for improvement. Competitive bench-marking is based on comparisons with a direct industry competitor. Functional benchmarking compares areas such as administration, customer service, and sales operations with those of outstanding firms in any industry. For instance, Xerox benchmarked its distribution function against L.L. Bean’s because L.L. Bean is renowned as a leading retailer in distribution efficiency and customer service. Internal benchmarking involves using an organizational unit with superior performance as the benchmark for other units. This form of benchmarking can be advantageous for firms that have several business units or divisions. All forms of benchmarking are best applied in situations where you are looking for a long-term program of continuous improvement.

Typical measures used in benchmarking include cost per unit, service upsets (breakdowns) per customer, processing time per unit, customer retention rates, revenue per unit, return on investment, and customer satisfaction levels.

Collecting benchmarking data can sometimes be a challenge. Internal benchmarking data are surely the most accessible. One way of benchmarking is always available—tracking the perfor-mance of a process over time. Functional benchmarking data are often collected by professional associations or consulting firms. Several corporations and government organizations have agreed to share and standardize performance benchmarks. The American Productivity and Quality Center, a nonprofit organization, created thousands of measures, as Figure 2.15 illustrates. A full range of metrics can be explored at www.apqc.org. Another source is the Supply Chain Council, which has defined key metrics in its Supply Chain Operations Reference (SCOR) model (see Chapter 14, “Supply Chain Integration”).

ImplementingImplementing a beautifully redesigned process is only the beginning to continually monitoring and improving processes. Metrics goals must be continually evaluated and reset to fit changing requirements. Avoid the following seven mistakes when managing processes:4

1. Not Connecting with Strategic Issues. Is particular attention being paid to core processes, competitive priorities, impact of customer contact and volume, and strategic fit during pro-cess analysis?

2. Not Involving the Right People in the Right Way. Does process analysis closely involve the people performing the process, or those closely connected to it as internal customers and suppliers?

3. Not Giving the Design Teams and Process Analysts a Clear Charter, and Then Holding Them Accountable. Does management set expectations for change and maintain pressure for results? Does it allow paralysis in process-improvement efforts by requiring excessive analysis?

4. Not Being Satisfied Unless Fundamental “Reengineering” Changes Are Made. Is the radical change from process reengineering the expectation? If so, the cumulative effect of many small improvements that could be made incrementally could be lost. Process management efforts should not be limited to downsizing or to reorganization only, even though jobs may be eliminated or the structure changed. It should not be limited to big technological innovation projects, even though technological change occurs often.

benchmarking

A systematic procedure that measures a firm’s processes, services, and products against those of industry leaders.

4Geary A. Rummler and Alan P. Brache, Improving Performance, 2nd ed. (San Francisco: Jossey-Bass, 1995), 126–133.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 103

5. Not Considering the Impact on People. Are the changes aligned with the attitudes and skills of the people who must implement the redesigned process? It is crucial to understand and deal with the people side of process changes.

6. Not Giving Attention to Implementation. Are processes redesigned but never implemented? A great job of flowcharting and benchmarking is of only academic interest if the proposed changes are not implemented. Sound project management practices are required.

7. Not Creating an Infrastructure for Continuous Process Improvement. Is a measurement system in place to monitor key metrics over time? Is anyone checking to see whether anticipated benefits of a redesigned process are actually being realized?

Failure to manage processes is failure to manage the business. Managers must make sure that their organization spots new performance gaps in the continual search for process improvements. Process redesign efforts need to be part of periodic reviews and even annual plans. Measurement is the par-ticular focus of the next chapter. It covers how a performance tracking system is the basis for feedback and improvement efforts. The essence of a learning organization is the intelligent use of such feedback.

◀ FIGURE 2.15Illustrative Benchmarking Metrics by Type of Process

Customer Relationship Process

• Total cost of “enter, process, and track orders” per $1,000 revenue• System costs of process per $100,000 revenue• Value of sales order line item not fulfilled due to stockouts, as percentage of revenue• Percentage of finished goods sales value that is returned• Average time from sales order receipt until manufacturing or logistics is notified• Average time in direct contact with customer per sales order line item• Energy consumed in transporting product• Total distance traveled for products• Greenhouse gas emissions

Order Fulfillment Process

• Value of plant shipments per employee• Finished goods inventory turnover• Reject rate as percentage of total orders processed• Percentage of orders returned by customers due to quality problems• Standard customer lead time from order entry to shipment• Percentage of orders shipped on time• Use of non-renewable energy sources• Use of toxic ingredients• Safe and healthy work environment

New Service/Product Development Process

• Percentage of sales due to services/products launched last year• Cost of “generate new services/products” process per $1,000 revenue• Ratio of projects entering the process to projects completing the process• Time to market for existing service/product improvement project• Time to market for new service/product project• Time to profitability for existing service/product improvement project

Supplier Relationship Process

• Cost of “select suppliers and develop/maintain contracts” process per $1,000 revenue• Number of employees per $1,000 of purchases• Percentage of purchase orders approved electronically• Average time to place a purchase order• Total number of active vendors per $1,000 of purchases• Percentage of value of purchased material that is supplier certified• Amount of toxic chemicals used in supplies production process• Energy consumed in transporting raw materials and parts• Total distance traveled for raw materials and parts• Greenhouse gas emissions• Supplier’s use of toxic chemicals in production process• Percentage of child labor used by supplier

Support Process

• Systems cost of finance function per $1,000 revenue• Percentage of finance staff devoted to internal audit• Total cost of payroll processes per $1,000 revenue• Number of accepted jobs as percentage of job offers• Total cost of “source, recruit, and select” process per $1,000 revenue• Average employee turnover rate

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104 PART 1 MANAGING PROCESSES

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources

2.1 Understand the process structure in services and how to position a service process on the customer-contact matrix.

The section “Process Structure in Services” shows at the pro-cess level the key contextual variables associated with service processes and how they relate to each other. There is a key figure in this section: Figure 2.2 brings together three key elements: (1) the degree of customer contact, (2) customization, and (3) process characteristics. It shows how the degree of customer contact and customization are linked with process divergence and line flows.

2.2 Understand the process structure in manufacturing and how to position a man-ufacturing process on the product-process matrix.

See the section “Process Structure in Manufacturing,” which focuses on the manufacturing processes. Figure 2.3 brings together three key elements: (1) volume, (2) product customization, and (3) process characteristics. The key drivers are customiza-tion and volume, which are linked with line flows and the extent of repetitive work. See the video “Manufacturing Process Structure Choices” to understand how SOME BURROS Mexican Restaurant, WT Graphix Custom Embroidery and Silk Screening, and Crayola make tradeoffs between customization and volume in designing their processes.

2.3 Explain the major pro-cess strategy decisions and their implications for operations.

“Process Strategy Decisions” explains three major process strat-egy decisions shown in Figure 2.1. Apart from process structure, these include customer involvement, resource flexibility, and capital intensity. Note that customer involvement has advantages and disadvantages, resource flexibility applies to both workforce and equipment, and economies of scope in certain situations can break the inverse relationship between resource flexibility and capital intensity.

OM Explorer Tutor: Break-Even for Equipment SelectionPOM for Windows: Break-Even Analysis

2.4 Discuss how process deci-sions should strategically fit together.

See “Strategic Fit” for a detailed discussion of ways manag-ers should understand how the four major process decisions tie together in service and manufacturing firms, so as to spot ways of improving poorly designed processes.

2.5 Compare and contrast the two commonly used strategies for change, and understand a system-atic way to analyze and improve processes.

The section “Strategies for Change” explains two different but complementary philosophies for process design and change: (1) process reengineering and (2) process improvement. The Six Sigma DMAIC model for process improvement then shows a systematic way in which processes can be defined, measured, analyzed, improved, and controlled.

2.6 Discuss how to define, measure, and analyze processes.

The section “Defining, Measuring, and Analyzing the Process” discusses three major techniques for effectively defining and measuring processes, including (1) flowcharts, (2) work mea-surement techniques, and (3) process charts. Review the Solved Problems for examples of flowchart, process chart, and Pareto chart construction. The time study method, elemental standard data method, predetermined data method, work sampling method, and learning curve analysis are briefly described in the “Work Measurement Techniques” section. Pareto charts and cause-and-effect diagrams help you to analyze and understand the causes of performance gaps.

Cases: Custom Molds, Inc.; José’s Authentic Mexican RestaurantOM Explorer Solvers: Learning Curve Analysis; Measuring Output Rates; Process Charts; Pareto ChartsOM Explorer Tutors: Process Charts; Pareto ChartsPOM for Windows: Learning Curve Analysis; Measuring Output RatesSupplement I: Learning Curve Analysis

2.7 Identify the commonly used approaches for effectively improving and controlling processes.

The section “Redesigning and Managing Process Improvements” discusses how the process analyst puts together a set of changes that will make the process better. Then seven mistakes to avoid when managing processes are discussed at the end. There must be a continual search for process improvements.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 105

Key Termsassemble-to-order strategy 81automation 83back office 78bar chart 97batch process 80benchmarking 102Black Belt 90brainstorming 101capital intensity 76cause-and-effect diagram 98checklist 96continuous-flow process 80customer contact 77customer involvement 76design-to-order strategy 80economies of scope 84elemental standard data 93fixed automation 84flexible (or programmable)

automation 84flexible flow 78

flexible workforce 82flowchart 91focused factories 87front office 78graphs 100Green Belt 90histogram 97hybrid office 78industrial robot 84job process 80layout 76learning curve 94line flow 78line process 80make-to-order strategy 81make-to-stock strategy 81mass customization 81mass production 81Master Black Belt 90metrics 90

Pareto chart 97plants within plants (PWPs) 86postponement 81predetermined data method 94process analysis 75process chart 95process choice 79process divergence 77process failure 96process improvement 88process simulation 101process strategy 75process structure 76reengineering 88resource flexibility 76scatter diagram 98service blueprint 92swim lane flowchart 91time study 93work sampling 94

Solved Problem 1Create a flowchart for the following telephone-ordering process at a retail chain that special-izes in selling books and music CDs. It provides an ordering system via the telephone to its time-sensitive customers besides its regular store sales.

First, the automated system greets customers and identifies whether they have a tone or pulse phone. Customers choose 1 if they have a tone phone; otherwise, they wait for the first available service representative to process their request. If customers have a tone phone, they complete their request by choosing options on the phone. First, the system checks to see whether custom-ers have an existing account. Customers choose 1 if they have an existing account or choose 2 if they want to open a new account. Customers wait for the service representative to open a new account if they choose 2.

Next, customers choose between the options of making an order, canceling an order, or talk-ing to a customer representative for questions and/or complaints. If customers choose to make an order, then they specify the order type as a book or a music CD, and a specialized customer representative for books or music CDs picks up the phone to get the order details. If customers choose to cancel an order, then they wait for the automated response. By entering the order code via phone, customers can cancel the order. The automated system says the name of the ordered item and asks for the confirmation of the customer. If the customer validates the cancellation of the order, then the system cancels the order; otherwise, the system asks the customer to input the order code again. After responding to the request, the system asks whether the customer has additional requests; if not, the process terminates.

SOLUTION

Figure 2.16 shows the flowchart.

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106 PART 1 MANAGING PROCESSES

FIGURE 2.16 ▶Flowchart of Telephone Ordering Process

AutomatedsystemgreetingSystem/Company action

Legend

Customer action

End call

Customer decision

Enterordercode

Systemrepeatsinput

Cancelorder

Cancel order Place order

Complaint

Wait forCSR

Tonephone?

Newaccount?

Customerconfirms?

Additionalrequests?

End call

End call

No

No

Yes

Yes

No

No

Yes

Yes

CSRcompletes

request

Requesttype?

Specifyordertype

Speak tospecialized

CSR

CSRplacesorder

Solved Problem 2An automobile service is having difficulty providing oil changes in the 29 minutes or less mentioned in its advertising. You are to analyze the process of changing automobile engine oil. The subject of the study is the service mechanic. The process begins when the mechanic directs the customer’s arrival and ends when the customer pays for the services.

SOLUTION

Figure 2.17 shows the completed process chart. The process is broken into 21 steps. A summary of the times and distances traveled is shown in the upper-righthand corner of the process chart.

The times add up to 28 minutes, which does not allow much room for error if the 29-minute guarantee is to be met and the mechanic travels a total of 420 feet.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 107

◀ FIGURE 2.17Process Chart for Changing Engine Oil

Insert Step

Summary

ActivityNumberof Steps

Time(min)

Distance(ft)

Append Step

Remove Step

Process:

Subject:

Beginning:

Ending:

Changing engine oil

Mechanic

Direct customer arrival

Total charges, receive paymentOperation

Transport

Inspect

Delay

Store

7

8

4

1

1

16.50

5.50

5.00

0.70

0.30

420

StepNo.

Step Description

123456789

101112131415161718192021

Direct customer into service bayRecord name and desired serviceOpen hood, verify engine type, inspect hoses, check fluidsWalk to customer in waiting areaRecommend additional servicesWait for customer decisionWalk to storeroomLook up filter number(s), find filter(s)Check filter number(s)Carry filter(s) to service pitPerform under-car servicesClimb from pit, walk to automobileFill engine with oil, start engineInspect for leaksWalk to pitInspect for leaksClean and organize work areaReturn to auto, drive from bayPark the carWalk to customer waiting areaTotal charges, receive payment

Distance(ft)

50.0

30.0

70.0

50.0

40.0

40.0

80.0

60.0

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Time(min)

0.801.802.300.800.600.700.901.900.400.604.200.702.701.300.501.003.000.700.300.502.30

Solved Problem 3What improvement can you make in the process shown in Figure 2.17?

SOLUTION

Your analysis should verify the following three ideas for improvement. You may also be able to come up with others.

a. Move Step 17 to Step 21. Customers should not have to wait while the mechanic cleans the work area.

b. Store Small Inventories of Frequently Used Filters in the Pit. Steps 7 and 10 involve travel to and from the storeroom. If the filters are moved to the pit, a copy of the reference mate-rial must also be placed in the pit. The pit will have to be organized and well lighted.

c. Use Two Mechanics. Steps 10, 12, 15, and 17 involve running up and down the steps to the pit. Much of this travel could be eliminated. The service time could be shortened by having one mechanic in the pit working simultaneously with another working under the hood.

Solved Problem 4Vera Johnson and Merris Williams manufacture vanishing cream. Their packaging process has four steps: (1) mix, (2) fill, (3) cap, and (4) label. They have had the reported process failures analyzed, which shows the following:

Process failure Frequency

Lumps of unmixed product 7

Over- or underfilled jars 18

Jar lids did not seal 6

Labels rumpled or missing 29

Total 60

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108 PART 1 MANAGING PROCESSES

Draw a Pareto chart to identify the vital failures.

SOLUTION

Defective labels account for 48.33 percent of the total number of failures:

2960

* 100% = 48.33%

Improperly filled jars account for 30 percent of the total number of failures:

1860

* 100% = 30.00%

The cumulative percent for the two most frequent failures is

48.33% + 30.00% = 78.33%

Lumps represent 760

* 100% = 11.67% of failures; the cumulative percentage is

78.33% + 11.67% = 90.00%

Defective seals represent 660

* 100% = 10% of failures; the cumulative percentage is

10% + 90% = 100.00%

The Pareto chart is shown in Figure 2.18.

Discussion Questions1. What processes at manufacturing firms are really service

processes that involve considerable customer contact? Can customer contact be high, even if the process only has internal customers?

2. Consider this sign seen in a local restaurant: “To-go orders do NOT include complimentary chips and salsa. If you have any questions, see our management, NOT our employees.” What impact does this message have on its employees, their service processes, and customer sat-isfaction? Contrast this approach with the one taken by a five-star restaurant. Are the differences primarily due to different competitive priorities?

3. How do the process strategies of eBay and McDonald’s differ, and how do their choices relate to customer-introduced variability?

4. Medical technology can outfit a patient with an artificial heart or cure vision defects with the touch of a laser. However, hospitals still struggle with their back-office processes, such as getting X-ray files from radiology on the fourth floor to the first-floor view boxes in the emer-gency room without having to send a runner. More than 90 percent of the estimated 30 billion health transac-tions each year are conducted by telephone, fax, or mail. To what extent, and how, can information technology

FIGURE 2.18 ▶Pareto Chart

40

36

32

28

24

20

16

12

8

4

0

100

90

80

70

60

50

40

30

20

10

0

Freq

uenc

y of

Fai

lure

s

Cum

ulat

ive

Perc

enta

ge o

f Fai

lure

s

Label Fill Mix Seal

48%

78%

90% 100%

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 109

improve productivity and quality for such processes? Remember that some doctors are not ready to give up their pads and pencils, and many hospitals have strong lines drawn around its departments, such as pharmacy, cardiology, radiology, and pediatrics.

5. Consider the range of processes in the financial services industry. What position on the customer-contact matrix would the process of selling financial services to munic-ipalities occupy? The process of preparing monthly fund balance reports? Explain why they would differ.

6. Assume you had your hair styled in a hair salon after making an online booking. Calculate a combined score for the overall customer contact after considering each of the five dimensions of customer contact in Table 2.1. Use a seven-point scale, where 1= very low and 7= very high. For example, online booking will have low customer contact score because the customer is not present. Did you use equal weightings in calculating the combined score? Why or Why not? Where would you position the process in customer-contact matrix? Is it properly aligned? Why or Why not?

7. Continuous improvement recognizes that many small improvements add up to sizeable benefits. Will continu-ous improvement take a company at the bottom of an industry to the top? Explain.

8. The Hydro-Electric Company (HEC) has three sources of power. A small amount of hydroelectric power is generated by damming wild and scenic rivers; a sec-ond source of power comes from burning coal, with emissions that create acid rain and contribute to global warming; the third source of power comes from nuclear fission. HEC’s coal-fired plants use obsolete pollution-control technology, and an investment of several hun-dred million dollars would be required to update it. Environmentalists urge HEC to promote conservation and purchase power from suppliers that use the cleanest fuels and technology.

However, HEC is already suffering from declining sales, which have resulted in billions of dollars invested in idle equipment. Its large customers are taking advantage of laws that permit them to buy power from low-cost suppliers. HEC must cover the fixed costs of idle capac-ity by raising rates charged to its remaining customers

or face defaulting on bonds (bankruptcy). The increased rates motivate even more customers to seek low-cost suppliers, the start of a death spiral for HEC. To prevent additional rate increases, HEC implements a cost-cutting program and puts its plans to update pollution controls on hold.

Form sides and discuss the ethical, environmental, and political issues and trade-offs associated with HEC’s strategy.

9. Paul O’Neill, former U.S. Treasury secretary, estimated that arguably half of the $2 trillion a year that Americans spend on health care is needlessly wasted. Brainstorm up to 10 blue-sky ideas to solve the following problems:

a. A typical retail pharmacy spends 20 percent of its time playing telephone tag with doctors, trying to find out the intent for a given prescription.

b. After the person responsible for filling the prescrip-tion determines what she thinks she is supposed to do, errors can be made even in filling the prescrip-tion. For example, administering an adult dose (rather than the dose for a premature baby) of heparin in a preemie ICU is fatal.

c. Drugs get distributed at a hospital on a batch basis. For example, carts can be filled on Monday, Wednesday, and Friday. A huge volume of drugs can come back on Monday because they are not consumed on the wards between Friday and Monday, patient conditions changed, or the doctor decided on a different intervention. A technician spends the rest of the day restocking the shelves with the returns and 40 percent of the intravenous materials prepared on Friday morning are poured down the drain.

d. Sometimes the administration of the drug was not done on the agreed-upon schedule, because the nurses were busy doing something else.

e. For every bed in an acute care hospital system, someone falls during the year. Most falls occur after 11 p.m. and before 6 a.m. Sometimes a bone is fractured, leading to immobilization and then pneumonia.

f. One in every 14 people who go to a U.S. hospital contract an infection in the hospital.

The OM Explorer, POM for Windows, and Active Model soft-ware is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how

to do the calculations by hand. At the least, the software pro-vides a check on your calculations. When calculations are particularly complex and the goal is interpreting the results in making decisions, the software replaces entirely the manual calculations.

Problems

Problems 1, 2, and 3 apply break-even analysis (discussed in Supplement A, “Decision Making”) to process decisions.

1. Dr. Gulakowicz is an orthodontist. She estimates that adding two new chairs will increase fixed costs by $150,000, including the annual equivalent cost of the capital investment and the salary of one more technician. Each new patient is expected to bring in

$3,000 per year in additional revenue, with variable costs estimated at $1,000 per patient. The two new chairs will allow Dr. Gulakowicz to expand her practice by as many as 200 patients annually. How many patients would have to be added for the new process to break even?

2. Two different manufacturing processes are being con-sidered for making a new product. The first process is

Process Strategy Decisions

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110 PART 1 MANAGING PROCESSES

less capital intensive, with fixed costs of only $50,000 per year and variable costs of $700 per unit. The second process has fixed costs of $400,000 but has variable costs of only $200 per unit.

a. What is the break-even quantity beyond which the second process becomes more attractive than the first?

b. If the expected annual sales for the product is 800 units, which process would you choose?

3. Gömböc shapes are interesting mathematical shapes attracting attention from mathematics enthusiasts. These blocks involve a complex manufacturing and molding process. A manufacturer is evaluating three machines that can be used for producing these shapes.

The annual capital and variable costs associated with each machine are provided in the accompanying table.

Types of MachinesAnnual Cost of

Capital RequiredVariable Costs per Machine

Machine 1 £25,000 £3

Machine 2 £15,000 £5

Machine 3 £10,000 £15

At what quantity range will each option be preferred?

Defining, Measuring, and Analyzing the Process

4. Consider the Custom Molds, Inc., case at the end of this chapter. Prepare a flowchart of the mold fabrication process and the parts manufacturing process, showing how they are linked.

5. Do Problem 4 using a process chart spreadsheet of your own design, one that differs from the Process Chart Solver in OM Explorer. It should have one or more col-umns to record information or metrics that you think are relevant, be they external customer contacts, time delays, completion times, percent rework, costs, capac-ity, or demand rates. Your entries should show what information you would collect, even though only part of it is available in the case.

6. Founded in 1970, ABC is one of the world’s largest insurance companies with locations in 28 countries. Given the following description, flowchart the new policy setup process as it existed in 1970:

Individual customers who wanted to set up a new policy would visit one of ABC’s 70 branch offices or make contact with an agent. They would then fill out an application and sometimes attach a check. The branch office then sent the application package through company mail to the XYZ division in London. In addition, a customer might also fill out the application at home and send it directly to any number of ABC locations, which would then transfer it to the London operation. Once received, XYZ separated the various parts of the application, then scanned and digitized it. The electronic image was then retrieved from a server and delivered to an associate’s desktop client computer. The associate was responsible for entering the information on the form into the appropriate database. If the information supplied on the application was complete, a confirmation notice was automatically printed and sent to the customer. If the information was incomplete, then another associate, trained to deal with customers on the telephone, would call the customer to obtain the additional information. If something was wrong on the confirmation notice received, the customer would either call a toll-free number or send in a letter describing the problem. The Customer Problem Resolution division dealt with problems arising at this point. An updated confirmation notice was sent to the customer. If the information was correct, the application transaction was complete.

7. Do Problem 6 using a process chart spreadsheet of your own design, one that differs from the Process Chart Solver in OM Explorer. It should have one or more columns to record information or metrics that you think should be collected to analyze the process (see Problem 5).

8. Prepare a flowchart of the field service division process at DEF, as described here. Start from the point where a call is received and end when a technician finishes the job.

DEF was a multibillion dollar company that manufac-tured and distributed a wide variety of electronic, pho-tographic, and reprographic equipment used in many engineering and medical system applications. The Field Service Division employed 475 field service technicians, who performed maintenance and warranty repairs on the equipment sold by DEF. Customers would call DEF’s National Service Center (NSC), which received about 3,000 calls per day. The NSC staffed its call center with about 40 call-takers. A typical incoming service call was received at the NSC and routed to one of the call-takers, who entered information about the machine, the caller’s name, and the type of problem into DEF’s mainframe computer. In some cases, the call-taker attempted to help the customer fix the problem. However, call-takers were currently only able to avoid about 10 percent of the incoming emergency maintenance service calls. If the service call could not be avoided, the call-taker usually stated the following script: “Depending upon the avail-ability of our technicians, you should expect to see a technician sometime between now and (now + X).” (“X” was the target response time based on the model number and the zone.) This information was given to the customer because many customers wanted to know when a tech would arrive on site.

Call-takers entered service call information on DEF’s computer system, which then sent the information elec-tronically to the regional dispatch center assigned to that customer location. (DEF had four regional dispatch centers with a total of about 20 dispatchers.) Service call information was printed on a small card at the dis-patch center. About every hour, cards were ripped off the printer and given to the dispatcher assigned to that customer location. The dispatcher placed each card on a magnetic board under the name of a tech that the dispatcher believed would be the most likely candidate for the service call, given the location of the machine,

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the current location of the tech, and the tech’s training profile. After completing a service call, techs called the dispatcher in the regional dispatch center, cleared the call, and received a new call assigned by the dispatcher. After getting the service call from a dispatcher, a tech called the customer to give an expected time of arrival, drove to the customer site, diagnosed the problem, repaired the machine if parts were available in the van, and then telephoned the dispatcher for the next call. If the tech did not have the right parts for a repair, the tech informed the NSC, and the part was express mailed to the customer; the repair was done the next morning.

9. Big Bob’s Burger Barn would like to graphically depict the interaction among its lunch-ordering customers and its three employees. Customers come into the restaurant and eat there rather than drive through and eat in the car. Using the brief process descriptions below, develop a service blueprint.

Fry Employee: receive customer order from counter employee, retrieve uncooked food, drop food into fry vat, wrap cooked food into special packaging, place wrapped items on service counter.

Grill Employee: receive customer order from counter employee, retrieve uncooked food, place food onto grill, build sandwich with requested condiments, deliver sandwich to Counter Employee.

Counter Employee: take order from customer, transmit appropriate orders to Fry and Grill Employee, transact payment, retrieve drinks, wrap sandwich, package order, and deliver order to customer.

10. As part of a COVID-19 response team, you have to put together a group of volunteers to cook hot meals for 300 health workers at a local hospital. The menu consists of the following items: flavored rice, tomato soup, vegetable salad, chocolate cake, and a bottle of fresh juice. All items except the chocolate cake and the fresh juice will be prepared inside a nearby tent with cooking facilities. For ease of distribution, the prepared meals will be packed in cardboard boxes which will be stored in reusable crates. Construct a flowchart and a process chart for the temporary kitchen. What inputs in terms of materials, human effort, and equipment are involved? Estimate the number of volunteers, food items, and packaging material required for this operation.

11. Assume you are working as an intern in the accounts pay-able department of a construction company. As an intern, you have to process the invoices you receive from sup-pliers on a weekly basis. You receive an average of 200 invoices per week. Suppliers send their invoices by post and email. The business processes are largely manual in nature with technology used only for making payment and accounting purposes. Before making payments, you have to complete the following steps: print out the purchase order if sent digitally (3 minutes each); identify the pur-chase order number and retrieve the actual purchase order from the purchasing ledger (3 minutes each); retrieve the goods received document from the stores office ledger and undertake a three-way match between invoice, purchase order, and goods receipt document (5 minutes each), if all the values match, approve the invoice, submit it to the procurement manager for approval (2 minutes each); inform supplier about the status via phone/email about the invoice status (5 minutes each).

a. Make a process chart for the above activity, assuming that it is a one-person operation.

b. Estimate how long will it take to process 200 invoices. Assume that you are paid $15 per hour. How much will it cost to process 200 invoices?

c. Consider each of the following process changes. Which changes would reduce the time and cost of the current process?

# All the relevant documents are scanned and stored as PDFs in a predetermined folder.

# There is a mismatch between the document values. # You are using an integrated ERP system that does

the three-way matching. # You are scanning the approved invoice and

emailing it to the procurement manager. # You are providing access to the invoice approval

process so that a supplier can view the status online.

d. Would any of these changes be likely to reduce the effectiveness of the mailing? If so, which ones? Why?

e. Would the changes that increase time and cost be likely to increase the effectiveness of the mailing? Why or why not?

12. Diagrams of two self-service gasoline stations, both located on corners, are shown in Figure 2.19(a) and (b). Both have two rows of four pumps and a booth at which an attendant receives payment for the gasoline. At neither station is it necessary for the customer to pay in advance. The exits and entrances are marked on the diagrams. Analyze the flows of cars and people through each station.

a. Which station has the more efficient flows from the standpoint of the customer?

b. Which station is likely to lose more potential cus-tomers who cannot gain access to the pumps because another car is headed in the other direction?

c. At which station can a customer pay without getting out of the car?

13. The management of the Just Like Home Restaurant has asked you to analyze some of its processes. One of these processes is making a single-scoop ice cream cone. Cones can be ordered by a server (for table service) or by a customer (for takeout).

Figure 2.20 illustrates the process chart for this operation.

# The ice cream counter server earns $10 per hour (including variable fringe benefits).

# The process is performed 10 times per hour (on average).

# The restaurant is open 363 days a year, 10 hours a day.a. Complete the Summary (top-right) portion of the chart.

b. What is the total labor cost associated with the process?

c. How can this operation be made more efficient? Make a process chart using OM Explorer’s Process Charts Solver of the improved process. What are the annual labor savings if this new process is implemented?

14. While undertaking a degree in operations management, you are interested in applying for internships in this field. These jobs are advertised in job portals such as Monster, business networking portals such as Linke-dIn, and in many cases through word of mouth. You are also planning to use novel approaches such as a

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112 PART 1 MANAGING PROCESSES

video curriculum vitae (CV). To land up in a job posi-tion of your choice, you have to understand the activities involved as an operations intern, search for opportu-nities, develop your CV, cover letter, create a social networking profile, and also reach out to friends and families for contacts apart from the university placement cell. You need to customize the CV and cover letter based on the opportunity and, in many cases, there will be no acknowledgment from employers. Prepare a list of pro-cess chart steps and place them in an efficient sequence.

15. At the Department of Motor Vehicles (DMV), the process of getting license plates for your car begins when you enter the facility and take a number. You walk 50 feet to the waiting area. During your wait, you count about 30 customers waiting for service. You notice that many cus-tomers become discouraged and leave. When a number is called, if a customer stands, the ticket is checked by a uniformed person, and the customer is directed to the available clerk. If no one stands, several minutes are lost while the same number is called repeatedly. Eventually, the next number is called, and more often than not, that customer has left, too. The DMV clerk has now been idle for several minutes but does not seem to mind.

After 4 hours, your number is called and checked by the uniformed person. You walk 60 feet to the clerk, and the process of paying city sales taxes is completed in 4 minutes. The clerk then directs you to the waiting area for paying state personal property tax, 80 feet away. You take a dif-ferent number and sit down with some different custom-ers who are just renewing licenses. There is a 1-hour, 40-minute wait this time, and after a walk of 25 feet you pay property taxes in a process that takes 2 minutes. Now that you have paid taxes, you are eligible to pay registra-tion and license fees. That department is 50 feet away, beyond the employees’ cafeteria.

▲ FIGURE 2.19Two Self-Service Gasoline Stations

Road

Road

Cashier’s booth

Grass

Entrance and exit

Entrance and exit

Air pump

Air pump

Gas pumps

(a)

Road

Road

Cashier’s booth

Exit only

Exit only

Entranceonly

Entranceonly

Gas pumps

(b)

Grass

Grass

FIGURE 2.20 ▶Process Chart for Making Ice Cream Cones

Insert Step

Summary

ActivityNumberof Steps

Time(min)

Distance(ft)

Append Step

Remove Step

Process:

Subject:

Beginning:

Ending:

Making one ice cream cone

Server at counter

Walk to cone storage area

Give it to server or customerOperation

Transport

Inspect

Delay

Store

StepNo.

Step Description

123456789

1011121314

Walk to cone storage areaRemove empty coneWalk to counterPlace cone in holderWalk to sink areaAsk dishwasher to wash scoopWalk to counter with clean scoopPick up empty coneWalk to flavor orderedScoop ice cream from containerPlace ice cream in coneCheck for stabilityWalk to order placement areaGive server or customer the cone

Distance(ft)

5.0

5.0

8.0

8.0

2.5

2.5

X

X

X

XX

X

X

X

X

X

X

XX

X

Time(min)

0.200.050.100.050.200.500.150.050.100.750.750.250.050.05

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The registration and license customers are called in the same order in which personal property taxes were paid. There is only a 10-minute wait and a 3-minute pro-cess. You receive your license plates, take a minute to complain to the license clerk about the wait, and leave exactly 6 hours after arriving.

Make a process chart using OM Explorer’s Process Charts Solver to depict this process, and suggest improvements.

16. Refer to the process chart for the automobile oil change in Solved Problem 2. Calculate the annual labor cost if:

# The mechanic earns $40 per hour (including variable fringe benefits).

# The process is performed twice per hour (on average). # The shop is open 300 days a year, 10 hours a day.

a. What is the total labor cost associated with the process?

b. If steps 7, 10, 12, and 15 were eliminated, estimate the annual labor savings associated with implement-ing this new process.

17. A time study of an employee assembling peanut valves resulted in the following set of observations. What is the standard time, given a performance rating of 95 percent and an allowance of 20 percent of the total normal time?

Average Time (seconds) Observations

15 14

20 12

25 15

18. An initial time study was done on a process with the following results (in minutes). Based on the data obtained so far, assuming an allowance of 20 percent of the normal time, what do you estimate for the time per customer served, based on this preliminary sample?

ElementPerformance

Rating Obs 1 Obs 2 Obs 3 Obs 4 Obs 5

Element 1 70 4 3 5 4 3

Element 2 110 8 10 9 11 10

Element 3 90 6 8 7 7 6

19. A work sampling study was conducted to determine the proportion of the time a worker is idle. The following information was gathered on a random basis.

DayNumber of Times

Worker IdleTotal Number of

Observations

Monday 17 44

Tuesday 18 56

Wednesday 14 48

Thursday 16 60

a. Based on these preliminary results, what percent of the time is the worker working?

b. If idle time is judged to be excessive, what additional categories might you add to a follow-up work sam-pling study to identify the root causes?

20. A contractor is preparing a bid to install swimming pools at a new housing addition. The estimated time to build the first pool is 35 hours. The contractor estimates an 85 percent learning rate. Without using the computer:

a. How long do you estimate the time required to install the second pool?

b. How long do you estimate the time required to install the fourth pool?

21. Return to Problem 20. Using OM Explorer’s Learning Curves Solver, how long do you estimate the time required to install the fifth pool? What is your estimate of the total time for all five pools?

22. On RainTite Window’s manual assembly line, a new employee can usually assemble the first window unit in 30 minutes. Management assumes a 90 percent learning rate.

a. How long should a new employee take to assemble the second window if management is correct in their assumption? How long should the 16th window take?

b. On RainTite’s semiautomated line, a new employee takes 45 minutes to assemble the first window; how-ever, the learning rate is 75 percent. At how many windows produced will the semiautomated line’s employee take less time to produce a window than an employee on the manual line?

23. A hospital emergency service department was analyz-ing the factors that were contributing to failing perfor-mance against response time targets set for urgent care response calls. It listed the main issues that prevented the ambulance from bringing the patient back to the hospital on time.

Problem Frequency

Ambulance driver unable to locate the patient 22

Road traffic 30

Ambulance performance issues 8

Staff availability 8

Equipment issues 12

Uncooperative patient 14

Delayed support from other agencies such as fire and police 6

Total 100

a. Use a Pareto chart to identify the “vital few” patient transport problems. Comment on potential root causes of these problems and identify any especially egregious quality failures.

b. To understand the root cause of the problem, the hospital management requested the ambulance crew to maintain a log of specific difficulties. After a week, the log included the following entries: drunk patient, caller unaware of the location, incorrect address pro-vided, vehicle had mechanical issues, unable to fit patient on a stretcher due to body size, and map system does not have real-time traffic updates.

Organize these causes into a cause-and-effect diagram.

24. Smith, Schroeder, and Torn (SST) is a short-haul house-hold furniture moving company. SST’s labor force, selected from the local community college football team,

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is temporary and part time. SST is concerned with recent complaints, as tabulated on the following tally sheet.

Complaint Tally

Broken glass ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Delivered to wrong address ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Furniture rubbed together while on truck

∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Late delivery ∙ ∙ ∙ ∙

Late arrival for pickup ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Missing items ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Nicks and scratches from rough handling

∙ ∙ ∙ ∙ ∙ ∙ ∙ ∙

Soiled upholstery ∙ ∙ ∙ ∙ ∙ ∙ ∙

a. Draw a bar chart and a Pareto chart using OM Explorer to identify the most serious moving problems.

b. The manager of Smith, Schroeder, and Torn is attempting to understand the root causes of com-plaints. He has compiled the following list of issues that occurred during problem deliveries:

truck broke down, ran out of packing boxes, multiple deliveries in one day caused truck to be late, no fur-niture pads, employee dropped several items, driver got lost en route to address, ramp into truck was bent, no packing tape, new employee doesn’t know how to pack, moving dolly has broken wheel, and employee late to work

Organize these causes into a cause-and-effect dia-gram.

25. Rick DeNeefe, manager of the Golden Valley Bank credit authorization department, recently noticed that a major competitor was advertising that applications for equity loans could be approved within 2 working days. Because fast credit approval was a competitive priority, DeNeefe wanted to see how well his department was doing relative to the competitor’s. Golden Valley stamps each application with the date and time it is received and again when a decision is made. A total of 104 applications were received in March. The time required for each decision, rounded to the nearest hour, is shown in the table. Golden Valley’s employees work 8 hours per day.

Decision Process Time (hours) Frequency

8 8

11 19

14 28

17 10

20 25

23 4

Decision Process Time (hours) Frequency

26 10

Total 104

a. Draw a bar chart for these data.

b. Analyze the data. How is Golden Valley Bank doing with regard to this competitive priority?

26. A business school undertook research to investigate the reasons for high-level absenteeism and lack of engage-ment from its students. It conducted a group discussion with students to uncover the key reasons that could be classified into the following categories.

Complaint Frequency

Subject not taught interestingly 45

Content is outdated 20

Health issues of students 15

Timing is not convenient 10

Little encouragement from teachers to participate

10

a. Draw a Pareto chart to identify the significant reasons for poor engagement.

b. Categorize the following identified problems into a cause-and-effect diagram: study material, people, delivery style, and health of students.

27. Oregon Fiber Board makes roof liners for the automo-tive industry. The manufacturing manager is concerned about product quality. She suspects that one particular failure, tears in the fabric, is related to production-run size. An assistant gathers the following data from pro-duction records.

Run Size Failures (%) Run Size Failures (%)

1 1,000 3.5 11 6,500 1.5

2 4,100 3.8 12 1,000 5.5

3 2,000 5.5 13 7,000 1.0

4 6,000 1.9 14 3,000 4.5

5 6,800 2.0 15 2,200 4.2

6 3,000 3.2 16 1,800 6.0

7 2,000 3.8 17 5,400 2.0

8 1,200 4.2 18 5,800 2.0

9 5,000 3.8 19 1,000 6.2

10 3,800 3.0 20 1,500 7.0

a. Draw a scatter diagram for these data.

b. Does there appear to be a relationship between run size and percent failures? What implications do these data have for Oregon Fiber Board’s business?

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28. Transport Research Laboratory, a UK-based global company, undertook a research to identify factors that contributed to the increasing number of road accidents. In its report titled “The effects of drivers’ speed on the frequency of road accidents,” it gathered the following data on the accident frequency (per link per year) and mean speed (miles/hour) in London.

Accident Frequency Mean Speed (miles/hour)

0.75 20

1.25 25

1.5 28

2 30

2.5 32

3 35

Source: http://www.20splentyforuk.org.uk/UsefulReports/TRLREports/trl421SpeedAccidents.pdf

a. Draw a scatter diagram for these data.

b. Is there a relationship between mean speed and accident frequency?

c. Do you think this relationship can be applied to regions outside London?

29. The operations manager for Superfast Airlines at Chicago’s O’Hare Airport noticed an increase in the number of delayed flight departures. She brainstormed possible causes with her staff:

# Aircraft late to gate # Acceptance of late passengers # Passengers arriving late at gate # Passenger processing delays at gate # Late baggage to aircraft # Other late personnel or unavailable items # Mechanical failures

Draw a cause-and-effect diagram to organize the possible causes of delayed flight departures into the following major categories: equipment, personnel, material, procedures, and other factors beyond managerial control. Provide a detailed set of causes for each major cause identified by the operations manager, and incorporate them in your cause-and-effect diagram.

30. A leading domestic gas meter manufacturer was facing a wide range of quality issues and observed wastage at several stages of the supply chain. It analyzed performance data of the process over a period of one month. The table presents the results.

Type of Wastage Number of Occurrences

Assembly components not con-forming to quality

345

Product damage during work in progress

140

Rejection after final assembly 55

Type of Wastage Number of Occurrences

Rejection from customer 40

Damage due to improper material handling in warehouse

75

Draw a Pareto chart to identify the key issues the business must focus on to improve the situation.

31. Polar Magnets Limited is a global supplier of neodym-ium magnets. Based in Japan, it manufactures magnets of various sizes and shapes such as circular, rectangu-lar, cylindrical, and spherical. Recently, it introduced a new ring-shaped magnet with a diameter of 25 mm and a pull strength of 6.5 kg. The manufacturing size tolerance is +/- 0.1 mm, the pull strength is 6.5 kg with a tolerance of +/- 200 g. To ensure that the new range is in line with the specification, an analyst gathered data of a random sample of 100 magnets.

a. Draw a histogram for these data.

b. Magnets with pull strength less than 5.8 kg or more than 6.2 kg are considered to be out of specification. Based on the sample data, what percentage of the magnets will be out of specification?

Pull Weight of the Magnet (kg)

6.05 6.22 6.14 6.51 6.19 6.73 6.25 6.45 6.51 6.44

6.01 6.06 6.79 6.51 6.54 6.95 6.16 6.5 6.03 6.43

6.2 6.37 6.44 6.69 6.78 6.05 6.68 6.47 6.86 6.4

6.97 6.91 6.82 6.22 6.79 6.41 6.14 6.96 6.65 6.97

6.15 6.68 6.7 6.6 6.36 6.25 6.23 6.02 6.81 6.52

6.71 6.45 6.31 6.9 6.1 6.31 6.21 6.1 6.02 6.09

6.34 6.33 6.85 6.4 6.52 6.56 6.96 6.96 6.58 6.31

6.06 6.14 6.9 6.66 6.63 6.06 6.94 6.22 6.23 6.82

6.58 6.99 6.4 6.36 6.32 6.7 6.38 6.4 6.34 6.12

6.3 6.08 6.52 6.24 6.98 6.64 6.42 6.42 6.18 6.78

32. This problem should be solved as a team exercise.

Shaving is a process that many men perform each morning. Assume that the process begins at the bathroom sink with the shaver walking (say, 5 feet) to the cabinet (where his shaving supplies are stored) to pick up bowl, soap, brush, and razor. He walks back to the sink, runs the water until it gets warm, lathers his face, shaves, and inspects the results. Then he rinses the razor; dries his face; walks over to the cabinet to return the bowl, soap, brush, and razor; and comes back to the sink to clean it up and complete the process.

a. Develop a process chart for shaving. (Assume suit-able values for the time required for the various activities involved in the process.)

b. Brainstorm to generate ideas for improving the shaving process. Having fewer than 20 ideas is unacceptable. (Do not try to evaluate the ideas until the group has compiled as complete a list as possible. Otherwise, judgment will block creativity.)

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33. Busybee Fabricators are manufacturers of high-quality steel chests used for storing car repair tools. All chests are subjected to rigorous quality checks prior to dispatch. As a quality assurance professional, you have been tasked to examine the reasons for rejects and present your find-ings to the business process improvement team. Upon examining the reasons for rejections, each reject has been attached to a specific category as labeled below.

Wheels not attached to the chest A 17

Missing handles B 9

Ball-bearing slides not functioning properly C 9

Locking mechanism does not work D 9

Dents and scratches at the back of the chest E 6

For 50 chests that had been rejected in the last quarter, the summary statement showed the following:

C B A D D A B C B D

A E A C D A C A A A

C D A E B C B D A C

D A A C A B E A E C

A B E D A E B A D B

a. Prepare a tally sheet (or checklist) listing the various reasons for rejection.

b. Develop a Pareto chart to identify the more signifi-cant types of rejection.

c. Examine the causes of the most significant type of defect, using a cause-and-effect diagram.

Active Model ExerciseThis Active Model is available online. Continuing on with Exam-ple 2.2, it allows you to evaluate the structure of a Pareto chart.

QUESTIONS

1. What percentage of overall complaints does discourte-ous service account for?

2. What percentage of overall complaints do the three most common complaints account for?

3. How does it affect the chart if we eliminate discourte-ous service?

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Custom Molds, Inc.CASECustom Molds, Inc., manufactures custom-designed molds for plastic parts and produces custom-made plastic connectors for the electronics industry. Located in Tucson, Arizona, Custom Molds was founded by the father-and-son team of Tom and Mason Miller in 1997. Tom Miller, a mechanical engineer, had more than 20 years of experience in the connector industry with AMP, Inc., a large multinational producer of electronic connectors. Mason Miller graduated from the Arizona State University in 1996 with joint degrees in chemistry and chemical engineering.

The company was originally formed to provide manufacturers of elec-tronic connectors with a source of high-quality, custom-designed molds for producing plastic parts. The market consisted mainly of the product design and development divisions of those manufacturers. Custom Molds worked closely with each customer to design and develop molds to be used in the customer’s product development processes. Thus, virtually every mold had to meet exacting standards and was somewhat unique. Orders for multiple molds would arrive when customers moved from the design and pilot-run stage of development to large-scale production of newly designed parts.

As the years went by, Custom Molds’s reputation grew as a designer and fabricator of precision molds. Building on this reputation, the Millers decided to expand into the limited manufacture of plastic parts. Ingredient-mixing facilities and injection-molding equipment were added, and by the mid-2000s, Custom Molds developed its reputation to include being a supplier of high-quality plastic parts. Because of limited capacity, the company concentrated its sales efforts on supplying parts that were used in limited quantities for research and development efforts and in preproduction pilot runs.

Production Processes

By 2017, operations at Custom Molds involved two distinct processes: one for fabricating molds and one for producing plastic parts. Although different, in many instances these two processes were linked, as when a customer would have Custom Molds both fabricate a mold and produce the necessary parts to support the customer’s research and design efforts. All fabrication and produc-tion operations were housed in a single facility. The layout was characteristic of a typical job shop, with like processes and similar equipment grouped in vari-ous places in the plant. Figure 2.21 shows a layout of the plant floor. Multiple pieces of various types of high-precision machinery, including milling, turning, cutting, and drilling equipment, were located in the mold-fabrication area.

Fabricating molds is a skill-oriented, craftsman-driven process. When an order is received, a design team, comprising a design engineer and 1 of 13 master machinists, reviews the design specifications. Working closely with the customer, the team establishes the final specifications for the mold and gives them to the master machinist for fabrication. It is always the same machinist who was assigned to the design team. At the same time, the pur-chasing department is given a copy of the design specifications, from which it orders the appropriate raw materials and special tooling. The time needed to receive the ordered materials is usually 3 to 4 weeks. When the materials are received for a particular mold, the plant master scheduler reviews the work-load of the assigned master machinist and schedules the mold for fabrication.

Fabricating a mold takes from 2 to 4 weeks, depending on the amount of work the machinist already has scheduled. The fabrication process itself takes only 3 to 5 days. Upon completion, the mold is sent to the testing and inspection area, where it is used to produce a small number of parts on one of the injection-molding machines. If the parts meet the design specifica-tions established by the design team, the mold is passed on to be cleaned and polished. It is then packed and shipped to the customer. One day is spent inspecting and testing the mold and a second day cleaning, polishing, packing, and shipping it to the customer. If the parts made by the mold do

not meet design specifications, the mold is returned to the master machin-ist for retooling and the process starts over. Currently, Custom Molds has a published lead time of 9 weeks for delivery of custom-fabricated molds.

The manufacturing process for plastic parts is somewhat different from that for mold fabrication. An order for parts may be received in conjunction with an order for a mold to be fabricated. In instances where Custom Molds has previously fabricated the mold and maintains it in inventory, an order may be just for parts. If the mold is already available, the order is reviewed by a design engineer, who verifies the part and raw material specifications. If the design engineer has any questions concerning the specifications, the customer is contacted and any revisions to specifications are mutually worked out and agreed upon.

Upon acceptance of the part and raw material specifications, raw mate-rial orders are placed and production is scheduled for the order. Chemicals and compounds that support plastic-parts manufacturing are typically ordered and received within 1 week. Upon receipt, the compounds are first dry-mixed and blended to achieve the correct composition. Then the mixture is wet-mixed to the desired consistency (called slurry) for injection into molding machines. When ready, the slurry is transferred to the injection-molding area by an overhead pipeline and deposited in holding tanks adjacent to the injection machines. The entire mixing process takes only 1 day.

When the slurry is staged and ready, the proper molds are secured—from inventory or from the clean and polish operation if new molds were fabricated for the order—and the parts are manufactured. Although different parts require different temperature and pressure settings, the time to produce a part is relatively constant. Custom Molds has the capacity to produce 5,000 parts per day in the injection-molding department; historically, however, the lead time for handling orders in this department has averaged 1 week. Upon completion of molding, the parts are taken to the cut and trim operation, where they are disconnected and leftover flashing is removed. After being inspected, the parts may be taken to assembly or transferred to the packing and shipping area for shipment to the customer. If assembly of the final parts is not required, the parts can be on their way to the customer 2 days after being molded.

Sometimes, the final product requires some assembly. Typically, this entails attaching metal leads to plastic connectors. If assembly is necessary, an additional 3 days are needed before the order can be shipped. Custom Molds is currently quoting a 3-week lead time for parts not requiring fabricated molds.

▲ FIGURE 2.21Plant Layout

Testing and inspection

Dock Dock

Receivingraw materials

inventory

Dry mix

Wet mix

Assembly

Offices

Lunch room

Cut andtrim

Injection machines

Mold fabrication

Packing andshipping finishedgoods inventory

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118 PART 1 MANAGING PROCESSES

The Changing Environment

In early 2021, Tom and Mason Miller began to realize that the electronics industry they supplied, along with their own business, was changing. Electronics manufacturers had traditionally manufactured their own component parts to reduce costs and ensure a timely supply of parts. But this trend had changed. Manufacturers were developing strategic partnerships with parts suppliers to ensure the timely delivery of high-quality, cost-effective parts. This approach allowed funds to be diverted to other uses that could provide a larger return on investment.

The impact on Custom Molds could be seen in sales figures over the past 3 years. The sales mix was changing. Although the number of orders per year for mold fabrication remained virtually constant, orders for multiple molds were declining, as shown in the accompanying table.

NUMBER OF ORDERS

Order Size Molds 2018 Molds 2019 Molds 2020

1 80 74 72

2 60 70 75

3 40 51 55

4 5 6 5

5 3 5 4

6 4 8 5

7 2 0 1

8 10 6 4

9 11 8 5

10 15 10 5

Total orders 230 238 231

The reverse was true for plastic parts, for which the number of orders per year had declined, but for which the order sizes were becoming larger, as illustrated in the next table.

NUMBER OF ORDERS

Order Size Parts 2018 Parts 2019 Parts 2020

50 100 93 70

100 70 72 65

NUMBER OF ORDERS

Order Size Parts 2018 Parts 2019 Parts 2020

150 40 30 35

200 36 34 38

250 25 27 25

500 10 12 14

750 1 3 5

1,000 2 2 8

3,000 1 4 9

5,000 1 3 8

Total orders 286 280 277

During this same period, Custom Molds began having delivery problems. Customers were complaining that parts orders were taking 4 to 5 weeks instead of the stated 3 weeks and that the delays were disrupting production schedules. When asked about the situation, the master scheduler said that determining when a particular order could be promised for delivery was difficult. Bottlenecks were occurring during the production process, but where or when they would occur could not be predicted. The bottlenecks always seemed to be moving from one operation to another.

