Supply Chain Cost Control Using Activity-Based Management (Supply Chain Integration)

Supply Chain Cost Control Using Activity-Based Management SUPPLY CHAIN INTEGRATION SERIES Modeling, Optimization, and...

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Supply Chain Cost Control Using Activity-Based Management

SUPPLY CHAIN INTEGRATION SERIES Modeling, Optimization, and Applications Sameer Kumar, Series Advisor University of St. Thomas, Minneapolis, MN Supply Chain Cost Control Using Activity-Based Management Sameer Kumar and Mathew Zander ISBN: 0-8493-8215-7 Financial Models and Tools for Managing Lean Manufacturing Sameer Kumar and David Meade ISBN: 0-8493-9185-7 Additional Titles in

RESOURCE MANAGEMENT SERIES Handbook of Supply Chain Management, Second Edition by James B. Ayers ISBN: 0-8493-3160-9 The Portal to Lean Production: Principles & Practices for Doing More With Less by John Nicholas and Avi Soni ISBN: 0-8493-5031-X Supply Market Intelligence: A Managerial Handbook for Building Sourcing Strategies by Robert Handfield ISBN: 0-8493-2789-X The Small Manufacturer’s Toolkit: A Guide to Selecting the Techniques and Systems to Help You Win by Steve Novak ISBN: 0-8493-2883-7 Velocity Management in Logistics and Distribution: Lessons from the Military to Secure the Speed of Business by Joseph L. Walden ISBN: 0-8493-2859-4 Supply Chain for Liquids: Out of the Box Approaches to Liquid Logistics by Wally Klatch ISBN: 0-8493-2853-5 Supply Chain Architecture: A Blueprint for Networking the Flow of Material, Information, and Cash by William T. Walker ISBN: 1-57444-357-7 ERP: Tools, Techniques, and Applications for Integrating the Supply Chain by Carol A. Ptak with Eli Schragenheim ISBN: 1-57444-358-5 Integral Logistics Management: Planning and Control of Comprehensive Supply Chains, Second Edition by Paul Schonsleben ISBN: 1-57444-355-0 Introduction to e-Supply Chain Management: Engaging Technology to Build Market-Winning Business Partnerships by David C. Ross ISBN: 1-57444-324-0 Supply Chain Networks and Business Process Orientation by Kevin P. McCormack and William C. Johnson with William T. Walker ISBN: 1-57444-327-5

Collaborative Manufacturing: Using Real-Time Information to Support the Supply Chain by Michael McClellan ISBN: 1-57444-341-0 The Supply Chain Manager’s Problem-Solver: Maximizing the Value of Collaboration and Technology by Charles C. Poirier ISBN: 1-57444-335-6 Lean Performance ERP Project Management: Implementing the Virtual Supply Chain by Brian J. Carroll ISBN: 1-57444-309-7 Integrated Learning for ERP Success: A Learning Requirements Planning Approach by Karl M. Kapp, with William F. Latham and Hester N. Ford-Latham ISBN: 1-57444-296-1 Basics of Supply Chain Management by Lawrence D. Fredendall and Ed Hill ISBN: 1-57444-120-5 Lean Manufacturing: Tools, Techniques, and How to Use Them by William M. Feld ISBN: 1-57444-297-X Disassembly Modeling for Assembly, Maintenance, Reuse, and Recycling by A.J.D. Lambert and Surendra M. Gupta ISBN: 1-57444-334-8 Back to Basics: Your Guide to Manufacturing Excellence by Steven A. Melnyk and R.T. Chris Christensen ISBN: 1-57444-279-1 Enterprise Resource Planning and Beyond: Integrating Your Entire Organization by Gary A. Langenwalter ISBN: 1-57444-260-0 Restructuring the Manufacturing Process: Applying the Matrix Method by Gideon Halevi ISBN: 1-57444-121-3 Inventory Classification Innovation: Paving the Way for Electronic Commerce and Vendor Managed Inventory by Russell G. Broeckelmann ISBN: 1-57444-237-6

Supply Chain Cost Control Using Activity-Based Management Sameer Kumar

St. Thomas University, Minneapolis, Minnesota, USA

Matthew Zander

Consultant, Rochester, Minnesota, USA

Boca Raton New York

Auerbach Publications is an imprint of the Taylor & Francis Group, an informa business

Auerbach Publications Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2007 by Taylor & Francis Group, LLC Auerbach is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-10: 0-8493-8215-7 (Hardcover) International Standard Book Number-13: 978-0-8493-8215-4 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www. copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Kumar, Sameer. Supply chain cost control using activity based management / by Sameer Kumar and Mathew Zander. p. cm. -- (Supply chain integration series) Includes bibliographical references and index. ISBN 0-8493-8215-7 1. Business logistics. 2. Activity-based costing. 3. Contracting out--Management. I. Zander, Matthew. II. Title. III. Series. HD38.5.K86 2006 658.7068’1--dc22

2006040492

Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the Auerbach Web site at http://www.auerbach-publications.com

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Dedication To our families and friends

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Preface Outsourcing has become a predominant practice, and the cost of procured components now makes up the majority of the cost in manufactured products. The literature provides a method for supply-chain cost evaluation called total cost of ownership and suggests the use of activity-based costing to quantify it. Activity-based management can be used to manage activitybased costs. This book discusses the competitive advantage that cost analysis and management can bring to the companies within a supply chain. It addresses a number of strategies for evaluating the total cost inherent in a customer-supplier relationship and proposes a model, using total cost of ownership (TCO), activity-based costing (ABC), and activitybased management (ABM) for analyzing and controlling supply-chain costs. It uses industry survey data to examine whether these techniques are being used in real life, which factors affect their usage in the supply chain, and whether they are producing results. Descriptive and statistical analyses of the data are used to validate these observations, and a versatile game theory matrix is combined with the survey results to suggest cost reduction strategies in competitive environments and predict the outcomes of these strategies. The results show the importance of partnerships in applying activity-based management principles to suppliers and the positive results that use of activity-based management can have on elements of the total cost of ownership.

Key Features The book suggests the application of activity-based management methods to manage product and service costs at suppliers and subsuppliers levels

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viii Supply Chain Cost Control Using Activity-Based Management

and studies whether these methods are being used in industry in producing meaningful results. The key selling points of this book that will distinguish it from others on the topic include: It extends the total cost of ownership concept into the supply chain. It studies actual effect of activity-based management concepts on supplier related costs and overall competitiveness. It studies actual effect that supplier partnerships have on applying activity-based management principles to supplier-related costs. It examines how interaction with competitive players in the marketplace will affect adoption of cost evaluation and management methods based on total cost of ownership and total life cycle cost. Game theory can provide us with a tool to examine these interactions. It examines whether offshoring knowledge work increases shareholder value. It evaluates differences in elemental task learning curves in a production line. It presents major trends in supply chain innovations.

Contribution of the Book Having an accurate assessment of the costs of doing business is a key to staying in business. Seems pretty fundamental, but when a supplier in a supply chain is working to create, design, and produce a piece of an automobile or something some other firm will assemble and market, understanding the real costs is often a moving target. Keeping an accurate picture of these costs becomes even more important as the members of supply chains become dependent on each other and the industry they supply. This dependency actually has a cost associated with it — a cost that is just beginning to be acknowledged. This cost assessment beyond just purchasing and inventory costs is referred to as a total cost of ownership. Understanding the concept of total cost of ownership in a supply chain escapes traditional cost accounting practices because traditional cost accounting simply assigns costs to products and service lines. Activitybased management is the only system that allows a manger to correctly assess the costs involved in a tightly knit supply chain and enables managers to understand not only the total cost of ownership, but how these costs can and should be allocated in a supply chain for a member of the supply chain to remain competitive and profitable.

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Preface ix

Organization of the Book This book covers the subject of supply-chain cost contr ol through activity-based management by addressing various related topics in the following chapters: Chapter 1 Activity-Based Management and Total Cost of Ownership — An Overview This chapter sets the stage for the research reported in this book. The relationship between activity-based management and total cost of ownership is also introduced. Some of the key factors with influence on total cost of ownership in a supply chain that are described include outsourcing, learning curves and supply chain costs analysis and control. Chapter 2 Major Trends in Supply-Chain Innovations This chapter exposes readers to significant trends taking place in innovative supply-chain initiatives for a better appreciation of supply-chain costs. It reviews the concept of the acceleration principle and its effects on the manufacturing environment and also presents how various supply-chain structures are forming across various industries. Chapter 3 Elemental Task Learning Curve in a Production Line This chapter presents an overview of learning curve with a focus on elemental task learning curves in a production line. It helps in improved product and process understanding when profits will occur based on plant size and cumulative output. Chapter 4 Offshoring Knowledge Work to Increase Shareholder Value This chapter seeks to report how offshoring knowledge work has become an important aspect of the American economy and the challenges companies should consider before making the conversion. It is observed that the benefits of utilizing low-cost labor in other countries not only result in direct savings, but indirect savings as well. These indirect savings are realized by reinvesting in more value-added activities across the organization. Through a case study, it is shown how one company that has announced it has offshored its work has relatively better year-to-year performance than the other using the DuPont financial analysis model. Chapter 5 Integrated Total Cost of Ownership and Activity-Based Management Process Model This chapter addresses a number of strategies for evaluating the total cost inherent in a customer-supplier relationship and proposes a model, using total cost of ownership (TCO), activity-based costing (ABC), and activity-based management (ABM) for analyzing and controlling supply chain costs, which can be integrated into a balanced scorecard (BSC) management system. A hypothetical model, which is the basis of the TCO process model, is also proposed. Eleven hypotheses are evaluated and validated as part of this study.

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Chapter 6 Methodology for Analysis In this chapter the survey construct is described in detail. This includes the attributes of subjects surveyed, survey instrument design, sample size, profile of the survey participants’ organizations, and the organization of the survey. Survey results were tallied at the macro level. Chapter 7 Analysis and Findings This chapter presents an analysis of the hypothetical model using descriptive and statistical analyses of data gathered from a detailed survey of companies in various industries. The results obtained from the analysis are summarized. This is followed by a game theory analysis of the same data to determine dominant TCO evaluation and management strategies. Chapter 8 Conclusion and Recommendations Finally, significant results realized from the research study show the importance of partnerships in applying activity-based management principles to suppliers and the positive results that use of this approach can have on the total cost of ownership in a supply chain. Limitations of this analytical work are outlined and a number of recommendations for future possibilities to further investigate this topic are described.

References The book provides a comprehensive list of up-to-date references on this topic to enable readers to study various subtopics more in depth.

Appendix The survey instrument used and the data collected from participants in various industries are also included.

Acknowledgments The authors would like to thank all those who helped us in bringing out this book for publication. First and foremost we have greatly benefited from the wealth of a vast array of published material on the subjects of supply-chain cost, activity-based management, offshoring, learning curves, total cost of ownership, and supply-chain management. We would like to thank the reviewers of the manuscript of the book. The contents of this book have benefited immensely from their valued insights, comments, and suggestions.

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The authors are especially grateful to the participants of industry surveys whose valued contributions facilitated enhanced understanding of the focus of this book. Their efforts in providing quality responses to questions were significant in validating research postulates. This book is largely based on information derived from the analysis of survey data. Names of participants are not listed here due to confidentiality of surveys conducted. Both authors are indebted to their families, parents, and friends for their support. Finally, we wish to thank our editor, Raymond O’Connell, and the entire production team at the Taylor & Francis Auerbach group for their assistance and guidance in successful completion of this book.

