lean and technology - pearsoncmg.comptgmedia.pearsoncmg.com/images/9780134291451/samplepages/...lean...

Lean and Technology

9780134291451_print.indb i9780134291451_print.indb i 30/09/16 8:44 PM30/09/16 8:44 PM

9780134291451_print.indb ii9780134291451_print.indb ii 30/09/16 8:44 PM30/09/16 8:44 PM

Lean and TechnologyWorking Hand in Hand to Enable and Energize Your

Global Supply ChainPaul A. Myerson

9780134291451_print.indb iii9780134291451_print.indb iii 30/09/16 8:44 PM30/09/16 8:44 PM

Associate Editor: Kim BoedigheimerSenior Marketing Manager: Stephane NakibCover Designer: Chuti PrasertsithManaging Editor: Sandra SchroderSenior Project Editor: Lori LyonsProduction Manager: DhayanidhiCopy Editor: Catherine WilsonProofreader: SudhakaranIndexer: Tim WrightCompositor: codeMantra

© 2017 by Pearson Education, Inc.Old Tappan, New Jersey 07675

For information about buying this title in bulk quantities, or for special sales opportunities (which may include electronic versions; custom cover designs; and content particular to your business, training goals, marketing focus, or branding interests), please contact our corporate sales department at [email protected] or (800) 382-3419.

For government sales inquiries, please contact [email protected].

For questions about sales outside the U.S., please contact [email protected].

Company and product names mentioned herein are the trademarks or registered trademarks of their respective owners.

All rights reserved. Printed in the United States of America. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permissions, request forms, and the appropriate contacts within the Pearson Education Global Rights & Permissions Department, please visit www.pearsoned.com/permissions/.

First Printing November 2016

ISBN-10: 0-13-429145-XISBN-13: 978-0-13-429145-1

Pearson Education LTD.Pearson Education Australia PTY, Limited.Pearson Education Singapore, Pte. Ltd.Pearson Education Asia, Ltd.Pearson Education Canada, Ltd.Pearson Educación de Mexico, S.A. de C.V. Pearson Education—JapanPearson Education Malaysia, Pte. Ltd.

Library of Congress Control Number: 2016952030

9780134291451_print.indb iv9780134291451_print.indb iv 30/09/16 8:44 PM30/09/16 8:44 PM

“Globalization is a fact, because of technology, because of an integrated global supply chain, because of changes in transportation.”

—Remarks by President Barack Obama, Joint Press Conference with Mexican President Enrique Pena Nieto,

White House East Room, July 22, 2016

9780134291451_print.indb v9780134291451_print.indb v 30/09/16 8:44 PM30/09/16 8:44 PM

9780134291451_print.indb vi9780134291451_print.indb vi 30/09/16 8:44 PM30/09/16 8:44 PM

Contents at a Glance

Part I Introduction and Overview . . . . . . . . . . . . . . . . . . . . . .1

Chapter 1 Lean Supply Chain and Technology: A Perfect Combination . . . . .3

Chapter 2 The Growing Importance of the Supply Chain and Technology to Business and Society . . . . . . . . . . . . . . . . . . . . . . . . .15

Chapter 3 Lean Concepts and Their Applications in the Supply Chain . . . . .27

Chapter 4 Software and Hardware Sourcing Process and Applications of Supply Chain and Logistics Management Technology . . . . . . . .53

Part II Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Chapter 5 Supply Chain Network Optimization . . . . . . . . . . . . . . . . . . . . . . . .75

Chapter 6 Demand Forecasting Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87

Chapter 7 Master Production Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Chapter 8 Sales and Operations Planning (S&OP) . . . . . . . . . . . . . . . . . . . . . 111

Part III Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

Chapter 9 Material Requirements Planning (MRP) . . . . . . . . . . . . . . . . . . . .125

Chapter 10 Procurement (and e-Procurement) Systems. . . . . . . . . . . . . . . . . .139

Part IV Make . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

Chapter 11 Enterprise Resource Planning (ERP) Systems . . . . . . . . . . . . . . . . 151

Chapter 12 Manufacturing Execution Systems (MES) . . . . . . . . . . . . . . . . . . . 161

Chapter 13 Short-Term Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

9780134291451_print.indb vii9780134291451_print.indb vii 30/09/16 8:44 PM30/09/16 8:44 PM

viii Contents at a Glance

Part V Deliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

Chapter 14 Distribution Requirements Planning (DRP) . . . . . . . . . . . . . . . . .185

Chapter 15 Transportation Management Systems (TMS). . . . . . . . . . . . . . . . .195

Chapter 16 Order-Fulfillment Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .205

Part VI Return. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217

Chapter 17 Reverse Logistics Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .219

Part VII Enable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

Chapter 18 Measurements, Metrics, and Analytics. . . . . . . . . . . . . . . . . . . . . .233

Part VIII Where Do We Go from Here?. . . . . . . . . . . . . . . . . . . 243

Chapter 19 Collaborative Supply Chain Systems . . . . . . . . . . . . . . . . . . . . . . . .245

Chapter 20 Emerging Technologies and Their Potential Impacts on the Lean Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .255

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .269

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .279

9780134291451_print.indb viii9780134291451_print.indb viii 30/09/16 8:44 PM30/09/16 8:44 PM

Contents

Part I Introduction and Overview . . . . . . . . . . . . . . . . . . . . . . 1

Chapter 1 Lean Supply Chain and Technology: A Perfect Combination . . . . .3It’s a Small World After All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3How Big an Opportunity Is It? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

The Extended and Often Global Supply Chain and Technology. . . . . . . . . . . . . . .6Information Systems (IS) Versus Information Technology (IT). . . . . . . . . . . . . . .6Risks and Rewards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Linking Competitive Strategy to the Value Chain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7Competitive Strategy, Business Processes, and IT Structure Aligned . . . . . . . . . . . . .11Using the SCOR Model to Help Enable Lean Opportunities with Technology . . . . . .13

Chapter 2 The Growing Importance of the Supply Chain and Technology to Business and Society . . . . . . . . . . . . . . . . . . . . . . . . .15Supply Chain Defined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15History of Supply Chain and Logistics Management . . . . . . . . . . . . . . . . . . . . . . . . . . .17The Role of Information Technology in the Supply Chain. . . . . . . . . . . . . . . . . . . . . . .19

Supply Chain Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19Interactive View of Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19Importance of Integration for Sharing Information. . . . . . . . . . . . . . . . . . . . . . . .21Viewpoints of Supply Chain Information Systems . . . . . . . . . . . . . . . . . . . . . . . . .22Supply Chain Macro Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22Supply Chain Information Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Supply Chain Technology Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

Chapter 3 Lean Concepts and Their Applications in the Supply Chain . . . . .27Lean Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27Value-Added Versus Non-Value-Added Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29Lean Culture and Teamwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35Elements of a Lean Supply Chain Strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

Basic Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37Advanced Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42Tools for Identifying and Solving Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

Lean, Supply Chain, and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

9780134291451_print.indb ix9780134291451_print.indb ix 30/09/16 8:44 PM30/09/16 8:44 PM

x Contents

Chapter 4 Software and Hardware Sourcing Process and Applications of Supply Chain and Logistics Management Technology . . . . . . . .53The Procurement Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

Identify and Review Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53Establish Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55Identify and Select Suppliers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55Determine the Right Price . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57Issue Purchase Orders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58Follow Up to Assure Correct Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60Receive and Accept Goods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60Approve Invoice for Payment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

Software and Hardware Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61Phase 1—Planning and Budgeting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61Phase 2—Requirements Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61Phase 3—Vendor Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62Phase 4—Demonstrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62Phase 5—Final Decision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62Phase 6—Contract Negotiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63Implementation Partner/VAR Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63

Make or Buy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63SCM System Costs and Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64“Best-in-Class” Versus Single Integrated Solution . . . . . . . . . . . . . . . . . . . . . . . . .64Consultants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65

Project Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65Supply Chain Software Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66

Supply Chain Planning (SCP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67Supply Chain Execution (SCE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68Other Supply Chain Technologies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

Current and Future Trends in Supply Chain Software . . . . . . . . . . . . . . . . . . . . . . . . . .70Short-Term Supply Chain Technology Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . .70Emerging Supply Chain Technology Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70

Part II Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Chapter 5 Supply Chain Network Optimization . . . . . . . . . . . . . . . . . . . . . . . .75Strategic Planning Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75Tactical Planning Level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75Operational Planning Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .76