Tom Miller thought that he had excess labor capacity in the mold-fabrication area. So, to help push through those orders that were behind schedule, he assigned one of the master machinists the job of identifying and expediting those late orders. However, that tactic did not seem to help much. Complaints about late deliveries were still being received. To add to the problems, two orders had been returned recently because of the number of defective parts. The Millers knew that something had to be done. The question was, “What?”5

QUESTIONS1. What are the major issues facing Tom and Mason Miller?2. What are the competitive priorities for Custom Molds’s processes and

the changing nature of the industry?3. What alternatives might the Millers pursue? What key factors should they

consider as they evaluate these alternatives?

5Source: This case was prepared by Dr. Brooke Saladin, Wake Forest University, as a basis for classroom discussion. Copyright © Brooke Saladin. Reprinted by permission.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 119

“Two bean tacos, a chicken burrito grande, and a side order of Spanish rice, please.” Ivan Karetski called his table’s order into the kitchen as he prepared the beverage orders. Business was brisk. Karetski liked it that way. Lots of customers meant lots of tips and, as a struggling graduate student, the extra income was greatly appreciated. Lately, however, his tips had been declining.

José’s is a small, 58-seat restaurant that offers a reasonably broad range of Mexican food prepared and presented in a traditional Mexican style. It is located in New England in a mature business district on the edge of a large metropolitan area. The site is adjacent to a central artery and offers limited free off-street parking. The restaurant’s interior decoration promotes the Mexican theme: The walls appear to be made of adobe and are draped with serapes, the furniture is Spanish–Mexican style, and flamenco guitar and mariachi alternate as background music.

Patrons enter the restaurant through a small vestibule that opens directly into the dining area; there is no separate waiting area. Upon arrival, patrons are greeted by a host and either seated directly or apprised of the expected wait. Seating at José’s is usually immediate except for Friday and Saturday nights, when waits of as long as 45 minutes can be encountered. Because space inside for waiting is very limited, patrons must remain outside until their party is called. José’s does not take reservations.

After seating patrons, the host distributes menus and fills glasses with water. If standards are being met, the server assigned to the table greets the patrons within 1 minute of their being seated. The server introduces himself or herself, announces the daily specials, and takes the beverage orders. After delivering the beverages, the server takes the meal orders.

The menu consists of 23 main entrees assembled from eight basic stocks (chicken, beef, beans, rice, corn tortillas, flour tortillas, tomatoes, and lettuce) and a variety of other ingredients (fruits, vegetables, sauces, herbs, and spices). Before the dining hours begin, the cook prepares the basic stocks so that they can be quickly combined and finished off to com-plete the requested meals. The typical amount of time needed to complete a meal once it has been ordered is 12 minutes. A good portion of this time is for final cooking, so several meals may be in preparation at the same time. As can be imagined, one of the skills a good cook needs is to be able to schedule production of the various meals ordered at a table so that they are ready at approximately the same time. Once all the meals and any side dishes have been completed by the cook, the server checks to see that all meals are correct and pleasing to the eye, corrects any mistakes, and adds any finishing touches. When everything is in order, the server assembles them on a tray and delivers them to the table. From this point on, the server keeps an eye on the table to detect when any additional service or assistance is needed.

When the diners at the table appear to be substantially finished with their main meal, the server approaches, asks if he can clear away any dishes, and takes any requests for dessert or coffee. When the entire meal has been completed, the server presents the bill and shortly thereafter collects payment. José’s accepts cash or major credit cards but no checks.

Karetski believes that his relationship with the cook is important. Because the cook largely controls the quality of the food, Karetski wants to stay on good terms with him. He treats the cook with respect, tries to place the items on his order slip in the sequence of longest preparation time, and makes sure to write clearly so that the orders are easy to read. Although it is not his job, he helps out by fetching food stocks from the refrigerator or the storage area when the cook is busy and by doing some of the food preparation himself. The cook has been irritable lately, complaining of the poor quality of some of the ingredients that have been delivered. Last week, for example, he received lettuce that appeared wilted and chicken that was tough and more bone than meat. During peak times, it can take more than 20 minutes to get good meals delivered to the table.

Karetski had been shown the results of a customer survey that manage-ment conducted last Friday and Saturday during the evening mealtime. The accompanying table shows a summary of the responses.

Customer Survey Results

Were you seated promptly? Yes: 70 No: 13

Was your server satisfactory? Yes: 73 No: 10

Were you served in a reasonable time? Yes: 58 No: 25

Was your food enjoyable? Yes: 72 No: 11

Was your dining experience worth the cost? Yes: 67 No: 16

As Karetski carried the tray of drinks to the table, he wondered whether the recent falloff in tips was due to anything that he could control.6

QUESTIONS1. How should process outcomes and quality be defined at this restaurant?2. What are the restaurant’s costs of process failures?3. Use some of the tools for process analysis to assess the situation

at José’s.

6Source: This case was prepared by Larry Meile, Boston College, as a basis for classroom discussion. Reprinted by permission.

CASE José’s Authentic Mexican Restaurant

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120 PART 1 MANAGING PROCESSES

Stocking Location Activity and Roles

SurgicalStorage 2

MainStoreroom

CentralSterilization

SurgicalStorage 1

Administrators“Old” O�ce

Ortho ImplantRoom

Clean StorageRoom

Inv. Coordinator

Material Handler

OR Assistant

Cardio Coordinator

Assistant Nurse Mgr.

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VIDEO CASE Process Strategy and Analysis at Cleveland Clinic

Cleveland Clinic is one of the nation’s most respected research and academic hos-pitals, garnering top ratings annually in U.S. News and Word Reports rankings of healthcare providers for more than two decades. Headquartered in Cleveland, Ohio, the organization has more than 260 facilities throughout the United States and the world and is focused on providing superior patient safety and quality as evidenced in its clinicians’ commitment to providing patients with the best care anywhere.

One of its top facilities in Cleveland, Fairview Hospital, is particularly well known as a clinical “Center of Excellence,” enjoying national recognition for its birthing services, cancer center, emergency and Level II trauma, heart center, and surgery. Founded in 1892, Fairview Hospital is a faith-based community hospital with 488 licensed beds and is fully accredited by The Joint Commission, the nation’s premier healthcare accrediting agency. The hospital performs about 11,000 surgical procedures annually. General surgeries have the highest volumes at about 3,000 procedures annually, followed closely by Obstetrics/ Gynecological, Urological, and Orthopedics as the most frequently performed procedures.

Recently, the Inventory Management Transformation team within the Supply Chain Management corporate organization, performed work flow assessments at Fairview Hospital utilizing Six Sigma Process Improvement concepts. Skilled and licensed clinical staff, such as registered nurses in the Surgery Department, were required to spend a great deal of time walking around their units to inspect and inventory critical surgical supplies. Could the design of the process be the culprit? The staff annually required over 18,400 unique supplies provided by 327 unique vendors, with a value of close to $20 million, spread over numerous storage locations. An enterprise initiative to support clinicians performing at the height of their licensure recognized that time away from direct patient care for this skilled clinical staff could have an adverse impact on patient safety and wished to minimize this risk.

As noted in Figure 2.6, a Six Sigma Process Improvement project includes the following five steps:

1. Define: Outlines the scope and boundaries of the process to be examined2. Measure: Selects the metrics for collecting data about the area of interest

3. Analyze: Discovers gaps between actual and expected performance4. Improve: Generates ideas for improving the process, based on the gath-

ered metrics5. Control: Observes how well the chosen improvement process is working

after implementation

To better understand the workflows and the amount of clinical time dedi-cated to daily supply procurement, the supply chain team conducted a “time and motion” study of the Fairview Surgery Department to measure different activities. The goal was to understand the current state of responsibilities and time commitments required for all supply chain functions within Materials Management staff, central sterilization technicians, Fairview surgery nurses and Fairview surgery inventory personnel. For the skilled and licensed staff, the team narrowed the scope to observing the time it took to inspect and inventory the required supply items each day. This included mapping not only travel time, but also locations of supplies routinely needed for medical and surgical care.

The study started with questioning and brainstorming with staff to understand the work being done, who was doing it, the frequency of each task, locations, and relative value in the greater scheme of job duties. An example of this work was the daily inspection of hardware needed for trauma surgeries, such as broken bones. On a daily basis, an assistant nurse man-ager had to physically inspect a large steel cabinet in the “administrators old office” that contained the essential hardware items for surgical proce-dures. This cabinet was located on the second floor, as noted in the Stocking Location Activity and Roles “before” diagram shown below. Similar to a hard-ware store, the cabinet contains multiple drawers filled with various sizes of small screws, pins, rods, and plates of a wide variety of configurations. Performing the inspection is a standard inventory review task, but does not require someone with a nursing degree and years of surgical experience to determine which product needs replenishment. Yet this was exactly what was happening.

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PROCESS STRATEGY AND ANALYSIS CHAPTER 2 121

As the team focused on ways to improve the process, they knew they needed to remove non-value-added activities from the purview of clinicians so they could spend their time on patient care responsibilities.

As a result of the time and motion study analysis, Fairview Hospital’s Surgery Department established a new staff workflow model under the con-trol of the Materials Management Department, shown below, that required a realignment of the existing surgical inventory coordinator to report to the sup-ply chain organization and take over those duties that were formerly handled by the hospital staff shown in the chart above. Three additional supply chain staff were hired by the Materials Management Team to support the entire Sur-gery Department. The hiring of these staff relieved the clinicians of the tasks of checking surgical hardware inventory, and implementation of this solution across the Cleveland Clinic enterprise, to date, has returned over 22,000 clini-cal work hours back to the nurses for increased time spent with patients under their care. While it did not reduce costs as additional supply chain staff had to be hired, the project brought standard work, tools, and inventory management expertise to the Surgery Department, and allowed clinicians to perform within the scope of their training and expertise.

A caregiver at the Cleveland Clinic scans a product for replenishment, allowing clinicians more time to spend on their patients.

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Additionally, the study revealed that the daily time commitments within these workflows equaled four full-time equivalent employees of work, spread across a total workforce of approximately 190 staff. This was time that was being taken away from patient care and safety, both mission-critical impera-tives for the hospital staff.

To measure staff movements, the project team mapped the actual travel activity. As shown in the graphic below, the arrows indicate the paths skilled and licensed personnel had to travel to secure inventory items. Not only did these trips require travel between multiple floors of the hospital, but the staff also had to move between multiple locations on those floors. The team knew that any time spent in transit was time not available for patient care.

As analysis began, the team brainstormed on ideas for improving the process. Was there a way to reorganize the supply procurement process for improved efficiency and increased patient safety? How would such a reorga-nization impact clinical and licensed staff workflow? If the staff were no longer tasked with procuring the necessary items each day, who would fill this role instead?

The chart below shows which personnel were observed and how much time they spent on non-value-added duties as part of this study, in terms of full-time equivalent (FTE) employees. For instance, the assistant nurse manager was spending over half her shift on inventory (material)-related tasks.

Staff Department Current Materials Duties Future

FTEs FTEs

Assistant Nurse Manager

Operational and administrative support. Training staff, assigning tasks, scheduling shifts, assessing performance.

Surgical Service 0.55

Cardiothoracic Coordinator

Provides professional nursing care and support the Cardiovascular Service.

Surgical Services 0.45

Lead Surgical Technician X2

Procedural set-up and support, Equipment/Supply Management, facilitation as needed.

Surgical Services 1.30

CS/SPD Supervisor

Surgical Instrumentation and Case Cart supply management.

Central Sterilization 0.50

Materials Handler

Inventory Management ordering and replenishment.

Materials Management 0.30

Inventory Coordinator

Procedural support, critical Supply and Implant Management, facilitation.

Surgical Service 0.85 4.00

Total 3.95 4.00

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122 PART 1 MANAGING PROCESSES

Fairview Hospital also incorporated “periodic automatic adjustment” of inventory levels to determine the quantity of supplies that should be on hand at all times for the Surgery Department. This reorganization gave the sup-ply chain organization the opportunity to optimize stocking levels, saving the organization over $2 million in 2019 alone.

As part of the last step of the Six Sigma process, Control, the Supply Chain organization leveraged the Inventory Management Transformation Center of Excellence. This group is charged with developing and managing approaches to exercise control over inventory movement, expiration dates, and consolidating supply chain roles and responsibilities to bolster the organization’s “Patient First” goals. For high-dollar inventory items, this team has added RFID tags to track serial numbers and expiration dates

and generate automatic reordering of those items as they are used in procedures.

QUESTIONS1. In addition to the time and motion study the Cleveland Clinic followed,

what other work measurement techniques might have been used? Why?2. Which data analysis tools and metrics might have been used to quantify

what the project team observed in the daily travel workflow?3. After reviewing the various process strategy and analysis techniques

in this chapter, what else could Cleveland Clinic do to make the Six Sigma process improvement project even more effective?

Future State Routes: Stocking Location Activity

SurgicalStorage 2

2nd

Floo

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Receivingand

Main Storeroom

CentralSterilization

SurgicalStorage 1

Administrator’sOld O�ce

Ortho ImplantRoom

Clean StorageRoom

1st F

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Inv. Coordinators (1,2,3 & 4)

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123

LEARNING OBJECTIVES After reading this chapter, you should be able to:

QUALITY AND PERFORMANCE 3

Lego

3.1 Define the four major costs of quality and their relationship to the role of ethics in determining the overall costs of delivering products and services.

3.2 Explain the basic principles of total quality management (TQM) and Six Sigma.

3.3 Understand how acceptance sampling and process performance approaches interface in a supply chain.

3.4 Describe how to construct process control charts and use them to determine whether a process is out of statistical control.

3.5 Explain how to determine whether a process is capable of producing a service or product to specifications.

3.6 Describe International Quality Documentation Standards and the Baldrige Performance Excellence Program.

3.7 Understand the systems approach to total quality management.

Lego family within the park Legoland Windsor UK.

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124 PART 1 MANAGING PROCESSES

Who has not played with Lego toys? Countless number of children and adults over the past half century have used the Lego bricks to build cars, airplanes, action figures, tall buildings, and intricate art sculptures,

to name just a few. These interlocking bricks, called “automatic binding bricks,” stand the test of time and function flawlessly over decades to retain their shape, smooth finish, and an ability to bear high stress and still be linked with and disassembled from other bricks. How do they do it? It is achieved through their relentless focus on never taking shortcuts on quality, which is reflected in the Lego group’s motto of “only the best is good enough.”

Lego in Danish means “play well.” Starting out as a wooden toy manufacturing company in Denmark in 1936, they migrated over 50% of their production to plastic toys by 1951. The modern brick design with the locking ability that allows the bricks to become a universal system for creative play was patented in 1958. Other innovations, such as Duplo for younger children, mini-figures, and Lego theme kits, followed over the course of years to make Lego one of the most valued brands—one that is highly visible, with eight Lego theme parks all over the globe, more than 125 retail stores, video and board games, books and magazines, children’s clothing, movies, and Lego-based television shows.

Manufacturing plants located in Czech Republic, Denmark, Hungary, Mexico, and China inject molten plastic into injection molding machines to produce up to 36 billion bricks a year to exacting quality standards. The molds designed by Lego engineers have a tolerance of 18 micrometers to ensure that bricks can stay connected. Inspectors check the output of molds to eliminate significant variation in color and thickness. Machines perform additional drop, torque, tension, compression, bite, impact, and measurement tests to ensure the safety and durability of the product. Only 18 bricks out of a million fail to meet quality standards, which are uniformly enforced irrespective of the global production location through knowledge sharing and use of standardized equipment at each manufacturing plant. During the automated packaging process, a precise number of bricks are dropped into polypropylene bags, which are then weighed to make sure that each bag has the right contents. At the end of the process, these bags are placed into boxes, and packaging operators check that the machines have not made any mistakes and add other necessary pieces before sealing a box. The process uses up to half a million environmentally friendly “green” boxes per year, which are subsequently shipped all over the world.

This single-minded focus on quality and attention to the tiniest details of designing, raw material sourcing, and manufacturing the product has created a company with an iconic brand that continues to maintain its grip on the imagination and wallets of its many happy and satisfied customers.1

1Sources: Tracey V. Wilson, “How Lego Bricks Work” (June 28, 2006), HowStuffWorks.com, https:// entertainment.howstuffworks.com/lego.htm (June 18, 2020); Michael Venables, “How Lego Makes Safe, Quality, Diverse and Irresistible Toys Everyone Wants: Part Two” (April 20, 2013), Forbes, https://www.forbes.com/sites/michaelvenables/2013/04/20/how-lego-makes-the-safe-quality-diverse-and-irresistible-toys-we-all-want-part-two/#49e519106118 (June 18, 2020); https://en.wikipedia.org/wiki/Lego (June 18, 2020).

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QUALITY AND PERFORMANCE CHAPTER 3 125

The challenge for businesses today is to satisfy their customers through the exceptional per-formance of their processes and products. Lego is one example of a company that met the challenge by designing and managing its manufacturing processes to provide customers with high-quality products and total satisfaction. Evaluating process performance is important if this is to happen. It is also necessary for managing supply chains.

Quality and performance should be everybody’s concern. Therefore, in this chapter, we first address the costs of quality and then focus on total quality management and Six Sigma, two philosophies and supporting tools that many companies embrace to evaluate and improve quality and performance. We subsequently describe how acceptance sampling and process performance approaches interface in a sup-ply chain, and the role played by process variation in determining whether a process is in statistical control or not. We finally conclude with techniques that can be used to measure and improve quality such that the product or service meets the custom-ers’ needs and specifications.

Costs of QualityWhen a process fails to satisfy a customer, the failure is considered a defect. For example, accord-ing to the California Academy of Family Physicians, defects for the processes in a doctor’s practice are defined as “anything that happened in my office that should not have happened, and that I absolutely do not want to happen again.” Obviously, this definition covers process failures that the patient sees, such as poor communication and errors in prescription dosages. It also includes failures the patient does not see, such as incorrect charting.

Closely tied to the notion of defects is the question of determining how much quality is enough. There is a greater societal effect that also must be factored into decision making involving the production of services or products that often requires balancing the costs of quality with the overall benefits to society. For example, in the health care industry, aiming for zero complications in cardiac surgery might sound good; however, if it comes at the cost of turning down high-risk patients, is society being served in the best way? Or how much time, energy, and money should go into delivering vaccines or preventing complications? These are questions that often do not have clear answers.

Many companies spend significant time, effort, and expense on systems, training, and orga-nizational changes to improve the quality and performance of their processes. They believe that it is important to be able to gauge current levels of performance so that any process gaps can be determined. Gaps reflect potential dissatisfied customers and additional costs for the firm. Most experts estimate that the costs of quality range from 20 to 30 percent of gross sales. These costs can be broken down into four major categories: (1) prevention, (2) appraisal, (3) internal failure, and (4) external failure. The American Society for Quality, also commonly known as ASQ (http://asq.org/learn-about-quality/cost-of-quality/overview/overview.html), provides several examples of these four types of costs. In addition, there is a fifth category of costs associated with unethical behavior in making quality decisions, and which can be significantly higher than all the other four costs combined.

Prevention CostsPrevention costs are associated with preventing defects before they happen. They include the costs of redesigning the process to remove the causes of poor performance, redesigning the service or product to make it simpler to produce, training employees in the methods of continuous improvement, and working with suppliers to increase the quality of purchased items or contracted services. To prevent problems from happening, firms must invest additional time, effort, and money. Some examples of where these investments are needed include (1) product or service requirements, which involve establishment of specifications for incoming materials, processes, finished products, and services; (2) quality planning, which involves creation of plans for quality, reliability, operations, production, and inspection; (3) quality assurance, which involves creation and maintenance of a well-defined quality system; and (4) training that is focused on the develop-ment, preparation, and maintenance of quality-related programs.

defect

Any instance when a process fails to satisfy its customer.

prevention costs

Costs associated with preventing defects before they happen.

Using Operations to Create Value

Part 1

Managing Processes

Designing andoperating processes inthe firm

Managing Supply Chains

Forecasting demands anddeveloping inventory plansand operating schedules

Designing an integrated andsustainable supply chain of

connected processes between firms

Managing Customer Demand

Managing Processes

Project Management

Process Strategy and AnalysisQuality and Performance

Lean SystemsCapacity Planning

Constraint Management

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126 PART 1 MANAGING PROCESSES

Appraisal CostsAppraisal costs are incurred when the firm assesses the level of performance of its processes. As the costs of prevention increase and performance improves, appraisal costs decrease because fewer resources are needed for quality inspections and the subsequent search for causes of any problems that are detected. Some examples of appraisal costs include (1) verification, which involves checking of incoming materials, process setups, and products against agreed upon specifications; (2) quality audits aimed at confirming that the quality system is functioning cor-rectly; and (3)  supplier rating, which is the assessment and approval of suppliers of products and services.

Internal Failure CostsInternal failure costs result from defects that are discovered during the production of a service or product. Defects fall into three main categories: (1) rework or rectification, which is incurred if some aspect of a service must be performed again or if a defective item must be rerouted to some previous operation(s) to correct the defect; (2) scrap, which is incurred if a defective item is unfit for further processing and cannot be repaired, used, or sold; and (3) waste, which involves performance of unnecessary work or holding stock as a result of errors or poor communication and organization.

External Failure CostsExternal failure costs arise when a defect is discovered after the customer receives the service or product. Dissatisfied customers talk about bad service or products to their friends, who in turn tell others. If the problem is bad enough, consumer protection groups may even alert the media. The potential impact on future profits is difficult to assess, but without doubt external failure costs erode market share and profits. Encountering defects and correcting them after the product is in the customer’s hands is costly. Examples of external failure costs include costs that are associated with (1) repairs and servicing of both returned products and those actually being used by customers; (2) complaints, which involve all costs and work associated with handling and servicing customers’ complaints; (3) returns, which involves transportation of rejected or recalled products; and (4) warranty service and litigation costs, where a warranty is a written guarantee that the producer will replace or repair defective parts or perform the service to the customer’s satisfaction. Usually, a warranty is given for some specified period. For example, television repairs may be guaranteed for 90 days and new automobiles for 5 years or 50,000 miles, whichever comes first. Warranty costs must be considered in the design of new services or products.

Ethical Failure CostsThe costs of quality go far beyond the out-of-pocket costs associated with training, appraisal, scrap, rework, warranties, litigation, or the lost sales from dissatisfied customers. Ethical failure costs are the societal and monetary costs associated with deceptively passing defective services or products to internal or external customers such that it jeopardizes the well-being of stockholders, customers, employees, partners, and creditors.

As a practical matter, ethical costs arise from internal or external failures. The main difference is that somebody tries to “cover them up” and knowingly passes the defects along to the customer, knowing that they can do harm. What makes the nature of ethical failure costs different from internal failure or external failure costs already mentioned is the punitive costs of litigation once the ethical lapses are discovered, the extraordinary magnitude of the fines and penalties, the loss of goodwill that can literally damage the firm for a long time, and the hidden costs of employee morale and attitude. Ethical costs are tied to deception and shifting the blame to other partners in the supply chain, and go beyond the internal or external failure costs associated with fixing the quality problems in an organization. Mattel—with brands like Fisher Price, Barbie Dolls, and Hot Wheels, among others—had to issue multiple product recalls in 2007 due to the presence of cheaper but toxic lead paint in its toys. Problems also existed with loosely attached small magnets in its toys, which if swallowed could cause injuries to children. Despite exerting downward pres-sures on costs, Mattel initially denied knowledge and responsibility for the use of lead paint, and instead placed the blame on the suppliers to its manufacturing plants in China. But later on, after stockholder lawsuits claiming the withholding of timely information and misleading financial statements, and also government and media pressure, Mattel instituted stringent inspection and quality programs to prevent the recurrence of such incidents. As a result, Mattel has significantly repaired its corporate image over the past decade.

appraisal costs

Costs incurred when the firm assesses the performance level of its processes.

internal failure costs

Costs resulting from defects that are discovered during the produc-tion of a service or product.

external failure costs

Costs that arise when a defect is discovered after the customer receives the service or product.

warranty

A written guarantee that the producer will replace or repair defective parts or perform the service to the customer’s satisfaction.

ethical failure costs

Societal and monetary costs associated with deceptively passing defective services or products to internal or external customers such that it jeopar-dizes the well-being of stock-holders, customers, employees, partners, and creditors.

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Deceptive business practices are a source of major concern for service or product quality. Deceptive business practice involves three elements: (1) The conduct of the provider is intentional and motivated by a desire to exploit the customer; (2) the provider conceals the truth based upon what is actually known to the provider; and (3) the transaction is intended to generate a disproportionate economic benefit to the provider at the expense of the customer. This behavior is unethical, diminishes the quality of the customers’ experience, and may impose a substantial cost on society. Quality is all about increasing the satisfaction of customers. When a firm engages in unethical behavior and the customer finds out about it, the customer is unlikely to favorably assess the quality of his or her experience with that firm or to return as a customer. Under these conditions, employees of firms that attempt to profit by deceiving customers are less likely to be motivated to put forth their best effort to create true value for customers; they erode a firm’s ability to compete now and in the future. Therefore, ethical behavior falls on the shoulders of all employees of an organization. Many firms like Patagonia, Starbucks, and the retailer H&M go the extra mile to ensure that they source their materials from suppliers that follow ethical business practices.

Overall, management must put in place the appropriate processes and approaches to manage the quality costs of prevention, assessment, internal fail-ure, external failure, and ethical failure. Developing the cultural environment for ethical behavior is not cost free. Employees must be educated in how ethics interfaces with their jobs. The firm may organize an ethics task force or an eth-ics public relations group to provide an interface between the firm and society. Documentation may be required.

Total Quality Management and Six SigmaWe now turn to a discussion of total quality management and Six Sigma, two philosophies companies use to evaluate and improve quality and process performance along technical, service, and ethical dimensions.

Total Quality ManagementTotal quality management (TQM) is a philosophy that stresses three principles for achieving high levels of process performance and quality. These principles are related to (1) customer satisfaction, (2) employee involvement, and (3) continuous improvement in performance. As Figure 3.1 indicates, TQM also involves a number of other important elements. We have covered tools and process analysis techniques useful for process problem solving, redesign, and improvement in Chapter 2 “Process Strategy and Analysis.” Service or product design and purchas-ing are covered later in this text. Here, we just focus on the three main principles of TQM, which must always be guided and supported by man-agement commitment and leadership in creating a quality-driven organization.

Customer Satisfaction Customers, internal or external, are satisfied when their expectations regarding a service or product have been met or exceeded. Often, customers use the general term quality to describe their level of satisfaction with a service or product. Quality has mul-tiple dimensions in the mind of the customer, which cut across the nine competitive priorities we introduced in Chapter 1, “Using Operations to Create Value.” One or more of the following five definitions apply at any one time.

▪▪ Conformance to Specifications. Although customers evaluate the service or product they receive, it is the processes that produced the service or product that are really being judged. In this case, a process failure would be the process’s inability to meet certain advertised or implied performance standards. Conformance to specifications may relate to consistent qual-ity, on-time delivery, or delivery speed.

▪▪ Value. Another way customers define quality is through value, or how well the service or product serves its intended purpose at a price customers are willing to pay. The service or product development process plays a role here, as do the firm’s competitive priorities relat-ing to top-quality versus low-cost operations. The two factors must be balanced to produce value for the customer. How much value a service or product has in the mind of the customer depends on the customer’s expectations before purchasing it.

total quality management (TQM)

A philosophy that stresses three principles for achieving high lev-els of process performance and quality: (1) customer satisfaction, (2) employee involvement, and (3) continuous improvement in performance.

quality

A term used by customers to describe their general satisfaction with a service or product.

▼ FIGURE 3.1TQM Wheel

Customer satisfaction

Empl

oyee

invo

lvem

ent

Continuous improvem

ent

Prob

lem-s

olvi

ng to

ols

Benchmarking

Purchasing

Process design

Serv

ice

/produ

ct design

Polly Pocket play sets and Batman action figures are seen in a basket at Kinder Haus Toy store in Arlington, Virginia. Mattel recalled 9 million Chinese made toys, including Polly Pocket play sets, Batman action figures, Fisher-Price toys and some die cast cars because of the presence of lead paint or their use of tiny magnets that could cause a choking hazard.

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128 PART 1 MANAGING PROCESSES

▪▪ Fitness for Use. When assessing how well a service or product performs its intended purpose, the customer may consider the convenience of a service, the mechanical features of a product, or other aspects such as appearance, style, durability, reliability, craftsmanship, and serviceability. For example, you may define the quality of the entertainment center you purchased on the basis of how easy it was to assemble and its appearance and styling.

▪▪ Support. Often the service or product support provided by the company is as important to customers as the quality of the service or product itself. Customers get upset with a company if its financial statements are incorrect, responses to its warranty claims are delayed, its advertising is misleading, or its employees are not helpful when problems are incurred. Good support once the sale has been made can reduce the consequences of quality failures.

▪▪ Psychological Impressions. People often evaluate the quality of a service or product on the basis of psychological impressions: atmosphere, image, or aesthetics. In the provision of ser-vices where the customer is in close contact with the provider, the appearance and actions of the provider are especially important. Nicely dressed, courteous, friendly, and sympathetic employees can affect the customer’s perception of service quality.

Attaining quality in all areas of a business is a difficult task. To make things even more dif-ficult, consumers change their perceptions of quality. In general, a business’s success depends on the accuracy of its perceptions of consumer expectations and its ability to bridge the gap between those expectations and operating capabilities. Good quality pays off in higher profits. High-quality services and products can be priced higher and yield a greater return. Poor quality erodes the firm’s ability to compete in the marketplace and increases the costs of producing its service or product.

Employee Involvement One of the important elements of TQM is employee involvement, as shown in Figure 3.1. A program in employee involvement includes changing organizational cul-ture and encouraging teamwork.

▪▪ Cultural Change. One of the main challenges in developing the proper culture for TQM is to define customer for each employee. In general, customers are internal or external. External customers are the people or firms who buy the service or product. Some employees, espe-cially those having little contact with external customers, may have difficulty seeing how their jobs contribute to the whole effort.

It is helpful to point out to employees that each employee also has one or more internal customers—employees in the firm who rely on the output of other employees. All employees must do a good job of serving their internal customers if external customers ultimately are to be satisfied. They will be satisfied only if each internal customer demands value be added that the external customer will recognize and pay for. The notion of internal customers applies to all parts of a firm and enhances cross-functional coordination. For example, accounting must prepare accurate and timely reports for management, and purchasing must provide high-quality materials on time for operations.

In TQM, everyone in the organization must share the view that quality control is an end in itself. Errors or defects should be caught and corrected at the source, not passed along to an internal or external customer. For example, a consulting team should make sure its billable hours are correct before submitting them to the accounting department. This philosophy is called quality at the source. In addition, firms should avoid trying to “inspect quality into the product” by using inspectors to weed out unsatisfactory services or defective products after all operations have been performed. By contrast, in some manu-facturing firms, workers have the authority to stop a production line if they spot quality problems.

▪▪ Teams. Employee involvement is a key tactic for improving processes and quality. One way to achieve employee involvement is by the use of teams, which are small groups of people who have a common purpose, set their own performance goals and approaches, and hold themselves accountable for success. The three approaches to teamwork most often used are (1) problem-solving teams, (2) special-purpose teams, and (3) self-managed teams. All three use some amount of employee empowerment, which moves responsibility for decisions further down the organizational chart—to the level of the employee actually doing the job.

The value of employee involvement and empowerment in creating high-quality products can be seen at the Santa Cruz Guitar Company in Managerial Practice 3.1.

quality at the source

A philosophy whereby defects are caught and corrected where they were created.

teams

Small groups of people who have a common purpose, set their own performance goals and approaches, and hold themselves accountable for success.

employee empowerment

An approach to teamwork that moves responsibility for deci-sions further down the organiza-tional chart—to the level of the employee actually doing the job.

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Continuous Improvement Based on a Japanese concept called kaizen, continuous improvement is the philosophy of continually seeking ways to improve processes. Continuous improvement involves identifying benchmarks of excellent practice and instilling a sense of employee ownership in the process. The focus of continuous improvement projects is to reduce waste, such as reducing the length of time required to process requests for loans at a bank, the amount of scrap generated at a milling machine, or the number of employee injuries at a construction site. The basis of the continu-ous improvement philosophy is the belief that virtually any aspect of a process can be improved and that the people most closely associated with a process are in the best position to identify the changes that should be made. The idea is not to wait until a massive problem occurs before acting.

Employees should be given problem-solving tools, such as the statistical process control (SPC) methods we discuss later in this chapter, and a sense of ownership of the process to be improved.

continuous improvement

The philosophy of continually seeking ways to improve processes based on a Japanese concept called kaizen.

MANAGERIAL PRACTICE

Improving Quality Through Employee Involvement at Santa Cruz Guitar Company

Founded in 1976, the Santa Cruz Guitar Company pro-duces acoustic guitars that are well recognized by famous artists such as Eric Clapton, Tony Rice, Warren Haynes, and Elvis Costello. The company is a small-scale manufacturer that produces about 500 to 700 guitars per year and emphasizes small production numbers in order to focus on instrument quality. In the competitive marketplace of musical instruments, the sole order winning competitive priority is top quality, which is represented by the sound of the instrument. Ironically, the company does not have a formal process of quality assurance through a dedicated department. Instead, the quality of the guitars is entrusted to employees at all levels. Every instrument is built as a team, and the company practices total quality management along with following the management principles of W. Edwards Deming.

The process of making a guitar is divided into seven steps, with each step requiring various degrees of inspection at all levels. The guitar-making process starts with selecting the wood. Each wood type is obtained from a few trusted suppliers located around the world. The tops are from Germany, the back and side materials are from India or Brazil, and so forth. The shop floor where the woods are treated is kept at a constant 47 percent humidity, which is optimum for maintaining the equilibrium of moisture conditions. For cutting the treated wood, the company invested in an expensive machine that relieves the craftsmen from performing repetitive tasks. While many artisan and luxury brand products claim to be 100 percent handcrafted, Santa Cruz Guitar Company made this choice so that the craftsmen can concentrate on more delicate processes that are best suited for human hands. It also keeps them highly motivated, and helps to reduce repetitive stress injuries. The craftsmen then take the fine-cut wood and bend the sides to the desired shapes using their hands. This process is best performed by human hands because sides that are shaped by machines have a tendency to spring back when they are being forced into molds. Next, the guitar top and back are cut to shape, and braced. The thicknesses of the top and the braces have the most influence on the final sound of the guitar. The craftsmen will tap the top of each finished piece to hear the tone and adjust the thickness of the wooden support braces attached under the top until the tone is perfect. The craftsmen document what they did while building the top, and if a guitar produces an exceptional sound, the craftsman making that guitar will be asked to check his or her notes, and the knowledge thus gained will be shared with others. The neck of the guitar requires consistent quality conforming to the tight cus-tomer specifications. Therefore, this process is carried out using machines. The guitar pieces are finished with 12 protective layers of lacquer and then assembled. A technician will play the guitar for the first time, and adjust the

neck or string height and make sure that the instrument provides optimized playability to the customer.

The company empowers workers to take quality initiatives at every step of the process, and this is possible due to their employee-supportive culture. Workers are encouraged to take external courses or practice their skills by allowing them to build two instruments a year for personal use. Craftsmen continuously explore new techniques in building guitars, and make quality improvement suggestions. The company also encourages the craftsmen to go out and open their own guitar brand business. While this may increase competition in the market and pose potential threats, the firm puts trust in furthering the welfare of its employees to enhance process quality. Promoting pride in workmanship, open communication with supervisors, and employee empowerment altogether make Santa Cruz Guitar Company an inspired and productive manufacturer of high-quality musical instruments.2

2Sources: L. T. Foo, “Good Vibrations: Ingrained Quality Practices Mirror Deming’s 14 Points,” Quality Progress (2008), http://asq.org/quality-progress/2008/02/quality-managementment/good-vibrations.html; Santa Cruz Guitar Company (February 18, 2017), http://www.santacruzguitar.com/our-story/ (June 16, 2020); https://en.wikipedia.org/wiki/Santa_Cruz_Guitar_Company.

3.1

A worker constructs an instrument at the Santa Cruz Guitar Company in Santa Cruz, California.

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130 PART 1 MANAGING PROCESSES

A sense of operator ownership emerges when employees feel a responsibility for the processes and methods they use and take pride in the quality of the service or product they produce. It comes from participation on work teams and in problem-solving activities, which instill in employees a feeling that they have some control over their workplace and tasks.

Most firms actively engaged in continuous improvement train their work teams to use the plan-do-check-act cycle for problem solving. Another name for this approach is the Deming wheel, named after the renowned statistician W. Edwards Deming who taught quality improvement techniques to the Japanese after World War II. Figure 3.2 shows this cycle, which lies at the heart of the continuous improvement philosophy. The cycle comprises the following steps:

1. Plan. The team selects a process (an activity, method, machine, or policy) that needs improvement. The team then documents the selected process, usually by analyzing related data; sets qualitative goals for improvement; and discusses various ways to achieve the goals. After assessing the benefits and costs of the alternatives, the team develops a plan with quantifiable measures for improvement.

2. Do. The team implements the plan and monitors progress. Data are collected continuously to measure the improvements in the process. Any changes in the process are documented, and further revisions are made as needed.

3. Check. The team analyzes the data collected during the do step to find out how closely the results correspond to the goals set in the plan step. If major shortcomings exist, the team reevaluates the plan or stops the project.

4. Act. If the results are successful, the team documents the revised process so that it becomes the standard procedure for all who may use it. The team may then instruct other employees in the use of the revised process.

Problem-solving projects often focus on those aspects of processes that do not add value to the service or product. Value is added in processes such as machining a part or serving a customer through a Web page. No value is added in activities such as inspecting parts for defects or routing requests for loan approvals to several different departments. The idea of continuous improvement is to reduce or eliminate activities that do not add value and, thus, are wasteful.

Six SigmaThe Six Sigma philosophy allows managers to think analytically about processes and their under-lying quality. It relies heavily on the principles of TQM, and is a comprehensive and flexible system for achieving, sustaining, and maximizing business success by minimizing defects and variability in processes. Six Sigma has a different focus than TQM does: It is driven by a close understanding of customer needs; the disciplined use of facts, data, and statistical analysis; and diligent attention to managing, improving, and reinventing business processes. Figure 3.3 shows how Six Sigma focuses on reducing variation in processes as well as centering processes on their target measures of performance. Either flaw—too much variation or an off-target process—degrades performance of the process. For example, a mortgage loan department of a bank might advertise loan approval decisions in 2 days. If the actual performance ranges from 1 to 5 days,

with an average of 2 days, those customers who had to wait longer than 2 days would be upset. Process variabil-ity causes customer dissatisfaction. Similarly, if actual performance consistently produced loan decisions in 3 days, all customers would be dissatisfied. In this case, the process is consistent, but off the target. Six Sigma is a rigorous approach to align processes with their target performance measures with low variability.

The name Six Sigma, originally developed by Motorola for its manufacturing operations, relates to the goal of achieving low rates of defective output by developing processes whose mean output for a performance measure is { 6 standard deviations (sigma) from the limits of the design specifications for the service or product. We will discuss variability and its implications on the capability of a process to perform at acceptable levels when we present the tools of statistical process control.

Although Six Sigma was rooted in an effort to improve manufacturing processes, credit General Electric with popularizing the application of the approach to non-manufacturing processes such as sales, human resources,

plan-do-check-act cycle

A cycle, also called the Deming wheel, used by firms actively engaged in continuous improve-ment to train their work teams in problem solving.

Six Sigma

A comprehensive and flexible system for achieving, sustaining, and maximizing business success by minimizing defects and vari-ability in processes.

▼ FIGURE 3.2Plan-Do-Check-Act-Cycle

Act

Plan

Check

Do

▼ FIGURE 3.3Six Sigma Approach Focuses on Reducing Spread and Centering the Process

Centerprocess

Reducespread

×××××××××

×

×

× ×××

×

× ×

× ××

×××

×××

Processon target withlow variability

Process average OK;too much variation

Process variability OK;process o� target

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QUALITY AND PERFORMANCE CHAPTER 3 131

customer service, and financial services. The concept of eliminating defects is the same, although the definition of “defect” depends on the process involved. For exam-ple, a human resource department’s failure to meet a hir-ing target counts as a defect. Using the DMAIC approach within the Six Sigma Improvement model highlighted in Chapter 2, “Process Strategy and Analysis,” Six Sigma process improvement specialists with black belts have been able to mentor employees and successfully apply Six Sigma to improve a host of service processes, includ-ing financial services, human resource processes, market-ing processes, and health care administrative processes.

Acceptance SamplingBefore any internal process can be evaluated for perfor-mance, the inputs to that process must be of good quality. Acceptance sampling, which is the application of statisti-cal techniques to determine if a quantity of material from a supplier should be accepted or rejected based on the inspection or test of one or more samples, limits the buy-er’s risk of rejecting good-quality materials (and unneces-sarily delaying the production of goods or services) or accepting bad-quality materials (and incurring downtime due to defective materials or passing bad products to customers). Relative to the specifica-tions for the material the buyer is purchasing, the buyer specifies an acceptable quality level (AQL), which is a statement of the proportion of defective items (outside of specifications) that the buyer will accept in a shipment. These days, that proportion is getting very small, often measured in parts per ten-thousand. The idea of acceptance sampling is to take a sample, rather than testing the entire quantity of material, because that is often less expensive. Therein lies the risk—the sample may not be representative of the entire lot of goods from the supplier. The basic procedure is straightforward.

1. A random sample is taken from a large quantity of items and tested or measured relative to the specifications or quality measures of interest.

2. If the sample passes the test (low number of defects), the entire quantity of items is accepted.

3. If the sample fails the test, either (a) the entire quantity of items is subjected to 100 percent inspection and all defective items repaired or replaced, or (b) the entire quantity is returned to the supplier.

In a supply chain, any company can be both a producer of goods purchased by another com-pany and a consumer of goods or raw materials supplied by another company. Figure 3.4 shows a flowchart of how acceptance sampling and internal process performance (TQM or Six Sigma) interface in a supply chain. From the perspective of the supply chain, the buyer’s specifications for various dimensions of quality become the targets the supplier shoots for in a supply contract. The supplier’s internal processes must be up to the task; TQM or Six Sigma can help achieve

acceptance sampling

The application of statistical techniques to determine whether a quantity of material should be accepted or rejected based on the inspection or test of a sample.

acceptable quality level (AQL)

The quality level desired by the consumer.

▲ FIGURE 3.4Interface of Acceptance Sampling and Process Performance Approaches in a Supply Chain

Fan Motor Order

Fan Blade Order

Blade sampling

Acceptblades?

Manufacturesfurnaces

Buyer

Manufacturesfurnace fan motors

TARGET: Buyer’s specs

Firm A

Manufacturesfan blades

TARGET: Firm A’s specs

Supplier

fan motors

fan blades

Firm A uses TQM or SixSigma to achieve internal

process performance

Supplier uses TQM or SixSigma to achieve internal

process performance

Motor sampling

Acceptmotors?

NoYes

NoYes

Harley Davidson Motorcycle Assembly Line in York, Pennsylvania. Harley Davidson uses Statistical Process Control to enhance the quality of its motorcycles in different areas of the plant where the motorcycles are assembled.

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132 PART 1 MANAGING PROCESSES

the desired performance. The buyer’s sampling plan will provide a high probability of accepting AQL (or better). Online Supplement G, “Acceptance Sampling Plans,” shows how to design an acceptance sampling plan that meets the level of risk desired.

Measuring quality of a process and monitoring its progress over time can be a complex task that involves a multitude of steps and decisions, as the following Managerial Challenge demonstrates.

M A N A G E R I A L CHALLENGE

Star Industries, Inc., manufactures highly engineered products for both the electric transmission and wireless communication industries. Rebecca Davis, corporate controller, oversees the accounting and budgeting functions for the company. Last year she directed a major overhaul of a number of internal processes, including payroll accounting and customer billing. The overhaul included new equipment and technologies as well as new manual procedures for the staff. Now that the new processes had about a year to iron out the glitches, she needed to know how many, if any, improvements were made. The motivation for the process improvement project was to reduce costly inefficiencies in payroll and to reduce the lead time to bill customers. The latter improvement was aimed at improving revenue flows and cash position.

Rebecca realized that she needed the help of someone who could develop budgets and had the skills to track budget expenses, analyze data, and audit ongoing processes. She hired Jamal Johnson, who recently graduated with a degree in accounting, to assume the role of budget analyst. Jamal began by studying the payroll accounting process. It consisted of a number of repetitive procedures that included the proper authorization of overtime, approval of time records, and checks on the calculation of gross pay and payroll deductions. Auditors could periodically sample individual employee pay records to verify the documentation of the required authorizations and approvals. A missing authorization or approval would constitute a process defect. Jamal wondered how big the sample should be? How often should it be taken? Over time, how would he know if the process is getting better or getting worse?

The customer billing process has revenue implications and therefore has high status in the account-ing department. Jamal realized that the important statistic in this process is the time between the point that goods are provided and the point that the customers are billed; reducing that time is a key step in speeding up collections. Auditors could randomly draw samples of invoices and measure the amount of time between delivery date and billing date. In this case, what would be considered a defect? How big should the sample be, and how often should a sample be taken? Finally, over time, how can he be sure that the process is running as planned? The remainder of this chapter will provide Jamal guidance in answering his questions.

Accounting

Statistical Process ControlRegardless of whether a firm is producing a service or a product, it is important to ensure that the firm’s processes are providing the quality that customers want. A key element of TQM or Six Sigma is building the capability to monitor the performance of processes so that corrective action can be initiated in a timely fashion. Evaluating the performance of processes requires a variety of data-gathering approaches. We already discussed checklists, histograms and bar charts, Pareto charts, scatter diagrams, cause-and-effect diagrams, and graphs (see Chapter 2, “Process Strategy and Analysis”). All of these tools can be used with TQM or Six Sigma. Here, we focus on the powerful statistical tools that can be used to monitor and manage repetitive processes.

Statistical process control (SPC) is the application of statistical techniques to determine whether a process is delivering what customers want. In SPC, tools called “control charts” are used primarily to detect defective services or products or to indicate that the process has changed and that services or products will deviate from their design specifications, unless something is done to correct the situation. SPC can also be used to inform management of improved process changes. Examples of process changes that can be detected by SPC include the following:

▪▪ A decrease in the average number of complaints per day at a hotel▪▪ A sudden increase in the proportion of defective gear boxes▪▪ An increase in the time to process a mortgage application▪▪ A decline in the number of scrapped units at a milling machine▪▪ An increase in the number of claimants receiving late payment from an insurance company

Let us consider the last situation. Suppose that the manager of the accounts payable depart-ment of an insurance company notices that the proportion of claimants receiving late payments

statistical process control (SPC)

The application of statistical techniques to determine whether a process is delivering what the customer wants.

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rose from an average of 0.01 to 0.03. The first question is whether the rise is a cause for alarm or just a random occurrence. Statistical process control can help the manager decide whether further action should be taken. If the rise in the proportion is not just a random occurrence, the manager should seek expla-nations of the poor performance. Perhaps the number of claims significantly increased, causing an overload on the employees in the department. The deci-sion might be to hire more personnel. Or perhaps the procedures being used are ineffective or the training of employees is inadequate. SPC is an integral part of TQM and Six Sigma.

Variation of OutputsNo two services or products are exactly alike because the processes used to produce them contain many sources of variation, even if the processes are working as intended. Nonetheless, it is important to minimize the varia-tion in outputs because frequently variation is what the customer sees and feels. Suppose a physicians’ clinic submits claims on behalf of its patients to a particular insurance company. In this situation, the physicians’ clinic is the customer of the insurance company’s bill payment process. In some cases, the clinic receives payment in 4 weeks, and in other cases 20 weeks. The time to process a request for payment varies because of the load on the insurance company’s processes, the medical history of the patient, and the skills and attitudes of the employees. Meanwhile, the clinic must cover its expenses while it waits for payment. Regardless of whether the process is producing services or products, nothing can be done to eliminate variation in output completely; however, management should investigate the causes of the variation in order to minimize it.

Performance Measurements Performance can be evaluated in two ways. One way is to measure variables—that is, service or product characteristics, such as weight, length, volume, or time, that can be measured. The advantage of using performance variables is that if a service or product misses its perfor-mance specifications, the inspector knows by how much. The disadvantage is that such measurements typically involve special equipment, employee skills, exacting procedures, and time and effort.

Another way to evaluate performance is to measure attributes; service or product character-istics that can be quickly counted for acceptable performance. This method allows inspectors to make a simple “yes or no” decision about whether a service or product meets the specifications. Attributes often are used when performance specifications are complex and measurement of variables is difficult or costly. Some examples of attributes that can be counted are the number of insurance forms containing errors that cause underpayments or overpayments, the proportion of airline flights arriving within 15 minutes of scheduled times, and the number of stove-top assemblies with spotted paint.

The advantage of counting attributes is that less effort and fewer resources are needed than for measuring variables. The disadvantage is that, even though attribute counts can reveal that pro-cess performance has changed, they do not indi-cate by how much. For example, a count may determine that the proportion of airline flights arriving within 15 minutes of their scheduled times declined, but the result does not show how much beyond the 15-minute allowance the flights are arriving. For that, the actual deviation from the scheduled arrival, a variable, would have to be measured.

Sampling The most thorough approach to inspec-tion is to examine each service or product at each stage of the process for quality. This method, called complete inspection, is used when the costs of passing defects to an internal or external customer outweigh the inspection costs. Firms often use automated inspection equipment that can record, summarize, and display data. Many companies find that automated inspection equipment can pay for itself in a reasonably short time.

variables

Service or product character-istics, such as weight, length, volume, or time, that can be measured.

attributes

Service or product characteristics that can be quickly counted for acceptable performance.

Wine production is an example of a situation in which complete inspection is not an option. Here a quality inspector draws a sample of white wine from a stainless steel maturation tank.

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134 PART 1 MANAGING PROCESSES

A well-conceived sampling plan can approach the same degree of protection as complete inspection. A sampling plan specifies a sample size, which is a quantity of randomly selected observations of process outputs, the time between successive samples, and decision rules that determine when action should be taken. Sampling is appropriate when inspection costs are high because of the special knowledge, skills, procedures, and expensive equipment that are required to perform the inspections, or because the tests are destructive.

Sampling Distributions Relative to a performance measure, a process will produce output that can be described by a process distribution, with a mean and variance that will be known only with a complete inspection with 100 percent accuracy. The purpose of sampling, however, is to estimate a variable or attribute measure for the output of the process without doing a complete inspection. That measure is then used to assess the performance of the process itself. For example, the time required to process specimens at an intensive care unit lab in a hospital (a variable mea-sure) will vary. If you measured the time to complete an analysis of a large number of patients and plotted the results, the data would tend to form a pattern that can be described as a process distribution. With sampling, we try to estimate the parameters of the process distribution using statistics such as the sample mean and the sample range or standard deviation.

1. The sample mean is the sum of the observations divided by the total number of observations:

x =an

i =1xi

nwhere

xi = observation of a quality characteristic (such as time)

n = total number of observations

x = mean

2. The range is the difference between the largest observation in a sample and the smallest. The standard deviation is the square root of the variance of a distribution. An estimate of the process standard deviation based on a sample is given by

s = R ani = 1(xi – x)2n – 1 or s = c ani = 1x 2 – ¢ ani = 1xi≤2nn – 1where

s = standard deviation of a sample

n = total number of observations in the sample

x = mean

xi = observation of a quality characteristic

Relatively small values for the range or the standard deviation imply that the observations are clustered near the mean.