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About the Authors Sameer Kumar is a professor and Qwest Endowed Chair in global communications and technology management in the College of Business at the University of St. Thomas, Minneapolis, Minnesota. Prior to this position he was a professor of engineering and technology management at the University of St. Thomas. Before joining St. Thomas, Dr. Kumar was a professor of industrial engineering in the Department of Industrial Management, University of Wisconsin–Stout. His major research areas include optimization concepts applied to design and operational management of production and service systems. He has been actively involved in a wide variety of challenging industry projects for more than 25 years in the United States and India. He has published and presented articles in various research journals and conferences. He is a registered professional engineer, certified manufacturing technologist, certified manufacturing engineer, and certified plant engineer, and has earned master’s degrees in mathematics (University of Delhi), computer science (University of Nebraska), and industrial engineering and operations research (University of Minnesota). He received his Ph.D. in industrial engineering from the University of Minnesota. Matthew Zander is a procurement quality engineer at IBM where he supports its engineering and technology services (E&TS) group in Rochester, Minnesota. He graduated from Michigan Technological University in Houghton with bachelor of science degrees in mechanical engineering and scientific and technical communications and from the University of St. Thomas in St. Paul, Minnesota, with a master’s degree in manufacturing systems engineering. He has previously worked in procurement cost engineering and server software system documentation at IBM and held quality system internship positions at Super Steel Products Corporation in Milwaukee, Wisconsin, and General Motors Corporation Technical Center in Warren, Michigan. xiii

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Contents 1 Activity-Based Management and Total Cost of Ownership — An Overview.........................................................1 Introduction ....................................................................................................... 1 References.......................................................................................................... 8

2 Major Trends in Supply-Chain Innovations ............................11 Introduction ..................................................................................................... 11 Influencing the Manufacturing Environment ................................................ 14 The Acceleration Principle ........................................................................ 14 Lead Time and Inventory Reduction Syndromes ............................... 14 Supply-Chain Structure ................................................................................... 15 References........................................................................................................ 22

3 Elemental Task Learning Curves in a Production Line ..........23 Introduction ..................................................................................................... 23 Learning Curves .............................................................................................. 24 Balancing Cycle Times ................................................................................... 27 Interrelationships of Elemental Task Learning Curves and Line Balance.. 28 Organizational Learning.................................................................................. 32 Conclusion ....................................................................................................... 33 Recommendation............................................................................................. 33 References........................................................................................................ 34

4 Offshoring Knowledge Work to Increase Shareholder Value ............................................................................................35 Introduction ..................................................................................................... 35 Knowledge Work ............................................................................................ 37 Drivers of Knowledge Work Offshoring ....................................................... 37 Benefits to Business........................................................................................ 42 Economic Implications ................................................................................... 44

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xvi Supply Chain Cost Control Using Activity-Based Management Drawbacks and Risks ..................................................................................... 45 Offshore Locations .......................................................................................... 46 Case Study ....................................................................................................... 48 Conclusion ....................................................................................................... 52 References........................................................................................................ 53

5 Integrated Total Cost of Ownership and Activity-Based Management Process Model ......................................................55 Introduction ..................................................................................................... 55 Literature Analysis ........................................................................................... 56 Process Models................................................................................................ 67 Hypothetical Model......................................................................................... 70 Game Theory .................................................................................................. 74 References........................................................................................................ 75

6 Methodology for Analysis..........................................................79 Introduction ..................................................................................................... 79 The Survey Construct ..................................................................................... 79 Data Analysis................................................................................................... 83

7 Analysis and Findings................................................................89 Introduction ..................................................................................................... 89 Hypothesis Testing.......................................................................................... 89 Results ............................................................................................................ 140 Game Theory Analysis ................................................................................. 146

8 Conclusions and Recommendations ......................................153 Appendix A Survey Instrument ............................................................................157

Appendix B Survey Data .......................................................................................167 Index..................................................................................................217

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Chapter 1

Activity-Based Management and Total Cost of Ownership — An Overview Introduction This book explains the competitive advantage that cost analysis and management can bring to the companies within a supply chain. It addresses a number of strategies for evaluating the total cost inherent in a customer–supplier relationship and proposes a model, using total cost of ownership (TCO), activity-based costing (ABC), and activity-based management (ABM) for analyzing and controlling supply-chain costs that can be integrated into a balanced scorecard (BSC) management system. Industry survey data is examined using descriptive and statistical analyses to determine whether these techniques are being used in real life, which factors affect their usage in the supply chain, and whether they ar e producing results. Whereas most businesses and enterprises conduct some form of budgeting and trend analysis to plan and forecast, many tools and techniques have evolved over the years to measure performance, control costs, and improve service. Some of these management tools include ABC, ABM,

1


2 Supply Chain Cost Control Using Activity-Based Management

1. Customers

served by

Activities

assigned to

Resources

consume

Resources

have

Costs

2. Costs

assigned to

Activity Pools

Costs Objectives

Figure 1.1 Activity-based costing model.

benchmarking, process improvement, process reengineering, Total Quality Management (TQM), balanced scorecard, and Six Sigma. Activity-based costing (ABC) is a procedure that measures the cost of objects, such as products, services, and customers. ABC first assigns resource costs to the activities performed by the organization, and activity costs are then assigned to the products, customers, and services that benefit from or create the demand for the activities (Kidwell et al., 2002). Morse et al. (2003, pp. 184–185) summarize the concepts underlying ABC (see Figure 1.1): 1. Activities performed to fill customer needs consume resources that cost money. 2. The cost of resources consumed by activities should be assigned to cost objectives on the basis of the units of activity consumed by the cost objective. A cost objective is typically a product or service provided to the customer. ABC is a relatively new approach to cost assignment. However, because of its ability to provide more detailed and relevant analysis of costs for internal decision making, it is gaining recognition as being superior to cost assignment systems traditionally used for financial reporting. On the other hand, each ABC system needs to be designed to fit the needs and circumstances of a particular organization, which make the implementation of ABC systems expensive and time consuming. As a result, some companies decide to only develop ABC data for processes that management deems critical for success (Morse et al., 2003, p. 191).


Activity-Based Management and Total Cost of Ownership 3

ABC data enables managers to engage in ABM. ABM consists of performing activities more efficiently, eliminating activities that do not add value for customers, improving delivery of services, and developing better relationships with customers and suppliers. The goal of ABM is to satisfy customer needs while making fewer demands on organizational resources (Kidwell et al., 2002). ABM focuses managerial attention on what is most important among activities performed to create value for customers. One way to do this is to classify each activity as value-added or non-value-added. Management can evaluate and either streamline, reduce, or eliminate non-value-added activities to save time and money. Once this is done, it can then address the more difficult task of reducing cost for value-added activities (Morse et al., 2003, pp. 193–194). Again, ABM is a major undertaking, and, in spite of its benefits, adoption remains low because of the time and resources involved in successful implementation (Gourdie, 2001). Benchmarking is the process of studying and comparing how other organizations perform similar activities and processes. The other organizations are generally selected because of their excellent performance of the benchmarked process (Kidwell et al., 2002). It encompasses both measurements and practices into a systematic and disciplined approach that stresses emulating (or “creatively swiping”) and implementing best practices (Kolarik, 2002). When executed well, benchmarking reveals gaps between the performance of the benchmarker and that of the benchmarked “best practices” leader, and often suggests what needs to be done to close these gaps (Stauffer, 2003). One of the biggest mistakes made when beginning a benchmarking endeavor is looking only at companies within the same industry or benchmarking the competition. But what if the competition is worse than one’s own company? Instead, the benchmarking team should evaluate a company that is well known for being a good model of successful business practices and processes. Another mistake companies make is measuring what is easy rather than what is needed (Stauffer, 2003; Forst, 2003). But this can fail to provide actionable information, something that is sufficiently detailed for a unit manager to make changes that improve performance. Instead, a company should examine the factors that are most important to a customer, and then identify companies that excel in each factor. With process improvement, or continuous improvement, an organization’s employees constantly evaluate products, services, and processes, seeking ways to do better. Some companies have the goal of drastically reducing costs or radically improving quality or service. In such cases, it may be necessary to reinvent or reengineer a process instead of simply improving it (Morse et al., 2003). Process reengineering is a technique that has been described as “the fundamental rethinking and radical redesign



of business processes to achieve rapid and dramatic improvements in critical contemporary measures of performance, such as cost, quality, service, and speed” (Hammer and Champy, 1993). Based primarily on the works of Thomas Davenport, J.E. Short, and Michael Hammer, reengineering creates new processes to displace the old ones (Selladurai, 2002). Reengineering was embraced in the 1990s with its promises, but then disappeared around 1997 when, in spite of how good it sounded, it was too vague and technologically challenging for users to apply successfully (Clermont, 2001). Today, it has reappeared under different names owing to the ease of accessing information via the Internet, as well as the new generation of powerful, flexible software packages that enable companies to integrate systems and extract real-time information. TQM, based on the ideas of Edward Deming, Joseph Juran, and Philip Crosby, aims to improve the processes within an organization by emphasizing continuous quality improvement through focus on implementing incremental change with minimal variation to existing processes (Selladurai, 2002). It is a management-led, organization-wide commitment to quality, as defined by both internal and external customers. It requires the development of a clear vision of what the organization does, what its values and goals are, and how it is going to achieve them. TQM focuses on understanding customers and their needs, as well as the needs of employees, while focusing on processes (Kidwell et al., 2002). It also proclaims the values of teamwork and employee participation, the use of reasoning-based statistical analysis of factual data, and the training of employees and managers across the organization. Although TQM has its share of critics, many others have expressed strong and continued support of the management technique (Selladurai, 2002). A balanced scorecard, established by Robert Kaplan and David Norton in the early 1990s, is a set of measures that give top managers a fast but comprehensive view of the business. It complements traditional financial measures with other nonfinancial, operational measures. Based on a firm’s overall strategy, the scorecard typically contains a diverse set of 16 to 28 measures, commonly organized into four categories (see Figure 1.2): customer satisfaction, internal processes, and the organization’s learning and growth activities — operational measurements that are the drivers of future financial performance (Kaplan and Norton, 2005; Gumbus, 2005; Kidwell et al., 2002; Salterio and Webb, 2003; Jensen and Sage, 2000). Four processes are involved in managing a balanced scorecard, and they follow the “plan, do, check, and act” sequence of Shewart and Deming in an iterative manner: business planning, feedback and learning, clarifying and translating the vision, and communicating and linking (Jensen and Sage, 2000). The balanced scorecard can help management form a link between long-term strategic objectives and short-term actions



Financial Perspective Objectives: Improve profitability

Measures: Return on Investment

Customer Perspective Objectives: Improve customer loyalty

Internal Business Process Perspective

Measures: Repeat sales; Response time per customer request

Objectives: Measures: Improve Orders filled processing quality w/out error; Ontime delivery

Learning and Growth Perspective Objectives: Improve staff skills

Measures: Employee productivity; Hours of training/employee

Figure 1.2 Categories of a balanced scorecard.

(Kidwell et al., 2002). Proponents of the scorecard claim that it clarifies and translates the firm’s vision and strategies, communicates and links strategic objectives and measures, enhances strategic feedback and learning in the firm, and helps plan, set targets, and align initiatives. The success of planning, target-setting, and aligning performance measures to strategic initiatives often depends on whether the managerial performance evaluation system directs managers’ attention to those areas. They found that if the manager’s compensation was tied to the results of the scorecard, the likelihood of the success of the objectives being met was increased. Six Sigma is a business improvement approach that seeks to find and eliminate causes of mistakes or defects in business processes by focusing on outputs that are of critical importance to customers. As a result, process performance is enhanced, customer satisfaction is improved, and the bottom line is impacted through savings and increased revenue (Bisgaard et al., 2002). It is a strategic approach that works across all processes, products, and industries. Six Sigma is also a measure of process performance. The ability to produce products and services with only 3.4 defects per million would yield a Six Sigma process that is considered to be world-class performance for many processes (Knowles et al., 2005; Meyer, 2005; Folan and Browne, 2005).