9780134291451_print.indb x9780134291451_print.indb x 30/09/16 8:44 PM30/09/16 8:44 PM

xiContents

Importance of the Supply Chain Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77The Location Decision and Its Impact on Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77How and Why Network Optimization Technology Can Help

Enable a Lean Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80Network Optimization Technology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80

Technology Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82Supply Chain Network Optimization Technology Case Studies . . . . . . . . . . . . . . . . . .83

Case 1: North American Industrial Manufacturer Optimizes Its Distribution Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83

Case 2: Semiconductor Manufacturer Re-Designs Its Global Supply Chain Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84

Chapter 6 Demand Forecasting Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87A Lean Approach to Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88

Typical Forecasting Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89Lean Forecasting Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90

Forecasting Technology Options and Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . .94Lean Forecasting Technology Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96

Case 1: Caribou Coffee Automates Forecasting Process with Logility Software. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96

Case 2: Butterball Uses JDA Software to Improve Its Forecasting Process . . . . .97Case 3: Kimberly-Clark Integrates Point of Sale (POS) Information

to Improve Its Resupply Process with Retailers. . . . . . . . . . . . . . . . . . . . . . . . .98

Chapter 7 Master Production Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . .101Master Production Schedule (MPS) Defined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101Lean Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102MPS/Production Planning Technology Options and Requirements . . . . . . . . . . . . .104

Lean and ERP for Production Planning: A Fine Balancing Act . . . . . . . . . . . . .104Lean Production Planning and Technology Case Studies . . . . . . . . . . . . . . . . . . . . . .105

Case 1: Energy Bar Company Upgrades Production Planning Technology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105

Case 2: Global Raw Materials Supplier Integrates MPS Process to Minimize Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .106

Case 3: Nestlé Innovates Its Milk Production Planning. . . . . . . . . . . . . . . . . . . .107Case 4: Durabuilt Windows and Doors Balances Lean and ERP

for Production Planning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110

Chapter 8 Sales and Operations Planning (S&OP) . . . . . . . . . . . . . . . . . . . . .111Sales and Operations Planning (S&OP) Defined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111S&OP and Lean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .113

9780134291451_print.indb xi9780134291451_print.indb xi 30/09/16 8:44 PM30/09/16 8:44 PM

xii Contents

Working Together . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114S&OP/Aggregate Planning Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115Lean S&OP/Aggregate Planning and Technology Case Studies . . . . . . . . . . . . . . . . .117

Case 1: Infineon Technologies AG Takes Planning to the Next Level with JDA S&OP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117

Case 2: Accelerated S&OP Collaboration at Lance . . . . . . . . . . . . . . . . . . . . . . . .118Case 3: Continental Mills Increases Productivity with S&OP Process. . . . . . . .119Case 4: Radisys Improves S&OP Process, Supporting Tools Rapidly After

Outsourcing Strategy Leads to Real Challenges . . . . . . . . . . . . . . . . . . . . . . .121

Part III Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

Chapter 9 Material Requirements Planning (MRP) . . . . . . . . . . . . . . . . . . . .125Procurement and Purchasing Defined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125

The Purchasing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126Types of Business Purchasing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .127

Material Requirements Planning Described . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .128Lean and Material Requirements Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .130Material Requirements Planning Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133Lean MRP and Technology Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135

Case 1: Gables Engineering Moves to a “Real” MRP System. . . . . . . . . . . . . . . .135Case 2: Transport Data Systems—A Picture-Perfect MRP

Implementation Helps Traffic Enforcement Camera Maker to Profitability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .136

Case 3: Raytheon Streamlines and Automates Its Material Requirement Planning Processes with Exostar’s Supply Chain Platform . . . . . . . . . . . . . .137

Chapter 10 Procurement (and e-Procurement) Systems . . . . . . . . . . . . . . . . .139The Procurement Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .139

Automation of Procurement Documents and Processes . . . . . . . . . . . . . . . . . . .139Lean and Procurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .140Procurement Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143Lean Procurement and Technology Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . .145

Case 1: Enabling Online Supplier Collaboration at Toshiba Semiconductor Company. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146

Case 2: Clariant—Increasing Interenterprise Productivity and Extending Its SAP Software Investment Value . . . . . . . . . . . . . . . . . . . . . . . .147

Case 3: New Purchase-to-Pay System Allows Smarter Processes at Atea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .147

9780134291451_print.indb xii9780134291451_print.indb xii 30/09/16 8:44 PM30/09/16 8:44 PM

xiiiContents

Part IV Make . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

Chapter 11 Enterprise Resource Planning (ERP) Systems . . . . . . . . . . . . . . . .151Lean Supply Chain and ERP Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152ERP Technology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .154Lean Supply Chain and ERP Systems Case Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . .156

Case 1: Radio Flyer Teamed with Ultra Consultants on ERP Selection, Business Process Improvement, and Implementation Management . . . . . .156

Case 2: Flexpipe Systems Inc. Works with IFS Applications for More Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .157

Case 3: Automotive Supplier Nissen Chemitec America Accelerates Lean Operations with IQMS ERP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159

Chapter 12 Manufacturing Execution Systems (MES). . . . . . . . . . . . . . . . . . . .161The Role of MES in Today’s Competitive Environment . . . . . . . . . . . . . . . . . . . . . . . .162Manufacturing Execution Systems and Lean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .163

MES, Lean, and Visual Management Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . .164Lean Supply Chain and Manufacturing Execution Systems

Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .165Case 1: Full Sail Brewing Taps Manufacturing Intelligence

to Enhance Brewing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .165Case 2: Merck Sharp & Dohme (MSD) Pharmaceutical Asian Factory

Implements MES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .166Case 3: EZ-MES Automates Production Tracking System at a

High-Power Laser Company . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167

Chapter 13 Short-Term Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .171Short-Term Scheduling Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172

Continuous Versus Discrete Industry Scheduling . . . . . . . . . . . . . . . . . . . . . . . .173Scheduling in Service Industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175Lean Short-Term Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .176

Advanced Planning and Scheduling (APS) Systems . . . . . . . . . . . . . . . . . . . . . .176Advanced Planning and Scheduling Systems Technology . . . . . . . . . . . . . . . . . . . . . .178Advanced Planning and Scheduling Systems Technology

Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .178Case 1: Auto Parts Manufacturer Chooses Asprova for Its Good

User Interface Reduces Labor of Adjusting the Schedule . . . . . . . . . . . . . . .178Case 2: Mueller Stoves Reduces the Assembly Line Stops after

Preactor Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .180

9780134291451_print.indb xiii9780134291451_print.indb xiii 30/09/16 8:44 PM30/09/16 8:44 PM

xiv Contents

Part V Deliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

Chapter 14 Distribution Requirements Planning (DRP) . . . . . . . . . . . . . . . . .185Lean and DRP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187DRP Software. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .188DRP Case Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .189

Case 1: Ford Auto Logistics: Revving Up Service Parts Logistics Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .189

Case 2: Everlast Builds a Championship Company with New Product Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .191

Case 3: Canadian Tire Keeps Stores Rolling with Replenishment Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .192

Chapter 15 Transportation Management Systems (TMS). . . . . . . . . . . . . . . . .195Lean and TMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .196Types of Savings and Improvements Resulting from the Use of a TMS . . . . . . . . . . .197Transportation Management System Technology. . . . . . . . . . . . . . . . . . . . . . . . . . . . .198TMS Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .199

Case #1: Papa John’s Pizza Orders “Optimization Supreme” withManhattan’s Supply Chain Process Platform . . . . . . . . . . . . . . . . . . . . . . . . . .199

Case #2: A Leading Dairy Trims 18% from Transportation Costs Using Optimizer Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .201

Case #3: Miller Brands UK Uses Transwide TMS to Manage Growing Transport Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .202

Chapter 16 Order-Fulfillment Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .205Warehouse Management System (WMS). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .205Order Management Systems (OMS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .206Customer Relationship Management (CRM) Systems . . . . . . . . . . . . . . . . . . . . . . . . .207Lean and Order Fulfillment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208

Order Placement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .209Order Processing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .209Order Preparation and Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .210Order Delivery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .210Faster Fulfillment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .211

Order Fulfillment Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .212Case 1: Regional Pharmaceutical Distributor Requires

Next Day Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .212

9780134291451_print.indb xiv9780134291451_print.indb xiv 30/09/16 8:44 PM30/09/16 8:44 PM

xvContents

Case 2: Whirlpool Spins Optimized Supply Chain with Help from Manhattan Associates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .213