These sample statistics have their own distribution, which we call a sampling distribution. For example, in the lab analysis process, an important performance variable is the time it takes to get results to the critical care unit. Suppose that management wants results available in an average

of 25 minutes. That is, it wants the process distribution to have a mean of 25 minutes. An inspector periodically taking a sample of five analyses and calculating the sample mean could use it to determine how well the process is doing. Suppose that the process is actually producing the analyses with a mean of 25 minutes. Plotting a large number of these sample means would show that they have their own sampling distribution with a mean centered on 25 minutes, as does the process distribution mean, but with much less variability. The reason is that the sample means offset the highs and lows of the individual times in each sample. Figure 3.5 shows the relationship between the sampling distribution of sample means and the process distribution for the analysis times.

Some sampling distributions (e.g., for means with sample sizes of 4 or more and pro-portions with sample sizes of 20 or more) can be approximated by the normal distribu-tion, allowing the use of the normal tables (see Appendix 1, “Normal Distribution”). For example, suppose you wanted to determine the probability that a sample mean will be more than 2.0 standard deviations higher than the process mean. Go to Appendix 1 and note that the entry in the table for z = 2.0 standard deviations is 0.9772. Consequently, the probability is 1.0000 – 0.9772 = 0.0228, or 2.28 percent. The probability that the sample mean will be more than 2.0 standard deviations lower than the process mean is

sampling plan

A plan that specifies a sample size, the time between successive samples, and decision rules that determine when action should be taken.

sample size

A quantity of randomly selected observations of process outputs.

▼ FIGURE 3.5Relationship Between the Distribution of Sample Means and the Process Distribution

MeanDistribution of sample means

Process distribution

25 Time

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QUALITY AND PERFORMANCE CHAPTER 3 135

also 2.28 percent, because the normal distribution is symmetric to the mean. The ability to assign probabilities to sample results is important for the construction and use of control charts.

Common Causes The two basic categories of variation in output include common causes and assignable causes. Common causes of variation are the purely random, unidentifiable sources of variation that are unavoidable with the current process. A process distribution can be characterized by its location, spread, and shape. Location is measured by the mean of the distribution, while spread is measured by the range or standard deviation. The shape of process distributions can be characterized as either symmetric or skewed. A symmetric distribution has the same number of observations above and below the mean. A skewed distribution has a greater number of observations either above or below the mean. If process variability results solely from common causes of variation, a typical assumption is that the distribution is symmetric, with most observations near the center.

Assignable Causes The second category of variation, assignable causes of variation, also known as special causes, includes any variation-causing factors that can be identified and eliminated. Assignable causes of variation include an employee needing training or a machine needing repair. Let us return to the example of the lab analysis process. Figure 3.6 shows how assignable causes can change the distribution of output for the analysis process. The green curve is the process distribution when only common causes of variation are present. The purple dashed curves depict a change in the distribution because of assignable causes. In Figure 3.6(a), the purple dashed curve indicates that the process took more time than planned in many of the cases, thereby increasing the average time of each analysis. In Figure 3.6(b), an increase in the variability of the time for each case affected the spread of the distribu-tion. Finally, in Figure 3.6(c), the purple dashed curve indicates that the process produced a prepon-derance of the tests in less-than-average time. Such a distribution is skewed, or no longer symmetric to the average value. A process is said to be in statistical control when the location, spread, or shape of its distribution does not change over time. After the process is in statistical control, managers use SPC procedures to detect the onset of assignable causes so that they can be addressed.

common causes of variation

The purely random, unidentifi-able sources of variation that are unavoidable with the current process.

assignable causes of variation

Any variation-causing factors that can be identified and eliminated.

◀ FIGURE 3.6Effects of Assignable Causes on the Process Distribution for the Lab Analysis Process

Average

(b) Spread

Average

(c) Shape

Average

(a) Location

Time Time Time

Control ChartsTo determine whether observed variations are abnormal, we can measure and plot the perfor-mance measure taken from the sample on a time-ordered diagram called a control chart. A control chart has a nominal value, or central line, which can be the process’s historic average or a target that managers would like the process to achieve, and two control limits based on the sampling distribution of the quality measure. The control limits are used to judge whether action is required. The larger value represents the upper control limit (UCL), and the smaller value represents the lower control limit (LCL). Figure 3.7 shows how the control limits relate to the sampling distribution. A sample statistic that falls between the UCL and the LCL indi-cates that the process is exhibiting common causes of variation. A statistic that falls outside the control lim-its indicates that the process is exhibiting assignable causes of variation.

Observations falling outside the control limits do not always mean poor quality. For example, in Figure 3.7 the assignable cause may be a new billing process introduced to reduce the number of incorrect bills sent to customers. If the proportion of incorrect bills—that is, the performance measure from a sample of bills—falls below the LCL of the control chart, the new procedure likely changed the billing process for the better, and a new control chart should be constructed.

control chart

A time-ordered diagram that is used to determine whether observed variations are abnormal.

▼ FIGURE 3.7How Control Limits Relate to the Sampling Distribution: Observations from Three Samples

UCL

Nominal

LCL

Assignablecauses likely

1 2Samples

3

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136 PART 1 MANAGING PROCESSES

Managers or employees responsible for evaluating a process can use control charts in the following ways:

1. Take a random sample from the process and calculate a variable or attribute performance measure.

2. If the statistic falls outside the chart’s control limits or exhibits unusual behavior, look for an assignable cause.

3. Eliminate the cause if it degrades performance; incorporate the cause if it improves perfor-mance. Reconstruct the control chart with new data.

4. Repeat the procedure periodically.

Sometimes, problems with a process can be detected even though the control limits have not been exceeded. Figure 3.8 contains four examples of control charts. Chart (a) shows a process that is in statisti-cal control. No action is needed. However, chart (b) shows a pattern called a run or a sequence of observations with a certain characteristic. A typical rule is to take reme-dial action when five or more observations show a downward or upward trend, even if the points have not yet exceeded the control limits. Here, nine sequential observations are below the mean and show a downward trend. The probability is low that such a result could take place by chance.

Chart (c) shows that the process takes a sudden change from its normal pattern. The last four observations are unusual: The first drops close to the LCL, the next two rise toward the UCL, and the fourth

remains above the nominal value. Managers or employees should monitor processes with such sudden changes even though the control limits have not been exceeded. Finally, chart (d) indi-cates that the process went out of control twice because two sample results fell outside the control limits. The probability that the process distribution has changed is high. We discuss more implica-tions of being out of statistical control when we discuss process capability later in this chapter.

Control charts are not perfect tools for detecting shifts in the process distribution because they are based on sampling distributions. Two types of error are possible with the use of control charts. A type I error occurs when the conclusion is made that the process is out of control based on a sample result that falls outside the control limits, when in fact it was due to pure randomness. A type II error occurs when the conclusion is that the process is in control and only randomness is present, when actually the process is out of statistical control.

These errors can be controlled by the choice of control limits. The choice would depend on the costs of looking for assignable causes when none exist versus the cost of not detecting a shift in the process. For example, setting control limits at { 3 standard deviations from the mean reduces the type I error, because chances are only 0.26 percent that a sample result will fall outside the control limits unless the process is out of statistical control. However, the type II error may be sig-nificant; more subtle shifts in the nature of the process distribution will go undetected because of the wide spread in the control limits. Alternatively, the spread in the control limits can be reduced to { 2 standard deviations, thereby increasing the likelihood of sample results from a nonfaulty process falling outside the control limits to 4.56 percent. Now, the type II error is smaller, but the type I error is larger because employees are likely to search for assignable causes when the sample result occurred solely by chance. As a general rule, use wider limits when the cost for searching for assignable causes is large relative to the cost of not detecting a shift in the process distribution.

SPC methods are useful for both measuring the current process performance and detecting whether the process has changed in a way that will affect future performance. Consequently, we first discuss mean and range charts for variable measures of performance and then consider control charts for attributes measures.

Control Charts for VariablesControl charts for variables are used to monitor the mean and the variability of the process distribution.

R-Chart A range chart, or R-chart, is used to monitor process variability. To calculate the range of a set of sample data, the analyst subtracts the smallest from the largest measurement in each sample. If any of the ranges fall outside the control limits, the process variability is not in control.

type I error

An error that occurs when the employee concludes that the process is out of control based on a sample result that falls outside the control limits, when in fact it was due to pure randomness.

type II error

An error that occurs when the employee concludes that the process is in control and only randomness is present, when actually the process is out of sta-tistical control.

R-chart

A chart used to monitor process variability.

▼ FIGURE 3.8Control Chart Examples

Vari

atio

ns

Vari

atio

nsVa

riat

ions UCL

Nominal

LCL

Sample number

(a) Normal—No action

UCL

Nominal

LCL

Sample number

(b) Run—Take action

Vari

atio

ns

Sample number

(d) Exceeds control limits—Take action

UCL

Nominal

LCL

UCL

Nominal

LCL

Sample number

(c) Sudden change—Monitor

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QUALITY AND PERFORMANCE CHAPTER 3 137

The control limits for the R-chart are

UCLR = D4R and LCLR = D3R

where

R = average of several past R values and the central line of the control chart

D3, D4 = constants that provide 3 standard deviation (three@sigma) limits for a given sample size

Notice that the values for D3 and D4 shown in Table 3.1 change as a function of the sample size. Notice, too, that the spread between the control limits narrows as the sample size increases. This change is a consequence of having more information on which to base an estimate for the process range.

x@Chart An x@chart (read “x-bar chart”) is used to see whether the process is generating output, on average, consistent with a target value set by management for the process or whether its cur-rent performance, with respect to the average of the performance measure, is consistent with its past performance. A target value is useful when a process is completely redesigned and past performance is no longer relevant. When the assignable causes of process variability have been identified and the process variability is in statistical control, the analyst can then construct an x@chart. The control limits for the x@chart are

UCL xQ = x + A2R and LCL xQ = x – A2R

x@chart

A chart used to see whether the process is generating output, on average, consistent with a target value set by management for the process or whether its current performance, with respect to the average of the performance measure, is consistent with past performance.

Size of Sample (n)

Factor for UCL and LCL for x@Chart (A2)

Factor for LCL for R-Chart (D3)

Factor for UCL for R-Chart (D4)

2 1.880 0 3.267

3 1.023 0 2.575

4 0.729 0 2.282

5 0.577 0 2.115

6 0.483 0 2.004

7 0.419 0.076 1.924

8 0.373 0.136 1.864

9 0.337 0.184 1.816

10 0.308 0.223 1.777

Source: NIST/SEMATECH e-Handbook of Statistical Methods, https://www.itl.nist.gov/div898/handbook/pmc/section3/pmc321.htm.

TABLE 3.1 | FACTORS FOR CALCULATING THREE SIGMA LIMITS FOR THE x @CHART AND R-CHART

where

x = central line of the chart, which can be either the average of past sample means or a target value set for the process

A2 = constant to provide three-sigma limits for the sample mean

The values for A2 are contained in Table 3.1. Note that the control limits use the value of R ; therefore, the x@chart must be constructed after the process variability is in control.

To develop and use x@ and R-charts, do the following:

Step 1. Collect data on the variable quality measurement (such as time, weight, or diameter) and organize the data by sample number. Preferably, at least 20 samples of size n should be taken for use in constructing a control chart.

Step 2. Compute the range for each sample and the average range, R, for the set of samples.

Step 3. Use Table 3.1 to determine the upper and lower control limits of the R-chart.

Step 4. Plot the sample ranges. If all are in control, proceed to step 5. Otherwise, find the assign-able causes, correct them, and return to step 1.

Step 5. Calculate x for each sample and determine the central line of the chart, x.

Step 6. Use Table 3.1 to determine the parameters for UCL xQ and LCL xQ and construct the x@chart.

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138 PART 1 MANAGING PROCESSES

Step 7. Plot the sample means. If all are in control, the process is in statistical control in terms of the process average and process variability. Continue to take samples and monitor the process. If any are out of control, find the assignable causes, address them, and return to step 1. If no assignable causes are found after a diligent search, assume that the out-of-control points represent common causes of variation and continue to monitor the process.

Using x- and R-Charts to Monitor a ProcessEXAMPLE 3.1

The management of West Allis Industries is concerned about the production of a special metal cylindrical bolt used by several of the company’s largest customers. The diameter of the bolt is critical to the cus-tomers. Data from 5 samples appear in the accompanying table. The sample size is 4. Is the process in statistical control?

SOLUTION

Step 1. For simplicity, we use only 5 samples. In practice, more than 20 samples would be desirable. The data are shown in the following table.

DATA FOR THE x @ AND R-CHARTS: OBSERVATIONS OF BOLT DIAMETER (INCH)OBSERVATIONS

Sample Number 1 2 3 4 R x

1 0.5014 0.5022 0.5009 0.5027 0.0018 0.5018

2 0.5021 0.5041 0.5024 0.5020 0.0021 0.5027

3 0.5018 0.5026 0.5035 0.5023 0.0017 0.5026

4 0.5008 0.5034 0.5024 0.5015 0.0026 0.5020

5 0.5041 0.5056 0.5034 0.5047 0.0022 0.5045

Average 0.0021 0.5027

Step 2. Compute the range for each sample by subtracting the lowest value from the highest value. For example, in sample 1 the range is 0.5027 – 0.5009 = 0.0018 inch. Similarly, the ranges for samples 2, 3, 4, and 5 are 0.0021, 0.0017, 0.0026, and 0.0022 inch, respectively. As shown in the table, R = 0.0021.

Step 3. To construct the R-chart, select the appropriate constants from Table 3.1 for a sample size of 4. The control limits are

UCLR = D4R = 2.282(0.0021) = 0.00479 inch

LCLR = D3R = 0(0.0021) = 0 inch

Step 4. Plot the ranges on the R-chart, as shown in Figure 3.9. None of the sample ranges falls outside the control limits. Consequently, the process variability is in statistical control. If any of the sample ranges fall outside the limits, or an unusual pattern appears (see Figure 3.9), we would search for the causes of the excessive variability, address them, and repeat step 1.

Online ResourcesTutor 3.1 in OM Explorer provides a new example to practice the use of x-bar and R-charts.

Active Model 3.1 provides additional insight on the x-bar and R-charts and their uses for the cylindrical bolt problem.

An analyst measures the diameter of a part with a micrometer. After he measures the sample, he plots the range on the control chart.

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FIGURE 3.9 ▶Range Chart from the OM Explorer x@ and R-Chart Solver, Showing That the Process Variability Is in Control

010

0.0045

2 3 4 5 6 7

0.005

0.0040.0035

0.0030.0025

0.0020.0015

0.0010.0005

Sample Number

Ran

ge

R-Chart UCLR = 0.00479

LCLR = 0

R = 0.0021

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QUALITY AND PERFORMANCE CHAPTER 3 139

If the standard deviation of the process distribution is known, another form of the x@chart may be used:

UCL xQ = x + zs xQ and LCL xQ = x – zs xQ

where

s xQ = s/2n = standard deviation of sample meanss = standard deviation of the process distribution

n = sample size

x = central line of the chart, which can be either the average of past sample means or a target value set for the process

z = normal deviate (number of standard deviations from the average)

The analyst can use an R-chart to be sure that the process variability is in control before constructing the x @chart. The advantage of using this form of the x @chart is that the analyst can adjust the spread of the control limits by changing the value of z. This approach can be useful for balancing the effects of type I and type II errors.

Step 5. Compute the mean for each sample. For example, the mean for sample 1 is

0.5014 + 0.5022 + 0.5009 + 0.50274

= 0.5018 inch

Similarly, the means of samples 2, 3, 4, and 5 are 0.5027, 0.5026, 0.5020, and 0.5045 inch, respectively. As shown in the table, x = 0.5027.

Step 6. Now, construct the x@chart for the process average. The average bolt diameter is 0.5027 inch, and the average range is 0.0021 inch, so use x = 0.5027, R = 0.0021, and A2 from Table 3.1 for a sample size of 4 to construct the control limits:

UCL xQ = x + A2R = 0.5027 + 0.729(0.0021) = 0.5042 inch

LCL xQ = x – A2R = 0.5027 – 0.729(0.0021) = 0.5012 inch

Step 7. Plot the sample means on the control chart, as shown in Figure 3.10. The mean of sample 5 falls above the UCL, indicating that the process average is out of statistical control and that assignable causes must be explored, perhaps using a cause-and-effect diagram.

◀ FIGURE 3.10The x@chart from the OM Explorer x@ and R-Chart Solver for the Cylindrical Bolt, Showing that Sample 5 Is Out of Controlx = 0.5027

10

0.5045

2 3 4 5 6 7

0.505

0.5040.5035

0.503

0.5025

0.502

0.50150.501

Sample Number

Aver

age

X-Bar Chart

UCLx = 0.5042

LCLx = 0.5012

DECISION POINTA new employee operated the lathe machine that makes the cylindrical bolt on the day sample 5 was taken. To solve the problem, management initiated a training session for the employee. Subsequent samples showed that the process was back in statistical control.

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140 PART 1 MANAGING PROCESSES

Designing an x-Chart Using the Process Standard DeviationEXAMPLE 3.2

The Sunny Dale Bank monitors the time required to serve customers at the drive-through window because it is an important quality factor in competing with other banks in the city. After analyzing the data gathered in an extensive study of the window operation, bank management deter-mined that the mean time to process a customer at the peak demand period is 5 minutes, with a standard deviation of 1.5 minutes. Management wants to monitor the mean time to process a customer by periodically using a sample size of six customers. Assume that the process variability is in statistical control. Design an x@chart that has a type I error of 5 percent. That is, set the control limits so that there is a 2.5 percent chance a sample result will fall below the LCL and a 2.5 percent chance that a sample result will fall above the UCL. After several weeks of sampling, two successive samples came in at 3.70 and 3.68 minutes, respectively. Is the customer service process in statistical control?

SOLUTION

x = 5.0 minutes

s = 1.5 minutes

n = 6 customers

z = 1.96

The process variability is in statistical control, so we proceed directly to the x@chart. The control limits are

UCL xQ = x + zs/2n = 5.0 + 1.96(1.5)/26 = 6.20 minutes LCL xQ = x – zs/2n = 5.0 – 1.96(1.5)/26 = 3.80 minutes

The value for z can be obtained in the following way. The appendix on normal distribution gives the proportion of the total area under the normal curve from – ∞ to z. We want a type I error of 5 percent, or 2.5 percent of the curve above the UCL and 2.5 percent below the LCL. Consequently, we need to find the z-value in the table that leaves only 2.5 percent in the upper portion of the normal curve (or 0.9750 in the table). The value is 1.96. The two new samples are below the LCL of the chart, implying that the average time to serve a customer has dropped. Assignable causes should be explored to see what caused the improvement.

DECISION POINTManagement studied the time period over which the samples were taken and found that the supervisor of the process was experimenting with some new procedures. Management decided to make the new procedures a permanent part of the customer service process. After all employees were trained in the new procedures, new samples were taken and the control chart reconstructed.

Online ResourcesActive Model 3.2 provides additional insight on the p-chart and its uses for the booking services department.

Tutor 3.2 in OM Explorer provides a new example to practice the use of the p-chart.

A customer making a bank deposit in Boise, Idaho, USA.

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Control Charts for AttributesTwo charts commonly used for performance measures based on attributes measures are the p- and c-chart. The p-chart is used for controlling the proportion of defects generated by the process. The c-chart is used for controlling the number of defects when more than one defect can be present in a service or product.

p-Charts The p-chart is a commonly used control chart for attributes. The performance char-acteristic is counted rather than measured, and the entire service or item can be declared good or defective. For example, in the banking industry, the attributes counted might be the number of nonendorsed deposits or the number of incorrect financial statements sent to customers. The method involves selecting a random sample, inspecting each item in it, and calculating the sample proportion defective, p, which is the number of defective units divided by the sample size.

Sampling for a p-chart involves a “yes or no” decision: The process output either is or is not defective. The underlying statistical distribution is based on the binomial distribution.

p-chart

A chart used for controlling the proportion of defective services or products generated by the process.

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QUALITY AND PERFORMANCE CHAPTER 3 141

However, for large sample sizes, the normal distribution provides a good approximation to it. The standard deviation of the distribution of proportion defectives, sp, is

sp = 2p(1 – p)/nwhere

n = sample size

p = central line on the chart, which can be either the historical average population proportion defective or a target value

We can use sp to arrive at the upper and lower control limits for a p-chart:

UCLp = p + zsp and LCLp = p – zsp

where

z = normal deviate (number of standard deviations from the average)

The chart is used in the following way. Periodically, a random sample of size n is taken, and the number of defective services or products is counted. The number of defectives is divided by the sample size to get a sample proportion defective, p, which is plotted on the chart. When a sample proportion defective falls outside the control limits, the analyst assumes that the pro-portion defective generated by the process has changed and searches for the assignable cause. Observations falling below the LCLp indicate that the process may actually have improved. The analyst may find no assignable cause, because it is always possible that an out-of-control propor-tion occurred randomly. However, if the analyst discovers assignable causes, those sample data should not be used to calculate the control limits for the chart.

Using a p-Chart to Monitor a ProcessEXAMPLE 3.3

The operations manager of the booking services department of Hometown Bank is concerned about the number of wrong customer account numbers recorded by Hometown personnel. Each week a random sample of 2,500 deposits is taken, and the number of incorrect account numbers is recorded. The results for the past 12 weeks are shown in the following table. Is the booking process out of statistical control? Use three-sigma control limits, which will provide a type I error of 0.26 percent.

Sample Number Wrong Account Numbers Sample Number Wrong Account Numbers

1 15 7 24

2 12 8 7

3 19 9 10

4 2 10 17

5 19 11 15

6 4 12 3

Total 147

SOLUTION

Step 1. Use these sample data to calculate p

p =Total defectives

Total number of observations=

14712(2,500)

= 0.0049

sp = 2p(1 – p) /n = 20.0049(1 – 0.0049) /2,500 = 0.0014UCLp = p + zsp = 0.0049 + 3(0.0014) = 0.0091

LCLp = p – zsp = 0.0049 – 3(0.0014) = 0.0007

Step 2. Calculate each sample proportion defective. For sample 1, the proportion of defectives is 15/2,500 = 0.0060.

Step 3. Plot each sample proportion defective on the chart, as shown in Figure 3.11.

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142 PART 1 MANAGING PROCESSES

c-Charts Sometimes services or products have more than one defect. For example, a roll of carpeting may have several defects, such as tufted or discolored fibers or stains from the produc-tion process. Other situations in which more than one defect may occur include accidents at a particular intersection, bubbles in a television picture face panel, and complaints from a patron at a hotel. When management is interested in reducing the number of defects per unit or service encounter, another type of control chart, the c-chart, is useful.

The underlying sampling distribution for a c-chart is the Poisson distribution. The Poisson distribution is based on the assumption that defects occur over a continuous region on the surface of a product or a continuous time interval during the provision of a service. It further assumes that the probability of two or more defects at any one location on the surface or at any instant of time is negligible. The mean of the distribution is c and the standard deviation is 2c. A useful tactic is to use the normal approximation to the Poisson so that the central line of the chart is c and the control limits are

UCLc = c + z2c and LCLc = c – z2c

c-chart

A chart used for controlling the number of defects when more than one defect can be present in a service or product.

Sample 7 exceeds the UCL; thus, the process is out of control and the reasons for the poor performance that week should be determined.

DECISION POINTManagement explored the circumstances when sample 7 was taken. The encoding machine used to print the account numbers on the checks was defective that week. The following week the machine was repaired; however, the recommended preventive maintenance on the machine was not performed for months prior to the failure. Management reviewed the performance of the maintenance department and instituted changes to the maintenance procedures for the encoding machine. After the problem was corrected, an analyst recalculated the control limits using the data without sample 7. Subsequent weeks were sampled, and the booking process was determined to be in statistical control. Consequently, the p-chart provides a tool to indicate when a process needs adjustment.

FIGURE 3.11 ▶The p-Chart from POM for Windows for Wrong Account Numbers, Showing That Sample 7 Is Out of Control

Using a c-Chart to Monitor Defects per UnitEXAMPLE 3.4

The Woodland Paper Company produces paper for the newspaper industry. As a final step in the pro-cess, the paper passes through a machine that measures various product quality characteristics. When the paper production process is in control, it averages 20 defects per roll.

a. Set up a control chart for the number of defects per roll. For this example, use two-sigma control limits.

b. Five rolls had the following number of defects: 16, 21, 17, 22, and 24, respectively. The sixth roll, using pulp from a different supplier, had 5 defects. Is the paper production process in control?

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QUALITY AND PERFORMANCE CHAPTER 3 143

Process CapabilityStatistical process control techniques help managers achieve and maintain a process distribu-tion that does not change in terms of its mean and variance. The control limits on the control charts signal when the mean or variability of the process changes. However, a process that is in statistical control may not be producing services or products according to their design specifica-tions, because the control limits are based on the mean and variability of the sampling distribu-tion, not the design specifications. Process capability refers to the ability of the process to meet the design specifications for a service or product. Design specifications often are expressed as a nominal value, or target, and a tolerance, or allowance above or below the nominal value.

For example, the administrator of an intensive care unit lab might have a nominal value for the turnaround time of results to the attending physicians of 25 minutes and a tolerance of { 5 minutes because of the need for speed under life-threatening conditions. The tolerance gives an upper specification of 30 minutes and a lower specification of 20 minutes. The lab process must be capable of providing the results of analyses within these specifications; otherwise, it will pro-duce a certain proportion of “defects.” The administrator is also interested in detecting occur-rences of turnaround times of less than 20 minutes because something might be learned that can be built into the lab process in the future. For the present, the physicians are pleased with results that arrive within 20 to 30 minutes.

Defining Process CapabilityFigure 3.13 shows the relationship between a process distribution and the upper and lower speci-fications for the lab process turnaround time under two conditions. In Figure 3.13(a), the pro-cess is capable because the extremes of the process distribution fall within the upper and lower

process capability

The ability of the process to meet the design specifications for a service or product.

nominal value

A target for design specifications.

tolerance

An allowance above or below the nominal value.

SOLUTION

a. The average number of defects per roll is 20. Therefore

UCLc = c + z2c = 20 + 2(220) = 28.94LCLc = c – z2c = 20 – 2(220) = 11.06

The control chart is shown in Figure 3.12.

b. Because the first five rolls had defects that fell within the control limits, the process is still in control. The sixth roll’s five defects, however, fall below the LCL, and therefore, the process is techni-cally “out of control.” The control chart indicates that something good has happened.

DECISION POINTThe supplier for the first five samples has been used by Woodland Paper for many years. The supplier for the sixth sample is new to the company. Management decided to continue using the new supplier for a while, monitoring the number of defects to see whether it stays low. If the num-ber remains below the LCL for 20 consecutive samples, management will make the switch permanent and recalculate the control chart parameters.

Online ResourceTutor 3.3 in OM Explorer provides a new example to practice the use of the c-chart.

◀ FIGURE 3.12The c-Chart from the OM Explorer c-Chart Solver for Defects per Roll of Paper

10 2 3 4 5 6 7

35

30

25

20

15

10

5

0

Sample Number

Num

ber

of D

efec

ts

c-Chart

UCLc = 28.94

LCLc = 11.06

c = 20

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144 PART 1 MANAGING PROCESSES

specifications. In Figure 3.13(b), the process is not capable because the lab process produces too many reports with long turnaround times.

Figure 3.13 shows clearly why managers are so concerned with reducing process variability. The less variability—represented by lower standard deviations—the less frequently bad output is produced. Figure 3.14 shows what reducing variability implies for a process distri-bution that is a normal probability distribution. The firm with two-sigma performance (the specification limits equal the process distribution mean { 2 standard deviations) produces 4.56 percent defects, or 45,600 defects per million. The firm with four-sigma performance produces only 0.0063 percent defects, or 63 defects per million. Finally, the firm with six-sigma performance produces only 0.0000002 percent defects, or 0.002 defects per million.3

How can a manager determine quantitatively whether a process is capable? Two measures commonly are used in practice to assess the capability of a process: the process capability index and the process capa-bility ratio.

Process Capability Index The process capability index, Cpk, is defined as

Cpk = Minimum of J x – Lower specification3s , Upper specification – x3s Rwhere

s = standard deviation of the process distribution

The process capability index measures how well the process is centered and whether the variability is acceptable. As a general rule, most values of any process distribution fall within { 3 standard deviations of the mean. Consequently, { 3 standard deviations are used as the bench-

mark. Because the process capability index is concerned with how well the process distribution is centered relative to the specifications, it checks to see if the process average is at least 3 standard deviations from the upper and lower specifications. We take the minimum of the two ratios because it gives the worst-case situation.

The process capability index must be compared to a critical value to judge whether a process is capable. Firms striving to achieve three-sigma performance use a critical value for the ratio of 1.0. A firm tar-geting four-sigma performance will use 1.33 (or 4/3), a firm targeting five-sigma performance will use 1.67 (or 5/3), and a firm striving for six-sigma performance will use 2.00 (or 6/3). Processes producing services or products with less than three-sigma performance will have Cpk values less than 1.0.

If a process passes the process capability index test, we can declare the process is capable. Suppose a firm desires its processes to produce at the level of four-sigma performance. If Cpk is greater than or equal to the critical value of 1.33, we can say the process is capable. If Cpk is less than the critical value, either the process average is too close to one of the tolerance limits and is generating defective output, or the process variability is too large. To find out whether the vari-ability is the culprit, we need another test.

Process Capability Ratio If a process fails the process capability index test, we need a quick test to see if the process variability is causing the problem. If a process is capable, it has a process distribution whose extreme values fall within the upper and lower specifications for a service or product. For example, if the process distribution is normal, 99.74 percent of the values fall within { 3 standard deviations. In other words, the range of values of the quality measure generated by a process is approximately 6 standard deviations of the process distribution. Hence, if a process is capable at the three-sigma level, the difference between the upper and lower specification, called the tolerance width, must be greater than 6 standard deviations. The process capability ratio, Cp, is defined as

Cp =Upper specification – Lower specification

6s

3Our discussion assumes that the process distribution has no assignable causes. Six Sigma programs, however, define defect performance with the assumption that the process average has moved 1.5 standard deviations. In such a case, there would be 3.4 defects per million. See http://www.isixsigma.com for the rationale behind that assumption.

process capability index, CpkAn index that measures the potential for a process to generate defective outputs relative to either upper or lower specifications.

process capability ratio, CpThe tolerance width divided by 6 standard deviations.

▲ FIGURE 3.14Effects of Reducing Variability on Process Capability

Mean

Nominal value

Upper specification

Lower specification

Two sigma

Four sigma

Six sigma

▲ FIGURE 3.13The Relationship Between a Process Distribution and Upper and Lower Specifications

20 25 30 Minutes

Lower specification

Upper specification

Process distribution

Process distribution

Nominal value

20 25 30 Minutes

Lower specification

Upper specification

Nominal value

(a) Process is capable

(b) Process is not capable

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QUALITY AND PERFORMANCE CHAPTER 3 145

Suppose management wants four-sigma capability in their processes, and a process just failed the process capability index test at that level. A Cp value of 1.33, say, implies that the variability of the process is at the level of four-sigma quality and that the process is capable of consistently pro-ducing outputs within specifications, assuming that the process is centered. Because Cp passed the test, but Cpk did not, we can assume that the problem is that the process is not centered adequately.

Using Continuous Improvement to Determine the Capability of a ProcessTo determine the capability of a process to produce outputs within the tolerances, use the fol-lowing steps.

Step 1. Collect data on the process output, and calculate the mean and the standard deviation of the process output distribution.

Step 2. Use the data from the process distribution to compute process control charts, such as an x@ and an R-chart.

Step 3. Take a series of at least 20 consecutive random samples of size n from the process and plot the results on the control charts. If the sample statistics are within the control limits of the charts, the process is in statistical control. If the process is not in statistical con-trol, look for assignable causes and eliminate them. Recalculate the mean and standard deviation of the process distribution and the control limits for the charts. Continue until the process is in statistical control.

Step 4. Calculate the process capability index. If the results are acceptable, the process is capable and document any changes made to the process; continue to monitor the output by using the control charts. If the results are unacceptable, calculate the process capability ratio. If the results are acceptable, the process variability is fine and management should focus on centering the process. If the results of the process capability ratio are unacceptable, management should focus on reducing the variability in the process until it passes the test. As changes are made, recalculate the mean and standard deviation of the process distribution and the control limits for the charts and return to step 3.

Assessing the Process Capability of the Intensive Care Unit LabEXAMPLE 3.5

The intensive care unit lab process has an average turnaround time of 26.2 minutes and a standard deviation of 1.35 minutes. The nominal value for this service is 25 minutes with an upper specification limit of 30 minutes and a lower specification limit of 20 minutes. The administrator of the lab wants to have four-sigma performance for her lab. Is the lab process capable of this level of performance?

SOLUTIONThe administrator began by taking a quick check to see if the process is capable by applying the process capability index:

Lower specification calculation =26.2 – 20.0

3(1.35)= 1.53

Upper specification calculation =30.0 – 26.2

3(1.35)= 0.94

Cpk = Minimum of [1.53, 0.94] = 0.94

Since the target value for four-sigma performance is 1.33, the process capability index told her that the process was not capable. However, she did not know whether the problem was the variability of the process, the centering of the process, or both. The options available to improve the process depended on what is wrong.

She next checked the process variability with the process capability ratio:

Cp =30.0 – 20.0

6(1.35)= 1.23

The process variability did not meet the four-sigma target of 1.33. Consequently, she initiated a study to see where variability was introduced into the process. Two activities, report preparation and specimen slide preparation, were identified as having inconsistent procedures. These procedures were modified to provide consistent performance. New data were collected and the average turnaround was

Online ResourcesActive Model 3.3 provides additional insight on the process capability problem at the intensive care unit lab.

Tutor 3.4 in OM Explorer provides a new example to practice the process capability measures.

A doctor examines a specimen through his microscope in a lab at St. Vincent’s Hospital.

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146 PART 1 MANAGING PROCESSES

International Quality Documentation Standards and AwardsOnce a company has gone through the effort of making its processes capable, it must document its level of quality so as to better market its services or products. This documentation of quality is especially important in international trade. However, if each country had its own set of stan-dards, companies selling in international markets would have difficulty complying with quality documentation standards in each country where they did business. To overcome this problem, the International Organization for Standardization devised a family of standards called ISO 9000 for companies doing business in the European Union.

The ISO 9001:2015 Documentation StandardsISO 9001:2015 is the latest update of the ISO 9000 standards governing documentation of a qual-ity program. According to the International Organization for Standardization, the ISO 9001:2015 standards are similar in scope to the 2008 standards, but some core terms were modified to better integrate with other international management standards. The change makes the new standard less prescriptive and more focused on performance. It helps ensure that customers get reliable and desired quality of goods and services by specifying what the firm does to fulfill the customer’s quality requirements and applicable regulatory requirements, while aiming to enhance customer satisfaction and achieve continual improvement of its performance in pursuit of these objectives. Companies become certified by proving to a qualified external examiner that they comply with all the requirements. Once certified, companies are listed in a directory so that potential customers can see which companies are certified and to what level. The certifications have to be renewed periodically. Compliance with ISO 9001:2015 standards, however, says nothing about the actual quality of a product. Rather, it indicates to customers that companies can provide documentation to support whatever claims they make about quality. As of 2014, more than 1.1 million organiza-tions worldwide have been certified in the ISO 9000 family of documentation standards.

Completing the certification process can take as long as 18 months and involve many hours of management and employee time. The cost of certification can exceed $1 million for large compa-nies. Despite the expense and commitment involved in ISO certification, it bestows significant external and internal benefits. The external benefits come from the potential sales advantage that companies in compliance have. Companies looking for a supplier will more likely select a company that has demonstrated compliance with ISO documentation standards, all other factors being equal. Consequently, more and more firms are seeking certification to gain a competitive advantage.

Internal benefits can be substantial. Registered companies report an average of 48 percent increased profitability and 76 percent improvement in marketing. The British Standards Institute, a leading third-party auditor, estimates that most ISO 9001–registered companies experience a 10 per-cent reduction in the cost of producing a product because of the quality improvements they make while striving to meet the documentation requirements. Certification in ISO 9001:2015 requires a company to analyze and document its procedures, which is necessary in any event for implementing continu-ous improvement, employee involvement, and similar programs. The guidelines and requirements of the ISO documentation standards provide companies with a jump-start in pursuing TQM programs.

Malcolm Baldrige Performance Excellence ProgramRegardless of where a company does business, it is clear that all organizations have to pro-duce high-quality products and services if they are to be competitive. To emphasize that point, in August 1987 the U.S. Congress signed into law the Malcolm Baldrige National Quality

ISO 9001:2015

A set of standards governing doc-umentation of a quality program.

now 26.1 minutes with a standard deviation of 1.20 minutes. She now had the process variability at the four-sigma level of performance, as indicated by the process capability ratio:

Cp =30.0 – 20.0

6(1.20)= 1.39

However, the process capability index indicated additional problems to resolve:

Cpk = Minimum of J (26.1 – 20.0)3(1.20) , (30.0 – 26.1)3(1.20) R = 1.08DECISION POINTThe lab process was still not at the level of four-sigma performance on turnaround time. The lab admin-istrator searched for the causes of the off-center turnaround time distribution. She discovered periodic backlogs at a key piece of testing equipment. Acquiring a second machine provided the capacity to reduce the turnaround times to four-sigma capability.

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QUALITY AND PERFORMANCE CHAPTER 3 147

Improvement Act, creating the Malcolm Baldrige National Quality Award, which is now called the Baldrige Performance Excellence Program (www.quality.nist.gov/baldrige). Named for the late secretary of commerce, who was a strong proponent of enhancing quality as a means of reducing the trade deficit, the award promotes, recognizes, and publicizes quality strategies and achievements.

The application and review process for the Baldrige award is rigorous. However, the act of prepar-ing the application itself is often a major benefit to organizations because it helps firms define what quality means for them. According to the U.S. Commerce Department’s National Institute of Standards and Technology (NIST), investing in quality principles and performance excellence pays off in increased productivity, satisfied employees and customers, and improved profitability, both for cus-tomers and investors. The seven major criteria for the award are leadership, strategic planning, cus-tomer focus, workforce focus, operations focus, measurement analysis, and results. Customer satisfaction underpins these seven criteria, with achievement of results being given the most weight in selecting winners. By 2016, 113 awards had been presented to over 106 organizations across the six award categories of manufacturing, service, small business, education, health care, and nonprofit.

Systems Approach to Total Quality ManagementFigure 3.15 integrates and summarizes the organizational components required to build an effec-tive culture of quality that underpins the total quality management philosophy outlined earlier in Figure 3.1, the TQM wheel. The overall focus of TQM is always on the needs of the customer through a culture of continuous improvement and an active engagement and involvement of employees at all levels. Continuous improvement and employee involvement are two pillars for customer sat-isfaction. In this chapter we have shown that there are two other pillars as well: (1) management commitment and leadership driving a relentless focus on quality, and (2) analytical process think-ing through the use of tools such as acceptance sampling, process control, and process capability.

The intersections between these four TQM pillars relate to cultural changes that are often the most difficult ones to estab-lish. The Continuous Improvement and Employee Involvement intersection requires that the employees are actually empow-ered to do their jobs and given autonomy in decision making. The Employee Involvement and Analytical Process Thinking intersection requires a commitment to ongoing employee train-ing in statistical tools and their usage. The intersection between Management Commitment/Leadership and Analytical Process Thinking requires management by fact, and not authority. Finally, the intersection between Continuous Improvement and Management Commitment/Leadership requires making quality an integral part of long-term planning.

Failure in managing the intersections is where most com-panies fall short in achieving their quality objectives. For instance, failing to plan for quality is not conducive to building a culture of continuous quality improvement. Likewise, firing trainers during times of economic stress in order to conserve financial resources compromises quality initiatives. Building a culture of long-term quality requires consistency of purpose, thinking, and action as outlined in this chapter.

Baldrige Performance Excellence Program

A program named for the late secretary of commerce Malcolm Baldrige, who was a strong pro-ponent of enhancing quality as a means of reducing the trade deficit; organizations vie for an award that promotes, recognizes, and publicizes quality strategies and achievements.

▼ FIGURE 3.15An integrative view of Total Quality Management

ContinuousImprovement

EmployeeInvolvement

AnalyticalProcess Thinking

Planning

Training

EmpowermentCustomer FocusManagement by Fact

ManagementCommitment& Leadership

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources

3.1 Define the four major costs of quality, and their relationship to the role of ethics in determining the overall costs of delivering products and services.

See the section “Costs of Quality” and understand how decep-tive business practices can affect a customer’s experiences and why the costs of quality should be balanced with ethical considerations.

3.2 Explain the basic principles of total quality manage-ment (TQM) and Six Sigma.

See the section “Total Quality Management and Six Sigma.” Focus on the five customer definitions of quality, and the key Figures 3.1 and 3.2. Be sure to understand Figure 3.3, which shows the goals of Six Sigma.

3.3 Understand how accep-tance sampling and process performance approaches interface in a supply chain.

See the section “Acceptance Sampling.” Figure 3.4 shows how TQM or Six Sigma works in a supply chain through the tactic of acceptance sampling.

POM for Windows: Acceptance SamplingSupplement G: Acceptance Sampling Plans

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148 PART 1 MANAGING PROCESSES

Key EquationsStatistical Process Control 1. Sample mean:

x =an

i = 1xi

n

2. Standard deviation of a sample:

s = S ani = 1(xi – x )2n – 1 or s = S ani = 1xi2 – (Σxi)2nn – 1 3. Control limits for variable process control charts

a. R-chart, range of sample:

Upper control limit = UCLR = D4 R

Lower control limit = LCLR = D3 R

b. x@chart, sample mean:

Upper control limit = UCLxQ = x + A2 R Lower control limit = LCLxQ = x – A2 R

c. When the standard deviation of the process distribution, s, is known:

Upper control limit = UCLxQ = x + zsxQ

Lower control limit = LCLxQ = x + zsxQ

where

s xQ =s2n

Learning Objective Guidelines for Review Online Resources

3.4 Describe how to construct process control charts and use them to determine whether a process is out of statistical control.

See the section “Statistical Process Control.” Understanding Figures 3.5 and 3.6 is key to understanding the methods to follow. The subsections on “Control Charts,” “Control Charts for Vari-ables,” and “Control Charts for Attributes” show you how to deter-mine if a process is in statistical control. Study Examples 3.1 to 3.4 as well as Solved Problems 1 to 3.

Active Model Exercises: 3.1: x-Bar and R-Charts; 3.2: p-ChartsOM Explorer Solvers: R-and x-Bar Charts; c-Charts; p-ChartsOM Explorer Tutors: 3.1: x-Bar and R-Charts; 3.2: p-Charts; 3.3: c-ChartsPOM for Windows: x-Bar Charts; p-Charts; c-Charts

3.5 Explain how to determine whether a process is capable of producing a service or product to specifications.

The major takeaway in the chapter is found in the section “Pro-cess Capability”. Be sure you understand Figures 3.13 and 3.14; study Example 3.5 and Solved Problem 4.

Active Model Exercise: 3.3: Process CapabilityOM Explorer Solver: Process CapabilityOM Explorer Tutor: 3.4: Process CapabilityPOM for Windows: Process Capability

3.6 Describe International Quality Documentation Standards and the Baldrige Performance Excellence Program.

The section “International Quality Documentation Standards and Awards” reviews details of ISO quality standards and the Baldrige Award Program.

3.7 Understand the systems approach to total quality management.

The section “Systems Approach to Total Quality Management” summarizes different pillars of the total quality management phi-losophy, and how managing the interaction between each pillar leads to higher quality.

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QUALITY AND PERFORMANCE CHAPTER 3 149

4. Control limits for attribute process control chartsa. p-chart, proportion defective:

Upper control limit = UCLp = p + zsp

Lower control limit = LCLp = p – zsp

where

sp = 2p (1 – p )/n b. c-chart, number of defects:

Upper control limit = UCLc = c + z2c Lower control limit = LCLc = c – z2c

Process Capability 5. Process capability index:

Cpk = Minimum of Jx – Lower specification3s , Upper specification – x3s R 6. Process capability ratio:

Cp =Upper specification – Lower specification

6s

Key Termsacceptable quality level (AQL) 131acceptance sampling 131appraisal costs 126assignable causes of variation 135attributes 133Baldrige Performance Excellence

Program 147c-chart 142common causes of variation 135continuous improvement 129control chart 135defect 125employee empowerment 128

ethical failure costs 126external failure costs 126internal failure costs 126ISO 9001:2015 146nominal value 143p-chart 140plan-do-check-act cycle 130prevention costs 125process capability 143process capability index, Cpk  144process capability ratio, Cp 144quality 127quality at the source 128

R-chart 136sample size 134sampling plan 134Six Sigma 130statistical process control (SPC) 132teams 128tolerance 143total quality management (TQM) 127type I error 136type II error 136variables 133warranty 126 x@chart 137

Solved Problem 1The Watson Electric Company produces incandescent lightbulbs. The following data on the number of lumens for 40-watt lightbulbs were collected when the process was in control.

OBSERVATION

Sample 1 2 3 4

1 604 612 588 600

2 597 601 607 603

3 581 570 585 592

4 620 605 595 588

5 590 614 608 604

a. Calculate control limits for an R-chart and an x@chart.

b. Since these data were collected, some new employees were hired. A new sample obtained the following readings: 625, 592, 612, and 635. Is the process still in control?

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150 PART 1 MANAGING PROCESSES

SOLUTION

a. To calculate x , compute the mean for each sample. To calculate R, subtract the lowest value in the sample from the highest value in the sample. For example, for sample 1,

x =604 + 612 + 588 + 600

4= 601

R = 612 – 588 = 24

Sample x R

1 601 24

2 602 10

3 582 22

4 602 32

5 604 24

Total 2,991 112

Average R = 22.4

The R-chart control limits are

UCLR = D4 R = 2.282(22.4) = 51.12

LCLR = D3 R = 0(22.4) = 0

The x@chart control limits are

UCLxQ = x + A2 R = 598.2 + 0.729(22.4) = 614.53

LCLxQ = x – A2 R = 598.2 – 0.729(22.4) = 581.87

b. First check to see whether the variability is still in control based on the new data. The range is 43 (or 635 – 592), which is inside the UCL and LCL for the R-chart. Since the process variability is in control, we test for the process average using the current estimate for R . The average is 616 [or (625 + 592 + 612 + 635)/4], which is above the UCL for the x@chart. Since the process average is out of control, a search for assignable causes inducing excessive average lumens must be conducted.

x = 598.2

Solved Problem 2The data processing department of the Arizona Bank has five data entry clerks. Each working day their supervisor verifies the accuracy of a random sample of 250 records. A record con-taining one or more errors is considered defective and must be redone. The results of the last 30 samples are shown in the table. All were checked to make sure that none was out of control.

SampleNumber of Defective

Records SampleNumber of Defective

Records SampleNumber of Defective

Records SampleNumber of Defective

Records

1 7 9 6 17 12 24 7

2 5 10 13 18 4 25 13

3 19 11 18 19 6 26 10

4 10 12 5 20 11 27 14

5 11 13 16 21 17 28 6

6 8 14 4 22 12 29 11

7 12 15 11 23 6 30 9

8 9 16 8

Total 300

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QUALITY AND PERFORMANCE CHAPTER 3 151

a. Based on these historical data, set up a p-chart using z = 3.

b. Samples for the next 4 days showed the following:

Sample Number of Defective Records

Tues 17

Wed 15

Thurs 22

Fri 21

What is the supervisor’s assessment of the data entry process likely to be?

SOLUTION

a. From the table, the supervisor knows that the total number of defective records is 300 out of a total sample of 7,500 [or 30(250)]. Therefore, the central line of the chart is

p =300

7,500= 0.04

The control limits are

UCLp = p + zBp (1 – p )n = 0.04 + 3A 0.04(0.96)250 = 0.077 LCLp = p – zBp (1 – p )n = 0.04 – 3A 0.04(0.96)250 = 0.003

b. Samples for the next 4 days showed the following:

Sample Number of Defective Records Proportion

Tues 17 0.068

Wed 15 0.060

Thurs 22 0.088

Fri 21 0.084

Samples for Thursday and Friday are out of control. The supervisor should look for the problem and, upon identifying it, take corrective action.

Solved Problem 3The Minnow County Highway Safety Department monitors accidents at the intersection of Routes 123 and 14. Accidents at the intersection have averaged three per month.

a. Which type of control chart should be used? Construct a control chart with three-sigma control limits.

b. Last month, seven accidents occurred at the intersection. Is this sufficient evidence to jus-tify a claim that something has changed at the intersection?

SOLUTION

a. The safety department cannot determine the number of accidents that did not occur, so it has no way to compute a proportion defective at the intersection. Therefore, the adminis-trators must use a c-chart for which

UCLc = c + z2c = 3 + 323 = 8.20 LCLc = c – z2c = 3 – 323 = – 2.196, adjusted to 0

There cannot be a negative number of accidents, so the LCL in this case is adjusted to zero.

b. The number of accidents last month falls within the UCL and LCL of the chart. We conclude that no assignable causes are present and that the increase in accidents was due to chance.

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152 PART 1 MANAGING PROCESSES

Solved Problem 4Pioneer Chicken advertises “lite” chicken with 30 percent fewer calories. (The pieces are 33 percent smaller.) The process average distribution for “lite” chicken breasts is 420 calories, with a standard deviation of the population of 25 calories. Pioneer randomly takes samples of six chicken breasts to measure calorie content.

a. Design an x @chart using the process standard deviation. Use three-sigma limits.

b. The product design calls for the average chicken breast to contain 400 { 100 calories. Calculate the process capability index (target = 1.33) and the process capability ratio. Interpret the results.

SOLUTION

a. For the process standard deviation of 25 calories, the standard deviation of the sample mean is

sxQ =s2n = 2526 = 10.2 calories

UCLxQ = x + zs xQ = 420 + 3(10.2) = 450.6 calories

LCLxQ = x – zsxQ = 420 – 3(10.2) = 389.4 calories

b. The process capability index is

Cpk = Minimum of Jx – Lower specification3s , Upper specification – x3s R = Minimum of J 420 – 300

3(25)= 1.60,

500 – 420325

= 1.07 R = 1.07The process capability ratio is

Cp =Upper specification – Lower specification

6s=

500 calories – 300 calories6(25)

= 1.33

Because the process capability ratio is 1.33, the process should be able to produce the product reliably within specifications. However, the process capability index is 1.07, so the current process is not centered properly for four-sigma performance. The mean of the process distribu-tion is too close to the upper specification.

Discussion Questions1. Pano Lefkara is a village in Cyprus known for its lace

and silver handicrafts. Their handmade embroidery design is used in tablecloths, curtain borders, and mats. However, the art is slowly dying as the village population is migrating to urban areas. Do you think it is a good idea to replace this handicraft with a machine? What would be the consequences?

2. Recently, the Polish General Corporation, well-known for manufacturing appliances and automobile parts, initiated a $13 billion project to produce automobiles. A great deal of learning on the part of management and employees was required. Even though pressure was mounting to get

a new product to market in early 2012, the production manager of the newly formed automobile division insisted on almost a year of trial runs before sales started because workers have to do their jobs 60 to 100 times before they can memorize the right sequence. The launch date was set for early 2013. What are the consequences of using this approach to enter the market with a new product?

3. Explain how unethical business practices degrade the quality of the experience a customer has with a service or product. How is the International Organization for Standardization trying to encourage ethical business behavior?

The OM Explorer, POM for Windows, and Active Model software is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how to do the calculations

by hand. At the least, the software provides a check on your cal-culations. When calculations are particularly complex and the goal is interpreting the results in making decisions, the software replaces entirely the manual calculations. The software also can be a valuable resource well after your course is completed.

Problems

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QUALITY AND PERFORMANCE CHAPTER 3 153

1. At Quick Car Wash, the wash process is advertised to take less than 7 minutes. Consequently, management has set a target average of 390 seconds for the wash pro-cess. Suppose the average range for a sample of 9 cars is 10 seconds. Use Table 3.1 to establish control limits for sample means and ranges for the car wash process.