Some believe these management tools and techniques are helpful in meeting the challenges of increased accountability, whereas others dismiss them as merely a fad (Kidwell et al., 2002, pp. 63–66). Many of the performance tools, including benchmarking, continuous improvement, reengineering, TQM, and Six Sigma, are variations of emulating how others do business. However, with most initiatives implemented by companies eager to outshine and outperform the competition, the emphasis is placed on instilling a new work culture within an existing one, without the benefit of a theoretical foundation to justify, tailor, and guide this superposition. Kolarik (2002) believes this may be the reason for the relatively low success rates associated with these well-intended efforts. Recently, the term outsourcing has taken on a distinct and politically charged definition: the exportation of labor, both manufacturing and technical services, to overseas locations such as China and India where labor costs are lower than in the United States. This is just the latest permutation, however, on a process that has been ongoing for several decades. In this larger context, outsourcing means taking activities that exist within the company or firm and transferring them to a supplier company or agency outside of the original company. For example, a manufacturing operation that was once vertically integrated into the company’s operations could be contracted out to another manufacturing company that specializes in that type of manufacturing activity. Even the supplier management activity itself can become a target of outsourcing (Maltz and Ellram, 1999). Companies outsource for numerous reasons. The outsourced supplier specializes in the activity and can conduct it much more efficiently than the purchasing company. This sometimes means that the purchasing company can gain access to supplier-owned technology that it might not otherwise have (Tully, 1994; Ehie, 2001; Angeloni, 2002). Eliminating the activity in the original company frees up fixed resources such as labor and overhead (Ehie, 2001; Angeloni, 2002). It provides the flexibility to switch product offerings on a relatively short-term basis through workforce balancing and accelerated product development (Tully, 1994; Ehie, 2001). Costs can be reduced by taking advantage of the contracted manufacturer’s economy of scale (Ehie, 2001). Whereas many companies once had monolithic vertical supply structures (own facilities that produced parts and subassemblies), most now focus on their core business, often just developing and marketing their end product. Parts and subassemblies are manufactured, and often designed, by suppliers and vendors. Some do not even view themselves as manufacturers anymore but as service providers, providing a linkage between end consumers and the manufacturer. This is particularly true in the electronics and automotive industries, in which the modularity of the



products allows for easy outsourcing of manufacturing (Tully, 1994), though recent downturns in the electronics market are pushing contract manufacturers to diversify into other industries (Serant, 2002). This has led to the development of supply chains, interconnected and highly dependent networks of companies that take products and services from concepts and raw materials all the way to the end customer. These organizations really came to prominence in the 1980s, as companies sought to enhance competitiveness by containing costs, enhancing product value, compressing the time to market, creating channel efficiency, and becoming more responsive to customers (Cavinato, 1991). As the outsourcing trend continues, companies will not merely compete against each other, entire supply chains will. The new strategy of supply chains will use a new set of principles: the only entity that puts money into the supply chain is the end customer, and the only viable solutions ensure that every element of the supply-chain profits. Therefore, supply-chain management is about economic value and total content; price is not the only issue anymore (Handfield, 2002, Johnston, 2004). To stay competitive, the companies that sit within these supply chains will need to understand and influence the costs within their supply chains. Marien and Keebler (2002) have suggested that there are six stages of cost focus in a company’s supply chain. Stage 1: Functional cost minimization — functional areas look to reduce their individual costs, often with cost penalties elsewhere in the system. Stage 2: Lowest delivered cost — company looks to minimize costs on acquired and delivered goods and services, often by looking at trade-offs in purchasing, transportation, and asset management. Stage 3: TCO — company begins to examine inventory and asset carrying costs. Stage 4: Enterprise value-add costs of sales — company begins to look at the costs beyond the mere costs of material ownership, e.g., sales and marketing, engineering, technical support, IT, etc. Stage 5: Interenterprise value-add cost with immediately adjacent trading partners — examines trade-offs and best working relationships with the immediate customer and supplier in the supply chain. Stage 6: Lowest end-user-delivered supply-chain cost — examines trade-offs and services between all members of the supply chain with focus on the ultimate end user. The supply-chain cost perspective is migrating toward a total view of the system both upstream and downstream, beyond just purchasing and inventory costs (Handfield, 2002).



In this environment, purchasing takes on a critical role. In most supplychain situations, procurement organizations become the manager of the wide and varied relationships with vendors, channeling communications from customer to vendor and leveraging buying power to the company’s advantage (Cavinato, 1991). They manage increasing amounts of the company’s overall expenses. Cavinato (1992) estimated that the cost of procurement specification and acquisition is 55 to 60 percent of the total cost in manufacturing firms. Carr and Ittner (1992) estimate that purchase materials, components, and subassemblies represent over 70 percent of manufacturing expense; Ellram (1995) placed it at 63.5 percent of total cost in manufacturing firms and 25 percent in nonmanufacturers. More recently, Handfield (2002) puts the cost of managing the supply chain at 56 percent of revenue in average manufacturing companies, increasing as one looks at more high-technology industries. Also, each dollar cut from the cost of purchasing generates the same bottom-line effect as increasing sales by $17 (Handfield, 2002). In a competitive worldwide market with thinning margins, purchasing finds itself under pressure to reduce procurement costs.

References Angeloni, J. (2002), Contract manufacturing and outsourcing can yield lower overhead and increase yields, Military and Aerospace Electronics, August 2002, p. 30. Bisgaard, S., Hoerl, R., and Snee, R. (2002), Improving business processes with Six Sigma quality, ASQ’s Annual Quality Congress Proceedings, 701–704. Carr, L.P. and Ittner, C.D. (1992), Measuring the cost of ownership, Cost Management, Fall, 42–51. Cavinato, J.L. (1992), A total cost/value model for supply chain competitiveness, Journal of Business Logistics, 13(2), 285–301. Cavinato, J.L. (1991), Identifying interfirm total cost advantages for supply chain competitiveness, Journal of Purchasing and Materials Management, 27(4), 10–15. Clermont, P. (2001), Reengineering revisited: death and reincarnation, Information Strategy: The Executive’s Journal, 17(4), 6–9. Ehie, I.C. (2001), Determinants of success in manufacturing outsourcing decisions: a survey study, Production and Inventory Management Journal, Fall, 31–39. Ellram, L.M. (1995), Activity-based costing and total cost of ownership: a critical link, Journal of Cost Management, 8(4), 22–30. Folan, P. and Browne, J. (2005), Development of an extended enterprise performance measurement system, Production Planning and Control, 16(6), 531–544. Forst, L. (July 2003), Benchmarking success hinges on internal data, Industrial Management, 20–23.


Activity-Based Management and Total Cost of Ownership 9 Gourdie, S. (November 2001), Tools of the Trade, Financial Management (CIMA), 38–39. Gumbus, A. (2005), Introducing the balanced scorecard: creating metrics to measure performance, Journal of Management Education, 29(4), 617–630. Hammer, M. and Champy, J. (1993), Reengineering the Corporation: A Manifesto for Business Revolution, New York: Harper Business. Handfield, R. (December 2002), Reducing Costs across the Supply Chain, Optimize, 54–60. Jensen, A. and Sage, A. (2000), A systems management approach for improvement of organizational performance measurement systems, Information Knowledge Systems Management, 2(1), 164–174. Johnston, S.J. (June 7, 2004), What Drives Supply Chain Behavior?, Harvard Business School — Working Knowledge. Available at http://working knowledge.hbs.edu/item.jhtml?id=4170&t=operations. Kaplan, R.S. and Norton, D.R. (2005), The Balanced Scorecard: Measures That Drive Performance, Harvard Business Review, 83(7–8), 172–180. Kidwell, L., Ho, S., Blake, J., Wraith, P., Roubi, R., and Richardson, A. (2002), New management techniques: an international comparison, The CPA Journal, 72(2), 63–66. Knowles, G., Whicker, L., Femat, J.H., and Canales, F.C. (2005), A conceptual model for the application of Six Sigma methodologies to supply chain improvement, International Journal of Logistics: Research and Applications, 8(1), 51–65. Kolarik, W. (2002), Process Design and Integration Theory, Stillwater, OK: Oklahoma State University. Retrieved on December 10, 2003, from http://citeseer.nj.nec.com/update/531979. Maltz, A. and Ellram, L. (1999), Outsourcing Supply Management, The Journal of Supply Chain Management, 35(2), 4–17. Marien, E.J. and Keebler, J. (December 16, 2002), 6 Stages in Supply-Chain Costing, Traffic World Online, 24. Available at http://www.trafficworld.com/. Meyer, M.W. (2005), Can performance studies create actionable knowledge if we can’t measure the performance of the firm?, Journal of Management Inquiry, 14(3), 287–291. Morse, W., Davis, J., and Hartgraves, A. (2003), Management Accounting: A Strategic Approach (3rd ed.), Mason, OH: South-Western. Salterio, S. and Webb, A. (2003), The Balanced Scorecard, CA Magazine.com. Retrieved December 3, 2005, from http://www.camagazine.com/index.cfm/ ci_id/16066/la_id/1/camagazine/1/print/true.htm. Selladurai, R. (2002), An organizational profitability, productivity, performance (PPP) model: going beyond TQM and BPR, Total Quality Management, 13(5), 613–619. Serant, C. (December 2, 2002), Weak Economy Proves a Drag on OEM Outsourcing Trend, EBN, 3. Retrieved August 23, 2003, from Business and Company Resource Center database. Stauffer, D. (September 1, 2003), Is Your Benchmarking Doing the Right Work?, Harvard Management Update, 1–4. Tully, S. (1994), You’ll Never Guess Who Really Makes …, Fortune, 130(7), 124–128.



Chapter 2

Major Trends in Supply-Chain Innovations Introduction New supply-chain initiatives inundated the marketplace in the past decade, starting with just-in-time inventory management to collaborative product commerce (see Table 2.1). Supply-chain programs launched have been successful in saving billions of dollars for a large number of companies though such programs failed to achieve optimal results for some companies (Koch, 2004). Successful supply-chain initiatives can make it possible for companies to meet customer needs more quickly, less expensively, and through more channels. Better-quality and more reliable goods can reach the market sooner. Mass-customized products and services can become a reality (McVey and Cundiff, 2005; Ertek and Griffin, 2002; Koch, 2002; Iyer and Bergen, 1997). Essentially, five major supply-chain management (SCM) innovations trends are currently taking shape (Poirier and Quinn, 2004): The front end of the supply chain is becoming as important as the back end in maximizing total economic yield. Historically, SCM dealt largely with vendors, making companies focus on improving logistics or the back end of the supply chain. Demand now manifests itself in many more ways — through online marketplaces or partnerships — causing companies to increase their emphasis on the supply chain’s front end. As a result, front-end SCM — 11



Table 2.1 A Decade of Supply-Chain Initiatives Year/Period

1992

During 1993–1994

During 1994–1995 During 1995–1996 During 1996–1997 1997 1998 During 1998–1999 1999 During 1999–2000 2000 2001

Initiatives

Lean manufacturing/just-in-time Third-party logistics Quality circles Manufacturing resource planning II Warehouse management Manufacturing execution systems Supplier integration Manufacturing outsourcing Total Quality Management Product data management Integrated product and process development Advanced planning and scheduling Enterprise resource planning Six Sigma Product life cycle management Integrated supply chain Collaborative planning Customer relationship management eProcurement eFulfillment Exchanges Collaborative product commerce

understanding and responding to customer needs — is becoming an inextricable part of supply-chain strategy. Companies with frontend capabilities should be better able economically to make what the market wants and sell what they have in stock, thus enhancing top-line and margin growth. As companies migrate from internal-only to extended supply chains, collaboration is becoming the most strategic capability. Companies that manage their businesses the old-fashioned way — by taking orders, buying supplies, building products, and shipping them from the warehouse — may lose out to businesses that focus their energies on design, brand management, sales, and marketing, and outsource the rest. Supply chains are becoming complex for any one entity to manage in a competitively dominant way. Assets and functions that are not core to value delivery may be entrusted to specialists. Companies usually outsource noncore functions to the lowest bidder. This is becoming a riskier strategy,


Major Trends in Supply-Chain Innovations 13

because vendors operating on slim margins are increasingly unable to match the types or levels of service offered by other operators. Leading companies are finding new ways to do business, perhaps through shared-profit arrangements in which suppliers benefit from their success. Companies can substitute new, variable-cost outsourcing contracts for owned fixed assets such as trucks and warehouses, thus reducing capital on the books and using only the capacity that is needed rather than owning the excess. The greatest margin potential may occur after a product ships, as service and support become as important as the product itself. With more customers seeking solutions instead of specific products or brands, a growing number of goods are becoming commodities that are mass-produced, low-priced products. Responding to this trend, supply-chain winners are working harder to bundle great products with strong service offerings, thereby maximizing longterm customer profitability and catering to customers’ increased emphasis on total cost of ownership. Customers are increasingly purchasing those products that are conduits for content or services that exceed the intrinsic value of the product itself (Dumond, 2000). Further, business customers are changing their focus from procuring a product based on its attributes alone to valuing the total service provided, such as maintenance and operational reliability. As a result, connecting product sales to the service network is becoming a prime value driver for many companies. supply-chain executives are needed to deliver not only the initial product, but also an ongoing stream of products and services to the consumer — often through different channels and even different locations. These changes have added complexity to most companies’ supplychain operations, but they also have become a major source of revenue and profit growth. The ability to integrate new and innovative capabilities with corporate business models is driving higher levels of value creation. A company’s ability to adapt and change itself is becoming even more critical. Part of the reason is collaboration. Companies positioned to work efficiently with multiple partners are getting most of the action, and those that are difficult to work with are being ignored. Rapid and virtual partnering also is the key to new SCM strategies, as the best integrators work together to attain the biggest prizes. The rest of the chapter examines the influence of acceleration principle on manufacturing environment and describes how the structure of supply chain is evolving.



Influencing the Manufacturing Environment The following section describes the effects of acceleration principle on the manufacturing environment.

The Acceleration Principle Jay Forester at MIT created a management training exercise in the 1950s called “The Beer Game” (Sherman, 1997). It was designed to simulate how products and information flow through multiechelon supply chains. The result of this simulation is what has been called the “Forester’s Effect,” or the acceleration principle. Simply stated, a 10 percent change in the rate of sale at the retail level can result in a 40 percent change in demand for the manufacturer. The acceleration principle results in two side effects that are described in the following subsections.