Case 3: TAGG Logistics Combines Cadence WMS and ADSI Ship-IT for Real-Time Supply Chain Execution System . . . . . . . . . . .214

Part VI Return. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217

Chapter 17 Reverse Logistics Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .219Lean Reverse Logistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .220

Elements Key to a Lean Reverse Logistics Process . . . . . . . . . . . . . . . . . . . . . . . .220Lean and Reverse Logistics Technology Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .226

Case 1: RTLTM Adds Up to Many Happy Returns for Philips Consumer Lifestyle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .226

Case 2: Nokia—Deployment of Global Service Strategy . . . . . . . . . . . . . . . . . . .227Case 3: Return Central—Reconstructed Network Yields Big Efficiencies,

Faster Processes for National Home Improvement Retailer . . . . . . . . . . . . .228

Part VII Enable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

Chapter 18 Measurements, Metrics, and Analytics . . . . . . . . . . . . . . . . . . . . . .233Measurement and Analysis Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .233What and Where to Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .234

Using the SCOR Model to Measure and Control. . . . . . . . . . . . . . . . . . . . . . . . . .234Supply Chain Analytics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .236Supply Chain Decision Support and Analytics Technology. . . . . . . . . . . . . . . . . . . . .238Lean and Supply Chain Analytics Technology Case Studies . . . . . . . . . . . . . . . . . . . .240

Case 1: Business Intelligence in the Supply Chain—Better Decisions Through Data for Anna’s Linens . . . . . . . . . . . . . . . . . . . . . . . . . . .240

Case 2: Steel Manufacturer Improves Performance, Profitability. . . . . . . . . . . .241Case 3: H.D. Smith: Why Analytics Is Eating the Supply

Chain—New Tools Are Helping Companies Achieve the Supply Chain’s “Holy Grails”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .241

Part VIII Where Do We Go from Here? . . . . . . . . . . . . . . . . . . 243

Chapter 19 Collaborative Supply Chain Systems . . . . . . . . . . . . . . . . . . . . . . . .245The 80/20 Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .246

Collaboration for a Lean Supply Chain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .247Integrated and Collaborative Technology for a Leaner Supply Chain . . . . . . . . . . . .250

9780134291451_print.indb xv9780134291451_print.indb xv 30/09/16 8:44 PM30/09/16 8:44 PM

xvi Contents

Lean and Collaboration Technology Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . .251Case 1: Agilent Technologies—Comprehensive Supply Chain Visibility

Across a Multi-Enterprise Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . .251Case 2: Arrow Electronics Automates Replenishment Program

with One Network’s Real-Time Value Network . . . . . . . . . . . . . . . . . . . . . . . .253

Chapter 20 Emerging Technologies and Their Potential Impacts on the Lean Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .255General Supply Chain Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .256Supply Chain Software and Connectivity Technology Trends. . . . . . . . . . . . . . . . . . .257

Supply Chain Software Best Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .258Supply Chain Hardware Technology Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .261

Hardware Technologies for a Competitive Advantage in the Next Decade . . . .265Future Supply Chain Technology Spending. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .265Looking Ahead. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .266

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .269

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .279

9780134291451_print.indb xvi9780134291451_print.indb xvi 30/09/16 8:44 PM30/09/16 8:44 PM

About the Author

Paul A. Myerson is a Professor of Practice in Supply Chain Management at Lehigh University and holds a B.S. in Business Logistics and an M.B.A. in Physical Distribution.Professor Myerson has an extensive background as a Supply Chain and Logistics professional, consultant, and teacher. Prior to joining the faculty at Lehigh, Professor Myerson was a successful change catalyst for a variety of clients and organizations of all sizes, having more than 30 years of experience in Supply Chain and Logistics strategies, systems, and operations that have resulted in bottom-line improvements for companies such as General Electric, Unilever, and Church and Dwight (Arm & Hammer).Professor Myerson created and has marketed a Supply Chain Planning software tool for Windows to a variety of companies worldwide.He is the author of the books Lean Supply Chain & Logistics (McGraw-Hill, 2012) and Lean Wholesale and Retail (McGraw-Hill, 2014), Supply Chain and Logistics Management Made Easy (Pearson 2015), as well as a Lean Supply Chain and Logistics Management simulation training game and training package (Enna.com, copyright 2012–13).Professor Myerson also writes a column on Lean Supply Chain for Inbound Logistics Magazine and a blog for Industry Week magazine.

9780134291451_print.indb xvii9780134291451_print.indb xvii 30/09/16 8:44 PM30/09/16 8:44 PM

9780134291451_print.indb xviii9780134291451_print.indb xviii 30/09/16 8:44 PM30/09/16 8:44 PM

3

1Lean Supply Chain and Technology:

A Perfect Combination

T raditionally, Lean has been thought of as a “pen and pencil” technique for identifying and eliminating waste in business processes. As a consequence, while there are many books written on the topic of applying Lean tools

and techniques in manufacturing, administration, and, to a lesser degree, supply chain, most if not all barely discuss the role and impact of technology in process improvement.

This book makes the case that technology is in fact a key enabler of a Lean supply chain and links Lean thinking with available and affordable systems and technologies to get the most out of improved processes.

Specifically, it details various supply chain, logistics, and operations management areas where Lean thinking (in its broadest possible sense) used in combination with existing and emerging systems and technologies—such as the Internet, e-commerce, enterprise resource planning (ERP) systems, 3D printers, bar code scanners, radio frequency identification (RFID) tags, etc.—can take an organization to the next level with increased speed, accuracy, integration, and collaboration among all parties in the extended, global supply chain.

We will discuss various tools, methodologies, best practices, examples, and cases of how, when and where technology can be combined with a Lean philosophy to “turbo charge” an organization’s supply chain for a distinct competitive advantage.

It’s a Small World After AllWe live in exciting times, with the convergence of many activities and advances, including a global marketplace and supply chain, the growth of the Internet and e-commerce, omni-channel marketing and distribution, enterprise, and point software solutions coming in a variety of “shapes and sizes,” and new hardware technologies

9780134291451_print.indb 39780134291451_print.indb 3 30/09/16 8:44 PM30/09/16 8:44 PM

4 Lean and Technology

for the gathering, analysis, and dissemination of information. This new world brings with it many risks and challenges as a result of the increased complexity from globalization, higher transportation costs, deteriorating or insufficient infrastructure, weather disasters, and terrorist threats. An organization’s ability to navigate all this can give it a distinct competitive advantage; if these things are not managed well, it can mean potential failure.

All this helps to explain the increased interest in both process improvement method-ologies such as Lean, Six Sigma, and the combined Lean Six Sigma and the increased use of technology to help enable and manage everything. However, as companies have limited resources, it is critical that they perform due diligence both in terms of process improvement and the selection and implementation of technology.

Like many other aspects of Lean thinking in the supply chain, technology can be an enabler of an improved process and can also help to retain and acquire new customers. So it’s no surprise that technology, when used to collaborate with sup-ply chain partners, can significantly reduce risk. This is explained quite clearly in the white paper “Mitigate Supply Chain Risk with Collaboration and Visibility to Achieve the Perfect Order,” by Ariba, a procurement software vendor. This white paper states,

In today’s global economy, no company works alone. Intricate supply net-works require interaction with hundreds—or even thousands—of outsourced resources, partners, suppliers and customers around the world. That’s why innovative manufacturers are embracing new collaboration and automation technologies to help overcome inefficient, error-prone, manual processes. By enabling collaboration without boundaries, industry leaders are providing greater visibility into direct materials to deliver the perfect order. [www.ariba.com, 2014]

The white paper points cites a recent survey of supply chain executives, which found that mitigating risk is the single biggest day-to-day challenge and one of the high-est priorities when collaborating with trading partners. The survey also showed that almost all respondents found value in collaboration and that it’s a top priority for most chief procurement officers. The collaboration can take many forms, including sharing information, automating processes, and using business networks or hubs. Most of those surveyed felt that manual processes were a major concern (and source of waste), and the majority of those surveyed also recognize that a new generation of technology is critical for automating processes, enhancing collaboration, and mitigat-ing supply chain risk.


5Chapter 1 Lean Supply Chain and Technology: A Perfect Combination

Ultimately, those who have used technology for visibility and collaboration attain significant benefits, such as improved order accuracy and faster, more automated transaction cycles—all signs of a leaner, more efficient supply chain.