2. At Isogen Pharmaceuticals, the filling process for its asthma inhaler is set to dispense 150 milliliters (ml) of steroid solution per container. The average range for a sample of 4 containers is 3 ml. Use Table 3.1 to estab-lish control limits for sample means and ranges for the filling process.

3. The Canine Gourmet Company produces delicious dog treats for canines with discriminating tastes. Management wants the box-filling line to be set so that the process aver-age weight per packet is 45 grams. To make sure that the process is in control, an inspector at the end of the filling line periodically selects a random box of 10 packets and weighs each packet. When the process is in control, the range in the weight of each sample has averaged 6 grams.

a. Design an R- and an x@chart for this process.

b. The results from the last five samples of 10 packets are

Sample x R

1 44 9

2 40 2

3 46 5

4 39 8

5 48 3

Is the process in control? Explain.

4. Aspen Plastics produces plastic bottles to customer order. The quality inspector randomly selects four bot-tles from the bottle machine and measures the outside diameter of the bottle neck, a critical quality dimension that determines whether the bottle cap will fit properly. The dimensions (in inches) from the last six samples are

BOTTLE

Sample 1 2 3 4

1 0.594 0.622 0.598 0.590

2 0.587 0.611 0.597 0.613

3 0.571 0.580 0.595 0.602

4 0.610 0.615 0.585 0.578

5 0.580 0.624 0.618 0.614

6 0.585 0.593 0.607 0.569

Assume that only these six samples are sufficient, and use the data to determine control limits for an R- and an x@chart

5. In an attempt to judge and monitor the quality of instruction, the administration of Mega-Byte Academy

Statistical Process Control

STUDENT

Year 1 2 3 4 5 6 7 8 9 10 Average

1 63 57 92 87 70 61 75 58 63 71 69.7

2 90 77 59 88 48 83 63 94 72 70 74.4

3 67 81 93 55 71 71 86 98 60 90 77.2

4 62 67 78 61 89 93 71 59 93 84 75.7

5 85 88 77 69 58 90 97 72 64 60 76.0

6 60 57 79 83 64 94 86 64 92 74 75.3

7 94 85 56 77 89 72 71 61 92 97 79.4

8 97 86 83 88 65 87 76 84 81 71 81.8

9 94 90 76 88 65 93 86 87 94 63 83.6

10 88 91 71 89 97 79 93 87 69 85 84.9

TABLE 3.2 | TEST SCORES ON EXIT EXAM

devised an examination to test students on the basic concepts that all should have learned. Each year, a ran-dom sample of 10 graduating students is selected for the test. The average score is used to track the quality of the educational process. Test results for the past 10 years are shown in Table 3.2.

Use these data to estimate the center and standard devia-tion for this distribution. Then, calculate the two-sigma control limits for the process average. What comments would you make to the administration of the Mega-Byte Academy?

6. The McGranger Mortgage Company is interested in monitoring the performance of the mortgage process. Fifteen samples of five completed mortgage transactions each were taken during a period when the process was believed to be in control. The times to complete the transactions were measured. The means and ranges of the mortgage process transaction times, measured in days, are as follows:

Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mean 17 14 8 17 12 13 15 16 13 14 16 9 11 9 12

Range 6 11 4 8 9 14 12 15 10 10 11 6 9 11 13

Subsequently, samples of size 5 were taken from the pro-cess every week for the next 10 weeks. The times were measured and the following results obtained:

Sample 16 17 18 19 20 21 22 23 24 25

Mean 11 14 9 15 17 19 13 22 20 18

Range 7 11 6 4 12 14 11 10 8 6

a. Construct the control charts for the mean and the range, using the original 15 samples.

b. On the control charts developed in part (a), plot the values from samples 16 through 25 and comment on whether the process is in control.

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154 PART 1 MANAGING PROCESSES

c. In part (b), if you concluded that the process was out of control, would you attribute it to a drift in the mean, an increase in the variability, or both? Explain your answer.

7. Webster Chemical Company produces mastics and caulking for the construction industry. The product is blended in large mixers and then pumped into tubes and capped. Management is concerned about whether the filling process for tubes of caulking is in statistical control. The process should be centered on 8 ounces per tube. Several samples of eight tubes were taken, each tube was weighed, and the weights in Table 3.3 were obtained.

a. Assume that only six samples are sufficient and develop the control charts for the mean and the range.

b. Plot the observations on the control chart and com-ment on your findings.

Minutes Diameter (thousandths of an inch)

1–12 15 16 18 14 16 17 15 14 14 13 16 17

13–24 15 16 17 16 14 14 13 14 15 16 15 17

25–36 14 13 15 17 18 15 16 15 14 15 16 17

37–48 18 16 15 16 16 14 17 18 19 15 16 15

49–60 12 17 16 14 15 17 14 16 15 17 18 14

61–72 15 16 17 18 13 15 14 14 16 15 17 18

73–80 16 16 17 18 16 15 14 17

TABLE 3.4 | SAMPLE DATA FOR PRECISION MACHINING COMPANY

TUBE NUMBER

Sample 1 2 3 4 5 6 7 8

1 7.98 8.34 8.02 7.94 8.44 7.68 7.81 8.11

2 8.33 8.22 8.08 8.51 8.41 8.28 8.09 8.16

3 7.89 7.77 7.91 8.04 8.00 7.89 7.93 8.09

4 8.24 8.18 7.83 8.05 7.90 8.16 7.97 8.07

5 7.87 8.13 7.92 7.99 8.10 7.81 8.14 7.88

6 8.13 8.14 8.11 8.13 8.14 8.12 8.13 8.14

TABLE 3.3 | OUNCES OF CAULKING PER TUBE

8. The Digital Guardian Company issues policies that protect clients from downtime costs due to computer system failures. It is very important to process the policies quickly because long cycle times not only put the client at risk but could also lose business for Digital Guardian. Management is concerned that customer service is degrading because of long cycle times, measured in days. The following table contains the data from five samples, each sample consisting of eight random observations.

OBSERVATION (DAYS)

Sample 1 2 3 4 5 6 7 8

1 13 9 4 8 8 15 8 6

2 7 15 8 10 10 14 10 15

3 8 11 4 11 8 12 9 15

4 12 7 12 9 11 8 12 8

5 8 12 6 12 11 5 12 8

a. What is your estimate of the process average?

b. What is your estimate of the average range?

c. Construct an R-chart and an x-chart for this process. Are assignable causes present?

9. The Precision Machining Company makes handheld tools on an assembly line that produces one product every minute. On one of the products, the critical quality dimension is the diameter (measured in thousandths of an inch) of a hole bored in one of the assemblies. Management wants to detect any shift in the process average diameter from 0.015 inch. Management considers the variance in the process to be in control. Historically, the average range has been 0.002 inch, regardless of the process average. Design an x@chart to control this process, with a center line at 0.015 inch and the control limits set at three sigmas from the center line.

Management provided the results of 80 minutes of output from the production line, as shown in Table 3.4. During these 80 minutes, the process average changed once. All measurements are in thousandths of an inch.

a. Set up an x@chart with n = 4. The frequency should be sample four and then skip four. Thus, your first sample would be for minutes 1- 4, the second would be for minutes 9-12, and so on. When would you stop the process to check for a change in the process average?

b. Set up an x@chart with n = 8. The frequency should be sample eight and then skip four. When would you stop the process now? What can you say about the desirabil-ity of large samples on a frequent sampling interval?

10. Using the data from Problem 9, continue your analysis of sample size and frequency by trying the following plans.

a. Using the x@chart for n = 4, try the frequency sam-ple four, then skip eight. When would you stop the process in this case?

b. Using the x@chart for n = 8, try the frequency sam-ple eight, then skip eight. When would you consider the process to be out of control?

c. Using your results from parts (a) and (b), determine what trade-offs you would consider in choosing between them.

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QUALITY AND PERFORMANCE CHAPTER 3 155

11. Garcia’s Garage desires to create some colorful charts and graphs to illustrate how reliably its mechanics “get under the hood and fix the problem.” The historic average for the proportion of customers that return for the same repair within the 30-day warranty period is 0.10. Each month, Garcia tracks 100 customers to see whether they return for warranty repairs. The results are plotted as a proportion to report progress toward the goal. If the control limits are to be set at 2 standard deviations on either side of the goal, determine the control limits for this chart. In March, 8 of the 100 customers in the sample group returned for war-ranty repairs. Is the repair process in control?

12. As a hospital administrator of a large hospital, you are concerned with the absenteeism among nurses’ aides. The issue has been raised by registered nurses, who feel they often have to perform work normally done by their aides. To get the facts, absenteeism data were gathered for the past 3 weeks, which is considered a representa-tive period for future conditions. After taking random samples of 64 personnel files each day, the following data were produced:

Day Aides Absent Day Aides Absent

1 4 9 7

2 3 10 2

3 2 11 3

4 4 12 2

5 2 13 1

6 5 14 3

7 3 15 4

8 4

Because your assessment of absenteeism is likely to come under careful scrutiny, you would like a type I error of only 1 percent. You want to be sure to identify any instances of unusual absences. If some are present, you will have to explore them on behalf of the registered nurses.

a. Design a p-chart.

b. Based on your p-chart and the data from the past 3 weeks, what can you conclude about the absenteeism of nurses’ aides?

13. The IRS is concerned with improving the accuracy of tax information given by its representatives over the telephone. Previous studies involved asking a set of 25 questions of a large number of IRS telephone representatives to determine the proportion of correct responses. Historically, the average proportion of correct responses has been 72 percent. Recently, IRS representatives have been receiving more training. On April 26, the set of 25 tax questions were again asked of 20 randomly selected IRS telephone representatives. The numbers of correct answers were 18, 16, 19, 21, 20, 16, 21, 16, 17, 10, 25, 18, 25, 16, 20, 15, 23, 19, 21, and 19.

a. What are the upper and lower control limits for the appropriate p-chart for the IRS? Use z = 3.

b. Is the tax information process in statistical control?

14. Management at Webster, in Problem 7, is now con-cerned as to whether caulking tubes are being properly

capped. If a significant proportion of the tubes are not being sealed, Webster is placing its customers in a messy situation. Tubes are packaged in large boxes of 144. Several boxes are inspected, and the following numbers of leaking tubes are found:

Sample Tubes Sample Tubes Sample Tubes

1 3 8 6 15 5

2 5 9 4 16 0

3 3 10 9 17 2

4 4 11 2 18 6

5 2 12 6 19 2

6 4 13 5 20 1

7 2 14 1 Total 72

Calculate p-chart three-sigma control limits to assess whether the capping process is in statistical control.

15. Janice Sanders, CEO of Pine Crest Medical Clinic, is concerned over the number of times patients must wait more than 30 minutes beyond their scheduled appoint-ments. She asked her assistant to take random samples of 64 patients to see how many in each sample had to wait more than 30 minutes. Each instance is considered a defect in the clinic process. The table below contains the data for 15 samples.

Sample Number of Defects

1 5

2 2

3 1

4 3

5 1

6 5

7 2

8 3

9 6

10 3

11 9

12 9

13 5

14 2

15 3

a. Assuming Janice Sanders is willing to use three-sigma control limits, construct a p-chart.

b. Based on your p-chart and the data in the table, what can you conclude about the waiting time of the patients?

16. A cake manufacturing business based in London has 120 branches spread all over the city. All cakes are cus-tomized as per the needs of the customers, including

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156 PART 1 MANAGING PROCESSES

19. A textile manufacturer wants to set up a control chart for irregularities (e.g., oil stains, shop soil, loose threads, and tears) per 100 square yards of carpet. The following data were collected from a sample of twenty 100-square-yard pieces of carpet:

Sample 1 2 3 4 5 6 7 8 9 10

Irregularities 11 8 9 12 4 16 5 8 17 10

Sample 11 12 13 14 15 16 17 18 19 20

Irregularities 11 5 7 12 13 8 19 11 9 10

a. Using these data, set up a c-chart with z = 3.

b. Suppose that the next five samples had 15, 18, 12, 22, and 21 irregularities. What do you conclude?

20. A travel agency is concerned with the accuracy and appearance of itineraries prepared for its clients. Defects can include errors in times, airlines, flight numbers, prices, car rental information, lodging, charge card numbers, and reservation numbers, as well as typographical errors. As the possible number of errors is nearly infinite, the agency measures the number of errors that do occur. The current process results in an average of three errors per itinerary.

a. What are the two-sigma control limits for these defects?

b. A client scheduled a trip to Dallas. Her itinerary con-tained six errors. Interpret this information.

21. Furniture Mart makes bespoke and standard house-hold furniture such as table, chairs, and cots using a variety of material such as wood, steel, and plastic. Due to rapid expansion and heavy workload, the qual-ity department identified a number of defects. The

type of cake and choice of toppings. For quality control and consistency, cakes are manufactured at a central location and distributed to the branches. Cakes are randomly inspected for errors such as the writing on the cake, toppings, delivery location, and type of cake. Even a single error makes a cake defective. The follow-ing data were collected over the last 30 days to see how many cakes turned out defective. Each sample has 200 randomly selected cakes.

Sample Defects Sample Defects

1 20 16 20

2 14 17 12

3 8 18 11

4 14 19 15

5 15 20 15

6 11 21 20

7 13 22 8

8 18 23 9

9 14 24 11

10 12 25 11

11 9 26 14

12 17 27 8

13 13 28 10

14 15 29 11

15 14 30 9

a. What are the upper and lower control limits of a p-chart for the number of defective cakes? Use z = 3.

b. Is the process in statistical control?

17. The manager of the customer service department of Data Tech Credit Card Service Company is concerned about the number of defects produced by the billing process. Every day a random sample of 250 statements was inspected for errors regarding incorrect entries involving account numbers, transactions on the custom-er’s account, interest charges, and penalty charges. Any statement with one or more of these errors was consid-ered a defect. The study lasted 30 days and yielded the data in Table 3.5.

a. Construct a p-chart for the billing process.

b. Is there any nonrandom behavior in the billing pro-cess that would require management attention?

SamplesNumber of Late Planes in Sample of 300 Arrivals

and Departures

1–10 3 8 5 11 7 2 12 9 1 8

11–20 3 5 7 9 12 5 4 9 13 4

21–30 12 10 6 2 1 8 4 5 8 2

TABLE 3.6 | SAMPLE DATA FOR RED BARON AIRLINES

Samples Number of Errors in Sample of 250

1–10 3 8 5 11 7 1 12 9 0 8

11–20 3 5 7 9 11 3 2 9 13 4

21–30 12 10 6 2 1 7 10 5 8 4

TABLE 3.5 | SAMPLE DATA FOR DATA TECH CREDIT CARD SERVICE

18. Red Baron Airlines serves hundreds of cities each day, but competition is increasing from smaller companies affiliated with major carriers. One of the key competitive priorities is on-time arrivals and departures. Red Baron defines on time as any arrival or departure that takes place within 15 minutes of the scheduled time. To stay on top of the market, management set the high standard of 98 percent on-time performance. The operations department was put in charge of monitoring the performance of the airline. Each week, a random sample of 300 flight arrivals and departures was checked for schedule performance. Table 3.6 contains the numbers of arrivals and departures over the past 30 weeks that did not meet Red Baron’s defi-nition of on-time service. Using three-sigma control limits based on 98 percent on-time arrivals or departures, what can you tell the management about the quality of service? Can you identify any nonrandom behavior in the process? If so, what might cause the behavior?

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QUALITY AND PERFORMANCE CHAPTER 3 157

furniture could be flawed in various ways, including incorrect dimensions, uneven stitches in the upholstery, and surface not polished properly. A random examina-tion of 10 products generated the following results:

Product Number of Defects

1 7

2 5

3 8

4 0

5 5

6 12

7 6

8 9

9 2

10 5

a. Assuming that 10 observations are adequate for these purposes, determine the three-sigma control limits for defects per product.

b. Suppose that the next product has 13 defects. What can you say about the process now?

22. Matrix Enterprises manufactures molded plastic chairs of various sizes and colors using the blow molding pro-cess. However, due to improper maintenance, defects have been steadily increasing. The following results are obtained from a random examination of 10 samples:

Chair Defects

1 8

2 4

3 6

Chair Defects

4 0

5 8

6 10

7 9

8 3

9 7

10 5

a. Assuming 10 observations are adequate for this purpose, determine the three-sigma control limits for defects per chair.

b. What conclusions can be drawn about the process if the next output being examined has 15 defects?

23. Ferrous steel company manufactures steel plates for the construction industry. During fabrication, it faces various defects such as blisters, cracks, and porosity. Since there could be internal cracks, testing plates can be a challenge and hence it adopts nondestructive testing techniques through ultrasonic sounds. The following results are obtained from testing eight randomly selected samples:

Steel Plate Number Defects

Steel Plate Number Defects

1 5 5 3

2 6 6 0

3 9 7 9

4 4 8 19

Determine the c-chart two-sigma upper and lower con-trol limits for this process. Is the process in statistical control?

Process Capability24. The production manager at Sunny Soda, Inc., is interested

in tracking the quality of the company’s 12-ounce bottle filling line. The bottles must be filled within the tolerances set for this product because the dietary information on the label shows 12 ounces as the serving size. The design stan-dard for the product calls for a fill level of 12.00 { 0.10 ounces. The manager collected the following sample data (in fluid ounces per bottle) on the production process:

OBSERVATION

Sample 1 2 3 4

1 12.00 11.97 12.10 12.08

2 11.91 11.94 12.10 11.96

3 11.89 12.02 11.97 11.99

4 12.10 12.09 12.05 11.95

5 12.08 11.92 12.12 12.05

6 11.94 11.98 12.06 12.08

OBSERVATION

Sample 1 2 3 4

7 12.09 12.00 12.00 12.03

8 12.01 12.04 11.99 11.95

9 12.00 11.96 11.97 12.03

10 11.92 11.94 12.09 12.00

11 11.91 11.99 12.05 12.10

12 12.01 12.00 12.06 11.97

13 11.98 11.99 12.06 12.03

14 12.02 12.00 12.05 11.95

15 12.00 12.05 12.01 11.97

a. Are the process average and range in statistical control?

b. Is the process capable of meeting the design standard at four-sigma quality? Explain.

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158 PART 1 MANAGING PROCESSES

25. The McGranger Mortgage Company of Problem 6 made some changes to the process and undertook a process capability study. The following data were obtained for 15 samples of size 5. On the basis of individual observations, management estimated the process stan-dard deviation to be 4.21 (days) for use in the process capability analysis. The lower and upper specification limits (in days) for the mortgage process times were 5 and 25.

Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mean 11 12 8 16 13 12 17 16 13 14 17 9 15 14 9

Range 9 13 4 11 10 9 8 15 14 11 6 6 12 10 11

a. Calculate the process capability index and the pro-cess capability ratio values.

b. Suppose management would be happy with three-sigma performance. What conclusions is manage-ment likely to draw from the capability analysis? Can valid conclusions about the process be drawn from the analysis?

c. What remedial actions, if any, do you suggest that management take?

26. A manufacturer of glass panes received a new order from a customer to supply 18 millimeters thick glass planes with a tolerance of +/−2 millimeters. The manufacturer is concerned about the capability of the process to produce this glass. The following data were randomly collected during five shifts of the production process:

OBSERVATION (Thickness of Glass Panes in Millimeters)

Shift 1 2 3 4 5 6 7 8

1 18.05 17.76 18.10 19.50 16.50 16.00 15.80 18.20

2 17.90 19.70 18.50 18.30 19.20 16.50 16.00 19.00

3 17.80 16.70 19.20 18.42 17.76 16.60 18.30 17.50

4 16.34 17.83 16.00 15.90 17.80 18.80 19.20 19.50

5 19.55 19.78 18.75 19.45 17.87 16.65 17.32 18.45

Assume that the process is in statistical control. Is the process capable of achieving six-sigma quality levels with regard to the thickness of the glass panes? Explain.

27. A critical dimension of the service quality of a call center is the wait time of a caller to get to a sales representative. Periodically, random samples of three customer calls are measured for time. The results of the last four samples are in the following table:

Sample Time (Sec)

1 495 501 498

2 512 508 504

3 505 497 501

4 496 503 492

a. Assuming that management is willing to use three-sigma control limits, and using only the historical information contained in the four samples, show that the call center access time is in statistical control.

b. Suppose that the standard deviation of the process distribution is 5.77. If the specifications for the access time are 500 { 18 seconds, is the process capable? Why or why not? Assume three-sigma performance is desired.

28. An automatic lathe produces rollers for roller bearings, and statistical process control charts are used to monitor the process. The central line of the chart for the sample means is set at 8.50 and for the range at 0.31 mm. The process is in control, as established by samples of size 5. The upper and lower specifications for the diameter of the rollers are (8.50 + 0.25) and (8.50 – 0.25) mm, respectively.a. Calculate the control limits for the mean and range

charts.

b. If the standard deviation of the process distribution is estimated to be 0.13 mm, is the process capable of meeting specifications? Assume four-sigma perfor-mance is desired.

c. If the process is not capable, what percent of the output will fall outside the specification limits? (Hint: Use the normal distribution.)

29. Canine Gourmet Super Breath dog treats are sold in boxes labeled with a net weight of 12 ounces (340 grams) per box. Each box contains 8 individual 1.5-ounce packets. To reduce the chances of shorting the customer, product design specifications call for the packet-filling process average to be set at 43.5 grams so that the average net weight per box of 8 packets will be 348 grams. Tolerances are set for the box to weigh 348 { 12 grams. The standard deviation for the packet-filling process is 1.01 grams. The target process capability ratio is 1.33. One day, the packet-filling process average weight drifts down to 43.0 grams. Is the packaging process capable? Is an adjustment needed?

30. Return to Problem 4 relating to Aspen Plastics pro-ducing plastic bottles to customer order. Suppose that the specification for the bottleneck diameter is 0.600 { 0.050 and the population standard deviation is 0.013 inch.

a. What is the process capability index?

b. What is the process capability ratio?

c. If the firm is seeking four-sigma performance, is the process capable of producing the bottle?

31. Marodin Brothers, Inc., is conducting a study to assess the capability of its 150-gram bar soap production line. A critical quality measure is the weight of the soap bars after stamping. The lower and upper specification limits are 162 and 170 grams, respectively. As a part of an ini-tial capability study, 25 samples of size 5 were collected by the quality assurance group and the observations in Table 3.7 were recorded.

After analyzing the data by using statistical control charts, the quality assurance group calculated the process capabil-ity ratio, Cp, and the process capability index, Cpk. It then decided to improve the stamping process, especially the feeder mechanism. After making all the changes that were

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QUALITY AND PERFORMANCE CHAPTER 3 159

deemed necessary, 18 additional samples were collected. The summary data FOR these samples are

x = 163 grams

R = 2.326 grams

s = 1 gram

All sample observations were within the control chart limits. With the new data, the quality assurance group recalculated the process capability measures. It was pleased with the improved Cp but felt that the process should be centered at 166 grams to ensure that every-thing was in order. Its decision concluded the study.

Sample OBS.1 OBS.2 OBS.3 OBS.4 OBS.5

1 167.0 159.6 161.6 164.0 165.3

2 156.2 159.5 161.7 164.0 165.3

3 167.0 162.9 162.9 164.0 165.4

4 167.0 159.6 163.7 164.1 165.4

5 156.3 160.0 162.9 164.1 165.5

6 164.0 164.2 163.0 164.2 163.9

7 161.3 163.0 164.2 157.0 160.6

8 163.1 164.2 156.9 160.1 163.1

9 164.3 157.0 161.2 163.2 164.4

10 156.9 161.0 163.2 164.3 157.3

11 161.0 163.3 164.4 157.6 160.6

12 163.3 164.5 158.4 160.1 163.3

13 158.2 161.3 163.5 164.6 158.7

14 161.5 163.5 164.7 158.6 162.5

15 163.6 164.8 158.0 162.4 163.6

16 164.5 158.5 160.3 163.4 164.6

17 164.9 157.9 162.3 163.7 165.1

18 155.0 162.2 163.7 164.8 159.6

19 162.1 163.9 165.1 159.3 162.0

20 165.2 159.1 161.6 163.9 165.2

21 164.9 165.1 159.9 162.0 163.7

22 167.6 165.6 165.6 156.7 165.7

23 167.7 165.8 165.9 156.9 165.9

24 166.0 166.0 165.6 165.6 165.5

25 163.7 163.7 165.6 165.6 166.2

TABLE 3.7 | SAMPLE DATA FOR MARODIN BROTHERS, INC.

a. Draw the control charts for the data obtained in the initial study and verify that the process was in statis-tical control.

b. What were the values obtained by the group for Cp and Cpk for the initial capability study? Comment on your findings and explain why further improvements were necessary.

c. What are the Cp and Cpk after the improvements? Comment on your findings, indicating why the group decided to change the centering of the process.

d. What are the Cp and Cpk if the process were centered at 166? Comment on your findings.

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160 PART 1 MANAGING PROCESSES

This Active Model is available online. It allows you to see the effects of sample size and z-values on control charts.

QUESTIONS

1. Has the booking process been in statistical control?

2. Suppose we use a 95 percent p-chart. How do the upper and lower control limits change? What are your conclu-sions about the booking process?

3. Suppose that the sample size is reduced to 2,000 instead of 2,500. How does this affect the chart?

4. What happens to the chart as we reduce the z-value?

5. What happens to the chart as we reduce the confidence level?

Active Model Exercise

p-Chart Using Data from Example 3.3

EXPERIENTIAL LEARNING 3.1 Statistical Process Control with a Coin CatapultExercise A: Control Charts for Variables

Materials1 ruler1 pen or pencil1 coin (a quarter will do nicely)1 yardstickAn exercise worksheetAccess to a calculator

TasksDivide into teams of two to four. If four people are on a team,

one person holds the yardstick and observes the action,

one person adjusts the catapult and launches the coin,

one person observes the maximum height for each trial, and

one person records the results.

If teams of fewer than four are formed, provide a support for the yardstick and combine the other tasks as appropriate.

PracticeTo catapult the coin, put a pen or pencil under the 6-inch mark of the ruler. Put the coin over the 11-inch mark. Press both ends of the ruler down as far as they will go. Let the end that holds the coin snap up, catapulting the coin into the air. The person holding the yardstick should place the stick so that it is adjacent to, but does not interfere with, the trajectory of the coin. To observe the maximum height reached by the coin, the observer should stand back with his or her eye at about the same level as the top of the coin’s trajectory. Practice until each person is comfortable with his or her role. The person operating the catapult should be sure that the pen or pencil fulcrum has not moved between shots and that the launch is done as consistently as possible.

Step 1. Gather data. Take four samples of five observations (launches) each. Record the maximum height reached by the coin in the first

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QUALITY AND PERFORMANCE CHAPTER 3 161

data table on the worksheet. When you have finished, determine the mean and range for each sample, and compute the mean of the means x and the mean of the ranges R .

Step 2. Develop an R-chart. Using the data gathered and the appropriate D3 and D4 values, compute the upper and lower three-sigma control limits for the range. Enter these values and plot the range for each of the four samples on the range chart on the worksheet. Be sure to indicate an appropriate scale for range on the y-axis.

Step 3. Develop an x @chart. Now, using the data gathered and the appropri-ate value for A2, compute the upper and lower three-sigma control limits for the sample means. Enter these values and plot the mean for each of the four samples on the x@chart on the worksheet. Again, indicate an appropriate scale for the y-axis.

Step 4. Observe the process. Once a control chart has been established for a process, it is used to monitor the process and to identify when it is not running normally. Collect two more samples of five trials each, as you did to collect the first set of data. Plot the range and the sample mean on the charts you constructed on the worksheet each time you collect a sample. What have you observed that affects the process? Does the chart indicate that the process is operating the way it did when you first collected data?

Step 5. Observe a changed process. Now change something (for instance, move the pencil out to the 8-inch mark). Collect data for samples 7 and 8. Plot the range and the sample mean on the charts you constructed on the worksheet as you complete each sample. Can you detect a change in the process from your control chart? If the process has changed, how sure are you that this change is real and not just due to the particular sample you chose?

Exercise B: Control Charts for AttributesMaterials

1 ruler1 pen or pencil1 coin (a quarter will do nicely)1 paper or plastic cup (with a 4-inch mouth)

An exercise worksheetAccess to a calculator

TasksDivide into teams of two or three. If three people are on a team,one person adjusts the catapult and launches the coin,one person observes the results and fetches the coin, andone person records the results.If teams of two are formed, combine the tasks as appropriate.

PracticeThe object is to flip a coin into a cup using a ruler. To catapult the coin, put a pen or pencil under the 6-inch mark of the ruler.

Put a coin over the 11-inch mark and let its weight hold that end of the ruler on the tabletop. Strike the raised end of the ruler with your hand to flip the coin into the air. Position a cup at the place where the coin lands so that on the next flip, the coin will land inside. You will have to practice several times until you find out how hard to hit the ruler and the best position for the cup. Be sure that the pen or pencil fulcrum has not moved between shots and that the launch is done as consistently as possible.

Step 1. Gather data. Try to catapult the coin into the cup 10 times for each sample. Record each trial in the data table on the worksheet as a hit (H) when the coin lands inside or a miss (M) when it does not. The proportion of misses will be the number of misses divided by the sample size, n, in this case 10. A miss is a “defect,” so the propor-tion of misses is the proportion defective, p.

Step 2. Develop a p-chart. Compute the upper and lower three-sigma control limits for the average fraction defective. Plot these values and the mean for each of the four samples on the p-chart on the worksheet.

Step 3. Observe the process. Once a chart has been established for a pro-cess, it is used to monitor the process and to identify abnormal behavior. Exchange tasks so that someone else is catapulting the coin. After several practice launches, take four more samples of 10. Plot the proportion defective for this person’s output. Is the process still in control? If it is not, how sure are you that it is out of control? Can you determine the control limits for a 95 percent confidence level? With these limits, was your revised process still in control?4

4Source: The basis for Exercise A was written by J. Christopher Sandvig, Western Washington University, as a variation of the “Catapulting Coins” exercise from Games and Exercises for Operations Management by Janelle Heinke and Larry Meile (Prentice Hall, 1995). Given these foundations, Larry Meile of Boston College wrote Exercise A. He also wrote Exercise B as a new extension. Reprinted by permission of Larry Meile.

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162 PART 1 MANAGING PROCESSES

VIDEO CASE Quality at Axon

Protect life. Protect truth. That’s the mission of Axon, the company that pro-duces public safety technologies such as Taser electrical smart weapons and body cameras for law enforcement around the globe. In business since 1993, the company manufactures three weapons lines inside its high-tech head-quarters in Scottsdale, Arizona. Ninety-nine percent of its customers are in law enforcement, military, correctional, and professional security organizations.

Designing and manufacturing smart weapons technologies requires precise engineering and production processes that can ensure both accuracy and operational safety for its organizational customers and personal protection buyers. This attention to detail is evidenced in the company’s commitment to quality, and can be seen in the way the manufacturing operation is organized. Axon’s manufacturing operations are ISO 9001:2008 certified.

All finished goods are produced to stock, so that the company can be responsive when an order is received. Sales history data help dictate which items to make to stock, and which could sit in inventory between 6 and 12 weeks before being sold. Most employees have undergone voluntary expo-sure to the weapons, including the founders.

Axon’s work cells are arranged by product. At the start of the week, each cell is given a “production order” document that lists the bill of materials for the finished goods that cell must produce during the week. The production order is released by Axon’s Enterprise Resource Planning (ERP) system, with raw materials required for assembly pulled and staged at each cell weekly. In addition to supporting the informational needs of all the functional areas of a firm, ERP systems support the manufacture of a firm’s products by scheduling the fabrication of components and the arrival of purchased materials in support of the overall production plan.

Axon’s attention to quality is embedded throughout its manufacturing processes. Raw materials are tested and inspected for quality conformance at the supplier to be certain no faulty components are shipped. Circuit boards, which are assembled domestically, are each tested prior to shipment, and then acceptance sampling at Axon’s receiving dock confirms shipment con-formance. The same process occurs for the supplier of injection molded com-ponents, such as weapons casings. Testing includes functionality checks, drop tests to ensure the product can withstand being dropped, and temperature checks to make sure the weapons will work between a temperature range of – 20 degrees Celsius and + 50 degrees Celsius. When finished goods are ready, Axon performs a final quality assurance check on 100% of goods to ensure everything functions properly prior to shipping to the customer. All goods come with a 1-year warranty.

In 2009, 25 company managers from engineering, manufacturing, R&D, and quality assurance enrolled in a Six Sigma Green Belt training program offered at a nearby university. While the coursework was meaningful, Axon faced intense pressure to bring new products to market, due to which man-agement focus on implementing Six Sigma principles waned. It wasn’t until 2011 that Axon would again revisit its Six Sigma journey with renewed interest. Management broadened the employee base to be trained, including customer service and marketing divisions, and chose to incorporate more stringent Six Sigma methodologies into its training. Six Black Belts emerged with projects targeted to strengthen operations at the company. One such project, initiated by Vice President of Manufacturing Bill Denzer, took aim at the softer side of production: its employees. Bill saw a need to empower manufacturing line employees with data so that they could take greater ownership of what was occurring within their environments. Although Axon collected manufactur-ing data daily for continuous improvement purposes prior to 2011, line level employees weren’t involved in the analysis and problem solving required to rapidly change or fix issues. The manufacturing engineering group reviewed the data only after problems emerged, taking some time to investigate and resolve even as production tried to continue.

Bill’s project sought to engage manufacturing engineering in the automa-tion of test data collection to develop baselines for processes and establish upper and lower control limits. Line workers were given explicit parameters for processes, and they immediately took ownership of those processes. As a result, it quickly became evident when something in the work cell was trending out of control so the issue could be resolved within hours. A formal escalation process further ensured that the right individuals were notified to get action.

In 2013, Axon installed computer monitors above each work cell so that all manufacturing employees could see the data related to how they were doing. The data include scrap dollars as a percentage of total production, pro-cess yield (units produced), average labor cost per unit compared to expected labor cost, average material costs per unit compared to expected material costs, daily/monthly/quarterly production output compared to planned output, throughput times compared to standards, and more.

To close the loop on data collection and performance analysis, Axon holds daily meetings at the start of each shift to review the metrics. In addition, the Axon Continuing Improvement program, or TCI, was created. This program generates over 15 suggestions weekly from employees across all areas of the manufacturing process. Bulletin boards in each work cell make it easy to write up issues, and the visibility of the suggestions gets immediate attention. Further, anyone can stop production if a problem is detected, and issues get resolved within hours instead of days or weeks, leading to reduced downtime and quality problems.

QUESTIONS1. Implementing Six Sigma programs takes considerable time and com-

mitment from an organization. Evaluate Axon’s efforts with regard to management commitment, measurement systems to track progress, tough goal setting, education, communication, and customer priorities.

2. How might Axon’s commitment to employee engagement help the com-pany avoid the four costs of poor process performance and quality (pre-vention, appraisal, internal failure, external failure)?

3. Describe Axon’s total quality management approach as it relates to customer satisfaction, employee involvement, and continuous improvement.

The AXON bodycams on their charge and download cradle. Body worn video cameras are being introduced into the South Wales Police force as part of operational equipment and will be rolled out over the next few months.

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163

LEARNING OBJECTIVES After reading this chapter, you should be able to:

LEAN SYSTEMS 4

Nike, Inc.

Nike, Inc., is a global designer, manufacturer, and distributor of athletic apparel, footwear, and sports equipment with sales in excess of $36 billion in 2018. Named after the Greek goddess of victory, Nike is one of the most

4.1 Describe how lean systems can facilitate the continuous improvement of processes.

4.2 Identify the strategic supply chain and process characteristics of lean systems.

4.3 Explain the differences between one-worker, multiple-machine (OWMM) and group technology (GT) approaches to lean system layouts.

4.4 Understand Kanban systems for creating a production schedule in a lean system.

4.5 Understand value stream mapping and its role in waste reduction.

4.6 Explain the implementation issues associated with the application of lean systems.

Shoppers and visitors outside the Nike House of Innovation flagship store on Fifth avenue in New York, USA-December 19, 2019. Nike is an American Company that designs, manu-factures, markets, and sells athletic shoes and apparel.rb

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164 PART 1 MANAGING PROCESSES

valuable brands, with well-recognized trademarks and logos such as “Just Do It” and “Swoosh.” While very successful now, Nike had a major image problem and falling customer demand in the 1990s centered on poor wages, forced overtime, and dismal working conditions in its factories. Over a two-decade journey, Nike engineered its turnaround by dramatically transforming its contract factories into following the lean principles and using them to affirm its commitment to corporate social responsibility.

Nike started by streamlining its supply chain and reducing the number of contract factories located across India, Philippines, Vietnam, and South America, from 910 to 785. Employing over one million people and manufacturing half a million unique products, Nike built a culture of empowerment in these factories that revolved around continuous improvement and respect for people. Managers responsible for lean transformation were sent to Nike’s training facility in Sri Lanka. Workers were increasingly seen as a key source of innovation and improvement, and were encouraged to shift to higher and diverse sets of skills while adopting newer tools and techniques. To deliver high-quality products at low cost, Nike had to not only improve the working conditions but also reduce waste and promote more efficient use of water. Several factories also had to change the physical layout of their shop floor.

To ensure compliance and attainment of uniformly high standards, Nike developed a sourcing and manufacturing sustainability index for its contract manufacturers. This manufacturing index can be used to assess each factory in terms of its lean capabilities, including quality, just in time, operational stability, and culture of empowerment. Other parts of the Manufacturing Index are Labor and Human Resource Management, Health and Safety practices, Energy and Carbon usage, and Environmental Sustainability. World-class factories are rated as gold, while bronze level reflects compliance with the standards that Nike expects from all its factories. By the end of 2015, 85% of the Nike factories had attained the bronze standard. This change was also associated with a 15% reduction in noncompliance, with labor standards measured by wages, benefits, and time off.

The benefits of a leaner supply chain resulted in lower overtime, elimination of late orders and sudden changes in material requirements, improvement in productivity by 10 to 20 percent, lowering of defect rates by 50 percent, and reduction of delivery times by 20 to 40 percent. Nike is now rated as one of the most lean manufacturers in the world. By pursuing systematic change through lean transformation, Nike turned its public relations woes into higher brand value, while at the same time also becoming an industry leader in sustainability and corporate social responsibility.1

1Sources: Lorenzo Del Malmor, “From Child Labor to Social Responsible Lean Innovation,” Lean Six Sigma Belgium, https://leansixsigmabelgium.com/blog/lean-innovation-nike/ (July 28, 2020); “Nike Gears up for a Manufacturing Revolution,” Manufacturing, https://www.manufacturingglobal.com/lean-manufacturing/nike-gears-manufacturing-revolution (June 10, 2020); https://theleadershipnetwork.com/article/how-nike-used-lean-manufacturing (October 31, 2016); https://en.wikipedia.org/wiki/Nike,_Inc. (July 28, 2020).

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Nike, Inc., is a learning organization and an excellent example of an approach for designing manufacturing and supply chains known as lean systems, which allow organizations to continu-ously improve their operations and spread the lessons learned across the entire corporation. Lean systems are operations systems that maximize the value added by each of a company’s activities by removing waste and delays from them. They encompass the company’s operations strategy, process design, quality management, constraint management, layout design, supply chain design, and technology and inventory management and can be used by both service and manufacturing firms. Like a manufacturer, each service business takes an order from a customer, delivers the service, and then collects revenue. Each service business purchases services or items, receives and pays for them, and hires and pays employees. Each of these activities bears con-siderable similarity to those in manufacturing firms. They also typically contain huge amounts of waste.

Lean systems affect a firm’s internal linkages between its core and supporting processes and its external linkages with its customers and suppliers. The design of supply chains using the lean systems approach is important to various departments and functional areas across the organization. Marketing relies on lean systems to deliver high-quality services or products on time and at reasonable prices. Human resources must put in place the right incentive systems that reward teamwork and also recruit, train, and evaluate the employees needed to create a flexible workforce that can successfully operate a lean system. Engineering must design products that use more common parts, so that fewer setups are required and focused factories can be used. Operations is responsible for maintaining close ties with suppliers, designing the lean system, and using it in the production of services or goods. Accounting must adjust its billing and cost accounting practices to provide the support needed to manage lean systems. Finally, top management must embrace the lean philosophy and make it a part of organizational culture and learning, as is done by Nike and also by Aldi, a discount supermarket chain with headquarters in Germany and over 10,000 stores worldwide in 20 countries, including Australia, Europe, Great Britain, Ireland, and the United States. Its empha-sis on core values of simplicity, consistency, and corporate responsibility are closely tied to the principles of lean production, which Aldi uses to keep costs down in all areas, provide custom-ers more value for their money, and remain more competitive in a business with razor-thin mar-gins. Aldi’s lean philosophy extends into the supply chain as well. Up to 60 percent of its fruits and vegetables are sourced locally to save on transportation costs and time. As part of its inventory reduction policies, suppliers are not allowed to hold more than 1 month of normal orders and requirements of Aldi’s private label products in inventory at any given point of time, unless Aldi submits a written authorization for a temporary or permanent change in suppliers’ inventory levels. Consequently, Aldi’s products can be as much as 30 percent cheaper than its competitors in some cases. Due to its relentless focus on lean principles, it is no wonder that Aldi is a clear leader in prices among leading grocery brands.

Thus far in the text, we have discussed many ways to improve manufacturing and service pro-cesses. We take that further in this chapter by showing how process improvement techniques can be used to make a firm lean by first discuss-ing the continuous improvement aspect of lean systems, followed by a discussion of the charac-teristics of lean systems, and the design of layouts needed to achieve these characteristics. We also address different types of lean systems used in practice and some of the implementation issues that companies face.

lean systems

Operations systems that maxi-mize the value added by each of a company’s activities by remov-ing waste and delays from them.

Using Operations to Create Value

Part 1

Managing Processes

Designing andoperating processes inthe firm

Managing Supply Chains

Forecasting demands anddeveloping inventory plansand operating schedules

Designing an integrated andsustainable supply chain of

connected processes between firms

Managing Customer Demand

Managing Processes

Project Management

Process Strategy and AnalysisQuality and Performance

Capacity PlanningConstraint Management

Lean Systems

Aldi Store grand opening on June 16, 2016 in Simi Valley, California. Aldi is a low price grocery outlet that is rapidly expanding in the USA.

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166 PART 1 MANAGING PROCESSES

Continuous Improvement Using a Lean Systems ApproachOne of the most popular systems that incorporate the generic elements of lean systems is the just-in-time (JIT) system. According to Taiichi Ohno, one of the earlier pioneers at Toyota Corporation, the just-in-time (JIT) system is a key foundation of lean systems, and represents a collection of practices that eliminate waste, or muda, by cutting excess capacity or inventory and removing nonvalue-added activities. Even though traditionally only seven types of waste have been dis-cussed in the literature,2 based on current management thinking we have added an eighth type that focuses on underutilization of employees. Table 4.1 shows the eight types of waste that often occur in firms in an interrelated fashion and that must be significantly reduced or eliminated in implementing lean systems.

2David McBride, “The Seven Manufacturing Wastes,” August 29, 2003, http://www.emsstrategies.com/dm090203article2.html.

Waste Definition

1. Overproduction Manufacturing an item before it is needed, making it difficult to detect defects and creating excessive lead times and inventory.

2. Inappropriate Processing Using expensive high-precision equipment when simpler machines would suffice. It leads to overutilization of expensive capital assets. Investment in smaller flexible equipment, immaculately maintained older machines, and combining process steps where appropriate reduce the waste associated with inappropriate processing.

3. Waiting Unbalanced workstations make operators lose time, because if a process step takes longer than the next, then the operators will either stand idly waiting, or they will be performing their tasks at a speed that makes it appear that they have work to complete. Operators can also be waiting when a previous process step breaks down, has quality issues, lacks certain parts or information, or has a long changeover.

4. Transportation Excessive movement and material handling of product between processes, which can cause damage and deterioration of product quality without adding any significant customer value.

5. Motion Unnecessary effort related to the ergonomics of bending, stretching, reaching, lifting, and walking. Jobs with excessive motion should be redesigned.

6. Inventory Excess inventory hides problems on the shop floor, consumes space, increases lead times, and inhibits communication. Work-in-process inventory is a direct result of overproduction and waiting.

7. Defects Quality defects result in rework and scrap and add wasteful costs to the system in the form of lost capacity, rescheduling effort, increased inspection, and loss of customer goodwill.

8. Underutilization of Employees Failure of the firm to learn from and capitalize on its employees’ knowledge and creativity impedes long-term efforts to eliminate waste.

TABLE 4.1 | THE EIGHT TYPES OF WASTE, OR MUDA

M A N A G E R I A L CHALLENGE

Oak Grove Health is a major hospital system with a level 1 trauma center that provides the highest level of trauma care to critically ill or injured patients. In an ever changing health care landscape following the passage of the Affordable Care Act in March 2010, there has been a renewed focus on patient care and satisfaction coupled with a focus on cost reduction and efficiencies. In a recent upper management meet-ing, CEO Don Ramsey discussed Oak Grove’s financial performance and noted that while patient care metrics were holding steady, cost per patient was rising far faster than at similar benchmark hospitals. In addition, revenues had declined in spite of high patient demand and backlogs. He charged Susan Richardson, the VP of finance, to take a closer look at this issue and identify specific opportunities where cost savings can be achieved without compromising patient care or investments in new technologies and nurses’ training, both of which are considered essential for Oak Grove to remain competitive.

Finance

The goals of a lean system are thus to eliminate these eight types of waste, produce services and products only as needed, and to continuously improve the value-added benefits of operations. Identifying and removing waste can help an organization in multiple ways, while an inability to do so can hurt its financial performance, as illustrated by the following Managerial Challenge in a health care setting.

just-in-time (JIT) system

The JIT system is a key founda-tion of a lean system, and rep-resents a collection of practices that eliminate waste, or muda, by cutting excess capacity or inventory and removing nonvalue-added activities.

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LEAN SYSTEMS CHAPTER 4 167

Susan formed three task forces to better understand and eliminate waste from staffing, hospital operations, and administrative services, respectively. Albert Pinto had the most complex assignment as the leader of the hospital operations task force. He decided to focus initially on the surgical unit, hoping to apply the lessons learned there to other major units within hospital operations. He tracked patient flows through the different stages: the patient being registered and scheduled at the front desk, pre-operative care, the actual surgery itself, recovery in an intensive care unit (ICU), further stay in a general medical unit, and discharge. Variability in the arrival rates of patients and uneven utilization of facilities in each of these stages resulted in longer wait times, which in turn drove higher operating costs because reimbursements were based on curing the specific patient condition and not on patient length of stay. After collecting additional data, he also found that due to the limited number of beds in the ICU and the shortage of nurses, patients could not be moved out as quickly, and this backed up the operating rooms. As a result, surgeons sat idle and performed a lower number of procedures in a given month than the actual demand, leading to loss of both revenue and patient experience.

Four years ago, Oak Grove had acquired Piedmont Hospital located 3 miles away, and had already completed the operational integration. Yet, Albert learned that the automated carousel system used for storing and dispensing expensive surgery and anesthesia-related drugs operated indepen-dently at each hospital instead of working in a coordinated fashion. This resulted in large financially wasteful investments at both hospitals, when the drugs could be more readily shared between them, given the locational proximity. Depending upon the patient mix and caseload, independent procure-ment and storage of drugs at each location led to shortages at one hospital and excess availability at the other. Unfortunately, further analysis showed that this problem extended to other units such as cardiology, neurology, pediatrics, and oncology as well, leading Albert to wonder if there were interconnected systems of wasteful practices across multiple units. He clearly needed to drill deeper to learn the root causes behind different types of wastes that were occurring in Oak Grove’s hospital operations, and how to identify and eliminate them. Concepts and techniques illustrated in the rest of this chapter can help Albert drive the kind of financial savings that Susan had requested him to find and implement.

By spotlighting areas that need improvement, lean systems lead to continuous improvement in quality and productivity. The Japanese term for this approach to pro-cess improvement is kaizen. The key to kaizen is the understanding that excess capacity or inventory hides underlying problems with the processes that produce a service or product. Lean systems provide the mechanism for management to reveal the problems by systematically lowering capacities or inventories until the problems are exposed. For example, Figure 4.1 characterizes the philosophy behind continuous improvement with lean systems. In services, the water surface represents service system capacity, such as staff levels. In manufacturing, the water surface represents product and component inventory levels. The rocks represent problems encoun-tered in the fulfillment of services or products. When the water surface is high enough, the boat passes over the rocks because the high level of capacity or inventory covers up problems. As capacity or inventory shrinks, rocks are exposed. Ultimately, the boat will hit a rock if the water surface falls far enough. Through lean systems, workers, supervisors, engineers, and analysts apply methods for continuous improvement to demolish the exposed rock. The coordination required to achieve smooth material flows in lean systems identifies problems in time for corrective action to be taken.

Maintaining low inventories, periodically stressing the system to identify problems, and focusing on the elements of the lean system lie at the heart of continuous improvement. For example, the plant may periodically cut its safety stocks almost to zero. The problems at the plant are exposed, recorded, and later assigned to employees as improvement projects. After improvements are made, inventories are permanently cut to the new level. Many firms use this trial-and-error process to develop more efficient manufacturing operations. In addition, work-ers using special presses often fabricate parts on the assembly line in exactly the quantities

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168 PART 1 MANAGING PROCESSES

needed. Service processes, such as scheduling, billing, order taking, accounting, and financial planning, can be improved with lean systems, too. In service operations, a common approach used by managers is to place stress on the sys-tem by reducing the number of employees doing a particular activity or series of activities until the process begins to slow or come to a halt. The problems can be identified, and ways for overcoming them explored. Other kaizen tac-tics can be used as well. Eliminating the prob-lem of too much scrap might require improving the firm’s work processes, providing employees with additional training, or finding higher qual-ity suppliers. Eliminating capacity imbalances might involve revising the firm’s master pro-duction schedule and improving the flexibility of its workforce. Irrespective of which problem is solved, there are always new ones that can be addressed to enhance system performance.

Often, continuous improvement occurs with the ongoing involvement and input of new ideas from employees, who play an important role in implementing the JIT philosophy. In one year alone, about 740,000 corporate-wide improve-ment suggestions were received at Toyota. A large majority of them got implemented, and employees making those suggestions received rewards rang-ing from 500 yen (about $5) to upwards of 50,000 yen (about $500) depending upon their bottom-line impact.

Strategic Characteristics of Lean SystemsThe philosophy of lean systems, applicable at the process level, is also applicable at the supply chain level. Factors, both within and outside the firm, arising from supply chain and process consider-ations that have an important impact in creating and implementing lean systems, are discussed next in this section.

Supply Chain Considerations in Lean SystemsIn this section, we discuss the two salient characteristics of lean systems that are related to creating and managing material flows in a supply chain: close supplier ties and small lot sizes.

Close Supplier Ties Because lean systems operate with low levels of capacity slack or inven-tory, firms that use them need to have a close relationship with their suppliers. Supplies must be shipped frequently, have short lead times, arrive on schedule, and be of high quality. A contract might even require a supplier to deliver goods to a facility as often as several times per day.

The lean system philosophy is to look for ways to improve efficiency and reduce inventories throughout the supply chain. Close cooperation between companies and their suppliers can be a win–win situation for everyone. Better communication of component requirements, for example, enables more efficient inventory planning and delivery scheduling by suppliers, thereby improv-ing supplier profit margins. Customers can then negotiate lower component prices. Close supplier relations cannot be established and maintained if companies view their suppliers as adversaries whenever contracts are negotiated. Rather, they should consider suppliers to be partners in a venture, wherein both parties have an interest in maintaining a long-term, profitable relationship. Consequently, one of the first actions undertaken when a lean system is implemented is to pare down the number of suppliers, and make sure they are located in close geographic proximity to promote strong partnerships and better synchronize product flows.

▲ FIGURE 4.1Continuous Improvement with Lean Systems

Material quality problems

Longsetups

Poortraining

Breakdowns

Material handling

Water = Inventory

Traditional systems use inventory (water) to bu�er the process from problems (rocks) that causedisruption.