Lead Time and Inventory Reduction Syndromes All business organizations involve two flows: material and information. The Beer Game only exposes the top layer of problems that manufacturing firms face today with managing these flows. Functional silos within each company affect the flow of information and materials in the same manner, as multiple companies do in the supply chain. Batch pr ocessing of information creates an acceleration principle within the organization. Distorted demand data and delayed information become commonplace, creating several other conditions. The first is a reaction typical of purchasing personnel and production planners. This reaction is referred to as the “lead time (or safety stock) syndrome,” and is illustrated in Figure 2.1. The effect continues to escalate and soon leads to the fatal mistake of increasing capacity based on this condition. This capacity increase is not without a corresponding cost increase. Eventually, the overload is relieved because increased capacity floods the supply chain, causing the second effect from distorted demand data, “the inventory reduction syndrome,” as shown in Figure 2.2. This effect is the result of the organization addressing excess inventory created by the first syndrome. Without process change, these two syndromes feed each other in a continuous loop. Eventually, another silo is established in the organization specifically chartered to run promotions, targeted at reducing excess inventory with the hope of increasing market share. This action is equally as fatal as increasing capacity. The organization has now combined perpetual reductions in sales prices from the inventory reduction syndrome with increasing production costs from the lead time syndrome (Plossl, 1991).



Orders Exceed Capacity in House or at Supplier

Shortage Increase

Lead Times Are Increased

Lead Times Get Longer

Increase lead Times / Safety Stock and More Orders Are Released Backlogs Get Larger

Figure 2.1 The lead time/safety stock syndrome.

Capacity Exceeds Demand Capacity Needs Are Established on Artificial Demand

Inventory Becomes Excessive

Production / Purchasing Plan Using Historical Trends

Sales Promotions Create Artificial Demand This Artificial Demand Reduces Inventory

Figure 2.2 Inventory reduction syndrome.

In a growing market, the combination of these two effects is consumed by the growth in demand. Companies can survive and even flourish during this growth period, in spite of the oscillating cycle to focus on reducing inventory during one time period, then expedite product regardless of cost during the next period. When the market experiences a plateau or drops off at this time, the organization can spiral itself right out of existence.

Supply-Chain Structure A new trend in SCM is to structure the supply chain less rigidly and more flexibly. These new flexible supply chains are sometimes called virtual



supply chains (Poirier and Reiter, 1996) or value web. A value web is a constantly evolving virtual enterprise in which members regularly reform their services, evaluate their customer relations, and coinvent products and services with customers. Most of the Fortune 1000 enterprises are already utilizing some form of value web management (VWM), ranging from ERP to Web sites, but the real power of VWM will be unleashed when these forms converge. VWM represents another plateau of excellence in enterprise design and performance (Andrews and Hahn, 1998). A company’s supply-chain structure may depend on the maturity of their markets, products, customer relationships, etc. A start-up group may have to begin with a loose virtual chain in which there is no formal longterm supplier organization. They will not have the steady business that large, existing firms have, so they bid their suppliers on a job-by-job basis. They need a competitive advantage to charge a higher price to compensate for their high initial costs. As they gain market share and work with their suppliers to find ways to lower costs, they can either make an optimized rigid chain with dedicated suppliers, or perfect their virtual chain. Either way, their costs will decrease as volumes go up, supplier–firm cooperation increases, and all firms determine ways to lower operational and inventory costs. Small (flexible, low-volume, start-up) firms favor working with small (flexible, low-volume, start-up) suppliers with excellent service. Small firms need a product performance advantage to overcome the lowest-price pressure. It would be very difficult for a start-up to create the lowestprice product in the market without a technical breakthrough in production costs, because initial supply-chain costs will be high. Their low volumes do not allow them to carry large inventories (high service) or low price (economies of scale). Large firms favor working with other large firms with similar rigid structures, economies of scale, strict quality systems, and proven records of accomplishment. They can handle larger inventories (better service) and get lower prices from economies of scale (if the orders are there). An exception might be a strong cross-functional team in a large firm that is given relative autonomy and acts like an entrepreneurial start-up. They might be able to gain the benefits of both large firms (economies of scale, strict quality systems, better service, and a proven track record) while still being lean and responsive. In addition, the maturity of the market influences decision. In a mature market, suppliers will already have good operational efficiency built into their business model. This lessens the entry cost into that market for startups. However, the start-up will still need an advantage to overcome the lessened, but still-real price difference. The choice between a rigid or virtual supply chain in a mature market would depend on the number of


Major Trends in Supply-Chain Innovations 17 Table 2.2 Purchasing Excellence versus Supply-Chain Management Purchasing

Functional excellence Tactical/transactional Focus on better buying People purchasing experts Measures are tactical and internalized Communicating with suppliers

Supply-Chain Management

Enterprise impact Strategic Focus also on linkages with multiple business elements Broad business knowledge and skills Measures with business impact and cross-functional goals Integrating suppliers

quality suppliers that fit the particular needs of the customer in the relevant market niche. With only one or just a few quality suppliers, a virtual chain may not be feasible, and a rigid chain may be necessary. Many in industry may take the view that SCM is merely good purchasing. SCM is in fact the linking of the business elements such as supplier, buyer, and customer, and aligning them to better achieve mutual business goals. Table 2.2 differentiates purchasing excellence from SCM. The supply marketplace has changed the need for suppliers to understand complex customer organization to be effective. Relationships between suppliers and customers have become more complex. Figure 2.3 depicts relationships in the past and as they are today. As a result, suppliers are reducing their customer base. They are focusing on competencies, market segmentation (essentially to make sure who they can serve best), identifying strategic customers (only strategic customers are served directly whereas others are served through distribTODAY/FUTURE

YESTERDAY

MANUFACTURING MANUFACTURING

DESIGN DESIGN

CUSTOMER

SUPPLIER SUPPLIER

PURCHASING

MARKETING

QUALITY

STRATEGIC SUPPLY MANAGEMENT

TOP MANAGEMENT TACTICAL ACQUISITION MANAGEMENT

Figure 2.3 More complex relationships between supplier and customer today.



TODAY/FUTURE

YESTERDAY Supply Base

A

B

C

Customer Base

D

CUSTOMER

“Buy from me ! Here is why…”

A

B

C

D

CUSTOMER

“Sell to me! Here is why…”

Figure 2.4 Shows era of reverse marketing.

utors), sharing technology roadmaps, and integrating their global supply chains so that strategic customers get materials and services with minimum effects of any allocations. As such, customers need to be perceived as significant to their suppliers for the best service. There has been worldwide allocation of critical materials and services. Thus, the challenge is whether a customer (a manufacturer of consumer product) is able to get all the strategic materials it needs to support its growth. A customer needs to grow its business without supply constraints. Two major issues confront a customer in the supply marketplace. The first is whether a customer (manufacturer) can easily meet its rapidly changing time-to-market goals. The second is whether suppliers are playing a bigger role in the success of new products. Clearly, cycle times for introducing new products are shrinking. Suppliers are managing their globally distributed customers as one customer. Customers should also manage their globally distributed suppliers as one supplier. Customers must leverage their global business and buying power effectively. Therefore the question is, how should we react? With all these changes occurring, do we think there is the need to have a strategy for supply? One interesting strategy is reverse marketing, proposed by Michiel R. Leenders of the University of Western Ontario. As shown in Figure 2.4, the buyer was passive in the past, whereas the buyer is now more proactive. As a result, suppliers are now reducing their customer base. So, the supplier relations in the 2000s have been more strategic in nature, multifunctionally integrated with increased sharing of information and technology. Such relationships have been less legally binding, with a focus on improving the process, and involve total cost, cycle time, and


Major Trends in Supply-Chain Innovations 19 Table 2.3 Elements of a Successful Partnership Alliance Partnership Elements

Commitment Long term For better or worse Resource sharing (not just material) Need companywide buy-in, not just a supply or sales program Communication Open Multifunctional Frequent Trust Understanding of each other’s businesses Demonstrated mutual benefit Extra value achieved by both parties Beyond traditional buy/sell relationship

quality goals for the life of the product. Finally, such interactions are more focused on solutions while recognizing the benefit of a “win-win” approach. We see more and more partnering strategy among customers and suppliers resulting in forming supplier alliances. The latter is the process of partnering with key suppliers to bring them on the manufacturer’s (customer) team as an extension, not only of its business, but also of the customer’s commitment to world-class excellence in the products and services provided to the manufacturer’s customers. The selection criteria include the following: Every supplier cannot be an alliance partner, and suppliers of strategic value should be the candidates for strategic alliance. Such suppliers should be unique or at least possess preferred capabilities, and also be technology leaders and have similar goals as the manufacturer. The selection process may include obtaining supplier commitment and the nomination and approval of the supplier by customer’s cross-functional steering committee which consists of supply management, development engineering, new-product-introduction engineering, manufacturing, and marketing. The customer’s (manufacturer’s) and supplier’s commitment to supplier alliance partnership include a mutually beneficial relationship, open and honest communication, professional and ethical conduct, accurate and timely performance feedback, first opportunity to supply new designs, and being involved in customer’s business and a long-ter m relationship. Table 2.3 lists the characteristics of healthy customer–supplier alliance partnership. From this partnership, the customer should strive to realize value from suppliers. Value may be defined as the ratio of benefits to costs incurred.


20 Supply Chain Cost Control Using Activity-Based Management Table 2.4 A Win-Win Scenario between Customer and Supplier Consignment Direct Floor Inventory Stocking

More business Access to new designs Stabilized production Fewer transactions Quicker payments Less selling expense Assured sales Access to information earlier

X

X

X X X X

X X X X

Releases from Rolling Forecast

Resident at Customer

X X X X

X X

X X X

So, the customer needs to reengineer its mindset and allocation of time and resources to improving benefits versus just focusing on the price it pays to the supplier. The value from suppliers will result in customized supply solutions. In other words, customers would like to be beneficiaries of solutions to their business problems, and not just a box delivered to their dock. Suppliers should be working with customers on lead times to establish rapid replenishment times and also to reduce the number of transactions it takes to do business. To achieve such goals would require suppliers working closely with customers in establishing joint business operating systems such as Kanban, Faxban, floor stocking, rolling forecasts, capacity reservation, and consignment inventory. They can utilize the following steps for each item or commodity: (1) Create a demand profile, (2) Create a supply profile, (3) Evaluate and establish improvement goals, and (4) Develop customized supply solutions to meet the goals. The point is, if a customer wants a world-class supplier, it must itself be a worldclass customer. Table 2.4 provides conditions to attain win-win scenario. If a customer (manufacturer) wants to improve the flow of materials from its suppliers, the customer in turn must improve the flow of information to its suppliers, as Figure 2.5 illustrates. A company should organize for success by choosing the following guidelines: 1. Organizational level at supply management equals to engineering, manufacturing, and marketing; not a subset of another function and no filtering of communications. 2. Segment supply management into strategic elements such as: a. Strategic, tactical, transactional



Material or Services

CUSTOMER (MANUFACTURER)

SUPPLIER

Information

Figure 2.5 Be a world-class customer.

b. c. d. e.

Future oriented versus today oriented Technical, administrative Colocate people for success Get the best people: A new profile of the supply professional i. Degreed: Supply chain, operations management, or engineering ii. MBA for business and financial basics iii. Strong interpersonal skills, creative, innovative, etc. f. Positive, supportive, involving, and challenging work environment Table 2.5 provides a list of traditional and SCM performance measures. Table 2.5 Traditional and SCM Performance Measures List Traditional Measures

SCM Measures

On-time delivery Incoming quality defects Supplier price reductions Supplier lead time Dollars and number of purchase orders per buyer

Percentage of components on new product from preferred suppliers Percentage of total expenditures from preferred suppliers Number of customer quality issues because of suppliers Product cost reduction Number of resident suppliers Working capital reductions Operating profit impact from supplier cost reductions Number of business initiatives jointly sponsored by supply and other business functions Material replenishment cycle time



In summary, measures of success in SCM should be more strategic, has higher-level business impact, requires cross-functional participation and cooperation, should be reported broadly, and should lead to change.