How Big an Opportunity Is It?A variety of studies (and my own experience) shows that anywhere from 50% to 95% of Lean programs fail. While a huge reason is the lack of an ingrained Lean culture, it can also be that the technology a company has, doesn’t have, or eventually selects isn’t a good match for its current or future processes. This can result in wasted time, money, and effort.

Many studies have shown that Lean can potentially result in significant (over 50%) improvements in areas such as cycle time, inventory, capacity, and quality. While Lean thinking can certainly create these types of improvements, modern technology enables these improved processes, serving as a kind of “lubricant” for the entire supply chain—not only institutionalizing the improvements but in many cases taking them further than first thought possible.

When businesses think of spending money on technology, which can range from 1% to 7% of total revenue (with manufacturing and retail at the lower end and financial and health care services at the higher end), it’s usually to benefit them in terms of the ability to:

■ Reach more potential customers and better service new and existing customers ■ Develop a tighter relationship with existing or potential customers, suppliers,

and other key partners ■ Improve or streamline operations, resulting in reduced costs and wastes,

improved efficiency, and greater profits

At least partially as a result of these types of perceived benefits, spending on infor-mation processing equipment and software increased from 18.2% of all business investments in 1987 to a peak of 46.7% at the end of 2000 [Pisello, 2001]. This has continued to increase, and a TD Bank survey of chief financial officers (CFOs) in 2015 found technology to be 58% of total capital spending by companies in 2016, fol-lowed by existing facilities (44%) and data security (41%) [www.tdbank.com, 2015].

It should come as no surprise then that worldwide information technology (IT) spending—including includes hardware, software, IT services, and telecom markets—totaled $3.8 trillion in 2015. Of this total, $335 billion was spent on enterprise



software, $732 billion on devices (including personal or mobile computers, mobile phones, tablets, and printers), $143 billion on data center systems (servers and storage and network equipment), $981 billion on IT services, and $1,638 billion on telecom services [Gartner, 2015].

The Extended and Often Global Supply Chain and TechnologyAs the number of partners and length of shipment times increase, so do the degree of complex, multi-enterprise interactions and the need for seamless integrated visibility and responsiveness across multiple enterprises. A lack of automation and visibility handcuffs companies with longer lead times, bigger inventory buffers, budget over-runs, and continued demand–supply imbalances. Three-quarters of respondents in an Aberdeen Global Benchmark survey reported that they don’t have enterprise-wide automation for global supply chain processes. On average, large companies said that their global supply chains are only 50% as automated as their domestic supply chains. Furthermore, 79% of large companies said that the lack of supply chain process visibility was their top concern, while 90% of all enterprises reported that their global supply chain technology was inadequate to provide the corporate finance organiza-tion with the timely information it requires for budget and cash flow planning and management. To address this, companies are moving away from building in-house applications and moving toward using packaged applications [Aberdeen Group, 2006].

A more recent Aberdeen Group survey found that “best practice” organizations have taken control of their own supply chains as they tend to be situated in the middle of dozens of supply chain partners, where they share data and adopt universal standards for bar coding, track and trace, and data exchange. That control may generate more information but also requires more collaborative technology.

Gaining visibility at all levels of product and shipment details and to all trade and financial costs and transactions can expose problems and opportunities. However, when they enable adaptive and collaborative (Lean) processes, leading organizations have superior cost, service, and competitive advantage. Still, there is plenty of room for improvement, as 63% of respondents felt that supply chain visibility was a high priority for improvement [Aberdeen Group, 2013].

Information Systems (IS) Versus Information Technology (IT)The terms information systems (IS) and information technology (IT) are often used interchangeably. Traditionally, IS refers to manual and/or computerized systems that are designed to create, modify, store, and distribute information and that consist of people, processes, machines, and information technology, while IT usually deals with



the technology part of any information system, such as hardware, servers, operating systems, software, and so on. It’s not surprising then that both IS and IT can help sup-port and enable Lean thinking in an organization.

Risks and RewardsWhile selecting and implementing systems and technology in an organization can be justified for a variety of reasons, such as improved productivity, inventory turns, and customer service levels, as discussed throughout this book, many risks need to be con-sidered as well. For example, a survey on the success of ERP systems implementations by Panorama Consulting Systems [www.zdnet.com, 2013] showed that most ERP projects run over budget, and buyers do not fully receive expected benefits. Some respondents felt that the ERP projects were failures. Specifically, the survey showed that the following:

■ More than 50% of projects experienced cost overruns. ■ More than 60% of projects experienced schedule overruns. ■ 60% of respondents received less than half of the expected benefit from their

ERP implementation.

So both separately and together, Lean thinking with IS and IT can have a huge impact on an organization; they can also be risky propositions that suck up vast resources and yield less-than-anticipated returns. My belief is that technology can enable a good process. So it’s only natural that a continuous improvement tool like Lean as part of a supply chain strategy can, and should, go hand in hand with technology—but only if done in the right way so that the investment of scarce resources (capital and human) are spent wisely. Therefore, one of the main purposes of this book is to help link the two together—to show the synergies between them and describe methodologies for determining which tools and technologies have the greatest impact in an organization.

Linking Competitive Strategy to the Value ChainHistorically, supply chain and operations management functions were viewed primarily as cost centers to be controlled. In recent years, it has become clear that these functions can be used to gain a competitive advantage that helps the top line as well. An organi-zation should establish competitive priorities that its supply chain must have in order to satisfy internal and external customers. It should then link the selected competitive priorities to its supply chain and operations management processes.

Krajewski et al. suggest breaking an organization’s competitive priorities into cost, quality, time, and flexibility capability groups (see Figure 1.1) [Krajewski, 2013]:



Cost

Flexibility

Quality

Time

Figure 1.1 Competitive Priorities

■ Cost strategy—This strategy focuses on delivering a product or service to the customer at the lowest possible cost without sacrificing quality. Walmart has been the low-cost leader in retail by operating an efficient supply chain.

■ Time strategy—A time strategy can focus on speed of delivery, response time, and consistency or even product development time. Dell has been a prime example of a manufacturer that has excelled at response time by assembling, testing, and shipping computers in as little as a few days. FedEx is known for fast, on-time deliveries of small packages.

■ Quality strategy—Consistent, high-quality goods or services require a reliable, safe supply chain to deliver on this promise. If Sony had an inferior supply chain with high damage levels, it wouldn’t matter to the customer that the company’s electronics are of the highest quality.

■ Flexibility strategy—This strategy can focus on priorities such as volume, variety, or customization. Many of today’s e-commerce businesses, such as Amazon, offer a great deal of flexibility in many of these categories.

Many organizations focus on more than one of these strategies, and even those that focus on only one of them must offer reasonable performance in the others (though perhaps not “best in class” performance).

The goal for today’s supply chain is integration through collaboration to achieve vis-ibility downstream, toward the customer, and upstream, to suppliers. In a way, many of today’s companies have been able to “substitute information for inventory” to achieve



efficiencies. The days of having “islands of automation” or having an internally focused internal system that may optimize one organization’s supply chain at the cost of some-one else’s (such as a supplier’s or customer’s) are over.

The Lean philosophy involves teamwork and critical thinking aided by the right technology to enable organizations to work with other functions internally as well as with other members of the external supply chain, including customers, suppliers, and partners. The organization can then achieve new levels of efficiency and use its supply chain to achieve a competitive advantage by focusing on adding value to the customer as opposed to just being a cost center within the organization.

Primary Activities

OperationsInboundLogistics

SupportActivities

OutboundLogistics

ServiceSales andMarketing

$

PurchasingTechnology Development

Human Resources ManagementFirm Infrastructure

Figure 1.2 Value Chain Model

The Value Chain model, originated by Michael Porter (which today is more like a “Value Web,” as each businesses’ chain intersects with other chains), shows the value-creating activities of an organization. As you can see in Figure 1.2, it relies heavily on supply chain functions.

In a value chain, each of a firm’s internal activities, listed below, adds incremental value to the final product or service by transforming inputs to outputs:

■ Inbound logistics—Activities including receiving, warehousing, and inventory control of input materials

■ Operations—Activities related to transforming inputs into the final product or service to create value

■ Outbound logistics—Actions that get the final product to the customer, including warehousing and order fulfillment



■ Marketing and sales—Activities related to buyers purchasing the product, including advertising, pricing, distribution channel selection, and the like

■ Service—Activities that maintain and improve a product’s value, including customer support, repair, warranty service, and the like

Porter also identifies support activities that can add value to an organization:

■ Procurement—Purchasing raw materials and other inputs that are used in value-creating activities

■ Technology development—Research and development, process automation, and similar activities that support value chain activities

■ Human resource management—Recruiting, training, development, and com-pensation of employees

■ Firm infrastructure—Finance, legal, quality control, and so on

Porter recommended Value Chain analysis to investigate areas that represent poten-tial strengths that can be used to achieve a competitive advantage. As shown in the Figure 1.3 example of a manufacturer, the supply chain adds value in a variety of ways, so it should be a critical area of focus.