The role of inventory in Traditional and JIT systems: The water and the rocks metaphor

Materialquality

problemsLong

setups

Poor training

Breakdowns

Materialhandling

JIT systems view inventory as waste and work to lower inventory levels to expose and correct the problems (rocks) that cause disruption. However, the problems that arise must be corrected quickly. Otherwise, without the decoupling inventory, the process will flounder.

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A particularly close form of supplier partnerships through lean systems is the JIT II system, which was conceived and implemented by Bose Corporation, a producer of high-quality profes-sional sound and speaker systems. In a JIT II system, also called vendor-managed inventories, the supplier is brought into the plant to be an active member of the purchasing office of the customer. The in-plant representative is onsite full time at the supplier’s expense and is empowered to plan and schedule the replenishment of materials from the supplier. Thus, JIT II fosters extremely close interaction with suppliers. The qualifications for a supplier to be included in the program are stringent.

In general, JIT II can offer benefits to both buyers and suppliers because it provides the orga-nizational structure needed to improve supplier coordination by integrating the logistics, produc-tion, and purchasing processes together. We have more to say about supplier relationships and vendor-managed inventories in Chapter 14, “Supply Chain Integration.”

Small Lot Sizes Lean systems use lot sizes that are as small as possible. A lot is a quantity of items that are processed together. Small lots have the advantage of reducing the average level of inventory relative to large lots. Small lots pass through the system faster than large lots, since they do not keep materials waiting. In addition, if any defective items are discovered, large lots cause longer delays because the entire lot must be examined to find all the items that need rework. Finally, small lots help achieve a uniform workload on the system and prevent overpro-duction. Large lots consume large chunks of capacity at workstations and, therefore, complicate scheduling. Small lots can be juggled more effectively, enabling schedulers to efficiently utilize capacities.

Although small lots are beneficial to operations, they have the disadvantage of increased setup frequency. A setup is the group of activities needed to change or readjust a process between successive lots of items, sometimes referred to as a changeover. This changeover in itself is a process that can be made more efficient. Setups involve trial runs, and the material waste can be substantial as the machines are fine-tuned for the new parts. Typically, a setup takes the same time regardless of the size of the lot. Consequently, many small lots, in lieu of several large lots, may result in waste in the form of idle employees, equipment, and materials. Setup times must be brief to realize the benefits of small-lot production.

Achieving brief setup times often requires close cooperation among engineering, manage-ment, and labor. For example, changing dies on large presses to form automobile parts from sheet metal can take 3 to 4 hours. At Honda’s Marysville, Ohio, plant—where four stamping lines stamp all the exterior and major interior body panels for Accord production—teams worked on ways to reduce the changeover time for the massive dies. As a result, a complete change of dies for a giant 2,400-ton press now takes less than 8 minutes. The goal of single-digit setup means having setup times of less than 10 minutes. Some techniques used to reduce setup times at the Marysville plant include using conveyors for die storage, moving large dies with cranes, simplifying dies, enacting machine controls, using microcomputers to automatically feed and position work, and preparing for changeovers while a job currently in production is still being processed.

Process Considerations in Lean SystemsIn this section, we discuss the following charac-teristics of lean systems: pull method of work-flow, quality at the source, uniform workstation loads, standardized components and work meth-ods, flexible workforce, automation, Five S (5S) practices, and total productive (or preventive) maintenance (TPM).

Pull Method of Workflow Managers have a choice as to the nature of the material flows in a process or supply chain. Most firms using lean operations use the pull method, in which customer demand activates the production of a good or service. In contrast, a method often used in conventional systems that do not emphasize lean systems is the push method, which involves using forecasts of demand and producing the item before the customer orders it. To differen-tiate between these two methods, let us use a service example that involves a favorite pastime, eating.

lot

A quantity of items that are processed together.

single-digit setup

The goal of having a setup time of less than 10 minutes.

pull method

A method in which customer demand activates production of the service or item.

push method

A method in which production of the item begins in advance of customer needs.

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A diner at a Chinese restaurant buffet. Because the food items must be prepared in advance, the restaurant uses a push method of workflow.

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For an illustration of the pull method, consider a five-star restaurant in which you are seated at a table and offered a menu of exquisite dishes, appetizers, soups, salads, and desserts. You can choose from filet mignon, porterhouse steak, yellow fin tuna, eggplant parmesan, grouper, and lamb chops. Your choice of several salads is prepared at your table. Although some appetizers, soups, and desserts can be prepared in advance and brought to temperature just before serving, the main course and salads cannot. Your order for the salad and the main course signals the chef to begin preparing your specific requests. For these items, the restaurant is using the pull method. Firms using the pull method must be able to fulfill the customer’s demands within an acceptable amount of time.

For an understanding of the push method, consider a cafeteria on a busy downtown corner. Dur-ing the busy periods around 12 p.m. and 5 p.m. lines develop, with hungry patrons eager to eat and then move on to other activities. The cafeteria offers choices of chicken (roasted or deep fried), roast beef, pork chops, hamburgers, hot dogs, salad, soup (chicken, pea, and clam chowder), bread (three types), beverages, and desserts (pies, ice cream, and cookies). Close coordination is required between the cafeteria’s “front office,” where its employees interface with customers, and its “back office,” the kitchen, where the food is prepared and then placed along the cafeteria’s buffet line. Because it takes substantial time to cook some of the food items, the cafeteria uses a push method. The cafeteria would have a difficult time using the pull method because it could not wait until a customer asked for an item before asking the kitchen to begin processing it. After all, shortages in food could cause riotous conditions (recall that customers are hungry), whereas preparing an excess amount of food will be wasteful because it will go uneaten. To make sure that neither of these conditions occurs, the cafeteria must accurately forecast the number of customers it expects to serve. A Chinese restaurant buffet (as shown on the previous page) would similarly follow a push method for serving its customers.

The choice between the push and pull methods is often situational. Firms using an assemble-to-order strategy sometimes use both methods: the push method to produce the standardized components, and the pull method to fulfill the customer’s request for a particular combination of the components.

Quality at the Source Consistently meeting the customer’s expectations is an important charac-teristic of lean systems. One way to achieve this goal is by adhering to a practice called quality at the source, which is a philosophy whereby defects are caught and corrected where they are created. The goal for workers is to act as their own quality inspectors and never pass on defec-tive units to the next process. Automatically stopping the process when something is wrong and then fixing the problems on the line itself as they occur is also known as jidoka. Jidoka tends to separate worker and machine activities by freeing workers from tending to machines all the time, thus allowing them to staff multiple operations simultaneously. Jidoka represents a visual management system whereby status of the system in terms of safety, quality, delivery, and cost performance relative to the goals for a given fabrication cell or workstation in an assembly line is clearly visible to workers on the floor at all times.

An alternative to jidoka or quality at the source is the traditional practice of pushing problems down the line to be resolved later. This approach is often ineffective. For example, a soldering opera-

tion at the Texas Instruments antenna department had a defect rate that varied from 0 to 50 percent on a daily basis, averaging about 20 percent. To compensate, production planners increased the lot sizes, which only increased inventory levels and did nothing to reduce the number of defective items. The company’s engineers then discovered through experimentation that gas temperature was a critical variable in producing defect-free items. They subsequently devised statistical control charts for the firm’s equipment operators to use to monitor the temperature and adjust it themselves. Process yields immediately improved and stabi-lized at 95 percent, and Texas Instruments was eventually able to implement a lean system.

One successful approach for implementing quality at the source is to use poka-yoke, or mistake-proofing methods aimed at designing fail-safe systems that attack and minimize human error. Poka-yoke systems work well in practice. Consider, for instance, a company that makes modular prod-ucts. The company could use the poka-yoke method by making different parts of the modular product in such a way that allows them to be assembled in only one way—the correct way. Similarly, a company’s shipping boxes could be designed to be packed only in a certain way to minimize damage and eliminate

jidoka

Automatically stopping the pro-cess when something is wrong and then fixing the problems on the line itself as they occur.

poka-yoke

Mistake-proofing methods aimed at designing fail-safe systems that minimize human error.

An example of poka-yoke is the design of new fuel doors in automobiles. They are mistake-proof, since the filling pipe insert keeps larger, leaded-fuel nozzles from being inserted. In addition, a gas cap tether does not allow the motorist to drive off without the cap, and is also fitted with a ratchet to signal proper tightness and prevent over-tightening.

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LEAN SYSTEMS CHAPTER 4 171

all chances of mistakes. At Toyota plants, every vehicle being assembled is accompanied by an RFID chip containing information on how many nuts and bolts need to be tightened on that vehicle for an operation at a given workstation. A green light comes on when the right numbers of nuts have been tightened. Only then does the vehicle move forward on the assembly line.

Another tool for implementing quality at the source is andon, which is a system that gives machines and machine operators the ability to signal the occurrence of any abnormal condi-tion, such as tool malfunction, shortage of parts, or the product being made outside the desired specifications. It can take the form of audio alarms, blinking lights, LCD text displays, or cords that can be pulled by workers to ask for help or stop the production line if needed. Stopping a production line can, however, cost a company thousands of dollars each minute production is halted. Management must realize the enormous responsibility this method puts on employees and must prepare them properly.

Building quality at the source and eliminating waste resulting from poor quality also requires the application of several quality tools, as discussed in Chapter 3. Alcoa in Managerial Practice 4.1 illustrates how it achieved leaner systems by utilizing process improvement tools and continuous improvement to build quality at the source.

MANAGERIAL PRACTICE Alcoa

Alcoa is the world’s eighth largest aluminum company by revenue, with operations in 10 countries and 13,800 employees globally. It was founded in 1888 by Charles Martin, who discovered a way to produce aluminum through electrolysis that drastically reduced production cost. Alcoa has operated for over 132 years as a vertically integrated company that is engaged in mining businesses as well as in fabricating a diverse set of products ranging from aluminum foils to aerospace alloys. In 2016, Alcoa separated its mining/refining/smelting and power businesses (retaining the name Alcoa) from its fabrication businesses (which are now known as Arconic).

In 2011, management identified that the current production processes were yielding significant amounts of scrap and rework due to product defects. From a lean systems perspective, defects are a form of muda, or waste, which represents a deviation from the optimal allocation of resources. Defects in processes in turn led to high levels of customer complaints and poor delivery performance. To identify the root cause, Alcoa formed a process improvement team, which included engineering process owners, business unit and site managers, operations personnel, and quality staff. In addition, Alcoa involved the business unit’s customers as external stakeholders to incorporate the voice of customers in the processes’ improvement project. The goal of the project was to build quality at the source, and develop a sustainable method to gradually reduce defects by 10 percent over a 3-year period.

Using various tools such as Pareto charts, cause-and-effect diagrams, and data analysis, the process improvement team was able to narrow the scope of the project to focus on wax, shell, and cast manufacturing opera-tions at nine selected locations. The team developed a three-staged approach to replace the previous processes. First, a new process was developed and implemented in a small number of pilot plants. Next, the process was trans-ferred to fast-follower plants that were already well positioned for making changes, and finally, the new process was shared at the broad business unit level. There were significant benefits to implementing the new process using a staged diffusion approach. For example, one of the pilot stage plants imple-mented a new casting/mold wrap process and demonstrated a 30 percent reduction in related scrap in 3 months. In the subsequent fast-follower plants, this process was implemented to yield the same benefits. However, the imple-mentation time was significantly reduced to 30 days. To overcome employee resistance to process change, the company conducted routine team-building

meetings and shared monthly process audit information. Involving employ-ees at the plant floor level in the process improvement project also helped them to prioritize activities, and to participate in several kaizen (continuous improvement) events.

Alcoa experienced drastic benefits from cost savings due to the lean process implementation project. For example, one of the plants was able to reduce 77 percent of the wax expenses, which resulted in annual savings of $38,000. In another plant, improvement in the shell weight control process yielded an annual savings of $400,000. The new lean process lowered scrap rates, reduced rework activities that are another form of muda, and reduced customer returns. This improvement led to more on-time deliveries and higher customer satisfaction. Another side benefit from the project was the accumu-lation of workers’ organizational knowledge, which strengthened their belief that preventive and proactive improvements on a regular basis minimize the time spent managing problems and fighting fires.3

3Sources: J. Jacobsen, “Process Management Approach Reduces Scrap, Saves Alcoa Millions.” http://asq .org/2016/05/process-management/approach-reduces-scrap-saves-alcoa-millions.pdf (May 2016); History of Alcoa. https://www.alcoa.com/global/en/who-we-are/history (July 27, 2020); https://en.wikipedia.org/wiki/Alcoa (July 27, 2020); https://investors.alcoa.com/~/media/Files/A/Alcoa-IR/documents/annual-reports-and-proxy-information/alcoa-annual-report-2019.pdf (July 29, 2020).

4.1

Workers walk by finished forged aluminum truck wheels at the Alcoa aluminum factory October 24, 2006 in Szekesefehervar, Hungary. Alcoa bought the factory, once one of the main suppliers of semi-finished aluminum in the former East Bloc, in 1993.

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172 PART 1 MANAGING PROCESSES

Uniform Workstation Loads A lean system works best if the daily load on individual workstations is relatively uniform. Service processes can achieve uniform workstation loads by using reserva-tion systems. For example, hospitals schedule surgeries in advance of the actual service so that the facilities and facilitating goods can be ready when the time comes. The load on the surgery rooms and surgeons can be evened out to make the best use of these resources. Another approach is to use differential pricing of the service to manage the demand for it. Uniform loads are the rationale behind airlines promoting weekend travel or red-eye flights that begin late in the day and end in the early morning. Efficiencies can be realized when the load on the firm’s resources can be managed.

For manufacturing processes, uniform loads can be achieved by assembling the same type and number of units each day, thus creating a uniform daily demand at all workstations. Capacity planning, which recognizes capacity constraints at critical workstations, and line balancing are used to develop the master production schedule. For example, at Toyota’s plant the production plan may call for 4,500 vehicles per week for the next month. That requires two full shifts, 5 days per week, producing 900 vehicles each day, or 450 per shift. Three models are produced: Camry (C), Avalon (A), and Highlander (H). Suppose that Toyota needs 200 Camrys, 150 Avalons, and 100 Highlanders per shift to satisfy market demand. To produce 450 units in one shift of 480 minutes, the line must roll out a vehicle every 480/450 = 1.067 minutes. The 1.067 minutes, or 64 seconds, represents the takt time of the process, defined as the cycle time needed to match the rate of production to the rate of sales or consumption.

With traditional big-lot production, all daily requirements of a model are produced in one batch before another model is started. The sequence of 200 Cs, 150 As, and 100 Hs would be repeated once per shift. Not only would these big lots increase the average inventory level, but they also would cause lumpy requirements on all the workstations feeding the assembly line.

But there are two other options for devising a production schedule for the vehicles. These options are based on the Japanese concept of heijunka, which is the leveling of production load by both volume and product mix. It does not build products according to the actual flow of cus-tomer orders but levels out the total volume of orders in a period so that the same amount and mix are being made each day.4

Let us explore two possible heijunka options. The first option uses leveled mixed-model assembly, producing a mix of models in smaller lots. Note that the production requirements at Toyota are in the ratio of 4 Cs to 3 As to 2 Hs, found by dividing the model’s production requirements by the greatest common divisor, or 50. Thus, the Toyota planner could develop a production cycle consisting of 9 units: 4 Cs, 3 As, and 2 Hs. The cycle would repeat in 9(1.067) = 9.60 minutes, for a total of 50 times per shift (480 min/9.60 min = 50).

The second heijunka option uses a lot size of one, such as the production sequence of C–H–C–A–C–A–C–H–A repeated 50 times per shift. The sequence would achieve the same total output as the other options; however, it is feasible only if the setup times are brief. The sequence generates a steady rate of component requirements for the various models and allows the use of small lot sizes at the feeder workstations. Consequently, the capacity requirements at those sta-tions are greatly smoothed. These requirements can be compared to actual capacities during the planning phase, and modifications to the production cycle, production requirements, or capacities can be made as necessary.

Standardized Components and Work Methods In highly repetitive service operations, analyz-ing work methods and documenting the improvements to use can gain great efficiencies. For example, UPS consistently monitors its work methods, from sorting packages to delivering them, and revises them as necessary to improve service. In manufacturing, the standardization of com-ponents increases the total quantity that must be produced for that component. For example, a firm producing 10 products from 1,000 different components could redesign its products so that they consist of only 100 different components with larger daily requirements. Because the requirements per component increase, each worker performs a standardized task or work method more often each day. Productivity tends to increase because workers learn to do their tasks more efficiently with increased repetition. Standardizing components and work methods help a firm achieve the high-productivity, low-inventory objectives of a lean system.

Flexible Workforce The role of workers is elevated in lean systems. Workers in flexible work-forces can be trained to perform more than one job. A benefit of flexibility is the ability to shift workers among workstations to help relieve bottlenecks as they arise without the need for inven-tory buffers—an important aspect of the uniform flow of lean systems. Also, workers can step in and do the job for those who are on vacation or who are out sick. Although assigning workers to tasks they do not usually perform can temporarily reduce their efficiency, some job rotation tends to relieve boredom and refreshes workers. At some firms that have implemented lean systems, cross-trained workers may switch jobs every 2 hours.

The more customized the service or product is, the greater the firm’s need for a multiskilled work-force. For example, stereo repair shops require broadly trained personnel who can identify a wide

takt time

Cycle time needed to match the rate of production to the rate of sales or consumption.

4David McBride, “Heijunka, Leveling the Load” (September 1, 2004), a www.emsstrategies.com.

heijunka

The leveling of production load by both volume and product mix.

mixed-model assembly

A type of assembly that produces a mix of models in smaller lots.

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variety of component problems when the customer brings the defective unit into the shop and who then can repair the unit. Alternatively, back-office designs, such as the mail-processing operations at a large post office, have employees with more nar-rowly defined jobs because of the repetitive nature of the tasks they must perform. These employees do not have to acquire as many alternative skills. In some situations, shifting workers to other jobs may require them to undergo extensive, costly training.

Automation Automation plays a big role in lean systems and is a key to low-cost operations. Money freed up because of inventory reductions or other efficiencies can be invested in automation to reduce costs. The benefits, of course, are greater profits, greater market share (because prices can be cut), or both. Automation can play a big role when it comes to providing lean services. For example, banks offer ATMs that provide various bank services on demand 24 hours a day. Automation should be planned carefully, however. Many managers believe that if some automation is good, more is bet-ter, which is not always the case. At times, humans can do jobs better than robots and automated assembly systems. In other instances, especially when production volumes are high, automation can result in higher quality, precision, and productivity.

Five S Practices Five S (5S) is a methodology for organizing, cleaning, developing, and sustaining a productive work environment. It represents five related terms, each beginning with an S, that describe workplace practices conducive to visual controls and lean production. As shown in Figure 4.2, these five practices of sort, straighten, shine, standardize, and sustain build upon one another and are done systematically to achieve lean systems. These practices are interconnected and are not some-thing that can be done as a stand-alone program. As such, they serve as an enabler and an essential foundation of lean systems. Table 4.2 shows the terms that represent the 5S and what they imply.

It is commonly accepted that 5S forms an important cornerstone of waste reduction and removal of unneeded tasks, activities, and materials. 5S practices can enable workers to visually see everything differently, prioritize tasks, and achieve a greater degree of focus. They can also be applied to a diverse range of manufacturing and service settings, including organizing work spaces, offices, tool rooms, shop floors, and the like. Implementation of 5S practices has been shown to lead to lowered costs, improved on-time delivery and productivity, higher product qual-ity, better use of floor space, and a safe working environment. It also builds the discipline needed to make the lean systems work well.

Five S (5S)

A methodology consisting of five workplace practices—sorting, straightening, shining, standard-izing, and sustaining—that are conducive to visual controls and lean production.

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Computerized Avocado sorting and packing plant in Israel shows that automation can occur in many different settings.

▲ FIGURE 4.25S Practices

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Total Productive Maintenance Because lean systems emphasize finely tuned flows of work and little capacity slack or buffer inventory between workstations, unplanned machine downtime can be disruptive. Total productive maintenance (TPM), which is also sometimes referred to as total preven-tive maintenance, can reduce the frequency and duration of machine downtime. After performing

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174 PART 1 MANAGING PROCESSES

their routine maintenance activities, technicians can test other machine parts that might need to be replaced. Replacing parts during regularly scheduled maintenance periods is easier and quicker than dealing with machine failures during production. Maintenance is done on a schedule that bal-ances the cost of the preventive maintenance program against the risks and costs of machine failure. Routine preventive maintenance is important for service businesses that rely heavily on machinery, such as the rides at Walt Disney World or Universal Studios.

Another tactic is to make workers responsible for routinely maintaining their own equipment, which will develop employee pride in keeping the machines in top condition. This tactic, how-

ever, typically is limited to general housekeeping chores, minor lubrication, and adjustments. Maintaining high-tech machines requires trained specialists. Nonetheless, performing even sim-ple maintenance tasks goes a long way toward improving the performance of machines.

For long-term improvements, data can be collected for establishing trends in the failure pattern of machines, which can subsequently be analyzed to establish better standards and pro-cedures for preventive maintenance. The data can also provide failure history and costs incurred to maintain the systems.

Toyota Production SystemIf you were to select one company that regularly invokes the abovementioned features of lean systems and also exemplifies excellence in automobile manufacturing, it would probably be Toyota. Despite its problems with quality and product recalls in 2014, as well as component shortages and delayed new model launches caused by the Great East Japan Earthquake in March 2011, Toyota has become one of the largest car manufacturers in the world, with 11 manufacturing plants in North America alone. Much of this success is attributed to the famed Toyota Production System (TPS), which is one of the most admired lean manufac-turing systems in existence. Replicating the system, however, is fraught with difficulties. What makes the system tick, and why has Toyota been able to use it so successfully in many different plants?

Most outsiders see the TPS as a set of tools and procedures that are readily visible during a plant tour. Even though they are important for the success of the TPS, they are not the key. What most people overlook is that through the process of continu-ous improvement, Toyota built a learning organization over the course of 50 years. Lean systems require constant improvements to increase efficiency and reduce waste. Toyota’s system stimu-lates employees to experiment to find better ways to do their jobs. In fact, Toyota sets up all of its operations as “experiments” and teaches employees at all levels how to use the scientific method of problem solving.

Four principles form the basis of the TPS. First, all work must be completely specified as to content, sequence, timing,

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5S Term Definition

1. Sort Separate needed items from unneeded items (including tools, parts, materials, and paperwork) and discard the unneeded.

2. Straighten Neatly arrange what is left, with a place for everything and everything in its place. Organize the work area so that it is easy to find what is needed.

3. Shine Clean and wash the work area and make it shine.

4. Standardize Establish schedules and methods of performing the cleaning and sorting. Formalize the cleanliness that results from regularly doing the first three S practices so that perpetual cleanliness and a state of readiness are maintained.

5. Sustain Create discipline to perform the first four S practices, whereby everyone understands, obeys, and practices the rules when in the plant. Implement mechanisms to sustain the gains by involving people and recognizing them through a performance measurement system.

TABLE 4.2 | 5S DEFINED

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and outcome. Detail is important; otherwise, a foundation  for improvements is missing. Second, every customer–supplier connection must be direct, unambiguously specifying the people involved, the form and quantity of the services or goods to be provided, the way the requests are made by each customer, and the expected time in which the requests will be met. Customer– supplier connections can be internal (employee to employee) or external (company to company). Third, the pathway for every service and product must be simple and direct. That is, services and goods do not flow to the next available person or machine but to a specific person or machine. With this principle, employees can determine, for example, whether a capacity problem exists at a particular work-station and then analyze ways to solve it.

The first three principles define the system in detail by specifying how employees do work and interact with each other and how the work-flows are designed. However, these specifica-tions actually are “hypotheses” about the way the system should work. For example, if something goes wrong at a workstation enough times, the hypothesis about the methods the employee uses to do work is rejected. The fourth principle, then, is that any improvement to the system must be made in accordance with the scientific method, under the guidance of a teacher, at the lowest possible organizational level. These four principles are deceptively simple. However, they are difficult but not impossible to replicate. Those organizations that successfully implement them enjoy the benefits of a lean system that adapts to change. Toyota’s lean system made it an innovative leader in the auto industry and served as an important cornerstone of its success.

House of Toyota Taiichi Ohno and Eiji Toyoda cre-ated a graphic representation (Figure 4.3) to define the TPS to its employees and suppliers, and which is now known as the House of Toyota. It captures the four prin-ciples of TPS described earlier, and represents all the essential elements of lean systems that make the TPS work well. The house conveys stability. The twin pil-lars of JIT and jidoka support the roof, representing the primary goals of high quality, low cost, waste elimina-tion, and short lead times. Within JIT, TPS uses a pull system that focuses on one-piece workflow methods that can change and match the takt time of the process to the actual market demand, because setup reduc-tions and small changeover times are facilitated by cross-trained workers in cellular layouts. Implementing various tools of jidoka ensures that quality is built into the product rather than merely inspected at the end. Finally, within an environment of continuous improve-ment, operational stability to the House of Toyota is provided at the base by leveraging other lean concepts such as heijunka, standard work methods, 5S practices, total preventive maintenance, and elimination of waste throughout the supply chain within which the Toyota products flow to reach their eventual customers.

Designing Lean System LayoutsLine flows are recommended in designing lean system layouts because they eliminate waste by reducing the frequency of setups. If volumes of specific products are large enough, groups of machines and workers can be organized into a line-flow layout to eliminate setups entirely. In a service setting, managers of back-office service processes can similarly organize their employees and equipment to provide uniform workflows through the process and, thereby, eliminate wasted employee time. Banks use this strategy in their check-processing operations, as does UPS in its parcel-sorting process.

Workers on a Toyota Camry assembly line in a Toyota car factory in St. Petersburg, Russia.

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▲ FIGURE 4.3House of Toyota

Culture ofContinuous

Improvement

Just in Time (JIT)• Takt Time• One-piece flow• Pull system

Jidoka• Manual or automatic line stop• Separate operator and machine activities• Error-proofing• Visual control

Highest quality, lowest cost,shortest lead time by eliminating

wasted time and activity

Operational Stability

Heijunka Standard Work TPM Supply Chain

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When volumes are not high enough to justify dedicating a single line of multiple workers to a single customer type or product, managers still may be able to derive the benefits of line-flow layout—simpler materials handling, low setups, and reduced labor costs—by creating line-flow layouts in some portions of the facility. Two techniques for creating such layouts are one-worker, multiple-machines (OWMM) cells and group technology (GT) cells.

One Worker, Multiple MachinesIf volumes are not sufficient to keep several workers busy on one production line, the manager might set up a line small enough to keep one worker busy. The one-worker, multiple-machines (OWMM) cell is a workstation in which a worker operates several different machines simultaneously to achieve a line flow. Having one worker operate several identical machines is not unusual. However, with an OWMM cell, several different machines are in the line.

Figure 4.4 illustrates a five-machine OWMM cell that is being used to produce a flanged metal part, with the machines encircling one operator in the center. (A U shape also is common.) The operator moves around the circle, performing tasks (typically loading and unloading) that have

not been automated. Different products or parts can be produced in an OWMM cell by chang-ing the machine setups. If the setup on one machine is especially time consuming for a particular part, management can add a dupli-cate machine to the cell for use whenever that part is being produced.

An OWMM arrangement reduces both inventory and labor requirements. Inventory is cut because, rather than piling up in queues waiting for transportation to another part of the plant, materials move directly into the next operation. Labor is cut because more work is automated. The addition of several low-cost automated devices can maximize the number of machines included in an OWMM arrange-ment: automatic tool changers, loaders and unloaders, start and stop devices, and fail-safe devices that detect defective parts or products. Manufacturers are applying the OWMM con-cept widely because of their desire to achieve low inventories.

Group TechnologyA second option for achieving line-flow layouts with low volume processes is group technology (GT). This manufacturing technique creates cells not limited to just one worker and has a unique way of selecting work to be done by the cell. The GT method groups parts or products with similar characteristics into families and sets aside groups of machines for their production. Families may be based on size, shape, manufacturing or routing requirements, or demand. The goal is to identify a set of products with similar processing requirements and minimize machine changeover or setup. For example, all bolts might be assigned to the same family because they all require the same basic processing steps regardless of size or shape.

Once parts have been grouped into families, the next step is to organize the machine tools needed to perform the basic processes on these parts into separate cells. The machines in each cell require only minor adjustments to accommodate product changeovers from one part to the next in the same family. By simplifying product routings, GT cells reduce the time a job is in the shop. Queues of materials waiting to be worked on are shortened or eliminated. Frequently, materials handling is automated so that, after loading raw materials into the cell, a worker does not handle machined parts until the job has been completed.

Figure 4.5 compares process flows before and after creation of GT cells. Figure 4.5(a) shows a shop floor where machines are grouped according to function: lathing, milling, drilling, grind-ing, and assembly. After lathing, a part is moved to one of the milling machines, where it waits in line until it has a higher priority than any other job competing for the machine’s capac-ity. When the milling operation on the part has been finished, the part is moved to a drilling machine, and so on. The queues can be long, creating significant time delays. Flows of materi-als are jumbled because the parts being processed in any one area of the shop have so many different routings.

one-worker, multiple-machines (OWMM) cell

A one-person cell in which a worker operates several differ-ent machines simultaneously to achieve a line flow.

group technology (GT)

An option for achieving line-flow layouts with low volume pro-cesses; this technique creates cells not limited to just one worker and has a unique way of selecting work to be done by the cell.

▲ FIGURE 4.4One-Worker, Multiple-Machines (OWMM) Cell

Materials in

Machine1

Machine2

Machine3

Machine4Machine

5

Finishedgoods out

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LEAN SYSTEMS CHAPTER 4 177

By contrast, the manager of the shop shown in Figure 4.5(b) identified three product families that account for a majority of the firm’s produc-tion. One family always requires two lathing operations followed by one operation at the mill-ing machines. The second family always requires a milling operation followed by a grinding opera-tion. The third family requires the use of a lathe, a milling machine, and a drill press. For simplicity, only the flows of parts assigned to these three fami-lies are shown. The remaining parts are produced at machines outside the cells and still have jum-bled routings. Some equipment might have to be duplicated, as when a machine is required for one or more cells and for operations outside the cells. However, by creating three GT cells, the manager has definitely created more line flows and simpli-fied routings.

The Kanban SystemOne of the most publicized aspects of lean systems, and the TPS in particular, is the Kanban system developed by Toyota. Kanban, meaning “card” or “visible record” in Japanese, refers to cards used to control the flow of production through a fac-tory. The goal of a Kanban system is to make sure that the company has the minimum amount of inventory that is just enough to keep production running, and that production is being pulled by customer demand. In the most basic Kanban sys-tem, a card is attached to each container of items produced. The container holds a given percent of the daily production requirements for an item. When the user of the parts empties a container, the card is removed from the container and put on a receiving post. The empty container is then taken to the storage area, and the card signals the need to produce another container of the part. When the container has been refilled, the card is put back on the container, which is then returned to a storage area. The cycle begins again when the user of the parts retrieves the container with the card attached.

Figure 4.6 shows how such a Kanban system works when it is managing inventory between a preceding process and a following process. The following steps, labeled from Figure 4.6(a) to Figure 4.6(e), are followed in a sequence that pulls products through the manufacturing system.

(a) The process starts with two containers full of parts A and B and one Kanban card in each container.

(b) As the following process needs a part, it pulls a full container from inventory. The Kanban card for part A is detached from the container and scheduled to be produced by the preceding process in a receiving post. The empty box also returns to the preceding process to be filled up.

(c) Part A begins production at the preceding process, and when completed, the full container with the Kanban card will be placed at the inventory to replenish the parts consumed by the following process. At the same time, the following process is withdrawing from inventory a full container of part B items. The Kanban for B parts is now taken to the receiving post, and the empty container is taken to be filled up by the preceding process.

(d) The Kanban signals the preceding process to begin producing part B, and when completed, the full container with the Kanban card will be placed in the inventory location between the two processes.

(e) The preceding process will have to wait for the following process to withdraw a container and a Kanban card to be taken to the receiving post to begin replenishment again.

Such a Kanban system allows firms to use a pull method of workflow to manufacture products in a typically make-to-stock production environment.

Kanban

A Japanese word meaning “card” or “visible record” that refers to cards used to control the flow of production through a factory.

▲ FIGURE 4.5Process Flows Before and After the Use of GT CellsSource: GROOVER, AUTOMATION, PRODUCTION SYSTEMS & COMPUTER-AIDED MANUFACTURING, 1st Ed., © 1980. Reprinted and Electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.

Cell 1

Cell 3

Cell 2

L L

L L

L L

L L

L

L M

M

M

M M

M M

M M

D D

D D

D

D

G

G G

G G

G G

G G

A A

A A

A A

L L

Lathing Milling

Assembly

Assemblyarea

Drilling

Grinding

Receiving and shipping

Shipping

(a) Jumbled flows in a job shop without GT cells

(b) Line flows in a job shop with three GT cells

Receiving

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178 PART 1 MANAGING PROCESSES

▲ FIGURE 4.6Kanban System illustration

Receiving post

Precedingprocess

Followingprocess

(a) Steady state starting condition

A

B

A

B

Receiving post

Precedingprocess

Followingprocess

(b) Withdrawal of Part A by the following process andreturn of empty box to the preceding process to be filled up

A

A

B B

Receiving Post

Precedingprocess

Followingprocess

(c) Production of Part A at the preceding process. Withdrawal of Part B by thefollowing process and return of empty box to the preceding process to be filled up

B

A

BA

Receiving post

Precedingprocess

Followingprocess

(d) Production of Part B at the preceding process

A

BB

A

Receiving post

Precedingprocess

Followingprocess

(e) Back to steady state again, waiting forproduction to start at the following process

A

B

A

B

General Operating RulesThe operating rules for Kanban systems are simple and are designed to facilitate the flow of materials while maintaining control of inventory levels.1. A full container must always have a Kanban card.2. The preceding process will never produce parts without

a Kanban card.3. The following process must post the Kanban card at the

receiving post before beginning consumption of the parts inside the containers.

4. The containers should always contain the same number of good parts (the Kanban card describes the number of parts per container). The use of nonstandard containers or irregularly filled containers disrupts the production flow of the assembly line.

5. Only non-defective parts should be put into inventory with the Kanban card to make the best use of materi-als and worker’s time. This rule reinforces the notion of building quality at the source, which is an important characteristic of lean systems, and guarantees that the following process will have enough inventory.

Determining the Number of ContainersThe number of authorized containers in the TPS determines the amount of authorized inventory. Management must make two determinations: (1) the number of units to be held by each container, and (2) the number of containers flowing back and forth between the supplier station and the user station. The first decision amounts to determining the size of the production lot.

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The number of containers flowing back and forth between two stations directly affects the quantities of work-in-process inventory, which includes any safety stock inventory to cover for unexpected requirements.5 The containers spend some time in production, in a line waiting, in a storage location, or in transit. The key to determining the number of containers required is to estimate the average lead time needed to produce a container of parts. The lead time is a function of the processing time per container at the supplier station, the waiting time during the production process, and the time required for materials handling. Little’s law, which says that the average work-in-process (WIP) inventory equals the average demand rate multiplied by the average time a unit spends in the manufacturing process, can be used to determine the num-ber of containers needed to support the user station (see Supplement B, “Waiting Lines”).

WIP = (average demand rate)(average time a container spends in the manufacturing process) + safety stock

In this application of determining the number of containers needed for a part, WIP is the product of k, the number of containers, and c, the number of units in each container. Consequently,

kc = d (v + r)(1 + a)

k = d (v + r)(1 + a)

cwherek = number of containers for a part d = expected daily demand for the part, in unitsv = average waiting time during the production process plus materials handling time per container, in fractions of a day

r = average processing time per container, in fractions of a dayc = quantity in a standard container of the parta = a policy variable that adds safety stock to cover for unexpected circumstances (Toyota uses a value of no more than 10 percent)

The number of containers must, of course, be an integer. Rounding k up provides more inven-tory than desired, whereas rounding k down provides less. The container quantity, c, and the effi-ciency factor, a, are variables that management can use to control inventory. Adjusting c changes the size of the production lot, and adjusting a changes the amount of safety stock. The Kanban system allows management to fine-tune the flow of materials in the system in a straightforward way. For example, removing cards from the system reduces the number of authorized containers of the part, thus reducing the inventory of the part. Thus, a major benefit is the simplicity of the system, whereby product mix or volume changes can easily be accomplished by adjusting the number of Kanbans in the system. Example 4.1 shows how to determine the appropriate number of containers for a manufacturing process.

5We discuss safety stocks, and their use, in more detail in Chapter 9, “Inventory Management,” and Chapter 12, “Supply Chain Design.”

Determining the Appropriate Number of ContainersEXAMPLE 4.1

The Westerville Auto Parts Company produces rocker-arm assemblies for use in the steering and sus-pension systems of four-wheel-drive trucks. A typical container of parts spends 0.02 day in processing and 0.08 day in materials handling and waiting during its manufacturing cycle. The daily demand for the part is 2,000 units. Management believes that demand for the rocker-arm assembly is uncertain enough to warrant a safety stock equivalent of 10 percent of its authorized inventory.

a. If each container contains 22 parts, how many containers should be authorized?

b. Suppose that a proposal to revise the plant layout would cut materials handling and waiting time per container to 0.06 day. How many containers would be needed?

SOLUTION

a. If d = 2,000 units/day, r = 0.02 day, a = 0.10, v = 0.08 day, and c = 22 units,

k =2,000(0.08 + 0.02)(1.1)

22=

22022

= 10 containers

b. Figure 4.7 from OM Explorer shows that the number of containers drops to 8.

▼ FIGURE 4.7OM Explorer Solver for Number of Containers

Daily Expected DemandQuantity in Standard ContainerContainer Waiting Time (days)Processing Time (days)Policy Variable

Containers Required

Solver-Number of ContainersEnter data in yellow-shaded area.

200022

0.060.0210%

8

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180 PART 1 MANAGING PROCESSES

Other Kanban SignalsCards are not the only way to signal the need for more production of a part. Other, less formal methods are possible, including container and containerless systems.

Container System Sometimes, the container itself can be used as a signal device: An empty container signals the need to fill it. Unisys took this approach for low-value items. Adding or removing containers adjusts the amount of inventory of the part. This system works well when the container is specially designed for a particular part and no other parts could accidentally be put in the container. Such is the case when the container is actually a pallet or fixture used to position the part during precision processing.

Containerless System Systems requiring no containers have been devised. In assembly-line oper-ations, operators use their own workbench areas to put completed units on painted squares, one unit per square. Each painted square represents a container, and the number of painted squares on each operator’s bench is calculated to balance the line flow. When the subsequent user removes a unit from one of the producer’s squares, the empty square signals the need to produce another unit. McDonald’s uses a containerless system. Information entered by the order taker at the cash register is transmitted to the cooks and assemblers, who produce the sandwiches requested by the customer.

Value Stream MappingValue stream mapping (VSM) is a widely used qualitative lean tool aimed at eliminating waste, or muda. Waste in many processes, also referred to as value streams, can be as high as 99 percent. Value stream mapping is helpful because it creates a visual representation of every process involved in the flow of materials and information in a product’s value stream, which can be used to identify the lean tools needed to reduce waste. These maps consist of a current state drawing, a future state drawing, and an implementation plan. Value stream mapping spans the supply chain from the firm’s receipt of raw materials or components to the delivery of the finished good to the customer. Thus, it tends to be broader in scope, displaying far more information than a typical process map or a flowchart used with Six Sigma process improve-ment efforts. Creating such a big picture representation helps managers identify the source of wasteful nonvalue-added activities.

Current State MapValue stream mapping follows the steps shown in Figure 4.8. The first step is to focus on one product family for which mapping can be done. It is then followed by drawing a cur-rent state map of the existing processes. Analysts start from the customer end and work upstream to draw the map by hand and record actual process times rather than rely on information not obtained by firsthand observation. Information for drawing the material and information flows can be gathered from the shop floor, including the data related to each process: cycle time (C/T), setup or changeover time (C/O), uptime (on-demand avail-able machine time expressed as a percentage), production batch sizes, number of people required to operate the process, number of product variations, pack size (for moving the product to the next stage), working time (minus breaks), and scrap rate. Value stream mapping uses a standard set of icons for material flow, information flow, and general information (to denote operators, safety stock buffers, etc.). Even though the complete VSM glossary is extensive, a representative set of these icons is shown in Figure 4.9. These icons provide a common language for describing in detail how a facility should operate to create a better flow.

value stream mapping (VSM)

A qualitative lean tool for eliminating waste, or muda, that involves a current state drawing, a future state drawing, and an implementation plan.

DECISION POINTThe average lead time per container is v + r. With a lead time of 0.10 day, 10 containers are needed. However, if the improved facility layout reduces the materials handling time and waiting time to v = 0.06 day, only 8 containers are needed. The maximum authorized inventory of the rocker-arm assembly is kc. Thus, in part (a), the maximum authorized inventory is 220 units, but in part (b), it is only 176 units. Reducing v + r by 20 percent reduces the inventory of the part by 20 percent. Management must balance the cost of the layout change (a one-time charge) against the long-term benefits of inventory reduction.

▼ FIGURE 4.8Value Stream Mapping StepsSource: Mike Rother and John Shook, Learning to See (Cambridge, MA: The Lean Enterprise Institute, 2003), p. 9. ©Copyright 2003 Lean Enterprise Institute, Inc. Cambridge, MA, lean.org. All rights reserved.

Current statedrawing

Product family

Future statedrawing

Work plan andimplementation

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LEAN SYSTEMS CHAPTER 4 181

Example 4.2 demonstrates the construction of a value stream map and the determination of the takt time and capacity for the current state of a bearing company.

◀ FIGURE 4.9Selected Set of Value Stream Icons Used for Mapping Current State

Material Flow Icons

ManualInformation Flow

Information Flow Icons

Supplier/Customer(outside sources)

Process Box Data Box Inventory

IData Box

C/T=C/O=

Uptime =Shifts

Avail. Time

pieces

ASSEMBLY

Operator

General Icons

Truck Shipment Movement ofMaterial by PUSH

1x/Day

Firm Name

External Deliveriesfrom Suppliers or

to Customers

ElectronicInformation Flow

Determining the Value Stream Map, Takt Time, and Total CapacityEXAMPLE 4.2

Jensen Bearings Incorporated, a ball-bearing manufacturing company located in Lexington, South Carolina, receives raw material sheets from Kline Steel Company every Monday for a product family of retainers (casings in which ball bearings are held), and then ships its finished product on a daily basis to a second-tier automotive manufacturing customer named GNK Enterprises. The product family of the bearing manufacturing company under consideration consists of two types of retainers—large (L) and small (S)—that are packaged for shipping in returnable trays with 40 retainers in each tray. The manufac-turing process consists of a value stream containing pressing operation; a piercing and forming cell, and a finish grind operation, after which the two types of retainers are staged for shipping. The information collected by the operations manager at Jensen Bearings Inc. is shown in Table 4.3.

Overall Process Attributes

Average demand: 3,200/week (1,000 “L”; 2,200 “S”)

Batch size: 40

Number of shifts per day: 1

Availability: 8 hours per shift with two 30-minute lunch breaks

Process Step 1 Press Cycle time = 12 secondsSetup time = 10 minUptime = 100%Operators = 1WIP = 5 days of sheets (Before Press)

Process Step 2 Pierce & Form Cycle time = 34 secondsSetup time = 3 minutesUptime = 100%Operators = 1WIP = 1,000 “L,” 1,250 “S” (Before Pierce & Form)

TABLE 4.3 | OPERATIONS DATA FOR A FAMILY OF RETAINERS AT JENSEN BEARINGS INC.

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182 PART 1 MANAGING PROCESSES

Overall Process Attributes

Average demand: 3,200/week (1,000 “L”; 2,200 “S”)

Batch size: 40

Number of shifts per day: 1

Availability: 8 hours per shift with two 30-minute lunch breaks

Process Step 3 Finish Grind Cycle time = 35 secondsSetup time = 0 minutesUptime = 100%Operators = 1WIP = 1,050 “L,” 2,300 “S” (Before Finish Grind)

Process Step 4 Shipping WIP = 500 “L,” 975 “S” (After Finish Grind)

Customer Shipments One shipment of 640 units each day in trays of 40 pieces, for a total of 3,200 each week

Information Flow All communications from the customer are electronic:

180/90/60/30/day Forecasts

Daily Order

All communications to the supplier are electronic

4-Week Forecast

Email

There is a weekly schedule manually delivered to Press, Pierce & Form, and Finish Grind and a Daily Ship Schedule manually delivered to Shipping

All material is pushed

a. Using data shown in Table 4.3, create a value stream map for Jensen Bearings Inc. and show how the data box values are calculated.

b. What is the takt time for this value stream?

c. What is the production lead time at each process in the value stream?

d. What is the total processing time of this value stream?

e. What is the capacity of this value stream?

SOLUTION

a. We use the VSM icons to illustrate in Figure 4.10 what a current state map would look like for Jensen Bearings Inc. The process characteristics and inventory buffers in front of each process are shown in the current state map of Figure 4.10. One worker occupies each station. The process flows shown at the bottom of Figure 4.10 are similar to the flowcharts discussed in Chapter 2, “Process Strategy and Analysis,” except that more detailed information is presented here for each process. However, what really sets the value stream maps apart from flowcharts is the inclusion of information flows at the top of Figure 4.10, which plan and coordinate all the process activities. The value stream maps are more comprehensive than process flowcharts and meld together planning and control systems (discussed in detail in Chapter 11, “Resource Planning”) with detailed flowcharts (discussed in Chapter 2) to create a comprehensive supply chain view that includes both information and material flows between the firm and its suppliers and customers.

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LEAN SYSTEMS CHAPTER 4 183

◀ FIGURE 4.10Current State Map for a Family of Retainers at Jensen Bearings Incorporated

I

Sheets5 days

5 days

C/T = 12 secondsC/O = 10 minutesUptime = 100%25,200 sec. avail.1 Shift

C/T = 34 secondsC/O = 3 minutesUptime = 100% 1 Shift25,200 sec. avail.

C/T = 35 secondsC/O = 0 minutesUptime = 100% 1 Shift25,200 sec. avail.

200 Sheets

4-weekForecast

PRODUCTIONCONTROL

Weekly Schedule

WeeklyFax

DailyOrder

Daily ShipSchedule

PRESS

12 seconds3.5 days

34 seconds5.2 days

35 seconds2.3 days

1I

1000 “L”1250 “S”

PIERCE & FORM

1I

1050 “L”2300 “S”

FINISH GRIND

1I

500 “L”975 “S”

1x WeekMonday

1x/Day

KlineSteel Co.

3,200 pieces/week1,000 “L”2,200 “S”

Tray = 40 pieces1 shift

GNKEnterprises

180/90/60/30/dayForecasts

SHIPPING

Staging

ProductionLead Time

= 16.0 days

ProcessingTime

= 81 seconds

b. The value stream’s takt time is the rate at which the cell must produce units to match demand.

Daily Demand = [(1,000 + 2,200) pieces per week]/5 working days per week] = 640 pieces per day

Daily Availability = (7 hours per day) * (3,600 seconds per hour) = 25,200 seconds per dayTakt Time = Daily Availability/Daily Demand = (25,200 seconds per day)/640 pieces per day

= 39.375 seconds per piece

c. The production lead time (in days) is calculated by summing the inventory held between each processing step divided by daily demand.

Raw Material lead time = 5.0 days

WIP lead time between Press and Pierce & Form = (2,250/640) = 3.5 days

WIP lead time between Pierce & Form and Finish Grind = (3,350/640) = 5.2 days

WIP lead time between Finish Grind and Shipping = (1,475/640) = 2.3 days

Total Production Lead time = (5 + 3.5 + 5.2 + 2.3) = 16 days

d. The value stream’s total processing time is calculated by adding the processing times of each indi-vidual process. The processing time is the lead time through a process, which for Jensen Bearings is the same as the cycle time because all process steps are processing one part at a time. The value stream’s total processing time is (12 + 34 + 35) = 81 seconds.

e. The value stream’s capacity may be calculated by locating the bottleneck and computing the num-ber of units that it can process in the available time per day at that bottleneck with the given batch size of 40 units.

M04_KRAJ9863_13_GE_C04.indd 183 15/05/21 5:01 PM

184 PART 1 MANAGING PROCESSES

Capacity at Press Capacity at Pierce & Form Capacity at Finish Grind

Cycle time = 12 seconds Cycle time = 34 seconds Cycle time = 35 seconds

Setup Time = (10 min * 60 seconds per min)/40 units per batch = 15.0 seconds

Setup Time = (3 minutes * 60 seconds per minute)/40 units per batch = 4.5 seconds

Setup Time = (0 minutes * 60 seconds per minute)/40 units per batch = 0.0 seconds

Per Unit Processing Time = (12 + 15) = 27 seconds

Per Unit Processing Time = (34 + 4.5) = 38.5 seconds

Per Unit Processing Time = (35 + 0.0) = 35.0 seconds

At a batch size of 40 units, Pierce & Form process is the bottleneck.

Availability at Pierce & Form = 25,200 seconds per day

Time at bottleneck (with setup) = 38.5 seconds

Capacity (Availability/Time at bottleneck) = 25,200/38.5 = 654 units per day

DECISION POINTAlthough the total processing time for each retainer is only 81 seconds, it takes 16 days for the cumulative production lead time. Clearly, muda, or waste, is present, and opportunities exist for reconfiguring the existing processes with the goal of eliminating inventories and reducing cumulative production lead time.

Future State MapOnce the current state map is done, the analysts can then use principles of lean systems to create a future state map with more streamlined product flows. The future state drawing eliminates the sources of waste identified on the current state drawing. Figure 4.11 shows the selected set of value stream icons used for mapping future state. The first step toward creating the future state is to determine if the process steps are capable of producing according to the takt time. If not, concepts from the theory of constraints, Chapter 6, “Constraint Management,” can be used to make the value stream capable of producing at the same rate as the customer demand.

The second step is to identify where in the value stream inventories can be totally eliminated by combining process steps. While there may be several different paths to creating the future state map, we present one potential solution here. In Jensen Bearings map, the process steps of Pierce & Form and Finish Grind have similar cycle times, which indicates that these two steps could be reorganized into one single manufacturing cell. For that to be possible, the changeover time of the Pierce & Form needs to be reduced to less than 1 minute, which can be addressed by using the concept of single-digit setup.

The third step to create the future state map is to design pull systems to manage the remaining inventories. Starting from the inventory closest to the customer and working toward the begin-ning of the value stream, inventories should work as pull systems, connecting all the process production rates to the customer’s actual demand. Jensen Bearing ships one truckload per day for this product family, and parts are going to be withdrawn from a finished goods inventory. For every tray of retainers pulled from the finished goods inventory, a Kanban card will send a

signal to the newly created Pierce & Form and Finish Grind manufacturing cell inform-ing the need to replenish the finished goods inventory. A Kanban card will have the same quantity per tray, 40 retainers. To replenish the finished goods Kanban, operators in the Pierce & Form and Finish Grind manufactur-ing cell will withdraw the WIP part from the upstream supermarket, and this withdrawal will also initiate a Kanban signal for the upstream Press process step.

Finally, the raw materials inventory of sheets is also managed by Kanban cards that are sent to Production Control, when sheets are used in the Press step process. Production Control will gather all Kanban cards for raw materials and send daily information to suppliers. To guarantee a more frequent delivery without increasing transportation costs, Jensen Bearings will need to establish Close Supplier Ties (another lean concept)

▼ FIGURE 4.11 Selected Set of Value Stream Icons Used for Mapping Future State

Kanbanarriving inbatches Supermarket

KanbanPost

Kaizenneeded

Withdrawal

Leveling the mixand volume

OXOX

SignalKanban

ProductionKanban C/O

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LEAN SYSTEMS CHAPTER 4 185

with Kline Steel Co. The size of the inventories in different stages of the Kanban system can be calculated as shown in Example 4.1 by estimating demand rates, lead times, and safety stocks needed for desired service levels.