References Andrews, P.P. and Hahn, J. (July–August, 1998), Transforming supply chains into value webs, Strategy and Leadership, 26(3), 6–11. Dumond, E.J. (2000), Value management: an underlying framework, International Journal of Operations and Production Management, 20(9), 1062–1077. Ertek, G. and Griffin, P.M. (2002), Supplier- and buyer-driven channels in a twostage supply chain, IIE Transactions, 34, 691–700. Iyer, A.V. and Bergen, M.E. (1997), Quick response in manufacturer-retailer channels, Management Science, 43(4), 559–570. Koch, C. (June 15, 2004), Nike Rebounds: How (and Why) Nike Recovered from Its Supply Chain Disaster , CIO Magazine. Available at http://www.cio.com/archive/061504/nike.html. Koch, C. (2002), The ABCs of Supply Chain Management, Supply Chain Management Research Center. Available at http://www.cio.com/research/scm/edit/ 012202_scm.html. McVey, S.R. and Cundiff, R. (2005), The Essential Supply Chain, Intranet Journal. Available at http://www.intranetjournal.com/features/supplychain.html. Plossl, G.W. (1991), Managing in the New World of Manufacturing, Prentice Hall, Englewood Cliffs, NJ. Poirier, C.C. and Quinn, F.J. (November–December 2004), How Are We Doing? A Survey of Supply Chain Progress, Supply Chain Management Review, 24–31. Poirier, C.C. and Reiter, S.E. (1996), Supply Chain Optimization: Building the Strongest Total Business Network, Berrett-Koehler Publishers, San Francisco, CA. Sherman, R. (1997), First establish demand, Manufacturing Systems, 15(8), 68–72.


Chapter 3

Elemental Task Learning Curves in a Production Line Introduction There have been many studies of learning curve impact in manufacturing processes; almost all of them look at the aggregate decreased production cost due to learning curve impacts. Similarly, the study of balancing production line elements by cycle time has been near exhaustive. But, the interrelation of line balancing and elemental task learning curves, along with the related concept of throughput time, has received little attention (Smunt and Watts, 2003). As background for the ultimate hypothesis, this chapter will briefly explain the learning curve concept and the concept of elemental task line balancing. It will then postulate that a line’s aggregate learning curve is a function disproportionately impacted by the line’s elemental task with the worst learning curve. It will then hypothesize that learning curves for elemental tasks are not static and can be manipulated to achieve better line balancing and, ultimately, further cost reduction through decreased throughput time. Ultimately, it concludes that owing to elemental task learning curves, a line design must be flexible enough to change to achieve proper balance and to achieve continuing improvement in throughput time.

23



Learning Curves Citing Linda Argote’s textbook on organizational learning, Macher and Mowery (2003) indicate that the literature on “learning by doing” and manufacturing performance is extensive. The basic theory is that experience lowers cost or speeds up production. As Farghal and Everett (1997) noted, the time or cost required to perform one cycle is less than that required to perform the previous cycle. The learning curve was adapted from historical observations that individuals (or organizations) that perform repetitive tasks exhibit an improvement over time. The learning curve measures the impact of workers’ experience on the costs of production. It describes the relationships between a firm’s cumulative output and the amounts of inputs needed to produce a unit of output. Learning (or experience) curve theory has a wide range of applications in the business world. In manufacturing, it can be used to estimate the time for product design and production, as well as costs. Learning curves are important and are sometimes overlooked as one of the trade-offs in just-in-time systems, in which sequencing and short runs achieve lower inventories by forfeiting some benefits of experience from long product runs. Learning curves are also an integral part in planning corporate strategy, such as decisions concerning pricing, capital investment, and operating costs based on experience curves. Learning curves can be applied to individuals or organizations. Individual learning is improvement that results when people repeat a process and gain skill or efficiency from their own experience. Organizational learning results from practice as well, but it also comes from changes in administration, equipment, and product design. In organizational settings, we expect to see both kinds of learning occurring simultaneously and often describe the combined effect with a single learning curve. The first application of the learning curve involved manufacturing processes that were highly labor intensive (Wright, 1936). It was reported that as cumulative output increased, unit labor costs decreased. Subsequent commentators argue that learning curves have more impact on costs when the actions in which the learning curve is measured involve labor-intensive tasks (Globerson and Shtub, 1984). Be that as it may, studies have determined that the learning effects (resulting in the learning curve) come from three sources. First, the labor force will accumulate experience over time, which will reduce the labor input needed to produce the same level of output. Second, management will gain experience and will improve management processes, such as modifying workstation assignments. Third, the industry in general might gain expertise or technical ability, such as advancements in-process techniques (Lundmark, 2003; Air Force, 2005).


Elemental Task Learning Curves in a Production Line 25

Hours of labor per product lot

10 8 6 4 2

0

10 20

30

40

50

60

70

Figure 3.1 The production line learning curve.

In addition to what were the sources of the learning curves’ effects, empirical studies yield three conclusions on learning curves: 1. The time required to perform a task decreases as the task is repeated (basic theory). 2. The amount of improvement decreases as more units are produced (theory of diminishing rate of return). 3. The rate of improvement has sufficient consistency to allow its use as a prediction tool. The consistency of improvement noted here has been found to exist in the form of a constant percentage in time required over successively doubled quantities of units produced. The constant percentage by which the costs of doubled quantities decrease is called the rate of learning. Thus, if it took 10 hr to produce the n-th unit and 8 hr to produce double the n-th unit, the learning curve would be described as a curve with an 80 percent slope. Representations of a sample learning curve (Figure 3.1) and a typical learning curve equation for a production line (Equation 3.1) are provided. In Figure 3.1, the horizontal axis measures the cumulative number of lots of a product the firm has produced. The vertical axis measures the number of hours of labor needed to produce each lot. The learning curve in Figure 3.1 is based on the following relationship: L = a + bN–λ

(Equation 3.1)



where N = cumulative units of output produced, L = labor input per unit of output, a, b, and λ are constants, a and b are positive, and λ is between 0 and 1. If N = 1, L = a + b, and this measures labor input to produce the first unit of output. If λ = 0, labor input remains constant as the cumulative level of output increases, so there is no learning. If λ > 0 and N increases, L approaches a, and a represents minimum labor input per unit of output after all learning has taken place. The larger the λ, the more important the learning effect. It may be noted that new firms may experience a learning curve, not economies of scale. On the other hand, older firms have relatively small gains from learning. Figure 3.2 differentiates between economies of scale and learning. The learning curve implies that the labor requirement falls per unit and costs will be high at first and then will fall with learning. We apply learning curves to determine if it is profitable to enter an industry and also to determine when profits will occur, based on plant size and cumulative output. However, for the learning curve concept to have impact, besides having a labor component, the production line must not be automatically paced. If it is, improvement will be limited (Fast.faa.gov, 1998). Here, we assume cycle times that are process paced. If the production process is automatically controlled in that in-process units are transferred between elemental task work stations at predetermined times, without regard to process cycle times, elemental task learning curves will have little impact on overall throughput time. It is also important to note that the smaller the batches the greater the learning effect. This is true because production in smaller Cost ($ per unit of output)

A

Economies of Scale reversible B

Learning

Average Cost E C Average Cost EL Output

Figure 3.2 Economics of scale versus learning (E: economy of scale; EL: economy of scale and learning).



batches provides better opportunities for learning and will therefore reduce the overall time to produce the same number of units when compared to production with larger batches.

Balancing Cycle Times A couple of the key aspects of production planning are throughput time and cycle time. Throughput time is the length of time, including delays, required for materials or a customer to move through a defined valueadding process. For simplicity, it will be considered the time it takes raw materials to be transformed into finished goods (aggregate of all cycles). Cycle time is the time it takes for an in-process good to move through its next value-adding activity. Just as delays at any given cycle account for addition to throughput time (and inventory cost), reductions in cycle time also reduce the throughput time. It is axiomatic that the desire of manufacturers is to have uniform (balanced) cycle times throughout production of a product, and to achieve the lowest possible cycle time. Although lot size also is relevant in this inquiry, for purposes of this analysis, it will be assumed that the lot size is 1, and that no buffer stock will be utilized at work stations. Although a buffer stock could be utilized to offset the differing cycle times, buffer stocks equate to inventory, and thus, may be considered an unnecessary additional cost. It has been found that the objectives gained (also lost if not balanced) from a balanced line include: 1. 2. 3. 4. 5. 6. 7.

Regular material flow Maximum usage of manpower and machine capacity Minimum process times Minimizing slack times Minimizing workstations Distribute slack times to workstations Reduce productions costs (Ozgurler et al., 2003)

Production lines consist of workstations that handle work in progress, add value to the work, and pass to the next workstation until the product is complete. In other words, it is a sequence of workstations, connected together by a material handling system, which is used to assemble components into a final product. At each station, the value added to the work in progress takes a certain amount of time. This is called cycle time. Line balancing involves partitioning the total time it takes for raw material to become a finished good, among a certain number of workstations, which have approximately the same cycle times (Becker and Scholl, 2006). It should be noted that the number of workstations is a number determined,



in some circumstances, by the demand for the product and the lead time allowed. For example, if the market demand requires 40 units to be produced each day and the line will operate for 8 hr a day, then the 480 min of line time must be divided by 40 (units produced) to derive a cycle time of 12 min. The result is that every 12 min, one unit must be produced. If the unit requires 48 min to make, the line might be designed to have four workstations with 12 min of value-adding work each. Each task that must be done at a particular workstation takes a number of time units to complete. Frequently, the design of a production line has assumed that conditions at the design phase of balancing will continue and eventually become the operating conditions throughout the life of the production line (Ozgurler et al., 2003). As noted later, when elemental task learning curves are factored into a production line with varying elemental task learning curves, the impact of these learning curves will frequently cause an unbalanced line.

Interrelationships of Elemental Task Learning Curves and Line Balance Because the goal of line balancing (as explained earlier) is to have balanced elemental task cycle time, in a balanced line, the pace of production is controlled by elemental task cycle times. If a line has elemental tasks that all have the same learning curve, the line would remain balanced throughout the production run on this basis, and the performance of time it takes for each elemental task would remain the same (Globerson and Shtub, 1984). If we assume that elemental tasks have different learning curves, units produced will take varying times to complete (except in the single instance that the slopes of all elemental learning curves intersect at a single future unit of production, which in a multiple task line of production would be improbable). Then, over time, each element task will take a different amount of time to complete (Globerson and Shtub, 1984). Globerson and Shtub’s research looked at two tasks with different learning curves. They concluded that an equilibrium point existed at which the two learning curves intersected. It was an overly simplistic model of a production line. Assuming that multiple tasks are involved in production, one can safely assume multiple elemental task learning curves. If this is the case, then it is highly unlikely that all of the curves would intersect at a single point, thus yielding an equilibrium point. It is more likely that the curves intersect each other at different points and no single equilibrium point could be ascertained. Figure 3.3 shows that when the line has just two varying elemental task learning curves, it is possible to ascertain the equilibrium (optimum) unit amount.



Time Needed to Complete Task

50 40 30 20 10 0 0.5

1

2

3

4

8

Number of Units Produced (100's) Learning Curve Task 1

Learning Curve Task 2

Figure 3.3 Optimum units to produce in a line with two elemental tasks with varying learning curves.

Time Needed to Complete Task

60 50 40 30 20 10 0 0.5

1

2

3

4

8

Number of Units Produced (100's) Learning Curve Task 1 Learning Curve Task 3

Learning Curve Task 2 Learning Curve Task 4

Figure 3.4 Multiple elemental tasks with varying learning curves.

Figure 3.4 indicates how this task is complicated when the line has multiple elemental task learning curves. The analysis presented is based on the assumption of a lot size of 1. The elemental task cycle times would control pace of production. Thus, the elemental task learning curves would impact cycle times and total throughput time. Thus, if elemental task learning curves are not the same in an initially balanced line, the line will become imbalanced.