The Value Chain model also includes linkages between the activities. For example, sales forecasts drive production, and production determines raw material and com-ponent needs. The tighter the linkages between these activities, at least in theory, the

Manufacturing ProcessMaterials Management Process

Sales Process

FinishedGoods

Database

RawMaterials(RM)

RM Rece

ived

Update

RM and

Compo

nents

RM Query

Order

Plac

ed

Inbound Logistics Sales and Marketing ServiceOutbound LogisticsOperations

SupplierRMReceived

RM Used Update

Finished Goods

Produced

RawMaterialsDatabase

OrderQuery

CustomerSales Call

Shi

pped

Ord

er U

pdat

e

Ship FG Order

Customer Order

Ord

er A

ppro

val

Finished Goods (FG) to Shipping

Production Update

! !

Figure 1.3 Manufacturer Processes, Linkages, and Information Flow



lower the inventory levels and associated costs. This model therefore was the driver for all encompassing business systems that crossed functions in an organization. It also led to business process redesign (BPR), which brings us back to the idea that just automating current (less-than-optimal) processes isn’t necessarily the best idea. Rather, new and more integrated processes should be created with linkages between the value-added activities [Porter, 1985].

Competitive Strategy, Business Processes, and IT Structure AlignedWhen an organization selects a competitive strategy, it designs business processes that include and link value-generating activities. The processes themselves will determine the organization’s IT requirements. It is therefore critical that businesses align their IT with their business objectives. Doing so requires them to do the following:

■ Identify business goals and objectives. ■ Break strategic goals into value activities and processes. ■ Identify specific measures to define success. ■ Decide how IT can help to achieve business goals. ■ Measure actual performance versus goals.

In Figure 1.3, the specific IT needed for the manufacturer would depend on its competitive strategy as well as where it feels it does or can add the most value.

For example, if the company is a low-cost business, it would want systems that help find and buy lower-cost raw materials and components, perhaps leveraging the Inter-net more on the procurement side to locate and negotiate with those type of suppliers. It might also want to utilize bar code technology to help speed orders and inventory through its finished goods warehouse. An example of this in the retail world is Walmart, which uses information systems to achieve the lowest operational costs and the low-est prices. Walmart’s inventory replenishment system sends orders to suppliers when purchases are recorded at cash registers; this helps the company minimize inventory at warehouses, reduce operating costs, and collaborate with manufacturers to improve forecast and replenishment speed, cost, and accuracy.

On the other hand, a company that has a more flexible, responsive strategy, inven-tory turns might not be a priority, but inventory availability, shorter lead times, and customer service might be. As a result, such a company might want systems and technology that help perform quicker changeovers on manufacturing equipment,



automated distribution management systems for orders to be processed more quickly, and tight integration with key customers to determine its ever-changing product and service requirements. Companies utilizing this type of competitive strategy, such as Dell Computer, may use information systems to customize and personalize products to fit specifications of individual consumers. At Dell’s e-commerce site, customers select the options they desire and order computers custom built to their specifications in a short amount of time. Dell’s assemble-to-order system gives the company a sig-nificant competitive advantage.

Other strategies include:

■ Focusing on a market niche—An organization may use information sys-tems to enable specific market focus and serve a narrow target market better than competitors. This strategy involves analyzing customer buying habits and preferences and making advertising pitches to smaller and smaller target markets.

■ Strengthening customer and supplier relationships—An organization may establish strong links to customers and suppliers while increasing switching costs and loyalty. Automakers use IS to facilitate direct access from suppliers to production schedules so that they can improve their forecasts and schedules. Many e-commerce sites keep track of user preferences for purchases and sug-gest titles to existing customers.

As in many other aspects of the business world, with competitive strategy there are multiple ways to do things. For example, Dell strives for both low cost and a respon-sive, customized product, and it is very successful, with inventory turns of 90 times per year and a lead time for a customized computer of around 4 days.

In addition, the Internet has had a huge impact on competition and has transformed many industries. The Internet has reduced the costs of operating globally, enabling smaller businesses to compete on a global scale and helping to establish new prod-ucts and services with faster time to market. It has also increased the bargaining power of customers and suppliers through transparency and scope and speed of communication.

Using IS to gain a competitive advantage requires coordination of people, process, and technology, which as will discuss throughout this book (see Figure 1.4).

According to Ramakrishman and Testani, “Far too often business transformation efforts concentrate on the process improvement strategies and business process reengineering; while essentially ignoring the people aspect of the change initiative.



Subsequently, these transformation initiatives do not achieve their desired results. Studies have shown that approximately three quarters of business re-engineering efforts do not achieve their objectives and subsequently do not sustain themselves over the long term, and one of the most commonly cited reasons for their failing is due to the lack of focus on the organization’s culture.” By aligning people, pro-cess, and technology, companies can develop “critical organizational competencies around organizational culture transformation and process improvement; resulting in a more effective and sustainable change effort” [Ramakrishman and Testani, 2011].

Using the SCOR Model to Help Enable Lean Opportunities with TechnologyWe will be discussing the interaction of supply chain and operations processes with technology throughout this book, and the most organized way to do this, I believe, is using the SCOR model (see Figure 1.5). This model, which was designed by the Supply Chain Council (which has since merged with APICS; see www.apics.org), divides the supply chain into six management processes:

1. Plan—This process involves balancing supply and demand, which we will discuss in detail along with the sales and operations planning (S&OP) process. These plans are communicated throughout the supply chain.

Process

People

Technology

Figure 1.4 People, Process, and Technology



2. Source—This process involves the procurement of goods to meet demand. It includes identification, selection, and performance measurement of sources of supply, as well as delivery and receipt of materials.

3. Make—This is the transformation process, which involves converting raw materials into finished products.

4. Deliver—This process involves the resources needed to move materials along the supply chain, from suppliers to manufacturing and then to customers. It includes order management, warehousing, and shipping.

5. Return—This is the reverse logistics process for product or material that is returned, including repair, maintenance, and overhaul.

6. Enable (added in SCOR version 11 in 2012)—This process focuses on sup-porting the other five process steps with best practices to support those steps.

Plan Plan

MakeMake

Enable

DeliverDeliverMakeSource SourceSource

Return Return Return Return Return Return

Plan

Deliver Source

Return Return

Deliver

Supplier’sSupplier

Customer’sCustomer

Supplier(Internal or External)

Customer(Internal or External)

Your Company

EnableEnable

Figure 1.5 SCOR Model

Before we get into specifics about applying Lean tools and technology to various processes, it is important to gain some insight into how and why the supply chain has grown in importance, understand some Lean concepts and tools, and discuss the general technology sourcing process.


280 Index

Benton, W.C., 132–133best-practice forecasting process, 89–90BI (business intelligence), 24, 69bid and auction POs, 59big data, 256blanket POs, 126BOM (bill of materials), 128bottlenecks

CBS systems, 177locating, 103–104

BPR (business process redesign), 11break-even analysis, 63–64bullwhip effect, 21, 187business logistics, 17business objectives, aligning with IT, 11–13Butterball, forecasting case study, 97–98“buyer driven” supply chains, 18

CCadence WMS, 214–215Canadian Tire, DRP case study, 192–193Cargomatic, 260Caribou Coffee, forecasting case study,

96–97case studies

APS systemsAsprova, 178–179Mueller Stoves, 180–181

collaborative supply chain systemsAgilent Technologies, 251–252Arrow Electronics, 253–254

DRPCanadian Tire, 192–193Everlast, 191–192Ford auto logistics, 189–191

ERPFlexpipe Systems Inc., 157–158Nissen Chemitec America, 159–160Radio Flyer, 156–157

forecastingButterball, 97–98Caribou Coffee, 96–97Kimberly-Clark, 98–99

Lean S&OPContinental Mills, 119–121Infineon Technologies AG, 117–118Lance, 118–119Radisys, 121–122