When comparing the current state and the future state value stream map shown in Figure 4.12, we can see that Jensen Bearings can reduce their production lead time and inventory from 16 days to 5.5 days, which represents a 65 percent reduction.

◀ FIGURE 4.12 Future State Map for a Family of Retainers at Jensen Bearings Incorporated

2 days

C/T = 12 secondsC/O = 10 minutesUptime = 100%1 shift25,200 seconds

C/T = 35 secondsC/O = 0 minutesUptime = 100%1 Shift25,200 seconds

200 Sheets

4-weekForecast

PRODUCTIONCONTROL

Dailyemail

DailyOrder

Daily ShipSchedule

PRESS

12 seconds

1.5 days70 seconds

2 days

1

Pierce and Formand Grind Cell

2

Daily Daily

KlineSteel Co.

3,200 pieces/day1,000 “L”1,200 “S”

Tray = 40 pieces

GNKEnterprises

Forecast180/90/60/30 day

SHIPPING

ProductionLead Time

= 5.5 days

ProcessingTime

= 82 seconds

OXOX

UWMMcell

CloseSupplier Ties

Pierce and FormC/O time

UniformWorkstation Load

40

The last step in value stream mapping is preparing and actively using an implementation plan to achieve the future state. It may take only a couple of days from the creation of a future state map to the point where implementation can begin for a single product family. At this stage, the future state map becomes a blueprint for implementing a lean system and is fine-tuned as implementation progresses. As the future state becomes reality, a new future state map is drawn, thus denoting continuous improvement at the value stream level.

Unlike the theory of constraints  (see Chapter 6, “Constraint Management”), which accepts the existing system bottlenecks and then strives to maximize the throughput given that set of constraint(s), value stream mapping endeavors to understand through current state and future state maps how existing processes can be altered to eliminate bottlenecks and other waste-ful activities. The goal is to bring the production rate of the entire process closer to the customer’s desired demand rate. The benefits of applying this tool to the waste-removal process include reduced lead times and WIP inventories, reduced rework and scrap rates, lower indirect labor costs, and increased direct labor productivity.

wun

kley

/Ala

my

Stoc

k Ph

oto

After the pathology lab at the University of Pittsburgh Medical Center adopted a lean operations approach based on a line system versus a batch-and-queue system, the time it took to process samples dropped from days to just hours. Diagnoses were made more quickly as a result, and patients’ stays at the hospital were shortened.

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186 PART 1 MANAGING PROCESSES

Operational Benefits and Implementation IssuesTo gain competitive advantage and to make dramatic improvements, a lean system can be the solution. Lean systems can be an integral part of a corporate strategy based on speed because they cut cycle times, improve inventory turnover, and increase labor productivity. Recent studies also show that practices representing different components of lean systems such as JIT, TQM, Six Sigma, total productive maintenance (TPM), and human resource management (HRM), individu-ally as well as cumulatively, improve the performance of manufacturing plants as well as service facilities. Lean systems also involve a considerable amount of employee participation through small-group interaction sessions, which have resulted in improvements in many aspects of opera-tions, not the least of which is service or product quality.

Even though the benefits of lean systems can be outstanding, problems can still arise after a lean system has long been operational, which was witnessed recently in product recalls and a perceived shift away from tightly controlled quality that has always been the standard at Toyota. In addition, implementing a lean system can take a long time. We address next some of the issues managers should be aware of when implementing a lean system.

Organizational ConsiderationsImplementing a lean system requires management to consider issues of worker stress, cooperation and trust among workers and management, and reward systems and labor classifications.

The Human Costs of Lean Systems Lean systems can be coupled with statistical process control (SPC) to reduce variations in output. However, this combination requires a high degree of regi-mentation and sometimes stresses the workforce. For example, in the TPS, workers must meet specified cycle times, and with SPC, they must follow prescribed problem-solving methods. Such systems might make workers feel pushed and stressed, causing productivity losses or quality reductions. In addition, workers might feel a loss of some autonomy because of the close link-ages in workflows between stations with little or no excess capacity or safety stocks. Managers can mitigate some of these effects by allowing for some slack in the system—either safety stock inventories or capacity slack—and by emphasizing workflows instead of worker pace. Managers also can promote the use of work teams and allow them to determine their task assignments within their domains of responsibility.

Cooperation and Trust In a lean system, workers and first-line supervisors must take on respon-sibilities formerly assigned to middle managers and support staff. Activities such as schedul-ing, expediting, and improving productivity become part of the duties of lower-level personnel. Consequently, the work relationships in the organization must be reoriented in a way that fosters cooperation and mutual trust between the workforce and management. However, this environ-ment can be difficult to achieve, particularly in light of the historical adversarial relationship between the two groups.

Reward Systems and Labor Classifications In some instances, the reward system must be revamped when a lean system is implemented. At General Motors, for example, a plan to reduce stock at one plant ran into trouble because the production superintendent refused to cut back on the number of unneeded parts being made. Why? Because his or her salary was based on the plant’s production volume.

The realignment of reward systems is not the only hurdle. Labor contracts traditionally crippled a company’s ability to reassign workers to other tasks as the need arose. For example, a typical automobile plant in the United States has several unions and dozens of labor classifica-tions. Generally, the people in each classification are allowed to do only a limited range of tasks. In some cases, companies have managed to give these employees more flexibility by agreeing to other types of union concessions and benefits. In other cases, however, companies relocated their plants to take advantage of nonunion or foreign labor.

Process ConsiderationsFirms using lean systems typically have some dominant workflows. To take advantage of lean practices, firms might have to change their existing layouts. Certain workstations might have to be moved closer together, and cells of machines devoted to particular component families may have to be established. However, rearranging a plant to conform to lean practices can be costly. For example, many plants currently receive raw materials and purchased parts by rail, but to facilitate smaller and more frequent shipments, truck deliveries would be preferable. Loading docks might have to be reconstructed or expanded and certain operations relocated to accommodate the change in transportation mode and quantities of arriving materials.

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LEAN SYSTEMS CHAPTER 4 187

Inventory and SchedulingManufacturing firms need to have stable master production schedules, short setups, and frequent, reliable supplies of materials and components to achieve the full potential of the lean systems concept.

Schedule Stability Daily production schedules in high-volume, make-to-stock environments must be stable for extended periods. At Toyota, the master production schedule is stated in frac-tions of days over a 3-month period and is revised only once a month. The first month of the schedule is frozen to avoid disruptive changes in the daily production schedule for each work-station; that is, the workstations execute the same work schedule each day of the month (see Chapter 11, “Resource Planning,” for more details on master production schedules and freezing). At the beginning of each month, Kanbans are reissued for the new daily production rate. Stable schedules are needed so that production lines can be balanced and new assignments found for employees who otherwise would be underutilized. Lean systems used in high-volume, make-to-stock environments cannot respond quickly to scheduling changes because little slack inventory or capacity is available to absorb these changes.

Setups If the inventory advantages of a lean system are to be realized, small lot sizes must be used. However, because small lots require a large number of setups, companies must significantly reduce setup times. Some companies have not been able to achieve short setup times and, there-fore, have to use large-lot production, negating some of the advantages of lean practices. Also, lean systems are vulnerable to lengthy changeovers to new products because the low levels of finished goods inventory will be insufficient to cover demand while the system is down. If changeover times cannot be reduced, large finished goods inventories of the old product must be accumulated to compensate. In the automobile industry, every week that a plant is shut down for new-model changeover costs between $16 and $20 million in pretax profits.

Purchasing and Logistics The shipments of raw materials and components must be reliable because of the low inventory levels in lean systems. A plant can be shut down because of a lack of materials. Similarly, recovery becomes more prolonged and difficult in a lean system after supply chains are disrupted, which is what happened immediately after 9/11.

Process design and continuous improvement are key elements of a successful operations strat-egy. In this chapter, we focused on lean systems as a directive for efficient process design and an approach to achieve continuous improvement. We showed how JIT systems, a popular lean systems approach, can be used for continuous improvement and how a Kanban system can be used to control the amount of work-in-process inventory. Transforming a current process design to one embodying a lean systems philosophy is a constant challenge for management, often fraught with implementa-tion issues. However, adopting appropriate tools and management approaches can facilitate such a transformation, as exemplified by firms like Nike, Aldi, Alcoa, and Toyota, among others.

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources4.1 Describe how lean systems

can facilitate the continuous improvement of processes.

See the section “Continuous Improvement Using a Lean Systems Approach.” Review Figure 4.1 and the opening vignette on the Nike Corporation.

4.2 Identify the strategic supply chain and process characteristics of lean systems.

See the subsections “Supply Chain Considerations in Lean Systems” and “Process Considerations in Lean Systems.” The subsection “Toyota Production System” illustrates how one firm implements lean characteristics to gain strategic advantage over its competition.

4.3 Explain the differences between one-worker, multiple-machine (OWMM) and group technology (GT) approaches to lean system layouts.

The section “Designing Lean System Layouts” shows you how to differentiate between two different types of layouts used to implement line flows, when volumes are not high to justify a single line of multiple workers to a single product.

4.4 Understand Kanban systems for creating a production schedule in a lean system.

The section “The Kanban System” shows how firms like Toyota use simple visual systems to pull production and make exactly what the market demands. Example 4.1 shows how to calculate the number of Kanban cards needed.

OM Explorer Tutor: 4.1: Calculate Number of Containers in a Kanban SystemOM Explorer Solver: Number of Containers

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188 PART 1 MANAGING PROCESSES

Key EquationsThe Kanban SystemNumber of containers:

k =d (v + r)(1 + a)

c

Key TermsFive S (5S) 173group technology (GT) 176heijunka 172jidoka 170just-in-time (JIT) system 166Kanban 177

lean systems 165lot 169mixed-model assembly 172one-worker, multiple-machines

(OWMM) cell 176poka-yoke 170

pull method 169push method 169single-digit setup 169takt time 172value stream mapping

(VSM) 180

Solved Problem 1A company using a Kanban system has an inefficient machine group. For example, the daily demand for part L105A is 3,000 units. The average waiting time for a container of parts is 0.8 day. The processing time for a container of L105A is 0.2 day, and a container holds 270 units. Currently, 20 containers are used for this item.

a. What is the value of the policy variable, a?

b. What is the total planned inventory (work-in-process and finished goods) for item L105A?

c. Suppose that the policy variable, a, was 0. How many containers would be needed now? What is the effect of the policy variable in this example?

SOLUTION

a. We use the equation for the number of containers and then solve for a:

k =d (v + r)(1 + a)

c

20 =3,000(0.8 + 0.2)(1 + a)

270and

(1 + a) =20(270)

3,000(0.8 + 0.2)= 1.8

a = 1.8 – 1 = 0.8b. With 20 containers in the system and each container holding 270 units, the total planned

inventory is 20(270) = 5,400 units.

c. If a = 0

k =3,000(0.8 + 0.2)(1 + 0)

270= 11.11, or 12 containers

The policy variable adjusts the number of containers. In this case, the difference is quite dra-matic because v + r is fairly large and the number of units per container is small relative to daily demand.

Learning Objective Guidelines for Review Online Resources4.5 Understand value stream

mapping and its role in waste reduction.

The section “Value Stream Mapping” shows you how to construct value stream maps and identify waste in the processes. Review Example 4.2 for details on mapping and creating data boxes, both the current and the future states.

4.6 Explain the implementation issues associated with the application of lean systems.

The section “Operational Benefits and Implementation Issues” reviews organizational and process considerations needed to successfully deploy lean systems and gain their benefits.

Case: Copper Kettle Catering

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LEAN SYSTEMS CHAPTER 4 189

Solved Problem 2Metcalf, Inc., manufactures engine assembly brackets for two major automotive customers. The manufacturing process for the brackets consists of a cell containing a forming operation, a drilling operation, a finish grinding operation, and packaging, after which the brackets are staged for shipping. The information collected by the operations manager at Metcalf, Inc., is shown in Table 4.4.

a. Using data shown in Table 4.4, create a current value stream map for Metcalf, Inc., and show how the data box values are calculated.

b. What is the takt time for this value stream?

c. What is the production lead time at each process in the value stream?

d. What is the total processing time of this value stream?

e. What is the capacity of this value stream?

Overall Process Attributes

Average demand: 2,700/day

Batch size: 50

Number of shifts per day: 2

Availability: 8 hours per shift with a 30-minute lunch break

Process Step 1 Forming Cycle time = 11 secondsSetup time = 3 minutesUptime = 100%Operators = 1WIP = 4,000 units (Before Forming)

Process Step 2 Drilling Cycle time = 10 secondsSetup time = 2 minutesUptime = 100%Operators = 1WIP = 5,000 units (Before Drilling)

Process Step 3 Grinding Cycle time = 17 secondsSetup time = 0 minutesUptime = 100%Operators = 1WIP = 2,000 units (Before Grinding)

Process Step 4 Packaging Cycle time = 15 secondsSetup time = 0 minutesUptime = 100%Operators = 1WIP = 1,600 units (Before Packaging)WIP = 15,700 units (Before Shipping)

Customer Shipments One shipment of 13,500 units each week

Information Flow All communications with customer are electronic

There is a weekly order release to Forming

All material is pushed

TABLE 4.4 | OPERATIONS DATA FOR BRACKETS AT METCALF, INC.

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190 PART 1 MANAGING PROCESSES

Capacity at Forming Capacity at Drilling Capacity at Grinding Capacity at Packaging

Cycle time = 11 seconds Cycle time = 10 seconds Cycle time = 17 seconds Cycle time = 15 seconds

Setup Time = (3 minutes * 60 seconds per minute)/ 50 units per batch = 3.6 seconds

Setup Time = (2 minutes * 60 seconds per minute)/ 50 units per batch = 2.4 seconds

Setup Time = zero seconds

Setup Time = zero seconds

▲ FIGURE 4.13Current State Value Stream Map for Metcalf, Inc.

I

4,000

1.48 days

C/T = 11 secondsS/T = 3 minutesUptime = 100%

C/T = 10 secondsS/T = 2 minutesUptime = 100%

C/T = 17 secondsS/T = 0 minutesUptime = 100%

C/T = 15 secondsS/T = 0 minutesUptime = 100%

PRODUCTIONCONTROL

FORMING

11 seconds

1.85 days10 seconds

0.74 days17 seconds

0.59 days15 seconds

5.81 days

1I

5,000

WeekyShipments

Supplier

Daily Demand = 2,700

Customer

SHIPPING

Staging

ProductionLead Time

= 10.47 days

ProcessingTime

= 53 seconds

Time Available per day

= 7.5 hrs. 2 shifts

WeekyShipments

I

1,600

I

2,000

I

15,700

DRILLING

1

GRINDING

1

PACKAGING

1

b. Daily Demand = 2,700 units per day

Daily Availability = (7.5 hours per day) * (3,600 seconds per hour) * (2 shifts per day) = 54,000 seconds per day

Takt Time = Daily Availability/Daily Demand = 54,000 seconds per day/2,700 units per day = 20 seconds per unit

c. The production lead time (in days) is calculated by summing the inventory held between each processing step divided by daily demand.

Raw Material lead time = [4,000/2,700] = 1.48 days

WIP lead time between Forming and Drilling = [5,000/2,700] = 1.85 days

WIP lead time between Drilling and Grinding = [2,000/2,700] = 0.74 day

WIP lead time between Grinding and Packaging = [1,600/2,700] = 0.59 day

Finished Goods lead time before Shipping = [15,700/2,700] = 5.81 days

The cell’s total production lead time is 1.48 + 1.85 + 0.74 + 0.59 + 5.81 = 10.47 daysd. The manufacturing cell’s total processing time is (11 + 10 + 17 + 15) = 53 seconds.e. The cell’s capacity may be calculated by locating the bottleneck and computing the number

of units that it can process in the available time per day at that bottleneck.

SOLUTION

a. Figure 4.13 shows the current value stream state map for Metcalf, Inc.

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LEAN SYSTEMS CHAPTER 4 191

Discussion Questions1. Compare and contrast the following two situations:

a. A company’s lean system stresses teamwork. Employees feel more involved, and therefore, pro-ductivity and quality increase at the company. The problem is that workers also experience a loss of indi-vidual autonomy.

b. A humanities professor believes that all students want to learn. To encourage students to work together and learn from each other—thereby increasing the involvement, productivity, and the quality of the learning experience—the professor announces that all students in the class will receive the same grade and that it will be based on the performance of the group.

2. Which elements of lean systems would be most troublesome for manufacturers to implement? Why?

3. List the pressures that lean systems pose for supply chains, whether in the form of process failures due to inventory shortages or labor stoppages, and so forth. Reflect on how these pressures may apply to a firm that is actually implementing lean philosophy in its operations.

4. Assume you are a management consultant tasked with improving the efficiency of a production process of an FMCG product of your choice. List the steps you will take to draw the value stream map. Who will you engage and what data will you collect? Identify challenges you might encounter in this process.

The OM Explorer, POM for Windows, and Active Model soft-ware is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how

to do the calculations by hand. At the least, the software pro-vides a check on your calculations. When calculations are particularly complex and the goal is interpreting the results in making decisions, the software replaces entirely the manual calculations.

Problems

Strategic Characteristics of Lean Systems

1. Swenson Saws produces bow, frame, dovetail, and tenon saws used by craft furniture makers. During an 8-hour shift, a saw is produced every 6 minutes. The demand for bow, frame, and dovetail saws is about the same, but the demand for tenon saws is twice the demand for the other three.

a. If mixed-model scheduling is used, how many of each saw will be produced before the cycle is repeated?

b. Determine a satisfactory production sequence for one unit production. How often is this sequence repeated?

c. How many of each saw does Swenson produce in one shift?

2. The Harvey Motorcycle Company produces three mod-els: the Tiger, a sure-footed dirt bike; the LX2000, a nimble café racer; and the Golden, a large interstate tourer. This month’s master production schedule calls for the production of 54 Goldens, 42 LX2000s, and 30 Tigers per 7-hour shift.

a. What average cycle time is required for the assembly line to achieve the production quota in 7 hours?

b. If mixed-model scheduling is used, how many of each model will be produced before the production cycle is repeated?

c. Determine a satisfactory production sequence for the ultimate in small-lot production: one unit.

d. The design of a new model, the Cheetah, includes features from the Tiger, LX2000, and Golden mod-els. The resulting blended design has an indecisive character and is expected to attract some sales from the other models. Determine a mixed-model sched-ule resulting in 52 Goldens, 39 LX2000s, 26 Tigers, and 13 Cheetahs per 7-hour shift. Although the total number of motorcycles produced per day will increase only slightly, what problem might be antici-pated in implementing this change from the produc-tion schedule indicated in part (b)?

3. The Farm-4-Less tractor company produces a grain com-bine (GC) in addition to both a large (LT) and small size tractor (SM). Its production manager desires to produce to customer demand using a mixed-model production line. The current sequence of production, which is repeated 30 times during a shift, is SM-GC-SM-LT-SM-GC-LT-SM. A new machine is produced every 2 minutes. The plant operates two 8-hour shifts. There is no down-time because the 4 hours between each shift are dedi-cated to maintenance and restocking raw material. Based on this information, answer the following questions.

a. How long does it take the production cycle to be completed?

b. How many of each type of machine does Farm-4-Less produce in a shift?

Capacity at Forming Capacity at Drilling Capacity at Grinding Capacity at Packaging

Per Unit Processing Time = (11 + 3.6) = 14.6 seconds

Per Unit Processing Time = (10 + 2.4) = 12.4 seconds

Per Unit Processing Time = (17 + 0) = 17.0 seconds

Per Unit Processing Time = (15 + 0) = 15.0 seconds

a. At a batch size of 50 units, Finish Grinding process is the bottleneck

b. Availability at Grinding = 54,000 seconds per day

c. Time at bottleneck (with setup) = 17.0 seconds

d. Capacity (Availability/Time at bottleneck) = 54,000/17 = 3,176 units per day

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192 PART 1 MANAGING PROCESSES

◀ FIGURE 4.14Components for End Item Bicycle

WS1 (2)

Bicycle

WS2 (3)

The Kanban System

4. A fabrication cell at Spradley’s Sprockets uses the pull method to supply gears to an assembly line. George Jit-son is in charge of the assembly line, which requires 500 gears per day. Containers typically wait 0.20 day in the fabrication cell. Each container holds 20 gears, and one container requires 1.8 days in machine time. Setup times are negligible. If the policy variable for unforeseen contin-gencies is set at 5 percent, how many containers should Jitson authorize for the gear replenishment system?

5. A bread manufacturing firm has recently implemented a Kanban system for tracking the consumption of raw mate-rials, especially wheat flour. The average daily demand for wheat is 2,500 kg. The firm’s records show that it takes around 4 hours for the flour to be transformed into bread and another 4 hours in material handling and wait-ing time during the manufacturing cycle. Due to uncer-tain demand, the firm has a safety stock of 25 percent. Each container can hold 250 kg of wheat flour.

a. Calculate the number of containers required by the firm.

b. Management is planning to reduce the number of containers used. A reliable supplier has been identi-fied, which eliminates the need for additional stock. Determine the required reduction in waiting time if one container is removed.

6. Terai Motors buys semi-finished products from suppliers and assembles them based on customer preferences. Dur-ing the customization process, two wheels, one handle-bar, one seat, and a luggage box are attached to develop the end product. Wheels are attached in workstation 1, while handlebar, seat, and luggage box are attached in workstation 2, as shown in Figure 4.14. The daily produc-tion quota on the assembly line is 80 bikes. The container for wheel assembly can hold eight units, and the policy variable for workstation 1 is 0.10. The average waiting time for container of wheels is 0.09 day, while 0.06 day is required for processing. The container for workstation 2 can hold 50 units, and the policy variable for workstation 2 is 0.08. The average waiting time for workstation 2 is 0.14 day, while processing time is 0.20 day.

demand can be satisfied with this system? (Hint: Recall that r is the average processing time per container, not per individual part.)

8. A watch manufacturing company in Switzerland is considering the number of trays it must deploy in its manufacturing process. Watches are hand-assembled by a team of experienced watchmakers and sent in a purpose-built watch holding tray for quality assurance. Each tray can hold 30 watches. The quality professional first examines the dial, sets the time, and loads the tray onto a metal container which simulates movement 24 hours. This process takes 2 minutes per watch. The watches are reexamined for time accuracy which takes another 45 seconds per watch and if they pass the test, they are sent for strap attachment. The empty trays are returned to the assembly line from the strap attachment department. How many trays should circulate between the assembly line and the strap attachment department if 1000 watches are to be examined during an 8-hour shift? The average processing time and waiting time is 2 days. The value of the safety stock policy variable, a, is zero.

9. The production schedule at Mazda calls for 1,200 Mazdas to be produced during each of 22 production days in January and 900 Mazdas to be produced during each of 20 production days in February. Mazda uses a Kanban system to communicate with Gesundheit, a nearby sup-plier of tires. Mazda purchases four tires per vehicle from Gesundheit. The safety stock policy variable, a, is 0.15. The container (a delivery truck) size is 200 tires. The average waiting time plus materials handling time is 0.16 day per container. Assembly lines are rebalanced at the beginning of each month. The average processing time per container in January is 0.10 day. The February processing time will average 0.125 day per container. How many containers should be authorized for January? How many for February?

10. Jitsmart is a retailer of plastic action-figure toys. The action figures are purchased from Tacky Toys, Inc., and arrive in boxes of 48. Full boxes are stored on high shelves out of reach of customers. A small inventory is maintained on child-level shelves. Depletion of the lower-shelf inventory signals the need to take down a box of action figures to replenish the inventory. A reorder card is then removed from the box and sent to Tacky Toys to authorize replenishment of a container of action figures. The average demand rate for a popular action figure, Agent 99, is 36 units per day. The total lead time (waiting plus processing) is 11 days. Jitsmart’s safety stocky policy variable, a, is 0.25. What is the authorized stock level for Jitsmart?

11. Markland First National Bank of Rolla utilizes Kanban techniques in its check processing facility. The fol-lowing information is known about the process. Each Kanban container can hold 50 checks and spends 24 minutes a day in profcessing and 2 hours a day in materials handling and waiting. Finally, the facility operates 24 hours per day and utilizes a policy variable for unforeseen contingencies of 0.25.

a. If 20 Kanban containers are in use, what is the cur-rent daily demand of the check processing facility?

b. If the muda, or the waste, in the system were elimi-nated completely, how many containers would then be needed?

a. Calculate the number of containers needed in work-station 1.

b. Calculate the number of containers needed in work-station 2.

7. Gestalt, Inc., uses a Kanban system in its automo-bile production facility in Germany. This facility operates 8 hours per day to produce the Jitterbug, a replacement for the obsolete but immensely popular Jitney Beetle. Suppose that a certain part requires 150 seconds of processing at machine cell 33B and a container of parts average 1.6 hours of waiting time there. Management allows a 10 percent buffer for unexpected occurrences. Each container holds 30 parts, and 8 containers are authorized. How much daily

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LEAN SYSTEMS CHAPTER 4 193

Value Stream Mapping

12. Figure 4.15 provides a new current state value stream map for the family of retainers at the Jensen Bearings, Inc. firm described in Example 4.1. This map depicts the value stream after Kline Steel agrees to accept daily orders for steel sheets and Jensen Bearings continues to deliver the finished goods on a daily basis.

Calculate each component of the new value stream’s reduced lead time.

a. How many days of raw material does the Bearing’s plant now hold?

b. How many days of work-in-process inventory is held between Press and Pierce & Form?

c. How many days of work-in-process inventory is held between Pierce & Form and Finish Grind?

d. How many days of work-in-process inventory is held between Finish Grind and Shipping?

e. What is the new value steam’s production lead time?

f. What is the new value stream’s processing time?

13. A garment manufacturer is interested in using the data col-lected during value stream mapping to evaluate the current state performance of the capacity of its manual assembly line process and would like to identify the ideal batch size for its operations. The productive capacity of the staff is 420 minutes per day. To manufacture a garment after design approval, clothes are cut into desired shape, fol-lowed by sewing of front and back, and then attachments of hand, collars, and buttons. The current operating charac-teristics of each processing step are found in the accompa-nying table. Note that each step can only process one part at a time and all steps must process the same sized batches.

Shape Sewing Hand Collar Buttons

Cycle time per shirt

2 minutes 7 minutes 3 minutes 5 minutes 6 minutes

Setup time per batch

15 minutes 18 minutes 0 minutes 10 minutes 20 minutes

a. Calculate the average processing time per unit and the capacity at each step assuming batch sizes of:

i. 20 shirtsii. 30 shirts

iii. 35 shirtsiv. 40 shirts

b. Identify the bottleneck operation for each batch size.c. What is the optimum batch size after which there

will be no improvement in the line’s processing capacity?

14. The manager at Ormonde, Inc., collected the value stream mapping data from the plant’s most problematic manufacturing cell that fabricates parts for washing machines. These data are shown in Table 4.5. Using these data, calculate the current state performance of the cell and answer the following questions.a. What is the cell’s current inventory level?b. What is the takt time for this manufacturing cell?c. What is the production lead time at each process in

the manufacturing cell?d. What is the total processing time of this

manufacturing cell?e. What is the capacity of this manufacturing cell?

◀ FIGURE 4.15New Current State Value Stream Map at Jensen Bearings, Inc.

I

Sheets1 day

a

C/T = 3 secondsC/O = 2 hoursUptime = 100%25,200 sec. avail.1 Shift

C/T = 22 secondsC/O = 30 minutesUptime = 100%

25,200 sec. avail.

C/T = 35 secondsC/O = 45 minutesUptime = 100%

25,200 sec. avail.

4-weekForecast

PRODUCTIONCONTROL

Weekly Schedule

DailyOrder

DailyOrder

Daily ShipSchedule

PRESS

3 secondsb

22 secondsc

35 secondsd

1I

1,050 “L”1,200 “S”

PIERCE & FORM

1I

250 “L”1,500 “S”

FINISH GRIND

1I

500 “L”1,200 “S”

1x/Day1x/Day

KlineSteel Co.

2,500 pieces/week–1,500 “L”–1,000 “S”

Tray = 50 pieces1 shift

GNKEnterprises

180/90/60/30/dayForecasts

SHIPPING

Staging

ProductionLead Time

= e

ProcessingTime

= f

1 Shift1 Shift

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194 PART 1 MANAGING PROCESSES

Overall Process Attributes

Average demand: 550/day

Batch size: 20

Number of shifts per day: 3

Availability: 8 hours per shift with a 45-minute lunch break

Process Step 1 Cutting Cycle time = 120 secondsSetup time = 3 minutesUptime = 100%Operators = 1WIP = 400 units (Before Cutting)

Process Step 2 Bending Cycle time = 100 secondsSetup time = 5 minutesUptime = 100%Operators = 1WIP = 500 units (Before Bending)

Process Step 3 Punching Cycle time = 140 secondsSetup time = noneUptime = 100%Operators = 1WIP = 200 units (Before Punching)WIP = 1,000 units (After Punching)

Customer Shipments One shipment of 2,750 units each week

Information Flow All communications with customer are electronic

There is a weekly order release to Cutting

All material is pushed

TABLE 4.5 | OPERATIONS DATA FOR ORMONDE, INC.

CASE Copper Kettle Catering

Copper Kettle Catering (CKC) is a full-service catering company that provides services ranging from box lunches for picnics or luncheon meetings to large wedding, dinner, or office parties. Established as a lunch delivery service for offices in 1972 by Wayne and Janet Williams, CKC has grown to be one of the largest catering businesses in Raleigh, North Carolina. The company divides customer demand into two categories: deliver only and deliver and serve.

The deliver-only side of the business delivers boxed meals consisting of a sandwich, salad, dessert, and fruit. The menu for this service is limited to six sandwich selections, three salads or potato chips, and a brownie or fruit bar. Grapes and an orange slice are included with every meal, and iced tea can be ordered to accompany the meals. The overall level of demand for this service throughout the year is fairly constant, although the mix of menu items delivered varies. The planning horizon for this segment of the business is short: Customers usually call no more than a day ahead of time. CKC requires customers to call deliver-only orders in by 10:00 a.m. to guarantee delivery the same day.

The deliver-and-serve side of the business focuses on catering large parties, dinners, and weddings. The extensive range of menu items includes a full selection of hors d’oeuvres, entrées, beverages, and special-request items. The demand for these services is much more seasonal, with heavier demands occurring in the late spring–early summer for weddings and the late fall–early winter for holiday parties. However, this segment also has a longer

planning horizon. Customers book dates and choose menu items weeks or months ahead of time.

CKC’s food preparation facilities support both operations. The physical facilities layout resembles that of a job process. Five major work areas consist of a stove–oven area for hot food preparation, a cold area for salad prepara-tion, an hors d’oeuvre preparation area, a sandwich preparation area, and an assembly area where deliver-only orders are boxed and deliver-and-serve orders are assembled and trayed. Three walk-in coolers store foods requiring refrigeration, and a large pantry houses nonperishable goods. Space limita-tions and the risk of spoilage limit the amount of raw materials and prepared food items that can be carried in inventory at any one time. CKC purchases desserts from outside vendors. Some deliver the desserts to CKC; others require CKC to send someone to pick up desserts at their facilities.

The scheduling of orders is a two-stage process. Each Monday, Wayne and Janet develop the schedule of deliver-and-serve orders to be processed each day. CKC typically has multiple deliver-and-serve orders to fill each day of the week. This level of demand allows a certain efficiency in the preparation of multiple orders. The deliver-only orders are scheduled day to day, owing to the short-order lead times. CKC sometimes runs out of ingredients for deliver-only menu items because of the limited inventory space.

Wayne and Janet have 10 full-time employees: two cooks and eight food preparation workers, who also work as servers for the deliver-and-serve orders.

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LEAN SYSTEMS CHAPTER 4 195

In periods of high demand, they hire additional part-time servers. The position of cook is specialized and requires a high degree of training and skill. The rest of the employees are flexible and move between tasks as needed.

The business environment for catering is competitive. The competitive priorities are high-quality food, delivery reliability, flexibility, and cost—in that order. “The quality of the food and its preparation is paramount,” states Wayne Williams. “Caterers with poor-quality food will not stay in business long.” Quality is measured by both freshness and taste. Delivery reliability encom-passes both on-time delivery and the time required to respond to customer orders (in effect, the order lead time). Flexibility focuses on both the range of catering requests that a company can satisfy and menu variety.

Recently, CKC began to notice that customers are demanding more menu flexibility and faster response times. Small specialty caterers who entered the market are targeting specific well-defined market segments. One example is a small caterer called Lunches-R-Us, which located a facility in

the middle of a large office complex to serve the lunch trade and competes with CKC on cost.

Wayne and Janet Williams are impressed by the lean systems concept, especially the ideas related to increasing flexibility, reducing lead times, and lowering costs. They sound like what CKC needs to remain competitive. However, the Williamses wonder whether lean concepts and practices are transferable to a service business.6

QUESTIONS1. Are the operations of Copper Kettle Catering conducive to the application

of lean concepts and practices? Explain.2. What, if any, are the major barriers to implementing a lean system at

Copper Kettle Catering?3. What would you recommend that Wayne and Janet Williams do to take

advantage of lean concepts in operating CKC?

6Source: This case was prepared by Dr. Brooke Saladin, Wake Forest University, as a basis for classroom discussion. Copyright © Brooke Saladin. Reprinted by permission.

VIDEO CASE Lean Systems at Autoliv

Autoliv is a world-class example of lean manufacturing. This Fortune 500 company makes automotive safety components such as seat belts, air-bags, and steering wheels, and has over 80 plants in more than 32 countries. Revenues in 2007 topped $6.7 billion. Autoliv’s lean manufacturing environment is called the Autoliv Production System (APS) and is based on the principles of lean manufacturing pioneered by Toyota, one of the world’s largest automobile manufacturers, and embodied in its Toyota Production System (TPS).

At the heart of Autoliv is a system that focuses on continuous improve-ment. Based on the “House of Toyota,” Autoliv’s Ogden, Utah, airbag module plant puts the concepts embodied in the house to work every day. The only difference between the Toyota house and the one at Autoliv is that the company has added a third pillar to its house to represent employee involvement in all processes because a culture of involvement, while the norm in Japan, is not always found in the United States.

Autoliv started its lean journey back in 1995. At that time, the Ogden plant was at manufacturing capacity with 22 work cells. Company managers acknowledge that, back then, Autoliv was “broken” and in need of significant and immediate change if it was to survive. This meant that everyone—from senior management to employees and suppliers—needed to be onboard with rebuilding the company. It was not that the company could not fulfill the needs of its automaker customers; however, with increasing demand for both reliable and cost-effective component supplies, pressure to change became obvious. Recognizing the value of Toyota’s approach, senior management made the commitment to embark on its own journey to bring the transformative culture of lean manufacturing to Autoliv.

In 1998, sensei Takashi Harada arrived from Japan to spend 3 years teaching top company managers the principles, techniques, and culture of the lean system. This helped managers create an environment in which con-tinuous improvement could be fostered and revered as an essential activity for long-term success. Because the environment was changing, it made it difficult at first for suppliers to meet Autoliv’s constantly changing and unstable processes. It also made problems visible and forced the company to address and resolve the problems instead of finding ways to work around them, as had been done in the past. Daily audits, monthly training, and more in-depth education programs were created to help focus attention on where changes

needed to be made. Workers and management were organized into teams that were held accountable for common goals and tasked with working toward common success.

By 2004, the lean culture was integrated into the company, and it now hosts regular visits by other corporations who want to learn from Autoliv’s journey and experiences. Compared to 1995, the space required for a typical work cell has been reduced by 88.5 percent, while the number of cells has grown over 400 percent. This has allowed Autoliv to dramatically increase its production capacity with minimal investment.

Lean concepts play out every day in each plant. For example, everyone gathers at the start of the workday for preshift stretching and a brief meeting—this is part of the employee involvement pillar in the APS House. Then, workers head to one of 104 work cells on the plant floor. Heijunka Room team members deliver heijunka cards to each cell to communicate the work to be done in that cell. Lot sizes may vary with each card delivered to the cell. Everything the workers need to make the lot is in the cell and regularly replenished through the Kanban card system. Every 24 minutes, another heijunka card comes to the cell to signal workers what they will build next. This is part of the JIT pillar in the house.

Since a culture of continuous improvement requires employees at every level to be responsible for quality, a worker may identify an “abnormal condi-tion” during work execution that slows down the work of the cell, or stops it altogether. This is embodied in the right pillar of the Toyota house—jidoka, which Autoliv interprets as “stop and fix.” This is a rare occurrence, how-ever, since both Autoliv and its suppliers are expected to deliver defect-free products. When a supplier is new or has experienced quality issues, the supplier pays for inspection in Autoliv’s receiving dock area until Autoliv is certain the supplier can meet quality expectations for all future deliveries. In this manner, workers in the cells know they can trust the integrity of the raw materials arriving through the Kanban system into their cells for assembly. Jidoka may also come into play when a machine does not operate properly or an employee notices a process that has deviated from the standard. When workers “stop and fix” a problem at the point of its creation, they save the company from added cost as well as lost confidence in the eyes of the customer.

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To help focus worker efforts daily, Autoliv has a blue “communication wall” that all workers see as they head to their worksite. The wall contains the company’s “policy deployment,” which consists of company-wide goals for customer satisfaction, shareholder/financial performance, and safety and quality. The policy deployment begins with the company-wide goals, which then flow down to the plant level through the plant manager’s goals, strate-gies, and actions for the facility. These linked activities ensure that Autoliv achieves its goals. By communicating this information—and more—in a visual manner, the central pillar of the APS House is supported. Other visual communication and management methods are in place as well. For example, each cell has an overhead banner that states how that cell is doing each month in the areas of safety, quality, employee involvement, cost, and delivery. These all tie into the policy deployment shown on the communication wall.

Another visual communication method is to use a “rail” for the manage-ment of the heijunka cards in each cell. The rail has color-coded sections. As each card is delivered, it slides down a color-coded railing to the team. At the end nearest the cell, the rail is green, indicating that any cards that fall into this area can be completed within normal working hours. The middle of the rail is yellow, indicating overtime for the cell that day. The end is red, meaning weekend overtime is required to bring work processes back into harmony with customer demand. As a heijunka card slides down the rail, it stops when it

hits the end or stacks up behind another card. If the cell is not performing at the required pace to meet customer demand, the cards will stack up on the rail and provide a very visual cue that the cell is not meeting expectations. This provides an opportunity for cell team members as well as management to implement immediate countermeasures to prevent required overtime if the situation is not remedied.

All aisles and walkways surrounding cells are to be clear of materi-als, debris, or other items. If anything appears in those areas, everyone can quickly see the abnormality. As team members work together to complete their day’s work, the results of their efforts are displayed boldly on each cell’s “communi-cube.” This four-sided rotating display visually tells the story of the cell’s productivity, quality, and 5S performance. The cube also contains a special section for the management of kaizen suggestions for the team itself. These kaizens enable the team to continuously improve the work environment as well as drive the achievement of team results.

Autoliv’s lean journey embodied in the Autoliv Production System has led to numerous awards and achievement of its policy deployment goals. Product defects have been dramatically reduced, inventory levels are lower, and inven-tory turnover is approaching world-class levels of 50. Employee turnover is close to 5 percent and remains well below that of other manufacturers in the industry. Yet the destination has not been reached. The company continues its emphasis on driving systemic improvement to avoid complacency and loss of competitive advantage. Best practices from sources beyond each immedi-ate area of the organization are studied and integrated. And finding ways to engage and reward Autoliv’s workforce in a maturing market is critical. Kaizen suggestions in the most recent year at the Ogden plant totaled 74,000, or nearly 60 per employee, indicating the culture of continuous improvement in Autoliv’s APS House is alive and well.

QUESTIONS1. Why is a visual management approach such an integral part of Autoliv’s

lean system?2. Describe the JIT considerations presented in the chapter as they relate

to Autoliv’s manufacturing environment.3. Which method of workflow is embodied in Autoliv’s system? Why is this

approach most suitable to its lean environment?4. When Autoliv started its lean journey, a number of operational benefits

and implementation issues had to be addressed. What were they, and how were they addressed?

Autoliv employee folds an air bag in a Toyota-inspired production cell.

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197

LEARNING OBJECTIVES After reading this chapter, you should be able to:

5CAPACITY PLANNING

3M

Minnesota Mining and Manufacturing (3M) company is a diversified conglomerate that has operations in more than 70 countries. It manufactures over 60,000 products, such as adhesives, window films,

paint protection films, laminates, and consumer products like Scotch tape and Post-its, among others, that are used in the health care, manufacturing, and construction industries, as well as several others. With nearly $33 billion in sales and 93,500 employees in 2018, 3M has been an icon of innovation and steady growth since its founding as a mining company in Minnesota in 1902.

5.1 Define long-term capacity and its relationship with econ-omies and diseconomies of scale.

5.2 Understand the main differences between the expan-sionist and wait-and-see capacity timing and sizing strategies.

5.3 Identify a systematic four-step approach for determining long-term capacity requirements and associated cash flows.

5.4 Describe how the common tools for capacity planning, such as waiting-line models, simulation, and decision trees, assist in capacity decisions.

3M produces the N95 type respirator masks for the coronavirus.NA

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3M is also the manufacturer of N95 respirator masks, which are so named because they can block 95% of airborne particles as small as 0.3 micron, which is 1/100 the thickness of human hair, from entering the mouth of the wearer. They were critically needed to protect frontline health care workers in hospitals and clinics when the global COVID-19 pandemic came to the U.S. shores early in 2020, and then escalated dramatically in March 2020. Manufacturing plants that make these masks are located in China, Latin America, Europe, and the United States. The demand soon far outstripped the available capacity, and the shortage was so acute that the U.S. government requested 3M not only to stop exporting N95 masks manufactured in the United States, but, through the Defense Production Act, also required 3M to import 166.5 million masks from its Shanghai plant over a 3-month period starting in April. Along with Honeywell and Kimberly Clark, 3M is the only major producer of such masks in the United States.

How does a firm increase its production capacity in such a short time to meet massive demand that could not have been foreseen ahead of time? Learning from the SARS epidemic in 2002–2003, 3M built “surge capacity” in its respirator manufacturing plants across the globe to prepare for such emergencies. Factories added assembly lines that would not be used in normal times, and suppliers were similarly put on alert to be ready when needed. 3M also started sourcing its materials for respirators close to its assembly plants, from which it served its customers in the same markets. Having secured over $200 million worth of federal contracts, 3M is now using this surge capacity and localized supply chains to make more than a billion masks by the end of 2020. At its 450,000-square-foot respirator mask factory in Aberdeen, South Dakota, idle machine capacity installed for this purpose was activated. Robots and other automation loaded assembly lines with mask components such as respirator cups, filters, nose clips, and nose foam. Its 650 workers started working overtime to keep packaging and other operations running 7 days a week, while maintaining a safe 6-foot social distancing rule by placing yellow markers on the shop floor. An additional 500 workers were hired and underwent medical exams and training before starting work. Workers generally take great pride in working at a respirator mask manufacturing plant.

3M has doubled its global production to 95 million masks a month in just 2 months, and is investing in new equipment to build two new N95 assembly lines at its Aberdeen, South Dakota plant. It is also building an N95 assembly line in Wisconsin, which will eventually move to Aberdeen, South Dakota. These additions in capacity will push its global output to two billion N95 masks within 12 months. Through astute forward planning, flawless execution, and massive capacity expansion, 3M could literally prove to be a life saver in the fight against a global pandemic that has shown little sign of abating since its advent in late 2019.1

1Sources: Brian Gruley and Rick Clough, “How 3M Plans to Make More Than a Billion Masks by End of Year,” Bloomberg Businessweek (March 25, 2020), https://www.bloomberg.com/news/features/2020-03-25/3m-doubled-production-of-n95-face-masks-to-fight-coronavirus (June 29, 2020); Dee DePass, “3M Wins Defense Contract, Boosting US N95 Production Even More to 95M Monthly,” Star Tribune (May 7, 2020); https://en.wikipedia.org/wiki/3M (June 29, 2020); https://www.assemblymag.com/articles/95705-m-to-triple-monthly-us-production-of-n95-masks (June 29, 2020).

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Capacity is the maximum rate of output of a process or a system. Managers are responsible for ensuring that the firm has the capacity to meet current and future demand. Otherwise, the organization will miss out on opportunities for growth and profits. Making adjustments to decrease capacity, or to increase it, is therefore an important part of the job. Acquisition of new capacity requires extensive planning and often involves significant expenditure of resources and time. Bringing new capacity online can take several years, for instance, in the semiconductor industry or in the construction of new nuclear power plants. Sometimes firms do not have enough time available to build new plants in order to meet sudden demand, and so must plan ahead by investing in excess surge capacity, as illustrated by 3M.

Capacity decisions related to a process need to be made in light of the role the process plays within the organization and the supply chain as a whole, because changing the capacity of a process will have an impact on other processes within the firm and across the chain. As such, capacity decisions have implications for different functional areas through-out the organization. Accounting needs to provide the cost information needed to evaluate capacity expansion decisions. Finance performs the financial analysis of proposed capacity expansion investments and raises funds to support them. Marketing provides demand forecasts required to identify capacity gaps. Management information systems design the electronic infrastructure that is needed to make data such as cost information, financial performance measures, demand forecasts, and work standards available to those needing it to analyze capacity options. Operations is involved in the selection of capacity strategies that can be implemented to effectively meet future demand. Purchasing facilitates acquisition of outside capacity from suppliers. Finally, human resources focuses on hiring and training employees needed to support internal capacity plans. So, all departments in a firm get involved with and are affected by long-term capacity planning decisions.

Increasing or decreasing capacity by itself is not as important as ensuring that the entire sup-ply chain, from order entry to delivery, is designed for effectiveness. Capacity decisions must be made in light of several long-term issues such as the firm’s economies and diseconomies of scale, capacity cushions, timing and sizing strategies, and trade-offs between customer service and capacity utilization. Therefore, this chapter focuses on how managers can best revise capac-ity levels and best determine when to add or reduce capacity for the long term. The type of capacity decisions differ for dif-ferent time horizons. Both long-term and short-term issues associated with plan-ning capacity and managing constraints are important and must be understood in conjunction with one another. While we deal with the long-term decisions here in the capacity management framework, short-term decisions centered on making the most of existing capacity by manag-ing constraints are more fully explored in Chapter 6, “Constraint Management.”

Planning Long-Term CapacityLong-term capacity plans deal with investments in new facilities and equipment at the organiza-tional level and require top management participation and approval because they are not easily reversed. These plans cover at least 2 years into the future, but construction lead times can some-times be longer and result in longer planning time horizons.

Long-term capacity planning is central to the success of an organization. Too much capacity can be as agonizing as too little. Often entire industries can fluctuate over time between too much and too little capacity, as evidenced in the airline and cruise ship industry over the past 20 years. When choosing a capacity strategy, managers must consider questions such as the following: How much of a cushion is needed to handle variable, or uncertain, demand? Should we expand capac-ity ahead of demand, as Tesla did with battery production by building the world’s largest battery

capacity

The maximum rate of output of a process or a system.

Using Operations to Create Value

Part 1

Managing Processes

Designing andoperating processes inthe firm

Managing Processes

Managing Supply Chains

Process Strategy and AnalysisQuality and Performance

Lean SystemsCapacity Planning

Constraint ManagementProject Management

Forecasting demands anddeveloping inventory plansand operating schedules

Designing an integrated andsustainable supply chain of

connected processes between firms

Managing Customer Demand

Capacity management

Constraint management (short-term)• Theory of constraints• Identification and management of bottlenecks• Product mix decisions using bottlenecks• Managing constraints in a line process

Capacity planning (long-term)• Economies and diseconomies of scale• Capacity timing and sizing strategies• Systematic approach to capacity decisions

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200 PART 1 MANAGING PROCESSES

drive costs down when output increases: (1) Fixed costs are spread over more units; (2) construction costs are reduced; (3) costs of purchased materials are cut; and (4) process advantages are found.

Spreading Fixed Costs In the short term, certain costs do not vary with changes in the output rate. These fixed costs include heating costs, debt service, and managers’ salaries. The deprecia-tion of plant and equipment already owned is also a fixed cost in the accounting sense. When the average output rate—and, therefore, the facility’s utilization rate—increases, the average unit cost drops because fixed costs are spread over more units.

Reducing Construction Costs Certain activities and expenses are required to build small and large facilities alike: building permits, architects’ fees, and rental of building equipment. Doubling the size of the facility usually does not double construction costs.

Cutting Costs of Purchased Materials Higher volumes can reduce the costs of purchased materi-als and services. They give the purchaser a better bargaining position and the opportunity to take advantage of quantity discounts. Retailers such as Walmart reap significant economies of scale because their national and international stores buy and sell huge volumes of each item.

Finding Process Advantages High-volume production provides many opportunities for cost reduction. At a higher output rate, the process shifts toward a line process, with resources dedi-cated to individual products. Firms may be able to justify the expense of more efficient technology or more specialized equipment. The benefits from dedicating resources to individual services or products may include speeding up the learning effect, lowering inventory, improving process and job designs, and reducing the number of changeovers.

Diseconomies of ScaleBigger is not always better, however. At some point, a facility can become so large that diseconomies of scale set in; that is, the average cost per unit increases as the facility’s size increases. The reason is that excessive size can bring complexity, loss of focus, and inefficien-cies that raise the average unit cost of a service or product. Too many layers of employees and bureaucracy can cause management to lose touch with employees and customers. A less agile organization loses the flexibility needed to respond to changing demand. Many large companies become so involved in analysis and planning that they innovate less and avoid risks. The result is that small companies outperform corporate giants in numerous industries.

Figure 5.1 illustrates the transition from economies of scale to diseconomies of scale. The 500-bed hospital shows economies of scale because the average unit cost at its best operating level, represented by the blue dot at which the lowest average unit cost is attained, is less than that of the 250-bed hos-pital. However, assuming that sufficient demand exists, further expansion to a 750-bed hospital leads to higher average unit costs and diseconomies of scale. One reason the 500-bed hospital enjoys greater economies of scale than the 250-bed hospital is that the cost of building and equipping it is less than twice the cost for the smaller hospital. The 750-bed facility would enjoy similar savings. Its higher average unit costs can be explained only by diseconomies of scale, which outweigh the savings realized in construction costs.

Figure 5.1 does not mean that the optimal size for all hospi-tals is 500 beds. Optimal size depends on the number of patients per week to be served. On the one hand, a hospital serving a small community could have lower costs by choosing a 250-bed capacity rather than the 500-bed capacity. On the other hand, a large community might be served more efficiently by two 500-bed hospitals than by one 1,000-bed facility if disecono-mies of scale exist at the bigger size.

Capacity Timing and Sizing StrategiesOperations managers must examine three dimensions of capacity strategy before making capacity decisions: (1) sizing capacity cushions, (2) timing and sizing expansion, and (3) linking process capacity and other operating decisions.

Sizing Capacity CushionsAverage utilization rates for any resource should not get too close to 100 percent over the long term, though it may occur for some processes from time to time in the short run. If the demand keeps increasing over time, then long-term capacity must be increased as well to provide some buffer against uncertainties. When average utilization rates approach 100 percent, it is usu-ally a signal to increase capacity or decrease order acceptance to avoid declining productivity.

economies of scale

A concept that states that the average unit cost of a service or good can be reduced by increas-ing its output rate.

diseconomies of scale

Occurs when the average cost per unit increases as the facility’s size increases.

factory at an expense of $4 to $5 billion, or wait until demand is more certain? Even before these questions can be answered, a manager needs to be able to measure a process’s capacity. So, a systematic approach is needed to answer these and similar questions and to develop a capacity strategy appropriate for each situation.

Measures of Capacity and UtilizationNo single capacity measure is best for all situa-tions. A retailer measures capacity as annual sales dollars generated per square foot, whereas an air-line measures capacity as available seat-miles (ASMs) per month. A theater measures capacity as number of seats, while a job shop measures capacity as number of machine hours. In general, capacity can be expressed in one of two ways: in terms of output measures or input measures.