When Globerson and Shtub analyzed the equilibrium optimum unit number on differing learning curves of elemental tasks in production, their study fixed elemental tasks and the learning curve associated with each element and tried to adjust the number of repetitions that would maximize the entire line utilization based upon each elemental tasks’ learning curve. This analysis, although not stated in these terms, shows that at future units of production there will be an excess capacity at one or more elemental tasks. Although their analysis of optimum production quantity, given the changing capacities of the elements because of learning, is a worthy one, a more basic question is begged. Why should the line remain static if excess capacity appears at an element task compared to other element tasks, and why does the line become unbalanced? If a line were not in balance due to other capacity issues (a particular elemental task is used on another production line and is doing double duty) a manager would add capacity elsewhere or reduce capacity at certain point to balance the line. Viewing elemental task learning curves as a capacity variable would require similar actions. Considering learning curves as a part of a capacity variable in a production line, it is clear that, based on the aforementioned analysis, the greatest element cycle time determines the cycle time for the entire production. The same concept holds true for elemental task learning curves. For instance, suppose a three-workstation production line is used as an example. In this example, two of the three elements have a learning curve of 70 percent, whereas the third has a curve of 80 percent. For the sake of this analysis, it is assumed that the learning curve rate is known at the start of production. In actual situations, the actual learning rate per elemental task would most likely be unknown at the beginning of production. As data is collected during initial production, one may be able to come to approximate learning curve rates per elemental task using the learning curve equation. Although cycle times per element at the start of production may be equivalent, at two times the n-th unit, two elemental tasks take 70 percent as much time to complete, and the third takes 80 percent as much time to complete. Because learning curve theory considers the aggregate decreased production time of the n-th unit to assigning a learning curve rate for the entire production, by considering the elemental tasks’ varying learning curves, one can understand how the worst elemental task learning curve may have a disproportional impact on the entire production’s learning curve. Thus, at the n-th unit, the learning curve for the entire production is 73 percent, despite the fact that the majority of the production has a 70 percent learning curve (Figure 3.5). This also has significant ramifications depending on where the 80 percent learning curve elemental task is located in the production line. For instance, in the example used, if the elemental task with the 80 percent learning curve is the second or



Step 1: 10 min/ 70% LC



1

2

3

At nth unit, cycle time for 1 and 2 is 7 minutes, while cycle time for 3 is 8 minutes. It takes 22 minutes to complete 1 unit of production. Inventory will start accumulating before step 3. Aggregate learning for the entire production is 73%.

Figure 3.5 Initial line design when 80 percent learning curve task is last in sequence. Step 1: 10 min/ 70% LC

1


2


3

Suppose the 80% LC task is the 2nd task. At nth unit, cycle time for 1 and 3 is 7 minutes, while cycle time for 2 is 8 minutes. It takes 23 minutes to complete 1 unit of production, because task 3 waits 1 minute each cycle for task 2 to complete. Inventory will start accumulating before step 2 and step 3 will experience idle time. Aggregate learning for the entire production is 77% instead of 73% percent.

Figure 3.6 N-th unit effects when 80 percent learning curve task is the task in the middle of the sequence.

first task, the entire production will have 77 percent and 80 percent learning curve, respectively (see Figure 3.6 and Figure 3.7). To take the example further, assume that it originally takes 10 min for each of the three stations to complete its assigned tasks. Suppose, owing to machinery upgrade, station 1 was able to complete its tasks in 7 min. Suppose that station 2 could complete its tasks in 8 min owing to learning curve effects. Also assume that because of learning curve effects, station 3 could complete its tasks in 7 min. The questions would become, would station 3 actually complete its tasks in 7 min, even though it receives its work in progress every 8 min? Although it could be argued that learning effects take place in a vacuum, it is equally plausible that learning is the product of necessity. It could be argued that humans, by nature, would not seek to learn or improve for the sake of it alone. In the previous example, station 3 has 8 min to complete its tasks before a new batch of work in progress arrives. Rather than learn and have 1 min of downtime per cycle,






1

2

3

Suppose the 80% LC task is the 1st task. At nth unit, cycle time for 2 and 3 is 7 minutes, while cycle time for 1 is 8 minutes. It takes 24 minutes to complete 1 unit of production, because tasks 2 and 3 wait 1 minute each cycle for task 1 to complete. Step 2 and step 3 will experience idle time. Aggregate learning for the entire production is 80%.

Figure 3.7 N-th unit effects when 80 percent learning curve task is the task in the beginning of the sequence.

it is plausible that station 3 will never achieve the learning curve effects it is capable of because there is no need for it. Even if it did achieve its capable learning, the cycle time would still be constrained by workstation 2, and the cycle time for the product and learning curve for the product would be constrained by the lowest common denominator, or workstation 2. By considering the impacts on cycle time of individual elemental learning curves in a production line, one may understand how elemental task learning curves interrelate with elemental capacity. When elemental capacity of a line becomes unbalanced because of elemental task learning curve effects, the result will be a bottleneck somewhere in the line. In Goldratt’s Theory of Constraints, this bottleneck is a capacity restraint that must be resolved without creating additional capacity restraints elsewhere. Historically, the bottleneck was considered a failure of engineered work flow (Bassett, 1995). The initial response was to manipulate work flow and allow for large buffer stock accumulation at each workstation. Although this may remedy the bottleneck issues, it may create other negative effects (Bassett, 1995). The new model of production assumes that bottlenecks are inevitable, and their occurrence must be anticipated and resolved rapidly (Bassett, 1995).

Organizational Learning It is commonly known that organizational learning is critical to sustaining a competitive advantage. For the individual, it is easy to conceptualize how knowledge is acquired and retained and how this results in an individual learning effect. Certainly, a main source of organizational learning is the individual learning of the employees. An organization also acquires knowledge in its technology, its structure, documents that it retains, and standard operating procedures. For example, as a manufac-



turing unit becomes experienced, knowledge is embedded in software and in tooling used for production. Knowledge can also be embedded in the organization’s structure. For example, when an organization shifts its operations research group from a functional organization centralized in one area to a decentralized organization in which individuals are deployed to particular parts of the plant floor, knowledge about how to become more productive is embedded in the organization’s structure. Knowledge can depreciate if individuals leave the organization. Knowledge can also depreciate if technologies become inaccessible or difficult to use.

Conclusion Understanding learning curve theory and elemental task learning curve impacts will allow one to anticipate when and where the capacity shortage (bottleneck) will emerge and allow for the quick resolution to it. Ultimately, varying elemental learning curves within a production line must be considered to be capacity variables, much like the more commonly thought of capacity constraints. Once it is accepted that learning impacts alone can cause line imbalance, managers may be able to better understand how to rebalance the line and reduce unnecessary cost. By anticipating which elemental tasks are learned at a slower rate than others, a prudent manager takes the necessary steps to keep the line balanced as much as possible. These steps may include adding capacity to the “slow learning” elemental tasks to keep the cycle time in pace with the “faster learners.” It may also include attempting to increase the rate of learning through a “continuous improvement” management approach to the particular elemental processes to attempt to balance each tasks’ learning curve (and by doing so, the entire process) (Zangwill and Karitor, 1998). One might also initiate adjustment of elemental tasks to rebalance the line, at least for the short term. This readjustment may also include an attempt to cause slow learning tasks to be “endloaded” in the production process to have the minimal impact on other elemental tasks. Endloading would attempt to keep the earlier tasks in a line balanced so that unbalanced tasks impact the minimum number of sequential tasks that follow them. This approach would also highlight the bottleneck in the line based on learning curve effects.

Recommendation Whatever approach is taken by management, the critical focus of this chapter is on the awareness of the issue. A prudent manager will account



for learning curve variables when designing a production line and should, among other data collected, collect initial run data in an attempt to identify elemental task learning curves. Using data acquired through production and based on previous research in the learning curve field, managers could predict where and when (what unit of production) the elemental task learning curve effects will cause a capacity imbalance between some elemental tasks, which will negatively impact the entire production process. With the benefit of observing a line process and collecting data, one would be able to more clearly quantify the issue and develop equations for predicting bottleneck appearance by units of production.

References Air Force (2005), The Learning Curve. Available at http://ax.losangeles.af. mil/se_revitalization/aa_functions/manufacturing/Attachments, pp. 1–29. Bassett, G. (1995), The new training: operations methods for high performance, Human Resources Development Quarterly, 6(3), 297–306. Becker, C. and Scholl, A. (2006), A survey on problems and methods in generalized assembly line balancing, European Journal of Operational Research, 168(3), 694–715. Farghal, S.H. and Everett, J.G. (March 1997), Learning curves: accuracy in predicting future performance, Journal of Construction Engineering and Management, 123(1), 41–45. Fast.faa.gov (1998), Direct Labor, 1–18. Available at http://fast.faa.gov/pricing/9830-c7.htm. Globerson, S. and Shtub, A. (1984), The impact of learning curves on the design of long cycle time lines, Industrial Management, 26(3), 5–100. Goldratt, E.M. (1990), Theory of Contraints, North River Press, Great Burlington, M.A. Lundmark, R. (November 2003), On the Existence of Learning Effects in Swedish Kraft Paper Mills, International Institute for Applied Systems Analysis, Sweden, p. 27. Macher, J.T. and Mowery, D.C. (2003), Managing learning by doing: an empirical study in semiconductor manufacturing, The Journal of Product Innovation Management, 20(5), 391–410. Ozgurler, M., Guneri, A.F.G., and Gulsun, B. (2003), A Simulation Approach to Line Balancing in Discrete Mass Production Flow System and an Application, Society of Manufacturing Engineers, Dearborn, MI. Smunt, T.L. and Watts, C.A. (2003), Improving operations planning with learning curves: overcoming the pitfalls of “messy” shop floor data, Journal of Operations Management, 21(1), 93–107. Wright, T.P. (February 1936), Learning curve, Journal of Aeronautical Sciences. Zangwill, W.I. and Karitor, P.B. (1998), Toward a theory of continuous improvement and the learning curve, Management Science, 44(7), 910–920.


Chapter 4

Offshoring Knowledge Work to Increase Shareholder Value Introduction CIO Magazine estimates that approximately one half to two thirds of Fortune 500 companies in the United States have already outsourced (offshored) IT to India, because it is one of the best ways to cut maintenance and application development, or knowledge work, costs (Koch, 2003). Many consulting companies and IT organizations are reporting that this trend will continue similar to the offshoring of manufacturing jobs before them. The benefits of utilizing low-cost labor in other countries not only result in direct savings, but indirect savings as well. These indirect savings are realized by reinvesting in more value-added activities across the organization. Obviously, if there were only benefits, more companies would seek to outsource their processes to lower-cost countries. This chapter seeks to report on the reasons why offshoring knowledge work has become such an integral part of the American economy and the challenges that companies should consider before making the conversion. The chapter is written as a guide for future CEOs (or other senior managers) and seeks to answer the question that leaders should be asking: “Can offshoring

35



Table 4.1 Number of U.S. Jobs Moving Offshore Job Category

2000

2005

2010

2015

Management Business Computer Architecture Life sciences Legal Art, design Sales Office Total

0 10,787 27,171 3,498 0 1,793 818 4,619 53,987 102,674

37,477 61,252 108,991 32,302 3,677 14,220 5,576 29,064 295,034 587,592

117,825 161,722 276,954 83,237 14,478 34,673 13,846 97,321 791,034 1,591,101

288,281 348,028 472,632 184,347 36,770 74,642 29,639 226,564 1,659,310 3,320,213

knowledge work increase shareholder value?” At the end of this chapter, we will introduce a case study of Best Buy and Staples and show how one company that has announced that it has offshored IT work has better year-over-year performance using the DuPont model of the return on net worth (RONW) than the other. Between 1950 and 2003, jobs in the manufacturing sector fell from 34 to just 12 percent of total U.S. jobs. Companies such as Zenith and RCA that did not show flexibility and adopt new strategies fell, whereas others such as IBM, GE, and Intel, which embraced the offshoring phenomenon have flourished (Karmarkar, 2004, p. 2). Today, the service sector is facing the same challenges that manufacturing experienced in the past. Forrester Research predicts that nearly 3.5 million jobs will be moved offshore between 2003 and 2015 (Table 4.1). In 1990, Uday Apte from Southern Methodist University estimated that “10 percent of American service sector jobs had the potential to be outsourced, moved offshore, or automated (Karmarkar, 2004, p. 1).” This alarming statistic tells not only the employees in these areas that their job could potentially be in danger, it also signals to company leaders that they should be well-informed of this phenomenon to remain competitive. As mentioned earlier, the following analysis seeks to answer the question that CEOs need to be asking: “Can offshoring knowledge work increase shareholder value?” First, definitions of knowledge work will be presented along with the types of jobs potentially affected. Next, drivers of this trend, along with economic benefits and business risks, will be discussed. Here, leaders can determine if the potential cost savings outweigh the potential hazards along the way.


Offshoring Knowledge Work to Increase Shareholder Value 37

Knowledge Services and Decision Analysis

Reasearch and Development

Figure 4.1 Offshoring opportunities across the organization. (From McKinsey and Company [2003], Offshoring: Is It a Win-Win Game?, McKinsey Global Institute. Available at http://www.mckinsey.com/knowledge/mgi/reports/Offshoring/offshore.asp.)

Knowledge Work Knowledge work includes such business processes as application outsourcing, business process outsourcing (BPO), data center services, as well as many other functions. These processes and services are higher up the corporate complexity ladder than functions such as data entry or transaction processing. The types of jobs listed here include such whitecollar positions as software developer and software engineer. Figure 4.1 shows how these offshoring opportunities across the organization fit in, as well as how increasingly complex these roles become. The farther you move to the right of the graph, the more highly skilled the workers need to be. Interesting to note is that as these positions move to the right, they become more aligned with defining business strategy and corporate objectives, and not simply receiving delegate mandates from above. As offshoring becomes more accepted, CEOs who offshore need to understand the implications that this process has on their organizations. Otherwise, as will be mentioned later, their organizations are subject to being opened up to security breaches, as well as technological “brain drain.”