Lean schedulingDurabilt windows, 110–111minimizing waste, 106–107Nestlé Pakistan, 107–110upgrading production planning

technology, 105–106MES

EZ-MES, 167–169Full Sail Brewing Company, 165–166Merck Sharp & Dohme, 166–167

MRPGables Engineering, 135–136Raytheon, 137–139Transport Data Systems, 136–137

for network optimizationglobal network design, 84–85North American distribution network

optimization, 83–84order-fulfillment systems

regional pharmaceutical distributor requiring next-day delivery, 212–213

TAGG Logistics, 214–215Whirlpool, 213–214

procurementAtea, 147–148Clariant, 147Toshiba Semiconductor

Company, 146reverse logistics

GENCO, 228–229Nokia, 227–228Philips Consumer Lifestyle, 226–227


281 Index

supply chain analyticsAnna’s Linens, 240–241H.D. Smith, 241–242steel manufacturer, 241

TMSMiller Brands UK, 202–203Papa John’s Pizza, 199–200UltraShipTMS, 201

cause-and-effect diagrams, 50CBS (constraint-based schedulers), 177changeovers, 47check sheets, 50CI (continuous improvement)

initiatives, 163Clariant, procurement case study, 147closed-loop systems, 129–130cloud computing, 70collaborative supply chain systems,

245–24680/20 rule, 246case studies

Agilent Technologies, 251–252Arrow Electronics, 253–254

Lean supply chain collaboration, 247–250

CPFR, 248customer collaboration, 247–248

prime enablers, 268technology options, 250–251

compacting the distribution cycle time, 222

comparingmedium-term and short-term

scheduling, 172–173value-added and non-value-added

activities, 28–29competitive bidding, 57competitive strategies

aligning with IT, 11–13linking to supply chain, 7–11

connected enterprises, 162

consultants, 65consumption methodology, 188Continental Mills, Lean S&OP case study,

119–121contingency planning, 76“Continuing Education—Making the

Right Selection”, 16continuous industry scheduling, 173contract POs, 127control charts, 50corporate purchase cards, 59cost, measuring, 234cost strategies, 8cost-based pricing, 57CPFR (Collaborative

Planning, Forecasting, and Replenishment), 248

CRC (centralized return centers), 224CRM (customer relationship

management), 22, 207–208CRP (capacity requirements planning),

130CSCMP (Council of Supply Chain

Management Professionals), 15CTO (configure-to-order), 153culture of Lean, 35–36customer collaboration, 247–248customer service, 16cyclical scheduling, 175

DDash, 264data analytics, categories of, 237–238data separation, 95days-on scheduling, 175DCM (distribution channel

management), 22decision support tools, 177decoupling points, 132


282 Index

defects, 30delivery of goods, 210–211

reliability, measuring, 235–236Dell Computer, 12demand forecasting, 16demand planning cross-functional

meeting, 112demand pull manufacturing, 27demand shaping, 95dependent demand inventory, 101DES (discrete event simulation), 177descriptive analytics, 237diagnostic analytics, 237diagrams

cause-and-effect diagrams, 50scatter diagrams, 50

digital imaging, 262digitization of the supply chain, 256direct procurement, 53discrete industry scheduling, 174–175discrete orders, 59disruption risk, 257distribution network design, 79distributive bargaining, 58documents, automating for

procurement, 139–140Dougherty, John, 114DRP (distribution requirements

planning), 185–187. See also MRP (material requirements planning)

case studiesCanadian Tire, 192–193Everlast, 191–192Ford auto logistics, 189–191

Lean DRP, 187–188software, 188–189

duplication of effort, 32Durabilt windows, case study, 110–111dynamic replenishment, 249

Ee-business, 24ECR (efficient consumer response),

247–248EDI (electronic data interchange) systems,

18, 24, 59–60elements of Lean supply chain strategy, 37emerging supply chain technology trends,

70–72End-to-End Lean Management:

A Guide to Complete Supply Chain Improvement, 31

ePayment, 145e-procurement, 59, 140

software vendors, 143ERP (enterprise resource planning), 7, 18,

68, 151Flexpipe Systems Inc., case study,

157–158Lean ERP, 152–154Nissen Chemitec America, case study,

159–160production planning, 104–105Radio Flyer, case study, 156–157system selection, 155–156technology options, 154–156

ESB (electronic scheduling board), 177establishing specifications, 55ETO (engineer-to-order), 153Everlast, DRP case study, 191–192excessive overhead, as waste, 32execution view of information systems, 22execution-driven planning solutions, 72EZ-MES, case study, 167–169

Ffacility location, importance of, 77–79

distribution network design, 79facility network, 16


283 Index

factor rating method, selecting vendors, 56–57

FCS (finite capacity scheduling), 172, 177–178

firm infrastructure, in value chain, 10flexibility

measuring, 236strategies, 8

Flexpipe Systems Inc., ERP case study, 157–158

flowcharts, 50focus on market niche, as competitive

strategy, 12Ford auto logistics, DRP case study,

189–191forecasting, 87–88. See also DRP

(distribution requirements planning)best-practice forecasting process,

89–90case studies

Butterball, 97–98Caribou Coffee, 96–97Kimberly-Clark, 98–99

Lean forecasting, 88–89, 90–94technology options, 94–96

Full Sail Brewing Company, MES case study, 165–166

functions of supply chain, 16–17future supply chain technology spending,

265–266

GGables Engineering, case study,

135–136gatekeeping, 221–222GENCO, 228global network design, case study, 84–85global supply chains, technology, 6globalization, 259Gray, Christopher, 114

HHANA in-memory data platform,

115–116hardware

selecting, 61–63“best in class” versus single integrated

solution, 64–65contract negotiation, 63demonstrations, 62make or buy decisions, 63–64planning and budgeting, 61requirements analysis, 61–62vendor research, 62

as source of future competitive advantage, 265

supply chain technology trends, 261–265

H.D. Smith, supply chain analytics case study, 241–242

Heijunka, 103heuristics, Lean scheduling, 103histograms, 50historical analysis, 95history

of Lean, 27–28of SCM, 17–19

“How Manufacturing Software Can Adjust to Lean Principles”, 132

human resource management in value chain, 10

human supply chain technology, 72

IIBP (integrated business planning),

111–113identifying

requirements, 53–54vendors, 56–57

implementation partners, selecting, 63


284 Index

inbound logistics in value chain, 9incremental MES implementations,

163–164indirect procurement, 54industrial purchasing, 127–128Infineon Technologies AG, case study,

117–118information, interactive view of, 19–21information management, 16Institute for Global Futures, 266integrative negotiation, 58interactive view of information, 19–21Internet, 24inventory, 16

dependent demand inventory, 101distribution network design, 79DRP, 185–187

Lean DRP, 187–188software, 188–189

JIT, 46VMI, 59as waste, 30

invoices, approving for payment, 60–61IS (information systems), 6–7

ERP systems, 7ISCM (internal supply chain

management), 22issuing purchase orders, 58–60IT (information technology)

aligning with business objectives, 11–13

consultants, 65expenditures, 5–6interactive view of information, 19–21and IS, 6–7role in supply chain, 19–25

macro processes, 22–23technology trends, 24–25viewpoints of information systems, 22

viewpoints of information systems, 22

J-KJDA Master Planning module, 104JIT (just-in-time), 46

versus MRP, 131kanban, 27, 131, 153, 249

visual management systems, 164–165key functionalities

of MES, 162of TMS, 195–196

Keychain Logistics, 260Kimberly-Clark, forecasting case study,

98–99Kowalke, Mae, 134–135KPIs (key performance indicators), 233KSFs (key success factors) of Lean, 36

LLance, Lean S&OP case study, 118–119layout, as basic tool of Lean, 41lead time, 28Lean

attributes of, 33–34collaborative supply chain systems,

247–250Agilent Technologies, case study,

251–252Arrow Electronics, case study, 253–254CPFR, 248customer collaboration, 247–248technology options, 250–251

culture and teamwork, 35–36demand pull manufacturing, 27DRP, 187–188

Canadian Tire, case study, 192–193Everlast, case study, 191–192Ford auto logistics, case study,