Output Measures of Capacity Output measures of capacity are best utilized when applied to indi-vidual processes within the firm or when the firm provides a relatively small number of standard-

ized services and products. High-volume processes, such as those in a car manufacturing plant, are a good example. In this case, capacity would be measured in terms of the number of cars produced per day. However, many processes produce more than one service or product. As the amount of customization and variety in the product mix increases, output-based capacity measures become less useful. Then input measures of capacity become the usual choice for measuring capacity.

Input Measures of Capacity Input measures are generally used for low-volume, flexible pro-cesses, such as those associated with a custom furniture maker. In this case, the furniture maker might measure capacity in terms of inputs such as number of workstations or number of workers. The problem with input measures is that demand is invariably expressed as an output rate. If the furniture maker wants to keep up with demand, he or she must convert the business’s annual demand for furniture into labor hours and number of employees required to fulfill those hours. We will explain precisely how this input–output conversion is done later in the chapter.

Utilization Utilization is the degree to which a resource such as equipment, space, or the work-force is currently being used and is measured as the ratio of average output rate to maximum capacity (expressed as a percent). The average output rate and the capacity must be measured in the same terms—that is, time, customers, units, or dollars. The utilization rate indicates the need for adding extra capacity or eliminating unneeded capacity.

Utilization =Average output rate

Maximum capacity* 100%

Here, we refer to maximum capacity as the greatest level of output that a process can reason-ably sustain for a longer period, using realistic employee work schedules and the equipment cur-rently in place. In some processes, this capacity level implies a one-shift operation; in others, it implies a three-shift operation. A process can be operated above its capacity level using marginal methods of production, such as overtime, extra shifts, temporarily reduced maintenance activities, overstaffing, and subcontracting. Although they help with temporary peaks, these options cannot be sustained for long. For instance, being able to handle 40 customers for a 1-week peak is quite different from sustaining it for 6 months. Employees do not want to work excessive overtime for extended periods, so quality drops. In addition, the costs associated with overtime drive up the firm’s costs. So operating processes close to (or even temporarily above) their maximum capacity can result in low customer satisfaction, minimal profits, and even losing money despite high sales levels. Such was the case with U.S. aircraft manufacturers in the late 1980s, which culminated in Boeing acquiring McDonnell Douglas in 1997 to rein in skyrocketing costs and plummeting profits.

Economies of ScaleDeciding on the best level of capacity involves consideration for the efficiency of the operations. A concept known as economies of scale states that the average unit cost of a service or good can be reduced by increasing its output rate. Four principal reasons explain why economies of scale can

utilization

The degree to which equip-ment, space, or the workforce is currently being used, and is measured as the ratio of average output rate to maximum capacity (expressed as a percent).

Tesla Supercharger station with 40 charging stations all on solar power. Supercharger sta-tions allow Tesla cars to be fast-charged at the network within an hour. Tesla’s battery charg-ing stations emphasize the close connection between the electric car and the batteries that serve as the main source of energy for this new generation automobile. Tesla’s long-term growth strategies are therefore tied to also expanding its battery manufacturing capacity.

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CAPACITY PLANNING CHAPTER 5 201

drive costs down when output increases: (1) Fixed costs are spread over more units; (2) construction costs are reduced; (3) costs of purchased materials are cut; and (4) process advantages are found.

Spreading Fixed Costs In the short term, certain costs do not vary with changes in the output rate. These fixed costs include heating costs, debt service, and managers’ salaries. The deprecia-tion of plant and equipment already owned is also a fixed cost in the accounting sense. When the average output rate—and, therefore, the facility’s utilization rate—increases, the average unit cost drops because fixed costs are spread over more units.

Reducing Construction Costs Certain activities and expenses are required to build small and large facilities alike: building permits, architects’ fees, and rental of building equipment. Doubling the size of the facility usually does not double construction costs.

Cutting Costs of Purchased Materials Higher volumes can reduce the costs of purchased materi-als and services. They give the purchaser a better bargaining position and the opportunity to take advantage of quantity discounts. Retailers such as Walmart reap significant economies of scale because their national and international stores buy and sell huge volumes of each item.

Finding Process Advantages High-volume production provides many opportunities for cost reduction. At a higher output rate, the process shifts toward a line process, with resources dedi-cated to individual products. Firms may be able to justify the expense of more efficient technology or more specialized equipment. The benefits from dedicating resources to individual services or products may include speeding up the learning effect, lowering inventory, improving process and job designs, and reducing the number of changeovers.

Diseconomies of ScaleBigger is not always better, however. At some point, a facility can become so large that diseconomies of scale set in; that is, the average cost per unit increases as the facility’s size increases. The reason is that excessive size can bring complexity, loss of focus, and inefficien-cies that raise the average unit cost of a service or product. Too many layers of employees and bureaucracy can cause management to lose touch with employees and customers. A less agile organization loses the flexibility needed to respond to changing demand. Many large companies become so involved in analysis and planning that they innovate less and avoid risks. The result is that small companies outperform corporate giants in numerous industries.

Figure 5.1 illustrates the transition from economies of scale to diseconomies of scale. The 500-bed hospital shows economies of scale because the average unit cost at its best operating level, represented by the blue dot at which the lowest average unit cost is attained, is less than that of the 250-bed hos-pital. However, assuming that sufficient demand exists, further expansion to a 750-bed hospital leads to higher average unit costs and diseconomies of scale. One reason the 500-bed hospital enjoys greater economies of scale than the 250-bed hospital is that the cost of building and equipping it is less than twice the cost for the smaller hospital. The 750-bed facility would enjoy similar savings. Its higher average unit costs can be explained only by diseconomies of scale, which outweigh the savings realized in construction costs.

Figure 5.1 does not mean that the optimal size for all hospi-tals is 500 beds. Optimal size depends on the number of patients per week to be served. On the one hand, a hospital serving a small community could have lower costs by choosing a 250-bed capacity rather than the 500-bed capacity. On the other hand, a large community might be served more efficiently by two 500-bed hospitals than by one 1,000-bed facility if disecono-mies of scale exist at the bigger size.

Capacity Timing and Sizing StrategiesOperations managers must examine three dimensions of capacity strategy before making capacity decisions: (1) sizing capacity cushions, (2) timing and sizing expansion, and (3) linking process capacity and other operating decisions.

Sizing Capacity CushionsAverage utilization rates for any resource should not get too close to 100 percent over the long term, though it may occur for some processes from time to time in the short run. If the demand keeps increasing over time, then long-term capacity must be increased as well to provide some buffer against uncertainties. When average utilization rates approach 100 percent, it is usu-ally a signal to increase capacity or decrease order acceptance to avoid declining productivity.

economies of scale

A concept that states that the average unit cost of a service or good can be reduced by increas-ing its output rate.

diseconomies of scale

Occurs when the average cost per unit increases as the facility’s size increases.

▼ FIGURE 5.1Economies and Diseconomies of Scale

Economiesof scale

Output rate (patients per week)

250-bedhospital

Lowest cost forthis size hospital

Lowest unit costacross all hospitals

of different capacities

Lowest cost forthis size hospital

500-bedhospital

Ave

rage

uni

t cos

t(d

olla

rs p

er p

atie

nt)

750-bedhospital

Diseconomiesof scale

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202 PART 1 MANAGING PROCESSES

The capacity cushion is the amount of reserve capacity a process uses to handle sudden increases in demand or temporary losses of production capacity; it measures the amount by which the aver-age utilization (in terms of total capacity) falls below 100 percent. Specifically,

Capacity cushion, C = 100 (%) – Average Utilization rate (%)

The appropriate size of the cushion varies by industry. In the capital-intensive paper industry, where machines can cost hundreds of millions of dollars each, cushions well under 10 percent are preferred. The less capital-intensive hotel industry breaks even with a 60 to 70 percent utilization (40 to 30 percent cushion), and begins to suffer customer-service problems when the cushion drops to 20 percent. The more capital-intensive cruise ship industry prefers cushions as small as 5 percent. Large cushions are particularly vital for front-office processes where customers expect fast service times.

Businesses find large cushions appropriate when demand varies. In certain service industries (the grocery industry, for example), demand on some days of the week is predictably higher than on other days, and even hour-to-hour changes are typical. Long customer waiting times are not acceptable because customers grow impatient if they have to wait in a supermarket checkout line for more than a few minutes. Prompt customer service requires supermarkets to maintain a capacity cushion large enough to handle peak demand. Large cushions also are necessary when future demand is uncertain, particularly if resource flexibility is low. Simulation and waiting-line analysis (see Supplement B, “Waiting Lines”) can help managers better anticipate the relationship between capacity cushion and customer service.

Another type of demand uncertainty occurs with a changing product mix. Though total demand measured in monetary terms might remain stable, the load can shift unpredictably from one workstation to another as the product mix changes. Supply uncertainty tied to delivery of purchased materials also makes large capacity cushions helpful. Capacity often comes in large increments because a complete machine has to be purchased even if only a fraction of its avail-able capacity is needed, which in turn creates a large cushion. Firms also need to build in excess capacity to allow for employee absenteeism, vacations, holidays, and any other delays. If a firm is experiencing high overtime costs and frequently needs to rely on subcontractors, it perhaps needs to increase its capacity cushions.

The argument in favor of small cushions is simple: Unused capacity costs money. For capital-intensive firms, minimizing the capacity cushion is vital. Studies indicate that businesses with high capital intensity achieve a low return on investment when the capacity cushion is high. This strong correlation does not exist for labor-intensive firms, however. Their return on investment is about the same because the lower investment in equipment makes high utilization less criti-cal. Small cushions have other advantages. By implementing a small cushion, a company can sometimes uncover inefficiencies that were difficult to detect when cushions were larger. These inefficiencies might include employee absenteeism or unreliable suppliers. Once managers and workers identify such problems, they often can find ways to correct them.

Timing and Sizing ExpansionThe second issue of capacity strategy concerns when to adjust capacity levels and by how much. At times, capacity expansion can be done in response to changing market trends. General Motors decided to increase production capacity of the four-seat series hybrid car Chevrolet Volt from 30,000 units to 45,000 units in 2012 because of strong public interest. While we deal with this issue from the perspective of capacity expansion in greater detail here, it must be noted that firms may not always be looking to expand capacity but at times may be forced to retrench, as evidenced by the situation in the airlines industry, where all major airlines have consolidated routes and reduced the total number of flights in the face of increasing oil costs. Some of this consolidation has been achieved through mergers like United Airlines and Continental to create the world’s largest airline company, as well as the merger between Delta and Northwest Airlines.

Figure 5.2 illustrates two extreme strategies for expanding capacity: the expansionist strategy, which involves large, infrequent jumps in capacity, and the wait-and-see strategy, which involves smaller, more frequent jumps.

Expansionist Strategy The timing and sizing of expansion are related; that is, if demand is increasing and the time between increments increases, the size of the increments must also increase. The expansionist strategy, which stays ahead of demand, minimizes the chance of sales lost to insufficient capacity.

Several factors favor the expansionist strategy. Expansion can result in economies of scale and a faster rate of learning, thus helping a firm reduce its costs and compete on price. This strategy might increase the firm’s market share or act as a form of preemptive marketing. By making a large capacity expansion or announcing that one is imminent, the firm can preempt the expan-sion of other firms. These other firms must sacrifice some of their market share or risk burdening

capacity cushion

The amount of reserve capac-ity a process uses to handle sudden increases in demand or temporary losses of production capacity; it measures the amount by which the average utilization (in terms of total capacity) falls below 100 percent.

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CAPACITY PLANNING CHAPTER 5 203

the industry with overcapacity. To be successful, however, the preempting firm must have the credibility to convince the competition that it will carry out its plans—and must signal its plans before the competition can act.

Wait-and-See Strategy The conservative wait-and-see strategy is to expand in smaller incre-ments, such as by renovating existing facilities rather than building new ones. The wait-and-see strategy lags behind demand. To meet any shortfalls, it relies on short-term options, such as use of overtime, temporary workers, subcontractors, stockouts, and the postponement of preventive maintenance on equipment. It reduces the risks of overexpansion based on overly optimistic demand forecasts, obsolete technology, or inaccurate assumptions regarding the competition.

◀ FIGURE 5.2Two Capacity Strategies

Time betweenincrements

Time

Planned unusedcapacity

Forecast of capacity required

Capa

city

Capacityincrement

(a) Expansionist strategy

Time betweenincrements

Time

Planned use of short-term options

Forecast of capacity required

Capa

city

Capacityincrement

(b) Wait-and-see strategy

Sharp’s Kameyama plant No. 2 in Japan.

Kyod

o/N

ewsc

om

However, this strategy has its own risks, such as being preempted by a competitor or being unable to respond if demand is unexpectedly high. Critics claim the wait-and-see strategy is a short-term strategy typical of some U.S. management styles. Managers on the fast track to corpo-rate advancement tend to take fewer risks. They earn promotions by avoiding the big mistakes and maximizing short-term profits and return on investment. The wait-and-see strategy fits this short-term outlook but can erode market share over the long run.

Management may choose one of these two strat-egies or one of the many between these extremes. With strategies in the more moderate middle, firms can expand more frequently (on a smaller scale) than they can with the expansionist strategy with-out lagging behind demand as with the wait-and-see strategy. An intermediate strategy could be to follow the leader, expanding when others do. If others are right, so are you, and nobody gains a competitive advantage. If others make a mistake and overex-pand, so do you, but everyone shares in the agony of overcapacity. Such a situation was noted for the airlines industry, and may yet occur in the liquid crystal display (LCD) industry due to large capac-ity expansions by Sharp Corporation, Sony, and Samsung.

Linking Capacity and Other DecisionsCapacity decisions should be closely linked to processes and supply chains throughout the organization. When managers make decisions about designing processes, determining degree of resource flexibility and inventory, and locating facilities, they must consider its impact on capac-ity cushions. Capacity cushions in the long run buffer the organization against uncertainty, as do resource flexibility, inventory, and longer customer lead times. If a change is made in any one decision area, the capacity cushion may also need to be changed to compensate. For example, capacity cushions for a process can be lowered if less emphasis is placed on fast deliveries (com-petitive priorities), if yield losses (quality) drop, or if investment in capital-intensive equipment increases or worker flexibility increases (process design). Capacity cushions can also be lowered if the company is willing to smooth the output rate by raising prices when inventory is low and decreasing prices when it is high.

As the following Managerial Challenge shows, selection of the best strategy for expanding capacity is situational. In addition, a well-thought-out approach is needed for making long-term capacity decisions that can not only flesh out all the alternatives but also systematically evaluate them to achieve organizational goals.

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A Systematic Approach to Long-Term Capacity DecisionsLong-term decisions for capacity would typically include whether to add a new plant or warehouse or to reduce the number of existing ones, how many workstations a given department should have, or how many workers are needed to staff a given process. Some of these decisions can take years to become operational. Hence, a systematic approach is needed to plan for long-term capacity decisions.

Although each situation is somewhat different, a four-step procedure generally can help managers make sound capacity decisions. (In describing this procedure, we assume that manage-ment already performed the preliminary steps of determining the process’s existing capacity and assessing whether its current capacity cushion is appropriate.)

1. Estimate future capacity requirements.

2. Identify gaps by comparing requirements with available capacity.

3. Develop alternative plans for reducing the gaps.

4. Evaluate each alternative, both qualitatively and quantitatively, and make a final choice.

Step 1: Estimate Capacity RequirementsA process’s capacity requirement is what its capacity should be for some future time period to meet the forecasted demand of the firm’s customers (external or internal), given the firm’s desired capacity cushion. Larger cushions than normal should be planned for those processes or worksta-tions that could potentially become bottlenecks in the future.

Capacity requirements can be expressed in one of two ways: with an output measure or with an input measure. Either way, the foundation for the estimate is forecasts of demand, productivity, competition, and technological change. These forecasts normally need to be made for several time periods in a planning horizon, which is the set of consecutive time periods considered for plan-ning purposes. Long-term capacity plans need to consider more of the future (perhaps a whole decade) than do short-term plans. Unfortunately, the further ahead you look, the more chance

planning horizon

The set of consecutive time periods considered for planning purposes.

capacity requirement

What a process’s capacity should be for some future time period to meet the demand of customers (external or internal), given the firm’s desired capacity cushion.

M A N A G E R I A L CHALLENGE

The Tower Medical Center (TMC) is a level II trauma center with 520 beds and 16 operating rooms. The emergency department (ED) has experienced an increase from 40,000 visits annually to over 55,000 this year. The increase in volume has increased the wait times for service and the length of stay until discharge. Further, 3,000 patients left the ED last year without being seen and given a medical evalua-tion. These are indicators of overcrowding, and lead to increased costs for admitted patients and even increased patient mortality.

The ED is not the only area experiencing capacity pressure. The OR performs over 10,000 surger-ies annually. However, demand for surgeries is increasing. In the first 8 months of this year, TMC has experienced a net increase of 1,200 new cases relative to last year. The perioperative department, which does ward admission, anesthesia, surgery, and recovery, is experiencing high levels of utilization that threaten the quality of care.

Nirav Patel, facility manager at TMC, must develop a capacity plan for the ED and the OR depart-ments. The ER experiences patient volumes that not only are increasing but also vary substantially throughout the year, particularly during specific seasons and holidays. Does the ER staff have the appro-priate capacity cushion for the changes in demand? Can the staffing pattern, such as the timing of hires and shift schedules, be changed to match demands? Can short-term capacity options such as overtime be used? Can the volume increase be trusted to continue into the future? Should Nirav use an expansion-ist or a wait-and-see strategy for the ED?

The OR poses a different problem. While the staffing pattern of the perioperative personnel can be restructured, such as changing nurse shifts to 12-hour shifts and adding some personnel, the opportunity exists to add some machinery to the OR. A DaVinci surgical robot would reduce surgical times and there-fore increase patient throughput. It would actually bring the capacity above the projected patient volume. However, the robot would cost in excess of $2 million and add about $200,000 a year in maintenance. Nirav has to decide what strategy to take. The remainder of this chapter will provide Nirav guidance in selecting the best long-term strategy and capacity plans for the ED and the OR departments.

Operations

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CAPACITY PLANNING CHAPTER 5 205

you have of making an inaccurate forecast. See Chapter 8, “Forecasting,” for a complete discussion of forecast errors and their origins.

Using Output Measures The simplest way to express capacity requirements is as an output rate. As discussed earlier, output measures are appropriate for high-volume processes with little product variety or process divergence. Here, demand forecasts for future years are used as a basis for extrapolating capacity requirements into the future. If demand is expected to double in the next 5 years, then the capacity requirements also double. For example, if a process’s current demand is 50 customers per day, then the demand in 5 years would be 100 customers per day. If the desired capacity cushion is 20 percent, management should plan for enough capacity to serve [100/(1 – 0.2)] = 125 customers in 5 years.

Using Input Measures Output measures may be insufficient in the following situations:

▪▪ Product variety and process divergence is high.▪▪ The product or service mix is changing.▪▪ Productivity rates are expected to change.▪▪ Significant learning effects are expected.

In such cases, it is more appropriate to calculate capacity requirements using an input mea-sure, such as the number of employees, machines, computers, or trucks. Using an input measure for the capacity requirement brings together demand forecasts, process time estimates, and the desired capacity cushion. When just one service or product is processed at an operation and the time period is a particular year, the capacity requirement, M, is

Capacity requirement =Processing hours required for years demand

Hours available from a single capacity unit (such as an employeeor machine) per year, after deducting desired cushion

M =Dp

N [1 – (C/100)]

where

D = demand forecast for the year (number of customers served or units produced)p = processing time (in hours per customer served or unit produced)N = total number of hours per year during which the process operatesC = desired capacity cushion (expressed as a percent)M = the number of input units required

M should be calculated for each year in the time horizon. The processing time, p, depends on the process and methods selected to do the work. The denominator is the total number of hours, N, available for the year from one unit of capacity (an employee or machine), multiplied by a pro-portion that accounts for the desired capacity cushion, C. The proportion is simply 1.0 – C /100, where C is converted from a percent to a proportion by dividing by 100. For example, a 20 percent capacity cushion means that 1.0 – C /100 = 0.80.

Setups may be involved if multiple products are being manufactured. Setup time is the time required to change a process or an operation from making one service or product to making another. The total setup time is found by dividing the number of units forecast per year, D, by the number of units made in each lot, Q (number of units processed between setups), which gives the number of setups per year, and then multiplying by the time per setup, s. For example, if the annual demand is 1,200 units and the average lot size is 100, there are 1,200/100 = 12 setups per year. Accounting for both processing and setup times for multiple services (products), we get

Capacity requirement =

Processing and setup hours required foryear’s demand, summed over all services or products

Hours available from a single capacity unit per year,after deducting desired cushion

M =[Dp + (D/Q )s]product 1 + [Dp + (D/Q )s]product 2 + g + [Dp + (D/Q )s]product n

N [1 – (C /100)]

where

Q = number of units in each lots = setup time in hours per lot

setup time

The time required to change a process or an operation from making one service or product to making another.

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206 PART 1 MANAGING PROCESSES

Step 4: Evaluate the AlternativesIn this final step, the manager evaluates each alternative, both qualitatively and quantitatively.

Qualitative Concerns Qualitatively, the manager looks at how each alternative fits the overall capacity strategy and other aspects of the business not covered by the financial analysis. Of par-ticular concern might be uncertainties about demand, competitive reaction, technological change, and cost estimates. Some of these factors cannot be quantified and must be assessed on the basis of judgment and experience. Others can be quantified, and the manager can analyze each alter-native by using different assumptions about the future. One set of assumptions could represent a worst case, in which demand is less, competition is greater, and construction costs are higher than expected. Another set of assumptions could represent the most optimistic view of the future. This type of “what-if” analysis allows the manager to get an idea of each alternative’s implications before making a final choice. Qualitative factors would tend to dominate when a business is trying to enter new markets or change the focus of its business strategy.

Quantitative Concerns Quantitatively, the manager estimates the change in cash flows for each alternative over the forecast time horizon compared to the base case. Cash flow is the difference between the flows of funds into and out of an organization over a period of time, including rev-enues, costs, and changes in assets and liabilities. The manager is concerned here only with calculating the cash flows attributable to the project. Example 5.2 shows how cash flow is used to evaluate capacity alternatives.

base case

The act of doing nothing and losing orders from any demand that exceeds current capacity, or incur costs because capacity is too large.

cash flow

The difference between the flows of funds into and out of an orga-nization over a period of time, including revenues, costs, and changes in assets and liabilities.

What to do when M is not an integer depends on the situation. For example, it is impossible to buy a fractional machine. In this case, round up the fractional part, unless it is cost efficient to use short-term options, such as overtime or stockouts, to cover any shortfalls. If, instead, the capacity unit is the number of employees at a process, a value of 23.6 may be achieved using just 23 employees and a modest use of overtime (equivalent to having 60 percent of another full-time person). Here, the fractional value should be retained as useful information.

Example 5.1 shows how to calculate capacity requirements using input measures of capacity.

Estimating Capacity Requirements When Using Input MeasuresEXAMPLE 5.1

A copy center in an office building prepares bound reports for two clients. The center makes multiple copies (the lot size) of each report. The processing time to run, collate, and bind each copy depends on, among other factors, the number of pages. The center operates 250 days per year, with one 8-hour shift. Management believes that a capacity cushion of 15 percent (beyond the allowance built into time standards) is best. It currently has three copy machines. Based on the following table of information, determine how many machines are needed at the copy center.

Item Client X Client Y

Annual demand forecast (copies) 2,000 6,000

Standard processing time (hour/copy) 0.5 0.7

Average lot size (copies per report) 20 30

Standard setup time (hours) 0.25 0.40

SOLUTION

M =[Dp + (D/Q)s]product 1 + [Dp + (D/Q)s]product 2 + g + [Dp + (D/Q)s]product n

N [1 – (C/100)]

=[2,000(0.5) + (2,000/20)(0.25)]client X + [6,000(0.7) + (6,000/30)(0.40)]client Y

[(250 days/year)(1 shift/day)(8 hours/day)][1.0 – (15/100)]

=5,3051,700

= 3.12

Rounding up to the next integer gives a requirement of four machines.

DECISION POINTThe copy center’s capacity is being stretched and no longer has the desired 15 percent capacity cushion with the existing three machines. Not wanting customer service to suffer, management decided to use overtime as a short-term solution to handle past-due orders. If demand continues at the current level or grows, it will acquire a fourth machine.

Step 2: Identify GapsA capacity gap is any difference (positive or negative) between projected capacity requirements (M ) and current capacity. Complications arise when multiple operations and several resource inputs are involved. Expanding the capacity of some operations may increase overall capacity. However, as we will learn later in Chapter 6, “Constraint Management,” if one operation is more constrained than others, total process capacity can be expanded only if the capacity of the con-strained operation is expanded.

Step 3: Develop AlternativesThe next step is to develop alternative plans to cope with projected gaps. One alternative, called the base case, is to do nothing and simply lose orders from any demand that exceeds current capacity or incur costs because capacity is too large. Other alternatives if expected demand exceeds current capacity are various timing and sizing options for adding new capacity, includ-ing the expansionist and wait-and-see strategies illustrated in Figure 5.2. Additional possibili-ties include expanding at a different location and using short-term options, such as overtime, temporary workers, and subcontracting. Alternatives for reducing capacity include the closing of plants or warehouses, laying off employees, or reducing the days or hours of operation.

capacity gap

Positive or negative difference between projected demand and current capacity.

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Step 4: Evaluate the AlternativesIn this final step, the manager evaluates each alternative, both qualitatively and quantitatively.

Qualitative Concerns Qualitatively, the manager looks at how each alternative fits the overall capacity strategy and other aspects of the business not covered by the financial analysis. Of par-ticular concern might be uncertainties about demand, competitive reaction, technological change, and cost estimates. Some of these factors cannot be quantified and must be assessed on the basis of judgment and experience. Others can be quantified, and the manager can analyze each alter-native by using different assumptions about the future. One set of assumptions could represent a worst case, in which demand is less, competition is greater, and construction costs are higher than expected. Another set of assumptions could represent the most optimistic view of the future. This type of “what-if” analysis allows the manager to get an idea of each alternative’s implications before making a final choice. Qualitative factors would tend to dominate when a business is trying to enter new markets or change the focus of its business strategy.

Quantitative Concerns Quantitatively, the manager estimates the change in cash flows for each alternative over the forecast time horizon compared to the base case. Cash flow is the difference between the flows of funds into and out of an organization over a period of time, including rev-enues, costs, and changes in assets and liabilities. The manager is concerned here only with calculating the cash flows attributable to the project. Example 5.2 shows how cash flow is used to evaluate capacity alternatives.

base case

The act of doing nothing and losing orders from any demand that exceeds current capacity, or incur costs because capacity is too large.

cash flow

The difference between the flows of funds into and out of an orga-nization over a period of time, including revenues, costs, and changes in assets and liabilities.

Evaluating the AlternativesEXAMPLE 5.2

Grandmother’s Chicken Restaurant is experiencing a boom in business. The owner expects to serve 80,000 meals this year. Although the kitchen is operating at 100 percent capacity, the dining room can handle 105,000 diners per year. Forecasted demand for the next 5 years is 90,000 meals for next year, followed by a 10,000-meal increase in each of the succeeding years. One alternative is to expand both the kitchen and the dining room now, bringing their capacities up to 130,000 meals per year. The initial investment would be $200,000, made at the end of this year (year 0). The average meal is priced at $10, and the before-tax profit margin is 20 percent. The 20 percent figure was arrived at by deter-mining that, for each $10 meal, $8 covers variable costs and the remaining $2 goes to pretax profit.

What are the pretax cash flows from this project for the next 5 years compared to those of the base case of doing nothing?

SOLUTIONRecall that the base case of doing nothing results in losing all potential sales beyond 80,000 meals. With the new capacity, the cash flow would equal the extra meals served by having a 130,000-meal capacity, multiplied by a profit of $2 per meal. In year 0, the only cash flow is – $200,000 for the initial investment. In year 1, the 90,000-meal demand will be completely satisfied by the expanded capacity, so the incremental cash flow is (90,000 – 80,000)($2) = $20,000. For subsequent years, the figures are as follows:

Year 2: Demand = 100,000; Cash flow = (100,000 – 80,000)($2) = $40,000 Year 3: Demand = 110,000; Cash flow = (110,000 – 80,000)($2) = $60,000 Year 4: Demand = 120,000; Cash flow = (120,000 – 80,000)($2) = $80,000 Year 5: Demand = 130,000; Cash flow = (130,000 – 80,000)($2) = $100,000

If the new capacity were smaller than the expected demand in any year, we would subtract the base case capacity from the new capacity (rather than the demand). The owner should account for the time value of money, applying such techniques as the net present value or internal rate of return methods (see online Supplement F, “Financial Analysis”). For instance, the net present value (NPV) of this project at a discount rate of 10 percent is calculated here, and equals $13,051.76.

NPV = – 200,000 + [20,000/1.1] + [40,000/(1.1)2] + [60,000/(1.1)3] + [80,000/(1.1)4] + [100,000/(1.1)5] = – $200,000 + $18,181.82 + $33,057.85 + $45,078.89 + $54,641.07 + $62,092.13 = $13,051.76

Online ResourceTutor 4.2 in OM Explorer provides a new example to practice projecting cash flows for capacity decisions.

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208 PART 1 MANAGING PROCESSES

Tools for Capacity PlanningCapacity planning requires demand forecasts for an extended period of time. Unfortunately, forecast accuracy declines as the forecasting horizon lengthens. In addition, anticipating what competitors will do increases the uncertainty of demand forecasts. Demand during any period of time may not be evenly distributed; peaks and valleys of demand may (and often do) occur within the time period. These realities necessitate the use of capacity cushions. In this sec-tion, we introduce three tools that deal more formally with demand uncertainty and variability: (1) waiting-line models, (2) simulation, and (3) decision trees. Waiting-line models and simulation account for the random, independent behavior of many customers, in terms of both their time of arrival and their processing needs. Decision trees allow anticipation of events, such as competi-tors’ actions, which requires a sequence of decisions regarding capacities.

Managerial Practice 5.1 shows how PacifiCorp used sophisticated optimization and simula-tion tools to evaluate different alternatives for long-term capacity planning, including balancing demand and supply of energy from multiple sources.

M A N A G E R I A L PRACTICE Capacity Planning at PacifiCorp

Energy demand in the United States is volatile, making it difficult to predict, while power generation facilities age over time and eventually need to be replaced. Therefore, one of the key decisions for utility companies is planning for the best capacity resource portfolio that is both cost effective and compliant with local government regulations. Capacity decision making in utility companies follows a standardized guideline known as Integrated Resource Planning (IRP). The IRP concept started in the late 1980s between state governments and local util-ity companies in response to the oil price fluctuations and the introduction of low-cost nuclear energy. An integrated resource plan is a long-term capacity plan for utilities to meet the growing forecasted annual energy demand. Extra

capacity cushions are built into the plan to deal with peak demands while meet-ing the varying state requirements regarding planning horizons, frequency of plan updates, resources to be considered, and stakeholder involvement.

PacifiCorp is a utility company that is a subsidiary of Berkshire Hathaway Energy, and currently operates one of the largest privately held transmission systems in the United States, serving the Western Energy Imbalance Market in multiple states such as Oregon, Washington, California, Idaho, Utah, and Wyoming. Headquartered in Portland, Oregon, PacifiCorp’s two business units, Pacific Power and Rocky Mountain Power, serve a combined market of over 1.6 million residential customers, 202,000 commercial customers, and 37,000 industrial and irrigation customers. The service area is 143,000 square miles, and transmission lines add up to 16,500 miles along with 64,000 miles of distribution lines and 900 substations. To prepare for future customer needs, PacifiCorp evaluates a 20-year study period for capacity planning, but mainly focuses on the first 10 years in its assessment of capacity requirements. In the planning horizon of 2011–2020, PacifiCorp forecasted that system peak load will grow at 2.1% per year, and that general energy needs will grow by 1.8% per year. The current capacity was estimated to fall short right from the first year (2011) of the forecast by 326 MW. This deficit was predicted to grow to 3,852 MW by 2020. PacifiCorp has set up plans to introduce additional measures such as demand-side management initiatives (reducing electricity use by promoting saving campaigns, or by implementing efficient load management systems such as smart grid technology), renewable energy, and market purchases. Yet the initial projection of shortfall in the available long-term capacity was significant.

On the basis of these plans, PacifiCorp developed the 2020 capacity mix portfolio using a comprehensive model called System Optimizer. The System Optimizer allows PacifiCorp to determine when and how much to expand resource capacity, run cost simulations on various resource port-folios, and assess the risks. Altogether, PacifiCorp defined 67 input sce-narios for the portfolio development. Each scenario was based on alternative transmission configurations, varying carbon dioxide emission control costs and regulation types, natural gas prices, and renewable resource policies. A subsequent sensitivity analysis examined additional incremental costs

5.1

DECISION POINTBefore deciding on this capacity alternative, the owner should also examine the qualitative con-cerns, such as future location of competitors. In addition, the homey atmosphere of the res-taurant may be lost with expansion. Furthermore, other alternatives should be considered (see Solved Problem 2).

A grid operator works at the PacifiCorp Transmissions Grid Operations center in Portland, Oregon, U.S. PacifiCorp, a unit of Warren Buffett’s Berkshire Hathaway Energy that operates the largest transmission system in the western United States, and delivers power to customers in Oregon, Washington, California, Utah, Wyoming, and Idaho. The utility is the second-largest owner of wind generation, behind only another Berkshire subsidiary.

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M05A_KRAJ9863_13_GE_C05.indd 208 15/05/21 5:06 PM

CAPACITY PLANNING CHAPTER 5 209

Waiting-Line ModelsWaiting-line models often are useful in capacity planning, such as selecting an appropriate capac-ity cushion for a high-customer-contact process. Waiting lines tend to develop in front of a work center, such as an airport ticket counter, a machine center, or a central computer. The reason is that the arrival time between jobs or customers varies, and the processing time may vary from one customer to the next. Waiting-line models use probability distributions to provide estimates of average customer wait time, average length of waiting lines, and utilization of the work center. Managers can use this information to choose the most cost-effective capacity, balancing customer service and the cost of adding capacity.

Supplement B, “Waiting Lines,” follows this chapter and provides a fuller treatment of these models. It introduces formulas for estimating important characteristics of a waiting line, such as average customer waiting time and average facility utilization for different facility designs. For example, a facility might be designed to have one or multiple lines at each operation and to route customers through one or multiple operations. Given the estimating capability of these formulas and cost estimates for waiting and idle time, managers can select cost-effective designs and capac-ity levels that also provide the desired level of customer service.

Figure 5.3 shows output from POM for Windows for waiting lines. A professor meeting students during office hours has students arriving on average every 20 minutes (three per hour) and can address their questions in 10 minutes (6 per hour). The professor’s utilization is 50 percent; therefore the capacity cushion is 50 percent. With that large a capacity cushion, you might expect that students would experience little or no waiting time. However, the output shows that the prob-ability of having two or more students in line, prob(num in sys > 1), is 0.25. This probability might be surprisingly high, given the large capacity cushion.

for coal plants, alternative load forecasts, renewable generation costs and incentives, and demand-side management resource availability. The best resource portfolios were chosen on the basis of the risk-adjusted total cost, 10-year customer rating impact, carbon dioxide emissions, supply reliability, resource diversity, and uncertainty risk from the regulatory policy change. The chosen portfolio showed a capacity mix of 62.5 percent traditional ther-mal resources, 13 percent of demand-side management initiatives, and 2.6 percent of renewables. Because the sophisticated simulation model at PacifiCorp can comprehensively evaluate the impact of efficiency-improving demand-side management practices on capacity, the company can make more accurate decisions on whether to add additional resources to its port-folio. This increased precision in capacity estimation saved PacifiCorp from

investing in an additional 2,500 MW of supply-side resources, which would have been costly.

Still, the usefulness of the capacity optimization model developed by PacifiCorp is only as good as the input assumptions. For example, the changing political environment is pressing on PacifiCorp to reduce the reliance on fossil fuels, even as it still operates 17 thermal electric facilities that generate electricity from coal, natural gas, or geothermal sources. Even though PacifiCorp’s power plants use specialized equipment to control environmental emissions, they are more and more looking toward increasing the proportion of renewable resources in the company’s portfolio. Factoring the environmental and compliance pressures into the capacity decision model would be the next challenge that PacifiCorp has to meet.2

2Sources: Rachel Wilson and Bruce Biewald, “Best Practices in Electric Utility Integrated Resource Planning,” Synapse Energy Economics, Inc. (June, 2013); PacifiCorp, “Integrated Resource Plan: Volume 1,” http://pacificorp .com/irp (March, 2011); U.S. Department of Energy, “What Is the Smart Grid?” https://www.smartgrid.gov/the_smart_grid/smart_grid.html; https://en.wikipedia.org/wiki/PacifiCorp (June 27, 2020); https://www.pacificorp .com/energy/thermal.html#:~:text=PacifiCorp%20operates%2017%20thermal%20electric%20facilities%20that%20generate, and %20comply%20with%20all%20state%20and%20federal%20requirements (June 27, 2020).

◀ FIGURE 5.3POM for Windows Output for Waiting Lines during Office Hours

SimulationMore complex waiting-line problems must be analyzed with simulation. It can identify the pro-cess’s bottlenecks and appropriate capacity cushions, even for complex processes with random demand patterns and predictable surges in demand during a typical day. The SimQuick simula-tion package available online allows you to build dynamic models and systems. Other simulation packages can be found with Extend, Simprocess, ProModel, and Witness.

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210 PART 1 MANAGING PROCESSES

Decision TreesA decision tree can be particularly valuable for evaluating different capacity expansion alterna-tives when demand is uncertain and sequential decisions are involved (see Supplement A, “Deci-sion Making”). For example, the owner of Grandmother’s Chicken Restaurant (see Example 5.2) may expand the restaurant now, only to discover in year 4 that demand growth is much higher than forecasted. In that case, she needs to decide whether to expand further. In terms of construc-tion costs and downtime, expanding twice is likely to be much more expensive than building a larger facility from the outset. However, making a large expansion now, when demand growth is low, means poor facility utilization. Much depends on the demand.

Figure 5.4 shows a decision tree for this view of the problem, with new information provided. Demand growth can be either low or high, with probabilities of 0.40 and 0.60, respectively. The initial expansion in year 1 (square node 1) can either be small or large. The second decision node (square node 2), whether to expand at a later date, is reached only if the initial expansion is small and demand turns out to be high. If demand is high and if the initial expansion was small, a decision must be made about a second expansion in year 4. Payoffs for each branch of the tree are estimated. For example, if the initial expansion is large, the financial benefit is either $40,000 or $220,000, depending on whether demand is low or high. Weighting these payoffs by the prob-abilities yields an expected value of $148,000. This expected payoff is higher than the $109,000 payoff for the small initial expansion, so the better choice is to make a large expansion in year 1.

FIGURE 5.4 ▶A Decision Tree for Capacity Expansion

Large expansion

Small expan

sion

21

$90,000

$135,000

$40,000

$220,000

Do not expand

Expand

$148,000

$148,000

$135,000

Low demand [0.40]

High demand [0.60]

$70,000Low demand [0.40]

High demand [0.60]$109,000

LEARNING OBJECTIVES IN REVIEW

Learning Objective Guidelines for Review Online Resources

5.1 Define long-term capacity and its relationship with economies and disecono-mies of scale.

Review the section “Measures of Capacity and Utilization” and understand why and how capacity measured in high-volume pro-cesses is different from its measurement in low-volume, flexible processes. Also see the section on “Economies of Scale” and “Diseconomies of Scale”. Figure 5.1 illustrates the relationship between average unit cost and output rate, and shows different output ranges over which economies and diseconomies of scale can occur.

5.2 Understand the main dif-ferences between the expansionist and wait-and-see capacity timing and sizing strategies.

The section “Capacity Timing and Sizing Strategies” and Figure 5.2 differentiate between the expansionist and wait-and-see strate-gies. Understand the notion of capacity cushions, and how they link to other decisions in the firm.

5.3 Identify a systematic four-step approach for deter-mining long-term capacity requirements and associ-ated cash flows.

The section “A Systematic Approach to Long-Term Capacity Deci-sions” shows you how capacity requirements can be estimated for both input-based and output-based measures. Focus on how different alternatives can be developed to fill the capacity gaps between requirements and current capacity.

OM Explorer Solvers: Capacity RequirementsOM Explorer Tutors: 5.1: Capacity Requirements; 5.2: Projecting Cash FlowsOnline Supplements: F. Financial Analysis; H. Measuring Output Rates; I. Learning Curve AnalysisCase: Fitness Plus B

5.4 Describe how the common tools for capacity plan-ning, such as waiting-line models, simulation, and decision trees, assist in capacity decisions.

The section “Tools for Capacity Planning” illustrates several dif-ferent methods and tools that can be used to arrive at capacity decisions. Read Managerial Practice 5.1 to understand how these tools can actually be used in the real world.

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CAPACITY PLANNING CHAPTER 5 211

Key EquationsPlanning Long-Term Capacity 1. Utilization, expressed as a percent:

Utilization =Average output rate

Maximum capacity* 100%

Capacity Timing and Sizing Strategies 2. Capacity cushion, C, expressed as a percent:

C = 100% – Average Utilization rate (%)

A Systematic Approach to Long-Term Capacity Decisions 3. Capacity requirement for one service or product:

M =Dp

N [1 – (C /100)]

4. Capacity requirement for multiple services or products:

M =[Dp + (D/Q )s]product 1 + [Dp + (D/Q )s]product 2 + g + [Dp + (D/Q )s]product n

N [1 – (C /100)]

Key Termsbase case 206capacity 199capacity cushion 202capacity gap 206

capacity requirement 204cash flow 207diseconomies of scale 201economies of scale 200

planning horizon 204setup time 205utilization 200

Solved Problem 1You have been asked to put together a capacity plan for a critical operation at the Surefoot Sandal Company. Your capacity measure is number of machines. Three products (men’s, women’s, and children’s sandals) are manufactured. The time standards (processing and setup), lot sizes, and demand forecasts are given in the following table. The firm operates two 8-hour shifts, 5 days per week, 50 weeks per year. Experience shows that a capacity cushion of 5 percent is sufficient.

TIME STANDARDS

Product Processing (hr/pair) Setup (hr/pair) Lot Size (pairs/lot) Demand Forecast (pairs/yr)

Men’s sandals 0.05 0.5 240 80,000

Women’s sandals 0.10 2.2 180 60,000

Children’s sandals 0.02 3.8 360 120,000

a. How many machines are needed?

b. If the operation currently has two machines, what is the capacity gap?

SOLUTION

a. The number of hours of operation per year, N, is N = (2 shifts/day)(8 hours/shifts) (250 days/machine@year) = 4,000 hours/machine@year

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212 PART 1 MANAGING PROCESSES

FIGURE 5.5 ▶Using the Capacity Requirements Solver for Solved Problem 1

Shifts/Day 2

Men’s sandalsWomen’s sandalsChildren’s sandals

0.050.100.02

Productive hours fromone capacity unit for a year

More ComponentsFewer Components

Components 3

3,800

ComponentsProcessing

(hr/unit)0.52.23.8

Setup(hr/lot)

240180360

Men’s sandalsWomen’s sandalsChildren’s sandals

Total hours required

0000

0.00.00.00.00.0

4,0006,0002,400

12,400

166.7733.3

1,266.72,166.7

14,566.7

0000

0.00.00.00.00.0

Total capacity requirements (M)RoundedScenarios that can be met with current system/capacity:

If capacity increased byExpanded current capacity

Total capacity requirements (M)RoundedScenarios that can be met with expanded current capacity:

0.000

0%3,800

0.000

3.834

3.834

0.000

0.000

80,00060,000

120,000

Lot Size(units/lot)

Demand ForecastsExpectedPessimistic Optimistic

Hours/Shift 8Days/Week 5Weeks/Year 50Cushion (as %) 5%Current capacity 2

PessimisticSetupProcess

Expected

Pessimistic, Optimistic

Pessimistic, Optimistic

SetupProcessOptimistic

SetupProcess

Solved Problem 2The base case for Grandmother’s Chicken Restaurant (see Example 5.2) is to do nothing. The capacity of the kitchen in the base case is 80,000 meals per year. A capacity alternative for Grandmother’s Chicken Restaurant is a two-stage expansion. This alternative expands the kitchen at the end of year 0, raising its capacity from 80,000 meals per year to that of the dining area (105,000 meals per year). If sales in year 1 and 2 live up to expectations, the capacities of both the kitchen and the dining room will be expanded at the end of year 3 to 130,000 meals per year. This upgraded capacity level should suffice up through year 5. The initial investment would be $80,000 at the end of year 0 and an additional investment of $170,000 at the end

The number of machines required, M, is the sum of machine-hour requirements for all three products divided by the number of productive hours available for one machine:

M =[Dp + (D/Q )s]men + [Dp + (D/Q )s]women + [Dp + (D/Q )s]children

N [1 – (C /100)]

[80,000(0.05) + (80,000/240)0.5] + [60,000(0.10) + (60,000/180)2.2]

= + [120,000(0.02) + (120,000/360)3.8]

4,000[1 – (5/100)]

=14,567 hours/years

3,800 hours/machine – year= 3.83 or 4 machines

b. The capacity gap is 1.83 machines (3.83 – 2). Two more machines should be purchased, unless management decides to use short-term options to fill the gap.

The Capacity Requirements Solver in OM Explorer confirms these calculations, as Figure 5.5 shows, using only the “Expected” scenario for the demand forecasts.

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CAPACITY PLANNING CHAPTER 5 213

YearProjected Demand

(meals/yr)Projected Capacity

(meals/yr)Calculation of Incremental Cash Flow Compared to Base

Case (80,000 meals/yr) Cash Inflow (outflow)

0 80,000 80,000 Increase kitchen capacity to 105,000 meals = ($80,000)

1 90,000 105,000 90,000 – 80,000 = (10,000 meals)($2/meal) = $20,000

2 100,000 105,000 100,000 – 80,000 = (20,000 meals)($2/meal) = $40,000

3 110,000 105,000 105,000 – 80,000 = (25,000 meals)($2/meal) = $50,000

Increase total capacity to 130,000 meals = ($170,000)

($120,000)

4 120,000 130,000 120,000 – 80,000 = (40,000 meals)($2/meal) = $80,000

5 130,000 130,000 130,000 – 80,000 = (50,000 meals)($2/meal) = $100,000

TABLE 5.1 | CASH FLOWS FOR TWO-STAGE EXPANSION AT GRANDMOTHER’S CHICKEN RESTAURANT

The OM Explorer, POM for Windows, and Active Model soft-ware is available to all students using the 13th edition of this textbook. Check with your instructor about where to go to download this software and how best to use these resources. In many cases, the instructor wants you to understand how to do the calculations by hand. At the least, the software pro-vides a check on your calculations. When calculations are

particularly complex and the goal is interpreting the results in making decisions, the software replaces entirely the manual calculations.

Problems 19, 20, 21, 22, 23, and 24 require reading of Supplement A, “Decision Making.” Problems 14, 15, 16, 23, and 24 require reading of online Supplement F, “Financial Analysis.”

Problems

Discussion Questions1. What are the economies of scale in college class size? As

class size increases, what symptoms of diseconomies of scale appear? How are these symptoms related to cus-tomer contact?

2. A young boy sets up a lemonade stand on the corner of College Street and Air Park Boulevard. Temperatures in the area climb to 100°F during the summer. The inter-section is near a major university and a large construc-tion site. Explain to this young entrepreneur how his

business might benefit from economies of scale. Explain also some conditions that might lead to diseconomies of scale.

3. Excess capacity of a firm can lead to underutilization of its assets, while a decision to decrease capacity can result in lost opportunities. Identify examples where businesses have incurred substantial losses due to excess capacity and vice versa. Explain the reasons that may have resulted in this problem.

of year 3. The pretax profit is $2 per meal. What are the pretax cash flows for this alternative through year 5, compared with the base case?

SOLUTION

Table 5.1 shows the cash inflows and outflows. The year 3 cash flow is unusual in two respects. First, the cash inflow from sales is $50,000 rather than $60,000. The increase in sales over the base is 25,000 meals (105,000 – 10,000) instead of 30,000 meals (110,000 – 80,000) because the restaurant’s capacity falls somewhat short of demand. Second, a cash outflow of $170,000 occurs at the end of year 3, when the second-stage expansion occurs. The net cash flow for year 3 is $50,000 – $170,000 = – $120,000.

For comparison purposes, the NPV of this project at a discount rate of 10 percent is calculated as follows, and equals negative $2,184.90.

NPV = – 80,000 + (20,000/1.1) + [40,000/(1.1)2] – [120,000/(1.1)3] + [80,000/(1.1)4] + [100,000/(1.1)5] = – $80,000 + $18,181.82 + $33,057.85 – $90,157.77 + $54,641.07 + $62,092.13 = – $2,184.90

On a purely monetary basis, a single-stage expansion seems to be a better alternative than this two-stage expansion. However, other qualitative factors as mentioned earlier must be considered as well.

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214 PART 1 MANAGING PROCESSES

Planning Long-Term Capacity 1. The Dahlia Medical Center has 30 labor rooms, 15 com-

bination labor and delivery rooms, 3 delivery rooms, and 1 special delivery room reserved for complicated births. All of these facilities operate around the clock. Time spent in labor rooms varies from hours to days, with an average of about a day. The average uncompli-cated delivery requires about 1 hour in a delivery room.

During an exceptionally busy 3-day period, 109 healthy babies were born at Dahlia Medical Center. Sixty babies were born in separate labor and delivery rooms, 45 were born in combined labor and delivery rooms, and only 4 babies required a labor room and the complicated delivery room. Which of the facilities (labor rooms, combination labor and delivery rooms, or delivery rooms) had the greatest utilization rate?

2. A process currently services an average of 50 customers per day. Observations in recent weeks show that its utilization is about 90 percent, allowing for just a 10 percent capacity cushion. If demand is expected to be 75 percent of the current level in 5 years and manage-ment wants to have a capacity cushion of just 5 percent, what capacity requirement should be planned?

3. A waste management company currently operates 25 trucks per day for collecting domestic waste. Observa-tions in recent weeks show that the trucks are operat-ing at a capacity of 70 percent, allowing for just a 10 percent capacity cushion. Due to population growth, more waste will be generated and trucks are expected

to operate at 80 percent. If so, what would be the new capacity utilization?

4. A manufacturer of bespoke handmade candles employs 2 machine operators and 3 packers to process customer orders. This team of 5 works for 6 hours a day for 5 days a week (Monday–Friday). Together, they make 100 candles per hour which are packed in boxes of 10. A machine operator and a packer require approximately 4 minutes to manufacture and 2 minutes to pack each box of candle.

a. Calculate the utilization of both machine operators and packers.

b. In order to improve productivity, management decided to cross-train both operators and packers to perform both activities. Now, it takes 8 minutes for one individual to manufacture and pack each box of candle. Which of the processes has the greatest utili-zation rate?

5. Returning to Problem 4, the business now requires a 20 percent capacity cushion.

a. What would be the new capacity utilization if the capacity cushion is implemented?

b. How many employees should the business sched-ule if it wishes to keep the capacity utilization unchanged?

c. Calculate the capacity utilization for machine opera-tor, packer, and cross-trained employees.

A Systematic Approach to Long-Term Capacity Decisions 6. A sandwich manufacturing firm makes sandwich plat-

ters with 20 pieces per platter. Each platter takes 30 minutes to prepare and pack. After 12 platters, the surface is cleaned and sanitized, which requires a 1-hour changeover. The company operates 7.5 hour shifts, 3 shifts per day, 220 days per year. If the firm manufactures 7000 platters per year, what is its capacity cushion?