Drivers of Knowledge Work Offshoring To better understand why offshoring knowledge work has proliferated, CEOs need to know the drivers. Some of the main reasons can be attributed



to technological advances: fiber-optic cables, commoditization of personal computers (PCs), the Internet, and shared software. With the hype of the dot.com era, many companies such as Global Crossing invested heavily in laying fiber-optic cables around the world and eventually drove down the cost of transmitting voice and image data (Friedman, 1998, p. 3). This allowed for the cheap and instantaneous connectivity of people anywhere around the world. Now, software developers no longer need to be at the same physical location as their employer. A second technological driver is the commoditization of PCs, allowing more and more people to own devices that allow for communication and analyses. With lower prices, a person in India or China can now buy a laptop and begin programming from their local Starbucks. These functions help facilitate workers in foreign countries to interact with counterparts in other parts of the world. Table 4.2 shows that there are millions of people around the world who are Internet users. With the advent of the Internet and the subsequent initial public offering of Netscape, people can connect and share information and data with others around the world (Friedman, 1998, p. 3). This along with other shared software programs like Microsoft Windows allowed for the people-to-people and application-to-application connectivity. Now, reports can be digitized, disaggregated, and shifted to any place in the world where labor is cheaper (Friedman, 1998, p. 4). Another driver supporting the spread of offshored knowledge work is the increased number of people speaking and writing English. The success of American businesses has led people around the world to pick English as their second language. Although this can be seen as a positive development, others may now see this in a negative light. Now, children around the world not only learn their own language and culture, but also the American language and culture. In essence, these people are now becoming more qualified to take away jobs that have been traditionally American. Table 4.2 shows the literacy rates and many other statistics for many countries. Although it does not specify the number of English-speaking citizens, it does tell that other countries are catching up with America in the number of people who are literate. This shows that there are millions of people around the world who are fast becoming competitors for software developers, and potentially new employees for CEOs. Shortage of labor is another driver to offshore knowledge work. It has been well documented that the American economy will have an increase in the number of baby boomer retirees soon. To employers, this means that a lot of their current employees will be leaving the workforce. Figure 4.2 shows this shortage and indicates there will be a need to look elsewhere for employees.

Population

Brazil 186,112,794 Chile 15,980,912 China 1,306,313,812 10,241,138 Czech Republic Hungary 10,006,835 India 1,080,264,388 Kenya 33,829,590 Malaysia 23,953,136 Philippines 87,857,473 Poland 38,635,144 Russia 143,420,309 South Africa 44,344,136 Thailand 65,444,371 United States 295,734,134 Venezuela 25,375,281

Country

4,164,000 1,600,000 472,000,000 18,481,000 400,000 11,450,000 10,260,000 8,692,100 34,560,000 3,500,000 16,920,000 8,970,000 71,680,000 6,000,000 3,100,000 16,350,000 34,900,000 6,031,300 147,400,000 159,000,000 11,380,000 1,274,400

–0.25 1.44 1.14 1.83 1.88 0.02 –0.45 –0.25 0.91 0.92 1.44

14,300,000 3,575,000 94,000,000 2,700,000

Internet Users

82,590,000 6,000,000 778,100,000 5,250,000

Labor Force

1.11 1.01 0.57 –0.05

Population Growth

Table 4.2 Data for Selected Countries

46,373,300 6,445,700 269,000,000 9,708,700 6,862,800 26,154,400 1,590,800 11,124,100 15,201,000 17,400,000 17,608,800 16,860,000 16,117,000 158,722,000 6,463,600

0.99 0.6 0.85 0.89 0.93 0.99 0.99 0.86 0.93 0.97 0.93

Telephones — Mobile Cellular

0.86 0.96 0.91 0.99

Literacy Rate

$13,900 $2,900 $1,000 $9,000 $4,600 $11,100 $8,900 $10,700 $7,400 $37,800 $4,800

$7,600 $9,900 $5,000 $15,700

0.65 0.23 N/A 0.50 0.40 0.50 0.65 0.45 0.37 0.76 0.64

0.53 0.63 0.28 0.60

0.06 0.10 0.40 0.04 0.11 0.20 0.09 0.31 0.02 0.06 0.18

0.12 0.09 0.10 0.10

Percentage of GDP — Population Per Capita Employed Unemployment Rate — in PPP in Services





2003

2012

100% = 277.8 million

312.3 million

28

44

28

34

Over 55 years 25-54 years Under 24 years 39

27

Figure 4.2 U.S. decline in working age population. (From McKinsey and Company [2003], Offshoring: Is It a Win-Win Game?, McKinsey Global Institute. Available at http://www.mckinsey.com/knowledge/mgi/reports/ Offshoring/offshore.asp.)

Fortunately for people in the knowledge work area, the Bureau of Labor and Statistics predicts that there will be a need for people with technical skills (Table 4.3). As you can see, four out of the top ten types of jobs will require knowledge work expertise. From software publishers to management consultants, there will be a need to hire these roles in the years to come. Unfortunately though, as stated earlier, a shortfall in the total number of applicants could still be an issue. Another driver that increases the practice of offshoring knowledge work is the use of automation in business processes. Figure 4.3 shows research done by Forrester that indicates there will be an increased need for knowledge work personnel owing to changes because of the use of the Internet. Think of the number of companies that have pushed their services out to their customers. Now, people can make airline reservations, bank, and shop online. This means that there is now a much greater need for software engineers and business process consultants who can help design such systems. A final reason for the increased use of offshored knowledge workers is the sheer size of countries such as India and China (Table 4.4). These two countries graduate more students from universities with computer science degrees than the United States. This fact alone shows that more


Offshoring Knowledge Work to Increase Shareholder Value 41 Table 4.3 Bureau of Labor Statistics, Employment Projections, 2002–2012 Industry

Software publishers Management and technical consulting services Community care facilities for the elderly Computer system design Employment services Rehabilitation services Ambulatory health care Water and sewage systems Internet and data processing Child day care services

2002

2012

Annual Growth Rate (Percentage)

256 732

430 1,137

5.3 4.5

695

1,077

4.5

1,163 3,249 1,269 1,444 49 529 734

1,798 5,012 1,867 2,113 71 773 1,050

4.5 4.4 3.9 3.9 3.9 3.9 3.6

Figure 4.3 Changing corporate models. (From Forrester Research.) Base: 182 sell-side E-commerce decision makers at North American companies.


42 Supply Chain Cost Control Using Activity-Based Management Table 4.4 Workers of the World United States

Total population Civilian labor force Percentage of population under the age of 25 Number of college graduates per year Number of computer science graduates per year As a percentage of population Cost of cup of gourmet coffee Percentage of country with electricity Percentage of population below poverty line Illiteracy rate (percentage)

India

China

0.29 billion 147 million 35



1.3 million

3.1 million

2.8 million

53,000

75,000

50,000

0.0200 $1.68 100

0.0070 $0.50 60

0.0004 $1.00 98

12

25

10

5

35

15

Source: From McKinsey and Company (2003), Offshoring: Is It a Win-Win Game?, McKinsey Global Institute. Available at http://www.mckinsey.com/knowledge/ mgi/reports/Offshoring/offshore.asp.

emphasis needs to be placed by American CEOs on the highly skilled and growing labor force outside of this country.

Benefits to Business Although the drivers may present the need for knowledge work, senior executives will not pursue offshoring unless benefits can be realized. A Star Tribune survey of 252 executives of Minnesota companies revealed many of the reasons why they offshore (Table 4.5). For services, by far the greatest reason is to control costs. Table 4.6 shows comparable U.S. and Indian jobs by category. Although this study shows a saving of 80 percent on average, other estimates show net savings of between 25 and 40 percent (ADTmag.com, Earls, p. 2). Still, at even a 25 percent reduction in costs, companies should very seriously consider the use of offshored IT labor. Table 4.7 shows another graph that the Star Tribune presented on what $1 spent on labor will cost in other countries. Note that all of the European labor costs were higher than the United States, and all South American and Asian countries’ costs were lower. This takes into consid-


Offshoring Knowledge Work to Increase Shareholder Value 43 Table 4.5 Reasons to Offshore (Executive Survey of 252 Minnesota Companies) Reason

Production

Services

Increase competitiveness Reduce or control costs Increase revenue potential Get closer to customers Quality of overseas workers Reduce time to market Free up resources in Minnesota Resources not available internally Have 24 × 7 operations

79 77 56 28 12 11 10 7 4

53 71 46 17 25 10 12 17 27

Source: From Star Tribune, Minneapolis-St. Paul, MN, September 5, 2004.

Table 4.6 Wage Comparison — United States and India

Telephone operator Medical transcriptionist Payroll clerk Legal assistant/paralegal Data entry clerk Accountant Financial researcher/analyst Software developer Software engineer

United States

India

$13 $13 $15 $18 $20 $23 $34 $60 $120

Less than $1 $2 $2 $7 $2 $11 $11 $6 $18

eration the direct savings of labor wage rates, as well as the savings that companies receive by not having to pay for benefits. Another benefit to companies is the increased competitiveness afforded by having operations open around the clock. Now, a business process consultant can design a project in the United States and assign tasks to others around the globe. While we are asleep in the United States, people in other countries can be working on the project during their waking hours. Also, a combined 24 × 7 operation with decreased costs allows for companies to have customer service representatives available to answer questions, should the need arise after typical business hours. Also, by offshoring certain functions, internal resources are freed up to work on more “value-added” needs. This provides for a decreased time


44 Supply Chain Cost Control Using Activity-Based Management Table 4.7 One Dollar Spent on Labor United States Brazil Canada Mexico Australia Japan Sri Lanka Belgium Switzerland Germany France

100 12 75 12 72 89 2 107 113 114 81

Source: From Star Tribune, Minneapolis-St. Paul, MN, September 5, 2004.

to market new products or services, and should result in additional positive revenues.

Economic Implications A CEO may want to know if offshoring in general is bad for the economy. Global Insight states that offshoring IT software decreases costs, lowers inflation, increases productivity, and lowers interest rates. This boosts business and consumer spending and increases economic activity (ITAA report, p. 1). They support this later in their analysis by showing that, on average, most industries will experience a growth in the number of net new jobs (Table 4.8). All in all, they predict that by 2008, over 300,000 net new jobs will have been cr eated directly owing to the benefits that U.S. companies receive from offshoring IT work. McKinsey and Company (2003) also tells of similar findings in their report entitled Offshoring: Is It a Win-Win Game? In it, they show that although the United States may be losing 3.3 million jobs over the next decade because of offshoring, the net benefits to the U.S. companies by direct cost savings and internal resource redistribution will substantially outweigh the losses. Figure 4.4 shows a graph in the study and the benefits of offshoring IT work to India. It shows that U.S. companies will capture economic value through several different channels: reduced costs, increased revenues, repatriated earnings, and the redeployment of additional labor (McKinsey, 2003, p. 7). To executives, these are the reasons why they should seriously consider offshoring knowledge work.


Offshoring Knowledge Work to Increase Shareholder Value 45 Table 4.8 Number of Net New Jobs Created because of Offshoring Number of Net New Jobs Industry Sector

Natural resources/mining Construction Manufacturing Wholesale trade Retail trade Transportation and utilities Publishing and software Financial services Professional and business services Education and health services Leisure, hospitality, and other services Government Total employment

2003

2008

1,046 19,815 3,078 20,456 12,552 18,895 –24,860 5,604 14,667 18,015 4,389 –3,393 90,264

1,182 75,757 25,010 43,359 30,931 63,513 –50,043 32,066 31,623 47,260 12,506 4,203 317,367

Source: From Anonymous (March 2004), Executive Summary: The Comprehensive Impact of Offshore IT Software and Services Outsourcing on the U.S. Economy and the IT Industry, Information Technology Association of America and Global Insight. Available at http://www.itaa.org/itserv/docs/execsumm.pdf.