189–191elements in supply chain strategy, 37ERP, 152–154


285 Index

Flexpipe Systems Inc., case study, 157–158

Nissen Chemitec America, case study, 159–160

Radio Flyer, case study, 156–157system selection, 155–156technology options, 154–156

forecasting, 88–89, 90–94Butterball, case study, 97–98Caribou Coffee, case study, 96–97Kimberly-Clark, case study, 98–99technology options, 94–96

history of, 27–28KSFs, 36lead time, 28MES, 163–164

EZ-MES, case study, 167–169Full Sail Brewing Company, case study,

165–166incremental implementations, 163–164Merck Sharp & Dohme, case study,

166–167visual management systems, 164–165VSM, 164

MRP, 130–133decoupling points, 132Gables Engineering, case study,

135–136Raytheon, case study, 137–139technology options, 133–135Transport Data Systems, case study,

136–137order-fulfillment systems, 208

regional pharmaceutical distributor requiring next-day delivery, case study, 212–213

TAGG Logistics, case study, 214–215Whirlpool, case study, 213–214

processing time, 28procurement, 140–143

Atea, case study, 147–148attributes, 141

Clariant, case study, 147software vendors, 143technology options, 143–145Toshiba Semiconductor Company,

case study, 146program failure, reasons for, 5reverse logistics, 220–225

asset recovery, 225compacting the distribution cycle time,

222CRC, 224financial management, 225gatekeeping, 221–222GENCO, case study, 228–229negotiation, 225Nokia, case study, 227–228outsourcing, 225Philips Consumer Lifestyle, case study,

226–227product returns process, 220remanufacture and refurbishment,

224–225technology options, 222–223zero returns, 224

S&OP, 113–114Continental Mills, case study,

119–121Infineon Technologies AG, case study,

117–118Lance, case study, 118–119Radisys, case study, 121–122

scheduling, 102–104Durabilt windows, case study,

110–111ERP, 104–105heuristics, 103minimizing waste, case study, 106–107Nestlé Pakistan, case study, 107–110production planning, 103takt time, 103upgrading production planning

technology, case study, 105–106


286 Index

Lean (Continued)short-term scheduling, 176

APS systems, 176–178FCS, 177–178technology options, 178

technology, leveraging, 50–52TMS, 196–197

Miller Brands UK, case study, 202–203Papa John’s Pizza, case study, 199–200ROI, 197–198technology options, 198–199UltraShipTMS, case study, 201

tools used in, 37–505 whys, 49batch size reduction, 46–47JIT, 46layout, 41seven tools of quality, 50standardized work, 37–38TPM, 48–49value stream mapping, 43visual workplace, 38–41work cells, 47–48workplace organization, 42

TPS, 27value-add activities, 28–29waste, 29–35

“The Lean Approach to Business Forecasting”, 91–93

“Lean Finds a Friend in Demand Driven MRP”, 131

“Lean Manufacturing: Five Tips for Reducing Waste in the Supply Chain”, 51

Lean Six Sigma, 4leveraging technology in Lean, 50–52licensing for TMS, 198light-directed WMS systems, 206linking competitive strategy to supply

chain, 7–11location of facilities

distribution network design, 79importance of, 77–79

Logility software, Caribou Coffee case study, 96–97

logistics management, 15history of, 17–19reverse logistics, 219–220

asset recovery, 225compacting the distribution cycle

time, 222CRC, 224financial management, 225gatekeeping, 221–222IT systems, 222–223negotiation, 225outsourcing, 225product returns process, 220remanufacture and refurbishment,

224–225zero returns, 224

TMS, 195–196key functionalities, 195–196Lean TMS, 196–197licensing, 198ROI, 197–198

lot sizing, 129

Mmanufacturing schedules, 171–172

continuous industry scheduling, 173discrete industry scheduling, 174–175

MAPE (mean absolute percentage error), 93

market niche, focusing on, 12market-based pricing, 57marketing, in value chain, 10materials handling, 16measuring

delivery reliability, 235–236flexibility, 236responsiveness, 236

medium-term scheduling, 172–173


287 Index

meetings, S&OP, 112–113mercantile purchasing, 127Merck Sharp & Dohme, MES case study,

166–167MES (manufacturing execution

systems), 161EZ-MES, case study, 167–169Full Sail Brewing Company, case study,

165–166goal of, 161incremental implementations, 163–164key functionalities, 162Lean MES, 163–164Merck Sharp & Dohme, case study,

166–167visual management systems, 164–165VSM, 164

Miller Brands UK, TMS case study, 202–203

minimizing waste, case study, 106–107“Mitigate Supply Chain Risk with

Collaboration and Visibility to Achieve the Perfect Order”, 4–5

mobile computing, 71models

forecasting models, selecting, 90for network optimization, 80–82

motion as waste, 30MPS (master production scheduling)

Lean scheduling, 102–104Durabilt windows, case study,

110–111heuristics, 103minimizing waste, case study,

106–107Nestlé Pakistan, case study, 107–110production planning, 103takt time, 103upgrading production planning

technology, case study, 105–106PSI reports, 102

RCCP, 101technology options, 104

MRP (material requirements planning), 33, 128–130

closed-loop systems, 129–130versus JIT, 131Lean MRP, 130–133

decoupling points, 132Gables Engineering, case study,

135–136Raytheon, case study, 137–139Transport Data Systems, case study,

136–137lot sizing, 129procurement, 125, 139

documents, automating, 139–140e-procurement, 140

purchasing, 125, 126–127industrial purchasing, 127–128mercantile purchasing, 127

strategic sourcing, 125–126technology options, 133–135

MTO (make-to-order), 153MTS (make-to-stock), 153Mueller Stoves, APS case study,

180–181multi-enterprise visibility systems, 71

Nnegotiations, 57–58

in Lean reverse logistics, 225network optimization, 80–85

case studiesglobal network design, 84–85North American distribution network

optimization, 83–84models, 80–82technology options, 82

Nissen Chemitec America, ERP case study, 159–160


288 Index

Nokia, reverse logistics case study, 227–228

non-value-added activities, 28–29waste, 29–35

North American distribution network optimization, case study, 83–84

OOBS (order-based scheduling), 177OMS (order management systems),

206–207operational planning level, 76–77operations management, 16–17

in MES, 162in value chain, 9

optimization, 25order-fulfillment systems

case studiesregional pharmaceutical distributor

requiring next-day delivery, 212–213TAGG Logistics, 214–215Whirlpool, 213–214

CRM systems, 207–208Lean order fulfillment, 208OMS, 206–207order delivery, 210–211order placement, 209order preparation and loading, 210order processing, 209–210shortening the order processing cycle,

211–212WMS, 205–206

light-directed systems, 206voice-directed picking, 206

Orlicky, Joseph, 130outbound logistics, in value chain, 10outsourcing, 225overdesign, as waste, 32overprocessing, 30overproduction, 30

PP2P (procure-to-pay), 145Papa John’s Pizza, TMS case study,

199–200Pareto charts, 50pCards, 59people-enabling software, 71–72performance

benchmarking, 233–234flexibility, measuring, 236KPIs, 233reliability of deliveries, measuring,

235–236responsiveness, measuring, 236

phases of hardware/software selection, 61–63

demonstrations, 62planning and budgeting, 61requirements analysis, 61–62vendor research, 62

Philips Consumer Lifestyle, reverse logistics case study, 226–227

physical distribution, 17planned POs, 126planning levels

operational planning level, 76–77strategic planning level, 75tactical planning level, 75–76

poor measurement, as waste, 32poor planning, as waste, 32–33portable printing, 262Porter, Michael, 9POs (purchase orders), 126–127

issuing, 58–60predictive analytics, 238pre-negotiated blanket POs, 59pre-negotiated VMI POs, 59prescriptive analytics, 238pricing, 57–58


289 Index

processing time, 28procurement, 16, 125, 139

approving invoice for payment, 60–61

assuring correct delivery, 60direct procurement, 53documents, automating, 139–140e-procurement, 140establishing specifications, 55identify and review requirements,

53–54indirect procurement, 54issuing purchase orders, 58–60Lean procurement, 140–143

Atea, case study, 147–148attributes, 141Clariant, case study, 147Toshiba Semiconductor Company,

case study, 146pCards, 59price negotiation, 57–58receipt of goods, 60selecting suppliers, 55–57software, 143–144standalone solutions, 144–145technology options, 143–145in value chain, 10

product returns process, 220production planning

ERP, 104–105technology options, 104upgrading technology, case study,

105–106project management, 65–66PSI (production, sales, and inventory)

reports, 102Ptak, Carol, 131pull systems, 33, 46purchasing, 125, 126–127

industrial purchasing, 127–128mercantile purchasing, 127

QQR (quick response), 247–248quality

measuring, 234seven tools of, 50

strategies, 8

RRadio Flyer, ERP case study, 156–157Radisys, Lean S&OP case study, 121–122Raytheon, MRP case study, 137–139RCCP (rough cut capacity planning), 101receipt of goods, 60reliability of deliveries, measuring,