7. Macon Controls produces three different types of control units used to protect industrial equipment from

overheating. Each of these units must be processed by a machine that Macon considers to be its process bottleneck. The plant operates on two 8-hour shifts, 5 days per week, 52 weeks per year. Table 5.2 provides the time standards at the bottleneck, lot sizes, and demand forecasts for the three units. Because of demand uncertainties, the operations manager obtained three demand forecasts (pessimistic, expected, and optimistic). The manager believes that a 20 percent capacity cushion is best.

TIME STANDARD DEMAND FORECAST

Component Processing (hr/unit) Setup (hr/lot) Lot Size (units/lot) Pessimistic Expected Optimistic

A 0.05 1.0 60 15,000 18,000 25,000

B 0.20 4.5 80 10,000 13,000 17,000

C 0.05 8.2 120 17,000 25,000 40,000

TABLE 5.2 | CAPACITY INFORMATION FOR MACON CONTROLS

a. How many machines are required to meet minimum (pessimistic) demand, expected demand, and maxi-mum (optimistic) demand?

b. How many machines are required if the operations manager decides to double lot sizes?

c. If the operations manager has three machines and believes that the plant can reduce setup time by 20 percent through process improvement initiatives, does that plant have adequate capacity to meet all demand scenarios without increasing lot sizes?

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CAPACITY PLANNING CHAPTER 5 215

8. Up, Up, and Away is a producer of kites and wind socks. Relevant data on a bottleneck operation in the shop for the upcoming fiscal year are given in the fol-lowing table:

Item Kites Wind Socks

Demand forecast 30,000 units/year 12,000 units/year

Lot size 20 units 70 units

Standard processing time 0.3 hour/unit 1.0 hour/unit

Standard setup time 3.0 hours/lot 4.0 hours/lot

The shop works two shifts per day, 8 hours per shift, 200 days per year. Currently, the company operates four machines, and desires a 25 percent capacity cushion. How many machines should be purchased to meet the upcoming year’s demand without resorting to any short-term capacity solutions?

9. Bespoke Furniture Mart assembles office chairs in a variety of colors, frame sizes, and models. These can be broadly categorized as work chairs and meeting chairs. Identical chairs are produced in lots of 50. The pro-jected demand, lot size, and time standards are shown in the following table.

Item Work Chair Meeting Chair

Projected demand 7,000 units/year 14,000 units/year

Lot size 50 50

Standard assembly time 30 mins/unit 15 mins/unit

Standard set up time 3 hours/lot 1.5 hours/lot

The company operates 8 hours a day, 5 days a week, 220 days a year. It currently has 6 work workstations, each capable of assembling both types of chairs. How many workstations will be required if the company wants to maintain a capacity cushion of 15 percent?

10. Knott’s Industries manufactures standard and super premium backyard swing sets. Currently it has four identical swing-set-making machines, which are operated 250 days per year and 8 hours each day. A capacity cushion of 20 percent is desired. The following information is also known:

Standard ModelSuper Premium

Model

Annual Demand 20,000 10,000

Standard Processing Time 7 min 20 min

Average Lot Size 50 30

Standard Setup Time per Lot 30 min 45 min

a. Does Knott’s have sufficient capacity to meet annual demand?

b. If Knott’s was able to reduce the setup time for the Super Premium Model from 45 minutes to 30 minutes, would there be enough current capacity to produce 20,000 units of each type of swing set?

11. Best Water Limited is a provider of high-quality insula-tion material to trade and commercial establishments. It employs an army of sales agents who regularly work with architects and pitch their products. The sales agents are remunerated based on performance and are usually paid 20 percent of sales value. Manufacturing costs and over-heads contributes to 30 percent of sales revenue. Busi-ness is affected by seasonality and the revenue generated varies per quarter is shown in the following table.

Year Quarter Sales (in 1000s)

1 1 300

2 700

3 900

4 200

2 1 320

2 735

3 940

4 220

a. Calculate the pretax profit based on the data provided.

b. In year 3, the company wishes to replace its existing product by importing a higher quality product from overseas, which reduces production costs from 30 percent to 15 percent. Sales is forecast to increase by 25 percent. However, the government has intro-duced an additional import duty of 10 percent. What will be the additional profits earned by Best Water through year 3?

12. The Astro World amusement park has the opportunity to expand its size now (the end of year 0) by purchas-ing adjacent property for $250,000 and adding attrac-tions at a cost of $550,000. This expansion is expected to increase attendance by 30 percent over projected attendance without expansion. The price of admission is $30, with a $5 increase planned for the beginning of year 3. Additional operating costs are expected to be $100,000 per year. Estimated attendance for the next 5 years, without expansion, is as follows:

Year 1 2 3 4 5

Attendance 30,000 34,000 36,250 38,500 41,000

a. What are the pretax combined cash flows for years 0 through 5 that are attributable to the park’s expansion?

b. Ignoring tax, depreciation, and the time value of money, determine how long it will take to recover (pay back) the investment.

13. Kim Epson operates a full-service car wash, which oper-ates from 8 a.m. to 8 p.m., 7 days a week. The car wash has two stations: an automatic washing and drying station and a manual interior cleaning station. The automatic washing and drying station can handle 30 cars per hour. The interior cleaning station can handle 200 cars per day. On the basis of a recent year-end review of operations, Kim estimates that future demand for the interior cleaning

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216 PART 1 MANAGING PROCESSES

water. Because of population growth, the demand for water next year will be more than the plant’s capacity of 120 million gallons per year. Therefore, the city must expand the facility. The estimated demand over the next 20 years is given in Table 5.3.

The city planning commission is considering three alter-natives.

# Alternative 1: Expand enough at the end of year 0 to last 20 years, which means an 80 million gallon increase (200 – 120).

# Alternative 2: Expand at the end of year 0 and at the end of year 10.

# Alternative 3: Expand at the end of years 0, 5, 10, and 15.

Each alternative would provide the needed 200 million gallons per year at the end of 20 years, when the value of the plant would be the same regardless of the alternative chosen. Significant economies of scale can be achieved in construction costs: A 20-million-gallon expansion would cost $18 million; a 40-million-gallon expansion, $30 million; and an 80-million-gallon expansion, only $50 million. The level of future interest rates is uncertain, leading to uncertainty about the hurdle rate. The city believes that it could be as low as 12 percent and as high as 16 percent (see online Supplement F, “Financial Analysis”).

a. Compute the cash flows for each alternative, com-pared to a base case of doing nothing. (Note: As a municipal utility, the operation pays no taxes.)

b. Which alternative minimizes the present value of construction costs over the next 20 years if the dis-count rate is 12 percent? 16 percent?

c. Because the decision involves public policy and compromise, what political considerations does the planning commission face?

station for the 7 days of the week, expressed in average number of cars per day, would be as follows:

Day Mon. Tues. Wed. Thurs. Fri. Sat. Sun.

Cars 160 180 150 140 280 300 250

By installing additional equipment (at a cost of $50,000), Kim can increase the capacity of the interior cleaning station to 300 cars per day. Each car wash generates a pretax contri-bution of $4.00. Should Kim install the additional equipment if she expects a pretax payback period of 3 years or less?

14. Roche Brothers is considering a capacity expansion of its supermarket. The landowner will build the addi-tion to suit in return for $200,000 upon completion and a 5-year lease. The increase in rent for the addition is $10,000 per month. The annual sales projected through year 5 follow. The current effective capacity is equiva-lent to 500,000 customers per year. Assume a 2 percent pretax profit on sales.

Year 1 2 3 4 5

Customers 560,000 600,000 685,000 700,000 715,000

Average Sales per Customer

$50.00 $53.00 $56.00 $60.00 $64.00

a. If Roche expands its capacity to serve 700,000 cus-tomers per year now (end of year 0), what are the projected annual incremental pretax cash flows attributable to this expansion?

b. If Roche expands its capacity to serve 700,000 cus-tomers per year at the end of year 2, the landowner will build the same addition for $240,000 and a 3-year lease at $12,000 per month. What are the pro-jected annual incremental pretax cash flows attribut-able to this expansion alternative?

15. A rice flour mill is seeking to maximize its productiv-ity with an improved grinder. It can repair its existing machinery or buy a new one. For buying purposes, two alternative machines are in consideration. Machine A costs £125,000 but yields a 10 percent savings over the current machine used. Machine B costs £525,000 but yields a 35 percent savings over the current machine used. The repair and maintenance costs of the existing machine are pro-vided in the following table.

a. Which machine should the mill purchase if a dis-count rate of 13 percent is considered?

b. Assuming the discount rate is reduced to 7 percent, will there be any change in the decision?

Year Projected Cost

1 600,000

2 615,000

3 625,000

4 630,000

5 650,000

16. Several years ago, River City built a water purification plant to remove toxins and filter the city’s drinking

Year Demand Year Demand Year Demand

0 120 7 148 14 176

1 124 8 152 15 180

2 128 9 156 16 184

3 132 10 160 17 188

4 136 11 164 18 192

5 140 12 168 19 196

6 144 13 172 20 200

TABLE 5.3 | WATER DEMAND

17. Mars Incorporated is interested in going to market with a new fuel savings device that attaches to electrically powered industrial vehicles. The device, code named “Python,” promises to save up to 15 percent of the electrical power required to operate the average electric forklift. Mars expects that modest demand expected during the introductory year will be followed by a steady increase in demand in subsequent years. The extent of this increase in demand will be based on cus-tomers’ expectations regarding the future cost of elec-tricity and is shown in Table 5.4. Mars expects to sell the device for $500 each and does not expect to be able to raise its price over the foreseeable future.

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CAPACITY PLANNING CHAPTER 5 217

Tools for Capacity Planning

Mars is faced with two alternatives:

# Alternative 1: Make the device itself, which requires an initial outlay of $250,000 in plant and equipment and a variable cost of $75 per unit.

# Alternative 2: Outsource the production, which requires no initial investment, but incurs a per-unit cost of $300.

a. Assuming small increases in the cost of electrical power, compute the cash flows for each alternative. Over the next 5 years, which alternative maximizes the NPV of this project if the discount rate is 10 percent?

b. Assuming large increases in the cost of electrical power, compute the cash flows for each alternative. Over the next 5 years, which alternative maximizes the NPV of this project if the discount rate is 10 percent?

18. Mackelprang, Inc., is in the initial stages of build-ing the premier planned community in the greater Phoenix, Arizona, metropolitan area. The main sell-ing point will be the community’s lush golf courses. Homes with golf course views will generate premiums far larger than homes with no golf course views, but building golf courses is expensive and takes up valu-able space that nonview homes could be built upon. Mackelprang, Inc., has limited land capacity. To maxi-mize its profits, it is faced with a decision as to how many golf courses it should build, which, in turn, will affect how many homes with and without golf course views it will be able to construct. Mackelprang, Inc., realizes that this decision is directly related to the premium buyers will be willing to spend to buy homes with golf course views. Mackelprang, Inc., is required to build at least one golf course but has enough space to build up to three golf courses. The following table indicates the costs and potential revenues for each course.

EXPECTED DEMAND OF THE DEVICE IN UNITS/YEAR

YearSmall Increases in the Cost of

Electrical PowerLarge Increases in the Cost

of Electrical Power

1 1,000 10,000

2 5,000 8,000

3 1,000 15,000

4 15,000 20,000

5 18,000 30,000

TABLE 5.4 | DEMAND FOR PYTHON POWER-SAVING DEVICE Woodlands The Cactus WildwoodCost $2.6M $1.25M $2.5M

Highest Possible Revenue $4M $2M $2M

Probability of High Revenue 0.3 0.2 0.3

Likely Revenue $2.5M $1.5M $4M

Probability of Likely Revenue 0.4 0.5 0.5

Lowest Possible Revenue $1M $1M $1M

Probability of Low Revenue 0.3 0.3 0.2

a. Which golf course or courses should Mackelprang, Inc., build?

b. What is the expected payoff for this project?

19. Two new alternatives have come up for expanding Grandmother’s Chicken Restaurant (see Solved Problem 2). They involve more automation in the kitchen and feature a special cooking process that retains the original-recipe taste of the chicken. Although the process is more capital intensive, it would drive down labor costs, so the pretax profit for all sales (not just the sales from the capacity added) would go up from 20 to 22 percent. This gain would increase the pretax profit by 2 percent of each sales dollar through $800,000 (80,000 meals * $10) and by 22 percent of each sales dollar between $800,000 and the new capacity limit. Otherwise, the new alternatives are much the same as those in Example 5.2 and Solved Problem 2.

# Alternative 1: Expand both the kitchen and the dining area now (at the end of year 0), raising the capacity to 130,000 meals per year. The cost of con-struction, including the new automation, would be $336,000 (rather than the earlier $200,000).

# Alternative 2: Expand only the kitchen now, raising its capacity to 105,000 meals per year. At the end of year 3, expand both the kitchen and the dining area to the 130,000 meals-per-year volume. Construction and equipment costs would be $424,000, with $220,000 at the end of year 0 and the remainder at the end of year 3. As with alternative 1, the contribution margin would go up to 22 percent.

With both new alternatives, the salvage value would be negligible. Compare the cash flows of all alternatives. Should Grandmother’s Chicken Restaurant expand with the new or the old technology? Should it expand now or later?

20. Dawson Electronics is a manufacturer of high-tech con-trol modules for lawn sprinkler systems. Denise, the CEO, is trying to decide if the company should develop one of two potential new products, the Water Saver 1000 or the Greener Grass 5000. With each product, Dawson can cap-ture a bigger market share if it chooses to expand capacity by buying additional machines. Given different demand scenarios, their probabilities of occurrence, and capacity

expansion versus no change in capacity, the potential sales of each product are summarized in Table 5.5.

a. What is the expected payoff for Water Saver 1000 and the Greener Grass 5000, with and without capac-ity expansion?

b. Which product should Denise choose to produce, and with which capacity expansion option?

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218 PART 1 MANAGING PROCESSES

21. A manager is trying to decide whether to buy one machine or two. If only one machine is purchased and demand proves to be excessive, the second machine can be purchased later. Some sales would be lost, however, because the lead time for delivery of this type of machine is 6 months. In addition, the cost per machine will be lower if both machines are purchased at the same time. The probability of low demand is estimated to be 0.30 and that of high demand to be 0.70. The after-tax NPV of the benefits from purchasing two machines together is $90,000 if demand is low and $170,000 if demand is high.

If one machine is purchased and demand is low, the NPV is $120,000. If demand is high, the manager has three options: (1) doing nothing, which has an NPV of $120,000; (2) subcontracting, with an NPV of $140,000; and (3) buying the second machine, with an NPV of $130,000.

a. Draw a decision tree for this problem.

b. What is the best decision and what is its expected payoff?

22. Brunel Engineering fabricates industrial ovens for hotels, schools, and restaurants. The company is planning to expand and export its products overseas. The current man-ual method of materials handling and assembly is inefficient. Brunel is considering a one-year lease of an industrial robot to increase capacity and improve manufacturing efficiency.

However, demand is uncertain and will depend on cur-rency fluctuations and performance of the global economy. If demand for exports stays at the current level, the prob-ability of which is 0.40, annual savings from utilizing the robot instead of paying wages to full-time employees will be £30,000. If demand rises, the robot will save £45,000 annu-ally because of operating efficiencies in addition to new sales. Finally, if demand falls, the robot will result in an esti-mated annual loss of £60,000. The probability is estimated to be 0.35 for higher demand and 0.25 for lower demand.

a. If Brunel hires a full-time employee in place of the robot, annual payoffs will be £30,000 if demand is unchanged, £35,000 if demand rises, and -£30,000 if demand falls. Draw a decision tree for this problem.

b. Compute the expected value of the payoff for each alternative. Which is the best alternative, based on the expected values?

Water Saver 1000 Dollar

Sales ($1,000)

Greener Grass 5000 Dollar

Sales ($1,000)Probability of Occurrence

With Capacity Expansion

Low Demand 1,000 2,500 0.25

Medium Demand 2,000 3,000 0.50

High Demand 3,000 5,000 0.25

Without Capacity Expansion

Low Demand 700 1,000 0.25

Medium Demand 1,000 2,000 0.50

High Demand 2,000 3,000 0.25

TABLE 5.5 | DEMAND AND SALES INFORMATION FOR DAWSON ELECTRONICS

23. Referring to Problem 7, the operations manager at Macon Controls believes that pessimistic demand has a probability of 20 percent, expected demand has a probability of 50 percent, and optimistic demand has a probability of 30 percent. Currently, new machines must be purchased at a cost of $500,000 a piece, the price charged for each control unit is $110, and the variable cost of production is $50 per unit. (Hint: Since the price and variable cost for each control unit are the same, the profit-maximizing product mix will be the same as the mix that maximizes the total number of units produced.)

a. Draw a decision tree for this problem.

b. How many machines should the company purchase, and what is the expected payoff?

24. Darren Mack owns the Gas n’ Go convenience store and gas station. After hearing a marketing lecture, he realizes that it might be possible to draw more customers to his high-margin convenience store by selling his gasoline at a lower price. However, the Gas n’ Go is unable to qualify for volume discounts on its gasoline purchases, and therefore cannot sell gasoline for profit if the price is low-ered. Each new pump will cost $95,000 to install, but will increase customer traffic in the store by 1,000 customers per year. Also, because the Gas n’ Go would be selling its gasoline at no profit, Darren plans on increasing the profit margin on convenience store items incrementally over the next 5 years. Assume a discount rate of 8 percent. The projected convenience store sales per customer and the projected profit margin for the next 5 years are as follows:

YearProjected Convenience Store

Sales per CustomerProjected Profit

Margin

1 $5.00 20%

2 $6.50 25%

3 $8.00 30%

4 $10.00 35%

5 $11.00 40%

a. What is the NPV of the next 5 years of cash flows if Darren had four new pumps installed?

b. If Darren required a payback period of 4 years, should he go ahead with the installation of the new pumps?

25. The vice president of operations at Dintell Corporation, a major supplier of passenger-side automotive air bags, is considering a $50 million expansion at the firm’s Fort Worth, Texas, production complex. The most recent economic projections indicate a 0.60 probability that the overall market will be $400 million per year over the next 5 years and a 0.40 probability that the market will be only $200 million per year during the same period. The marketing department estimates that Dintell has a 0.50 probability of capturing 40 percent of the market and an equal probability of obtaining only 30 percent of the market. The cost of goods sold is estimated to be 70 percent of sales. For planning purposes, the company currently uses a 12 percent discount rate, a 40 percent tax rate, and the MACRS depreciation schedule. The cri-teria for investment decisions at Dintell are (1) the net expected present value must be greater than zero; (2) there must be at least a 70 percent chance that the net present value will be positive; and (3) there must be

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CAPACITY PLANNING CHAPTER 5 219

no more than a 10 percent chance that the firm will lose more than 20 percent of the initial value.

a. On the basis of the stated criteria, determine whether Dintell should fund the project.

b. What effect will a probability of 0.70 of capturing 40 percent of the market have on the decision?

c. What effect will an increase in the discount rate to 15 percent have on the decision? A decrease to 10 percent?

d. What effect will the need for another $10 million in the third year have on the decision?

CASE Fitness Plus, Part A

Fitness Plus is a full-service health and sports club in Greensboro, North Carolina. The club provides a range of facilities and services to support three primary activities: fitness, recreation, and relaxation. Fitness activities gener-ally take place in four areas of the club: (1) the aerobics room, which can accommodate 35 people per class; (2) a room equipped with free weights; (3) a workout room with 24 pieces of Nautilus equipment; and (4) a large work-out room containing 29 pieces of cardiovascular equipment. This equipment includes nine stairsteppers, six treadmills, six life-cycle bikes, three Airdyne bikes, two cross-aerobics machines, two rowing machines, and one climber. Recreational facilities comprise eight racquetball courts, six tennis courts, and a large outdoor pool. Fitness Plus also sponsors softball, volleyball, and swim teams in city recreation leagues. Relaxation is accomplished through yoga classes held twice a week in the aerobics room, whirlpool tubs located in each locker room, and a trained massage therapist.

Situated in a large suburban office park, Fitness Plus opened its doors in 1995. During the first 2 years, membership was small and use of the facilities was light. By 1997, membership had grown as fitness began to play a large role in more and more people’s lives. Along with this growth came increased use of club facili-ties. Records indicate that in 2000, an average of 15 members per hour checked into the club during a typical day. Of course, the actual number of members per hour varied by both day and time. On some days during a slow period, only six to eight members would check in per hour. At a peak time, such as Mondays from 4:00 p.m. to 7:00 p.m., the number would be as high as 40 per hour.

The club was open from 6:30 a.m. to 11:00 p.m. Monday through Thursday. On Friday and Saturday, the club closed at 8:00 p.m., and on Sunday the hours were 12:00 p.m. to 8:00 p.m.

As the popularity of health and fitness continued to grow, so did Fitness Plus. By May 2005, the average number of members arriving per hour during a typical day had increased to 25. The lowest period had a rate of 10 members per hour; during peak periods, 80 members per hour checked in to use the facilities. This growth brought complaints from members about overcrowding and unavailability of equipment. Most of these complaints centered on the Nautilus, cardiovascular, and aerobics fitness areas. The owners began to wonder whether the club was indeed too small for its membership. Past research indicated that individuals work out an average of 60 minutes per visit. Data collected from member surveys showed the following facilities usage pattern: 30 percent of the members do aerobics, 40 percent use the

cardiovascular equipment, 25 percent use the Nautilus machines, 20 percent use the free weights, 15 percent use the racquetball courts, and 10 percent use the tennis courts. The owners wondered whether they could use this information to estimate how well existing capacity was being utilized.

If capacity levels were being stretched, now was the time to decide what to do. It was already May, and any expansion of the existing facility would take at least 4 months. The owners knew that January was always a peak membership enroll-ment month and that any new capacity needed to be ready by then. However, other factors had to be considered. The area was growing both in terms of population and geography. The downtown area just received a major facelift, and many new offices and businesses were moving back to it, causing a resurgence in activity.

With this growth came increased competition. A new YMCA was offering a full range of services at a low cost. Two new health and fitness facilities had opened within the past year in locations 10 to 15 minutes from Fitness Plus. The first, called the Oasis, catered to the young adult crowd and restricted the access of children under 16 years old. The other facility, Gold’s Gym, provided excellent weight and cardiovascular training only.

As the owners thought about the situation, they had many questions: Were the capacities of the existing facilities constrained, and if so, where? If capacity expansion was necessary, should the existing facility be expanded? Because of the limited amount of land at the current site, expansion of some services might require reducing the capacity of others. Finally, owing to increased competition and growth downtown, was now the time to open a facility to serve that market? A new facility would take 6 months to renovate, and the financial resources were not available to do both.

Fitness Plus, Part B, explores alternatives to expanding a new downtown facility and is included in the Instructor’s Resource Manual. If you are inter-ested in this topic, ask your instructor for a preview.

QUESTIONS1. What method would you use to measure the capacity of Fitness Plus?

Has Fitness Plus reached its capacity?2. Which capacity strategy would be appropriate for Fitness Plus? Justify

your answer.3. How would you link the capacity decision being made by Fitness Plus to

other types of operating decisions?

VIDEO CASE Gate Turnaround at Southwest Airlines

Rollin King and Herb Kelleher started Southwest Airlines in 1971 with this idea: If they could take airline passengers where they want to go, on time, at the low-est possible price, and have a good time while doing it, people would love to fly their airline. The result? No other airline in the industry’s history has enjoyed the customer loyalty and extended profitability for which Southwest is now famous.

There’s more to the story, however, than making promises and hoping to fulfill them. A large part of the success of Southwest Airlines lies in its ability to plan long-term capacity to better match demand and also improving the utilization of its fleet by turning around an aircraft at the gate faster than its competitors. Capacity at Southwest is measured in seat-miles, and even a

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220 PART 1 MANAGING PROCESSES

single minute reduction in aircraft turnaround time systemwide means addi-tional seat-miles being added to the available capacity of Southwest Airlines.

As soon as an aircraft calls “in range” at one of Southwest’s airport loca-tions, called a station, the local operations manager notifies the ground operations team so that the team can start mobilizing all the parties involved in servicing the aircraft in preparation for its next departure. The grounds operations team consists of a baggage transfer driver who has responsibility for getting connecting flight bags to their proper planes, a local baggage driver who moves bags to baggage claim for passenger pickup, a lavatory truck driver who handles restroom recep-tacle drainage, a lead gate agent to handle baggage carts and track incoming and outgoing bag counts, and a bin agent to manage baggage and cargo inside the plane. The ground operations team knows it must turn the plane around in 25 minutes or less. The clock starts when the pilot sets the wheel brakes.

Inbound and outbound flights are coordinated by the supervisors between all of Southwest’s airport stations through the company’s Operations Terminal Information System (OTIS). Each local supervisor is able to keep track of flights and manage any delays or problems that may have crept into the system by keeping in touch with headquarters in Dallas for systemwide issues that may affect a local station, along with using the OTIS information coming from stations sending flights their way.

Just what, exactly, does it take to turn around an aircraft? In-bound flight 3155 from Phoenix to Dallas’s Love Field is a good example. In Phoenix, the operations coordinators and ground operations team push back the plane as scheduled at 9:50 a.m. The flight is scheduled to arrive at 3:35 p.m. in Dallas. The Phoenix team enters into OTIS the information the ground operations team will need in Dallas, such as wheelchairs, gate-checked baggage, cargo bin locator data, and other data needed to close out the flight on their end. This action lets the Dallas station know what to expect when the plane lands.

In Dallas, the local ground operations coordinators have been monitor-ing all 110 inbound flights and now see Phoenix flight 3155 in the system, scheduled for an on-time arrival. When the pilot calls “in range” as it nears Dallas, the ground crew prepares for action.

As the plane is guided to its “stop mark” at the gate, the lead agent waits for the captain’s signal that the engines have been turned off and brakes set. Within just 10 seconds, the provisioning truck pulls up to open the back door for restocking supplies such as drinks and snacks. The waiting fuel truck extends its hose to the underwing connection and in less than 2 minutes picks up refueling instructions and starts to load fuel. As soon as the aircraft is in position, the operations team steers the jetway into position and locks it against the aircraft. The door is opened, the in-flight crew is greeted, and passengers start to deplane.

Outside, less than 40 seconds after engine shutdown, baggage is rolling off the plane and gets placed onto the first cart. Any transfer bags get sent to their next destination, and gate-checked bags are delivered to the top of the jetway stairs for passenger pickup.

While passengers make their way out of the plane, the in-flight crew helps clean up and prepare the cabin for the next flight. If all goes well, the last passenger will leave the plane after only 8 minutes. By this time, passengers waiting to board have already lined up in their designated positions for boarding. The gate agent confirms that the plane is ready for passenger boarding and calls for the first group to turn in their boarding passes and file down the jetway.

At the completion of boarding, the operations agent checks the fuel invoice, cargo bin loading schedule with actual bag counts in their bins from the baggage agents, and a lavatory service record confirming that cleaning has taken place. Final paperwork is given to the captain. The door to the aircraft is closed, and the jetway is retracted. Thirty seconds later, the plane is pushed back and the operations agent gives a traditional salute to the captain to send the flight on its way. Total elapsed time: less than 25 minutes.

Managing Southwest’s capacity has been somewhat simplified by strategic decisions made early on in the company’s life. First, the company’s fleet of aircraft is all Boeing 737s. This single decision affects all areas of operations—from crew training to aircraft maintenance. The single-plane configuration also provides Southwest with crew scheduling flexibility. Since pilots and flight crews can be deployed across the entire fleet, there are no constraints with regard to training and certification pegged to specific aircraft types.

The way Southwest has streamlined its operations for tight turnarounds means it must maintain a high capacity cushion to accommodate variability in its daily operations. Anything from weather delays to unexpected maintenance issues at the gate can slow down the flow of operations to a crawl. To handle these unplanned but anticipated challenges, Southwest builds into its sched-ules enough cushion to manage these delays yet not so much that employees and planes are idle. Additionally, the company encourages discussion to keep on top of what’s working and where improvements can be made. If a problem is noted at a downstream station—say, bags were not properly loaded—this information quickly travels back up to the originating station for correction so that it does not happen again.

Even with the tightly managed operations Southwest Airlines enjoys, company executives know that continued improvement is necessary if the company is to remain profitable into the future. Company executives know they have achieved their goals when internal and external metrics are reached. For example, the Department of Transportation (DOT) tracks on-time departures, customer complaints, and mishandled baggage for all airlines. The company sets targets for achievement on these dimensions and lets employees know on a monthly basis how the company is doing against those metrics and the rest of the industry. Regular communication with all employees is delivered via meetings, posters, and newsletters. Rewards such as prizes and profit sharing are given for successful achievement.

As for the future, Bob Jordan, Southwest’s executive vice president for strategy and planning, puts it this way: “We make money when our planes are in the air, not on the ground. If we can save one minute off every turn system-wide, that’s like putting five additional planes in the air. If a single plane generates annual revenue of $25 million, there’s $125 million in profit potential from those time savings.”

QUESTIONS1. How can capacity and utilization be measured at an airline such as

Southwest Airlines?2. Which factors can adversely impact turnaround times at Southwest

Airlines?3. How does Southwest Airlines know it is achieving its goals?4. What are the important long-term issues relevant for managing capac-

ity, revenue, and customer satisfaction for Southwest Airlines?

Baggage transfer starts less than 40 seconds after engine shutdown at Southwest Airlines.

Pear

son

Educ

atio

n

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221

Anyone who has ever waited at a stoplight, at McDonald’s, or at the registrar’s office has experienced the dynamics of waiting lines. Perhaps one of the best examples of effective management of waiting lines is that of Walt Disney World. One day the park may have only 25,000 customers, but on another day the numbers may top 90,000. Careful analysis of process flows, technology for people-mover (materials handling) equipment, capacity, and layout keeps the waiting times for attractions to acceptable levels.

A waiting line is one or more “customers” waiting for service. The customers can be people or inanimate objects, such as machines requiring maintenance, sales orders waiting for shipping, or inventory items waiting to be used. A waiting line forms because of a temporary imbalance between the demand for service and the capacity of the system to provide the service. In most real-life waiting-line problems, the demand rate varies; that is, customers arrive at unpredictable intervals. Most often, the rate of producing the service also varies, depending on customer needs. Suppose that bank customers arrive at an average rate of 15 per hour throughout the day and that the bank can process an average of 20 customers per hour. Why would a waiting line ever develop? The answers are that the customer arrival rate varies throughout the day and the time required to process a customer can vary. During the noon hour, 30 customers may arrive at the bank. Some of them may have complicated transactions requiring above-average process times. The waiting line may grow to 15 customers for a period of time before it eventually disappears. Even though the bank manager provided for more than enough capacity on average, waiting lines can still develop.

In a similar fashion, waiting lines can develop even if the time to process a customer is con-stant. For example, a subway train is computer controlled to arrive at stations along its route. Each train is programmed to arrive at a station, say, every 15 minutes. Even with the constant service time, waiting lines develop while riders wait for the next train or cannot get on a train because of the size of the crowd at a busy time of the day. Consequently, variability in the rate of demand determines the sizes of the waiting lines in this case. In general, if no variability in the demand or service rate occurs and enough capacity is provided, no waiting lines form.

waiting line

One or more “customers” waiting for service.

SUPPLEMENT

BWAITING LINES

LEARNING OBJECTIVES After reading this supplement, you should be able to:

B.1 Identify the structure of waiting lines in real situations.B.2 Use the single-server, multiple-server, and finite-source

models to analyze operations and estimate the operating characteristics of a process.

B.3 Describe the situations where simulation should be used for waiting-line analysis and the nature of the informa-tion that can be obtained.

B.4 Explain how waiting-line models can be used to make managerial decisions.

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222 PART 1 MANAGING PROCESSES

Waiting-line theory applies to service as well as manufacturing firms, relating customer arrival and service-system processing characteristics to service-system output characteristics. In our discussion, we use the term service broadly—the act of doing work for a customer. The service system might be hair cutting at a hair salon, satisfying customer complaints, or processing a production order of parts on a certain machine. Other examples of customers and services include lines of theatergoers waiting to purchase tickets, trucks waiting to be unloaded at a warehouse, machines waiting to be repaired by a maintenance crew, and patients waiting to be examined by a physician. Regardless of the situation, waiting-line problems have several common elements.

The analysis of waiting lines is of concern to managers because it affects process design, capacity planning, process performance, and ultimately, supply chain performance. In this supplement we discuss why waiting lines form, the uses of waiting-line models in operations management, and the structure of waiting-line models. We also discuss the decisions managers address with these models. Waiting lines can also be analyzed using computer simulation. Software such as SimQuick or Excel spreadsheets can be used to analyze the problems in this supplement.

Structure of Waiting-Line ProblemsAnalyzing waiting-line problems begins with a description of the situation’s basic elements. Each specific situation will have different characteristics, but four elements are common to all situations:

1. An input, or customer population, that generates potential customers

2. A waiting line of customers

3. The service facility, consisting of a person (or crew), a machine (or group of machines), or both, necessary to perform the service for the customer

4. A priority rule, which selects the next customer to be served by the service facility

Figure B.1 shows these basic elements. The triangles, circles, and squares are intended to show a diversity of customers with different needs. The service system describes the number of lines and the arrangement of the facilities. After the service has been performed, the served customers leave the system.

Customer PopulationA customer population is the source of input to the service system. If the potential number of new customers for the service system is appreciably affected by the number of customers already in the system, the input source is said to be finite. For example, suppose that a maintenance crew is assigned responsibility for the repair of 10 machines. The customer population for the maintenance crew is 10 machines in working order. The population generates customers for the maintenance crew as a function of the failure rates for the machines. As more machines fail and enter the service system, either waiting for service or for being repaired, the customer population becomes smaller or the rate at which it can generate another customer falls. Consequently, the customer population is said to be finite.

customer population

An input that generates potential customers.

service facility

A person (or crew), a machine (or group of machines), or both, necessary to perform the service for the customer.

priority rule

A rule that selects the next customer to be served by the service facility.

service system

The number of lines and the arrangement of the facilities.

FIGURE B.1 ▶Basic Elements of Waiting-Line Models

Customerpopulation

Waiting line

Priorityrule

Servicefacilities

Servedcustomers

Service system

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WAITING LINES SUPPLEMENT B 223

Alternatively, an infinite customer population is one in which the number of customers in the system does not affect the rate at which the population generates new customers. For example, consider a mail-order operation for which the customer population consists of shoppers who have received a catalog of products sold by the company. Because the customer population is so large and only a small fraction of the shoppers place orders at any one time, the number of new orders it generates is not appreciably affected by the number of orders wait-ing for service or being processed by the service system. In this case, the customer population is said to be infinite.

Customers in waiting lines may be patient or impatient, which has nothing to do with the colorful language a customer may use while waiting in line for a long time on a hot day. In the context of waiting-line problems, a patient customer is one who enters the system and remains there until being served; an impatient customer is one who either decides not to enter the system (balks) or leaves the system before being served (reneges). For the methods used in this supple-ment, we make the simplifying assumption that all customers are patient.

The Service SystemThe service system may be described by the number of lines and the arrangement of facilities.

Number of Lines Waiting lines may be designed to be a single line or multiple lines. Figure B.2 shows an example of each arrangement. Generally, single lines are utilized at airline coun-ters, inside banks, and at some fast-food restaurants, whereas multiple lines are utilized in grocery stores, at drive-in bank oper-ations, and in discount stores. When multiple servers are avail-able and each one can handle general transactions, the single-line arrangement keeps servers uniformly busy and gives customers a sense of fairness. Customers believe that they are being served on the basis of when they arrived and not on how well they guessed their waiting time when selecting a particular line. The multiple-line design is best when some of the servers provide a limited set of services. In this arrangement, customers select the services they need and wait in the line where that service is provided, such as at a grocery store that provides special lines for customers paying with cash or having fewer than 10 items.

Sometimes customers are not organized neatly into “lines.” Machines that need repair on the production floor of a factory may be left in place, and the maintenance crew comes to them. Nonetheless, we can think of such machines as forming a single line or multiple lines, depending on the number of repair crews and their specialties. Likewise, passengers who telephone for a taxi also form a line even though they may wait at different locations.

Arrangement of Service Facilities Service facilities consist of the personnel and equipment nec-essary to perform the service for the customer. Service facility arrangement is described by the number of channels and phases. A channel is one or more facilities required to perform a given service. A phase is a single step in providing the service. Some services require a single phase, while others require a sequence of phases. Consequently, a service facility uses some combina-tion of channels and phases. Managers should choose an arrangement based on customer volume and the nature of services provided. Figure B.3 shows examples of the five basic types of service facility arrangements.

In the single-channel, single-phase system, all services demanded by a customer can be per-formed by a single-server facility. Customers form a single line and go through the service facility one at a time. Examples are a drive-through car wash and a machine that must process several batches of parts.

The single-channel, multiple-phase arrangement is used when the services are best performed in sequence by more than one facility, yet customer volume or other constraints limit the design to one channel. Customers form a single line and proceed sequentially from one service facility to the next. An example of this arrangement is a McDonald’s drive-through, where the first facility takes the order, the second takes the money, and the third provides the food.

The multiple-channel, single-phase arrangement is used when demand is large enough to warrant providing the same service at more than one facility or when the services offered by the

channel

One or more facilities required to perform a given service.

phase

A single step in providing a service.

Sometimes customers are not organized neatly into lines. Here cars, other vehicles, and people are caught in a messy traffic in Mumbai, one of India’s largest cities.

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224 PART 1 MANAGING PROCESSES

facilities are different. Customers form one or more lines, depending on the design. In the single-line design, the first available server serves customers, as is usually done in the lobby of a bank. If each channel has its own waiting line, customers wait until the server for their line can serve them, as at a bank’s drive-through facilities.

The multiple-channel, multiple-phase arrangement occurs when customers can be served by one of the first-phase facilities but then require service from a second-phase facility, and so on. In some cases, customers cannot switch channels after service has begun; in others they can. An example of this arrangement is a laundromat. Washing machines are the first-phase facilities, and dryers are the second-phase facilities. Some of the washing machines and dryers may be designed for extra-large loads, thereby providing the customer a choice of channels.

The most complex waiting-line problem involves cus-tomers who have unique sequences of required services; consequently, service cannot be described neatly in phases. A mixed arrangement is used in such a case. In the mixed arrangement, waiting lines can develop in front of each facil-ity, as in a medical center, where a patient goes to an exam room for a nurse to take his or her blood pressure and weight, goes back to the waiting room until the doctor can see him or her, and after consultation proceeds to the laboratory to give a blood sample, radiology to have an X-ray taken, or the pharmacy for prescribed drugs, depending on specific needs.

Priority RuleThe priority rule determines which customer to serve next. Most service systems that you encoun-ter use the first-come, first-served (FCFS) rule. The customer at the head of the waiting line has the highest priority, and the customer who arrived last has the lowest priority. Other priority disciplines might take the customer with the earliest promised due date (EDD) or the customer with the shortest expected processing time (SPT).1

▲ FIGURE B.2Waiting-Line Arrangements

Service facilities

Service facilities

Service facilities

(b) Multiple lines

(a) Single line

Servicefacility

(a) Single channel, single phase

Servicefacility 1

Servicefacility 2

(b) Single channel, multiple phase

Servicefacility 2

Servicefacility 1

Servicefacility 2

Servicefacility 1 Service

facility 1Servicefacility 2

Servicefacility 3

Servicefacility 4

Servicefacility 4

Servicefacility 3

(c) Multiple channel, single phase

Routing for : 1–2–4

Routing for : 2–4–3

Routing for : 3–2–1–4

(d) Multiple channel, multiple phase (e) Mixed arrangement

▲ FIGURE B.3Examples of Service Facility Arrangements

1We focus on FCFS in this supplement. See Chapter 10, “Operations Planning and Scheduling,” for additional discussion of FCFS and EDD. See also Supplement J, “Operations Scheduling,” for SPT and additional rules.

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WAITING LINES SUPPLEMENT B 225

A preemptive discipline is a rule that allows a customer of higher priority to interrupt the service of another customer. For example, in a hospital emergency room, patients with the most life-threatening injuries receive treatment first, regardless of their order of arrival. Modeling of systems having complex priority disciplines is usually done using computer simulation.

Probability DistributionsThe sources of variation in waiting-line problems come from the random arrivals of customers and the variations in service times. Each of these sources can be described with a probability distribution.

Arrival DistributionCustomers arrive at service facilities randomly. The variability of customer arrivals often can be described by a Poisson distribution, which specifies the probability that n customers will arrive in T time periods:

Pn =(lT )n

n!e -lT for n = 0, 1, 2, c

where

Pn = probability of n arrivals in T time periods

l = average number of customer arrivals per period

e = 2.7183

The mean of the Poisson distribution is lT, and the variance also is lT. The Poisson distribution is a discrete distribution; that is, the probabilities are for a specific number of arrivals per unit of time.

preemptive discipline

A rule that allows a customer of higher priority to interrupt the service of another customer.

Calculating the Probability of Customer ArrivalsEXAMPLE B.1

Management is redesigning the customer service process in a large department store. Accommodating four customers is important. Customers arrive at the desk at the rate of two customers per hour. What is the probability that four customers will arrive during any hour?

SOLUTIONIn this case l = 2 customers per hour, T = 1 hour, and n = 4 customers. The probability that four customers will arrive in any hour is

P4 =[2(1)]4

4! e-2(1) =

1624

e-2 = 0.090

DECISION POINTThe manager of the customer service desk can use this information to determine the space requirements for the desk and waiting area. There is a relatively small probability that four customers will arrive in any hour. Consequently, seating capacity for two or three customers should be more than adequate unless the time to service each customer is lengthy. Further analysis on service times is warranted.

Another way to specify the arrival distribution is to do it in terms of customer interarrival times—that is, the time between customer arrivals. If the customer population generates customers accord-ing to a Poisson distribution, the exponential distribution describes the probability that the next customer will arrive, or that service to a customer will conclude, in the next T time periods.

Service Time DistributionThe exponential distribution describes the probability that the service time of the customer at a particular facility will be no more than T time periods. The probability can be calculated by using the formula

P (t … T ) = 1 – e -mT

where

m = average number of customers completing service per period

t = service time of the customer

T = target service time

interarrival times

The time between customer arrivals.

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226 PART 1 MANAGING PROCESSES

The mean of the service time distribution is 1/m, and the variance is (1/m)2, As T increases, the probability that the customer’s service time will be less than T approaches 1.0.

For simplicity, let us look at a single-channel, single-phase arrangement.

Calculating the Service Time ProbabilityEXAMPLE B.2

The management of the large department store in Example B.1 must determine whether more training is needed for the customer service clerk. The clerk at the customer service desk can serve an average of three customers per hour. What is the probability that a customer will require 10 minutes or less of service?

SOLUTIONWe must have all the data in the same time units. Because m = 3 customers per hour, we convert minutes of time to hours, or T = 10 minutes = 10/60 hour = 0.167 hour. Then

P(t … T ) = 1 – e-mT

P(t … 0.167 hour) = 1 – e-3(0.167) = 1 – 0.61 = 0.39

DECISION POINTThe probability that the customer will require only 10 minutes or less is not high, which leaves the pos-sibility that customers may experience lengthy delays. Management should consider additional training for the clerk so as to reduce the time it takes to process a customer request.

Some characteristics of the exponential distribution do not always conform to an actual situ-ation. The exponential distribution model is based on the assumption that each service time is independent of those that preceded it. In real life, however, productivity may improve as human servers learn about the work. Another assumption underlying the model is that very small, as well as very large, service times are possible. However, real-life situations often require a fixed-length start-up time, some cutoff on total service time, or nearly constant service time.

Using Waiting-Line Models to Analyze OperationsOperations managers can use waiting-line models to balance the gains that might be made by increasing the efficiency of the service system against the costs of doing so. In addition, managers should consider the costs of not making improvements to the system: Long waiting lines or long waiting times may cause customers to balk or renege. Managers should therefore be concerned about the following operating characteristics of the system.

1. Line Length. The number of customers in the waiting line reflects one of two conditions. Short lines could mean either good customer service or too much capacity. Similarly, long lines could indicate either low server efficiency or the need to increase capacity.

2. Number of Customers in System. The number of customers in line and being served also relates to service efficiency and capacity. A large number of customers in the system cause congestion and may result in customer dissatisfaction, unless more capacity is added.

3. Waiting Time in Line. Long lines do not always mean long waiting times. If the service rate is fast, a long line can be served efficiently. However, when waiting time seems long, cus-tomers perceive the quality of service to be poor. Managers may try to change the arrival rate of customers or design the system to make long wait times seem shorter than they really are. For example, at Walt Disney World, customers in line for an attraction are entertained by videos and also are informed about expected waiting times, which seems to help them endure the wait.

4. Total Time in System. The total elapsed time from entry into the system until exit from the system may indicate problems with customers, server efficiency, or capacity. If some

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WAITING LINES SUPPLEMENT B 227

customers are spending too much time in the service system, it may be necessary to change the priority discipline, increase productivity, or adjust capacity in some way.

5. Service Facility Utilization. The collective utilization of service facilities reflects the percent-age of time that they are busy. Management’s goal is to maintain high utilization and profit-ability without adversely affecting the other operating characteristics.

The best method for analyzing a waiting-line problem is to relate the five operating character-istics and their alternatives to dollars. However, placing a dollar figure on certain characteristics (such as the waiting time of a shopper in a grocery store) is difficult. In such cases, an analyst must weigh the cost of implementing the alternative under consideration against a subjective assessment of the cost of not making the change.

We now present three models and some examples showing how waiting-line models can help operations managers make decisions. We analyze problems requiring the single-server, multiple-server, and finite-source models, all of which are single-phase. References to more advanced models are cited at the end of this supplement.

Single-Server ModelThe simplest waiting-line model involves a single server and a single line of customers, commonly referred to as a single-channel, single-phase system. To further specify the single-server model, we make the following assumptions:

1. The customer population is infinite and all customers are patient.

2. The customers arrive according to a Poisson distribution, with a mean arrival rate of l.

3. The service distribution is exponential, with a mean service rate of m.

4. The mean service rate exceeds the mean arrival rate.

5. Customers are served on a first-come, first-served basis.

6. The length of the waiting line is unlimited.

With these assumptions, we can apply various formulas to describe the operating characteristics of the system:

r = Average utilization of the system

=l

m

Pn = Probability that n customers are in the system = (1 – r)rn

P0 = Probability that zero customers are in the system = 1 – r

L = Average number of customers in the service system

=l

m – l

Lq = Average number of customers in the waiting line

= rL

W = Average time spent in the system, including service

=1

m – l

Wq = Average waiting time in line

= rW

Teenagers waiting in line to enter the Line Friends cafe and shop in Shanghai, China.

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228 PART 1 MANAGING PROCESSES

(Number of servers s assumed to be 1 in single-serve model)3035

Probability of zero customers in the system (P0)Probability of exactly 0 customers in the systemAverage utilization of the server (p)Average number of customers in the system (L)Average number of customers in line (Lq)Average waiting/service time in the system (W )Average waiting time in line (Wq )

0.14290.14290.85716.00005.14290.20000.1714

ServersArrival Rate ( )Service Rate ( )

FIGURE B.4 ▶Waiting-Lines Solver for Single-Channel, Single-Phase System

Calculating the Operating Characteristics of a Single-Channel, Single-Phase System with the Single-Server Model

EXAMPLE B.3

The manager of a grocery store in the retirement community of Sunnyville is interested in providing good service to the senior citizens who shop in her store. Currently, the store has a separate checkout counter for senior citizens. On average, 30 senior citizens per hour arrive at the counter, according to a Poisson distribution, and are served at an average rate of 35 customers per hour, with exponential service times. Find the following operating characteristics:

a. Probability of zero customers in the system

b. Average utilization of the checkout clerk

c. Average number of customers in the system

d. Average number of customers in line

e. Average time spent in the system

f. Average waiting time in line

SOLUTIONThe checkout counter can be modeled as a single-channel, single-phase system. Figure B.4 shows the results from the Waiting-Lines Solver from OM Explorer. Manual calculations of the equations for the single-server model are demonstrated in the Solved Problem at the end of the supplement.

Online ResourceActive Model B.1 provides additional insight on the single-server model and its uses for this problem.

Both the average waiting time in the system (W) and the average time spent waiting in line (Wq) are expressed in hours. To convert the results to minutes, simply multiply by 60 minutes/hour. For example, W = 0.20(60) = 12.00 minutes, and Wq = 0.1714(60) = 10.28 minutes.

Analyzing Service Rates with the Single-Server ModelEXAMPLE B.4

The manager of the Sunnyville grocery in Example B.3 wants answers to the following questions:

a. What service rate would be required so that customers averaged only 8 minutes in the system?

b. For that service rate, what is the probability of having more than four customers in the system?

c. What service rate would be required to have only a 10 percent chance of exceeding four customers in the system?

SOLUTIONThe Waiting-Lines Solver from OM Explorer could be used iteratively to answer the questions. Here we show how to solve the problem manually.

a. We use the equation for the average time in the system and solve for m.

W =1

m – l

8 minutes = 0.133 hour =1

m – 30 0.133m – 0.133(30) = 1

m = 37.52 customers/hour

Online ResourceTutor B.1 in OM Explorer provides a new example to practice the single-server model.

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WAITING LINES SUPPLEMENT B 229

Multiple-Server ModelWith the multiple-server model, customers form a single line and choose one of s servers when one is available. The service system has only one phase; consequently, we are focusing our discussion on multiple-channel, single-phase systems. We make the following assumptions in addition to those for the single-server model: There are s identical servers, and the service distribution for each server is exponential, with a mean service time of 1/m. It should always be the case that sm exceeds l.

b. The probability of more than four customers in the system equals 1 minus the probability of four or fewer customers in the system.

P = 1 – a4

n = 0Pn

= 1 a4

n = 0(1 – r)rn

and

r =30

37.52= 0.80

Then,

P = 1 – 0.2(1 + 0.8 + 0.82 + 0.83 + 0.84) = 1 – 0.672 = 0.328

Therefore, there is a nearly 33 percent chance that more than four customers will be in the system.

c. We use the same logic as in part (b), except that μ is now a decision variable. The easiest way to proceed is to find the correct average utilization first, and then solve for the service rate.

P = 1 – (1 – r)(1 + r + r2 + r3 + r4) = 1 – (1 + r + r2 + r3 + r4) + r(1 + r + r2 + r3 + r4) = 1 – 1 – r – r2 – r3 – r4 + r + r2 + r3 + r4 + r5

= r5

or

r = P1/5

If P = 0.10,

r = (0.10)1/5 = 0.63

Therefore, for a utilization rate of 63 percent, the probability of more than four customers in the system is 10 percent. For l = 30, the mean service rate must be

30m

= 0.63

m = 47.62 customers/hour

DECISION POINTThe service rate would only have to increase modestly to achieve the 8-minute target. However, the probability of having more than four customers in the system is too high. The manager must now find a way to increase the service rate from 35 per hour to approximately 48 per hour. She can increase the service rate in several different ways, ranging from employing a high school student to help bag the groceries to installing self-checkout stations.

Multiple-server model of shoppers in checkout lines at a Costco store in Brooklyn, New York.

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230 PART 1 MANAGING PROCESSES

For example, if 40 customers arrive per hour and the average number of customers being served or waiting is 30, the average time each customer spends in the facility can be computed as

Average time in the facility = W =L customers

l customers/hour=

3040

= 0.75 hour, or 45 minutes

If the time a customer spends at the facility is unreasonable, the manager can focus on either adding capacity or improving the work methods to reduce the time spent serving the customers.

Likewise, Little’s law can be used for manufacturing processes. Suppose that a production manager knows the average time a unit of product spends at a manufacturing process (W ) and the average number of units per hour that arrive at the process (l). The production manager can then estimate the average work-in-process (L) using Little’s law. Work in process (WIP) consists of items, such as components or assemblies, needed to produce a final product in manufactur-ing. For example, if the average time a gear case used for an outboard marine motor spends at a machine center is 3 hours, and an average of five gear cases arrive at the machine center per hour, the average number of gear cases waiting and being processed (or work in process) at the machine center can be calculated as

Work@in@process = L = lW = (5 gear