235–236remanufacture and refurbishment,

224–225reports, PSI reports, 102requirements, identifying, 53–54researching vendors, 62responsiveness, measuring, 236reverse logistics, 219–220

Lean reverse logistics, 220–225asset recovery, 225compacting the distribution cycle

time, 222CRC, 224financial management, 225gatekeeping, 221–222GENCO, case study, 228–229negotiation, 225Nokia, case study, 227–228outsourcing, 225Philips Consumer Lifestyle, case study,

226–227remanufacture and refurbishment,

224–225zero returns, 224

product returns process, 220technology options, 222–223


290 Index

Reverse Logistics Executive Council, 220reviewing requirements, 53–54RFI (request for information), 55–56RFID (radio frequency identification), 24,

71, 222–223, 263RFP (request for proposal), 56RFQ (request for quotation), 56risk management, 259R-Log software, 228ROI (return on investment), for TMS,

197–198routine view of information systems, 22RTLS (real-time location systems), 263

SS&OP (sales and operations planning),

111–113Lean S&OP, 113–114

Continental Mills, case study, 119–121Infineon Technologies AG, case study,

117–118Lance, case study, 118–119Radisys, case study, 121–122

meetings, 112–113technology options, 115–117

SaaS (Software-as-a-Service), 94–95sales

S&OP, 111–113in value chain, 10

Sales and Operations Planning—Best Practices, 114–115

sales force automation, 207–208SAS white paper, “The Lean Approach

to Business Forecasting”, 91–93scatter diagrams, 50SCE (supply chain execution), 23

software, 68–69scheduling

APS systems, 176–178Asprova, case study, 178–179

Mueller Stoves, case study, 180–181technology options, 178

FCS, 172, 177–178Lean scheduling, 102–104

Durabilt windows, case study, 110–111ERP, 104–105heuristics, 103minimizing waste, case study, 106–107Nestlé Pakistan, case study, 107–110production planning, 103takt time, 103upgrading production planning

technology, case study, 105–106manufacturing schedules, 171–172medium-term scheduling, 172–173MPS, PSI reports, 102RCCP, 101short-term scheduling, 171–172

continuous industry scheduling, 173discrete industry scheduling, 174–175Lean short-term scheduling, 176in service industries, 175

SCM (supply chain management), 4–5collaboration, 245–246

80/20 rule, 246Lean supply chain collaboration,

247–250technology options, 250–251

consultants, 65defined, 15history of, 17–19SCOR model, 13–14software

best practices, 258–260market, 66–67SCE, 68–69SCP, 67–68selecting, 64–72trends, 257–258

Value Chain model, 9–11SCOR model, 13–14, 234–236

asset management metrics, 236


291 Index

cost metrics, 236delivery reliability, measuring, 235–236flexibility, measuring, 236responsiveness, measuring, 236

SCP (supply chain planning), 23software, 67–68

selectingERP systems, 155–156hardware/software, 61–63

“best in class” versus single integrated solution, 64–65

contract negotiation, 63demonstrations, 62make or buy, 63–64planning and budgeting, 61requirements analysis, 61–62vendor research, 62

implementation partners, 63suppliers, 55–57vendors, 56–57

service, 77–78service industries, scheduling, 175service orientation, 25seven tools of quality, 50shift scheduling, 175Shin, Hojung, 132–133shortening the order processing cycle,

211–212short-term scheduling, 171–172

APS systems, 176–178continuous industry scheduling, 173discrete industry scheduling, 174–175in service industries, 175technology options, 178

short-term supply chain technology trends, 70

“silo” mentality, avoiding, 256Six Sigma, 4skills, as waste, 30SM (supplier management), 22Smith, Chad, 131

softwareDRP, 188–189market, 66–67people-enabling software, 71–72procurement, 143–144

standalone solutions, 144–145R-Log, 228SCE, 68–69SCM

best practices, 258–260emerging trends, 257–258

SCP, 67–68selecting, 61–63

“best in class” versus single integrated solution, 64–65

contract negotiation, 63demonstrations, 62make or buy decisions, 63–64planning and budgeting, 61requirements analysis, 61–62SCM systems costs and options, 64vendor research, 62

supply chain analytics, 238–239trends, 70–72

source-to-pay solutions, 145sourcing, 125–126specifications, establishing, 55speech recognition, 262“square root” rule, 79staff scheduling, 175standard POs, 126standardized work, 37–38strategic planning level, 75strategic sourcing, 125–126strategic view of information

systems, 22suppliers, selecting, 55–57supply chain

“buyer driven”, 18functions of, 16–17future technology spending, 265–266


292 Index

supply chain (Continued)IT, 19–25

interactive view of information, 19–21macro processes, 22–23technology trends, 24–25viewpoints of information systems, 22

network optimization, 80–85models, 80–82technology options, 82

paradigm shifts to expect, 267versus SCM, 15trends, 256–257

supply chain analytics, 236–240case studies

Anna’s Linens, 240–241H.D. Smith, 241–242steel manufacturer, 241

software, 238–239technology options, 238–240

Supply Chain Council, 13–14supply chain event management, 69supply planning cross-functional

meeting, 112sustainability, 25, 256

Ttactical planning level, 75–76tactical view of information systems, 22TAGG Logistics, order fulfillment case

study, 214–215takt time, 103Taylor, Frederick, 17teamwork, in Lean, 35–36technology

APS systems, 178in collaborative supply chain systems,

250–251ERP, 154–156forecasting technology options, 94–96global supply chains, 6

IS, 7IT, aligning with business objectives,

11–13leveraging in Lean, 50–52MRP, 133–135network optimization, 80–85

global network design, case study, 84–85

models, 80–82North American distribution

network optimization, case study, 83–84

standalone systems, 82procurement, 143–145reverse logistics, 222–223S&OP, 115–117selecting, 61–63

contract negotiation, 63demonstrations, 62make or buy, 63–64planning and budgeting, 61requirements analysis, 61–62vendor research, 62

supply chain analytics, 238–240TMS, 198–199in value chain, 10

Terra Technology, 98“Tim Woods”, 30time, measuring, 234time buckets, 89–90time strategies, 8TM (transactional management), 23TMS (transportation management

systems), 68, 195–196case studies

Miller Brands UK, 202–203Papa John’s Pizza, 199–200UltraShipTMS, 201

key functionalities, 195–196Lean TMS, 196–197licensing, 198


293 Index

ROI, 197–198technology options, 198–199

Toshiba Semiconductor Company, procurement case study, 146

tour scheduling, 175TPM (total productive maintenance), 48–49TPS (Toyota Production System), 27Traansmission, 260traceability, 256Transport Data Systems, MRP case study,

136–137transportation, 16

as waste, 30trends

general supply chain trends, 256–257in SCM software, 257–258in supply chain technology, 24–25

emerging trends, 70–72short-term trends, 70

Trent, Robert, 31Trunick, Perry, 16

UUber, 260UltraShipTMS, TMS case study, 201untapped creativity, as waste, 32upgrading production planning

technology, case study, 105–106

VValue Chain model, 9–11value stream mapping, 43

order processing, 210value-added activities, 28–29VAR (value-added reseller), 63vendors

identifying, 56–57procurement software vendors, 143

researching, 62software vendor consultants, 65

VICS (Voluntary Inter-Industry Commerce Standard Association), 248

visual management systems, 164–165visual workplace, 38–41VMI (vendor-managed inventory), 59voice-directed picking, 206VSM (value stream mapping), 164

Wwaiting, as waste, 30warehousing, 16waste, 29–35

changeovers, 47minimizing waste, case study,

106–107websites, APICS, 13–14what-if analysis, 95Whirlpool, order-fulfillment system

case study, 213–214white papers

“The Lean Approach to Business Forecasting”, 91–93

“Lean Finds a Friend in Demand Driven MRP”, 131

“Mitigate Supply Chain Risk with Collaboration and Visibility to Achieve the Perfect Order”, 4–5

WMS (warehouse management systems), 68, 205–206

light-directed systems, 206voice-directed picking, 206

work cells, 47–48workplace organization, 42

X-Y-ZYMS (yard management systems), 196zero returns, 224