Drawbacks and Risks Until now, we have painted a positive picture as to why offshoring should increase shareholder value. However, if all there was were benefits, then all companies would be taking advantage. Unfortunately, there are many drawbacks and risks that are associated with offshoring a company’s IT work. The first risk to a company is that their data will now be residing in someone else’s hands. Chances of security breaches increase with the time that data takes to be transferred over cables. Also, because the data is now in another country, a company may not have control over what happens to it. Another drawback to offshoring work is that a company is potentially training a new global competitor. Now, not only does the new company have your files, they also have your current business processes and your customers’ names. Also, as more and more knowledge is exported to the overseas partner and away from the U.S. headquarters, it will be



Further value creation potential through: Increased global competitiveness of U.S. business Multiplier efffect of increased national savings 0.04

0.67

1.12-1.14 0.450.47

0.58 0.05

Savings accrued to U.S. investors and/ or customers

Import of U.S. goods and services by providers in India

Transfer of profits by U.S. providers in low-wage country to parent

Current direct benefit*

Total direct benefit retained in the U.S.

Value from U.S. labor reemployed

Potential for total value creation in the U.S. economy

Potential future benefit

Figure 4.4 Value potential accrued to the United States. (From McKinsey and Company [2003], Offshoring: Is It a Win-Win Game?, McKinsey Global Institute. Available at http://www.mckinsey.com/knowledge/mgi/reports/Offshoring/ offshore.asp.)

increasingly difficult to bring back the laid-off talent to rebuild the infrastructure here. Recently, especially last year during the Presidential race, firms based in the United States were criticized for offshoring work. This bad publicity could lead to decreased sales by boycotting customers, as well as through isolation from U.S. suppliers. Having to hire public relations personnel to communicate with the media could negate all cost savings. Other risks have to do with the offshored country. Not every country has a stable infrastructure, including roads, telecommunications, and electricity. A loss in power or cut fiber cables could isolate the offshored group from its U.S.-based counterpart. Also, political or economic unrest in foreign countries could spell trouble to offshored operations. Instability in some areas of the world could lead to data and people being taken hostage and held for ransom.

Offshore Locations Once CEOs consider offshoring knowledge work, which country should they choose? Consulting firm A.T. Kearney did a study entitled the Offshore


Offshoring Knowledge Work to Increase Shareholder Value 47 Table 4.9 A.T. Kearney Country Evaluation Metrics for Offshoring Category

Financial structure

People skills and availability

Business environment

Subcategories

Compensation costs Infrastructure costs Tax/regulatory costs Business process experience Labor force availability Education and language Attrition rates Economic/political environment Country infrastructure Cultural adaptability Security of intellectual property

Source: From A.T. Kearney Country Location.

Table 4.10 Top 20 Countries to Offshore Work India China Malaysia Czech Republic Singapore Philippines Brazil Canada Chile Poland

Hungary New Zealand Thailand Mexico Argentina Costa Rica South Africa Australia Portugal Vietnam

Source: From A.T. Kearney.

Location Attractiveness Index, in which they evaluate several weighted categories (Table 4.9) to come up with the list of countries (Table 4.10). The categories include financial structure, people skills and availability, and business environment. Financial structure includes the subcategories of compensation, infrastructure, and tax/regulatory costs. People skills and availability evaluates the countries by business process experience, labor force experience, education and language, and attrition rates. The business environment category looks at economic and political environment, country infrastructure, cultural adaptability, and security of intellectual property. Most of these areas have been presented earlier, and should definitely be considered prior to offshoring knowledge work.



Gross Margin

Staples - 2001 (in 000s) Net Profit Margin

Net Profit

2,794

Direct Expenses

Net Worth = Assets – Liabilities

1,038

10,674

Sales

0.41

=

2.26

×

2,075

Total Expenses

Return on Assets

Financial Leverage

0.18

Net Profits = Total Assets × Net Profit Net Worth Net Worth Total Assets

COGS 7,879

719

0.07

Return on Net Worth

Sales 10,674

1,038

Indirect Expenses Inventory

Sales 10,674

2,356

2.68

Asset Turnover

Current Assets

1,640

Accounts Receivable 298

3,989

Total Assets

Other 1,633

419

Fixed Assets

Figure 4.5 DuPont financial analysis — Staples, 2001.

Many of the countries listed are probably not unusual. India tops the list, with China right behind. However, some of the other countries listed in the top 20 may surprise people. Malaysia came in third, with Chile and Poland coming in the top 10. In the end, the list shows that there are many countries from which to select and that CEOs should carefully consider the benefits and risks of each prior to making any decisions.

Case Study To see if there is an increased likelihood that offshoring knowledge work could increase shareholder value, we used the DuPont system of financial analysis on two comparable companies from the years of 2001 through 2004 (Figure 4.5 through Figure 4.12). The companies selected are both U.S.-based multibillion dollar corporations in the retail sector. One, Best Buy, has stated they have been using offshore development since at least the early 2000s (TATA Web site). The other, Staples, has no release that we could find, announcing they are using offshored work. Obviously, this analysis is not meant to be a definitive statement on the benefits of offshoring because there are many other variables not included. Rather, it is intended to be a discussion topic of reference. As we can see in the preceding models (Figure 4.5 through Figure 4.12), over the time period, Staples did not have an increase in its Return



Gross Margin


Net Profit

2,813

Direct Expenses


1,028

10,744

Sales

0.37

=

1.99

×

2,056

Total Expenses

Return on Assets

Financial Leverage

0.18


COGS 7,932

757

0.07

Return on Net Worth

Sales 10,744

1,028


Sales 10,744

2,403

2.63

Asset Turnover

Current Assets

1,460


4,093

Total Assets

Other 1,690

605

Fixed Assets


Gross Margin


Net Profit

3,209

Direct Expenses


1,129

11,596

Sales

0.36

=

2.15

×

2,259

Total Expenses

Return on Assets

Financial Leverage

0.17


COGS 8,388

950

0.08

Return on Net Worth

Sales 11,596

1,129


Sales 11,596

2,718

2.03

Asset Turnover

Current Assets

1,555


5,721

Total Assets


Other 3,004

Fixed Assets

798



Gross Margin


Net Profit

3,897

Direct Expenses


1,408

13,181

Sales

0.30

=

1.78

×

2,816

Total Expenses

Return on Assets

Financial Leverage

0.17


1,408


Sales 13,181

Return on Net Worth has decreased Higher Net Profit Margin than BBY

COGS 9,284

1,081

0.08

Return on Net Worth

Sales 13,181

3,479

2.03

Asset Turnover

Current Assets

1,466


6,503

Total Assets

Other 3,024

1,603

Fixed Assets


Gross Margin

Best Buy - 2001 (in 000s) Net Profit Margin

Net Profit

3,227

Direct Expenses

0.05

1,227

15,327

Sales

0.42

=

2.66

×

2,455

Total Expenses

Return on Assets

Financial Leverage

0.16


COGS 12,100

772


Return on Net Worth

Sales 15,327

1,227


Sales 15,327

2,929

3.17

Asset Turnover

Current Assets

1,767


4,840

Total Assets

Figure 4.9 DuPont financial analysis — Best Buy, 2001.

Other 1,911

Fixed Assets

953



Gross Margin


Net Profit

4,739

Direct Expenses


1,747

19,597

Sales

0.49

=

2.93

×

3,493

Total Expenses

Return on Assets

Financial Leverage

0.17


COGS 14,858

1,246

0.06

Return on Net Worth

Sales 19,597

1,747


Sales 19,597

4,611

2.66

Asset Turnover

Current Assets

2,258


7,375

Total Assets

Other 2,764

2,106

Fixed Assets


Gross Margin


Net Profit

5,546

Direct Expenses

0.06

2,113

20,946

Sales

0.48

=

2.81

×

4,226

Total Expenses

Return on Assets

Financial Leverage

0.17


COGS 15,400

1,320


Return on Net Worth

Sales 20,946

2,113


Sales 20,946

4,867

2.73

Asset Turnover

Current Assets

2,046


7,663

Total Assets


Other 2,796

Fixed Assets

2,509



Gross Margin


Net Profit

6,582

Direct Expenses


2,447

24,547

Sales

0.49

=

2.53

×

4,893

Total Expenses

Return on Assets

Financial Leverage

0.20


2,447


Sales 24,547

Net Profit Margin has increased Return on Net Worth has increased Rerutn on Assets has increased

COGS 17,965

1,689

0.07

Return on Net Worth

Sales 24,547

5,724

2.84

Asset Turnover

Current Assets

2,607


8,652

Total Assets

Other 2,928

2,774

Fixed Assets


on Net Worth. Best Buy, however, showed consistent gains year after year in Return on Net Worth, Profit Margin, and Return on Assets. This seems to indicate that Best Buy may have experienced these increases through the lower costs realized from offshored knowledge work.

Conclusion Although this chapter cannot definitively answer the question whether offshoring knowledge work can increase shareholder value, hopefully the insights gained have posed questions to CEOs, inducing further reviews. Whatever a CEO does, one thing is for certain. In a globally competitive service economy, if this leader does not focus on providing the best service to customers at the best price, while returning the highest value to shareholders, then that person will not be around for long. In the end, although offshoring knowledge work is similar to offshoring manufacturing work in many ways, one way they are not is that knowledge work cannot simply be transferred to the country with the lowest cost of labor. Although language and cultural barriers are much higher in the information age than they were earlier, offshoring knowledge work has the scope to provide far greater benefits to the global society through increased learning and communication.



References Aberdeen Group (August 6, 2003), Global Sourcing: What You Need to Know to Make It Work. Available at http://www.aberdeen.com/2001/research/ 08030004.asp. Anonymous (March 2004), Executive Summary: The Comprehensive Impact of Offshore IT Software and Services Outsourcing on the U.S. Economy and the IT Industry, Information Technology Association of America and Global Insight. Available at http://www.itaa.org/itserv/docs/execsumm.pdf. Anonymous. (September 5, 2004), Executive Survey of 252 Minnesota Companies, Star Tribune, Minneapolis-St. Paul, MN. Available at http://www.star tribune.com. Forrester Research. (2005), Changing Corporate Models Available at http:// www.forrester.com. Friedman, D.D. (October 1998), Price Theory: An Intermediate Text [electronic version]. Available at http://daviddfriedman.com/Academic/Price_Theory/. Karmarkar, U. (June 2004), Will You Survive the Services Revolution?, Harvard Business Review. Available at http://search.epnet.com/direct.asp?an= 13208542&db=buh, Will You Survive the Services Revolution? (login is required). Kearney, A.T. (2005), Selecting a Country for Offshore Business Processing — Where to Look. Available at http://www.atkearney.com/. Koch, C. (September 1, 2003), Offshore Outsourcing — Special Report, CIO Magazine. Available at http://www.cio.com/archive/090103/backlash.html. McKinsey and Company (2003), Offshoring: Is it a Win-Win Game?, McKinsey Global Institute. A vailable at http://www.mckinsey.com/knowledge/mgi/reports/Offshoring/offshore.asp.



Chapter 5

Integrated Total Cost of Ownership and Activity-Based Management Process Model Introduction In highly competitive worldwide industries, companies need a strategic edge to gain and maintain market share. Traditionally, companies choose to compete using one of five factors: price, dependability, innovation, quality, or flexibility (Hayes and Wheelwright, 1984). Effective control of bottom-line cost can provide opportunities to exploit a number of these factors. Obviously, lower costs can allow a company to offer lower prices without sacrificing profit margins. Also, lower costs mean that more profits can be invested on developing new products or on improving product quality and dependability. To gain improved understanding, we begin with reviewing the professional literature on total cost of ownership (TCO) and activity-based management, and the interconnections suggested between them.

55



Literature Analysis Because procured components and services make up such a large part of the overall cost of a product in these competitive industries, it makes sense to examine them and to try to control their contribution to the overall cost. TCO is a process of analyzing supply-chain activities and their associated costs. It was proposed by Ellram and Siferd (1993), but the general concept has been around prior to 1993 under a number of different names: total cost (Cavinato, 1991; Cavinato, 1992), life-cycle costing (Jackson and Ostrom, 1980), cost-based supplier performance evaluation system (Monczka and Trecha, 1988), cost of ownership (Carr and Ittner, 1992), zero base pricing (Burt et al., 1990), and product lifecycle costs (Shields and Young, 1991). All of these concepts are structured around three basic supporting ideas: (1) that cost must be examined from a long-term perspective beyond just the initial price, (2) that purchasing must consider the effects of other business functions on the value of a specific purchase, and (3) that purchasing must understand the cost impacts of all purchasing activities (Ferrin and Plank, 2002). For example, Ellram (1994) estimated that the purchase price only accounts for 35 percent of the TCO in manufacturing equipment. This concept too is not new to the 1980s and 1990s; purchasing management sources from as far back as 1928 have been emphasizing the importance of looking beyond initial purchase prices (Ellram and Siferd, 1993). The U.S. Department of Defense (DOD), in particular, started using total cost principles for its procurement activities, starting in the early 1960s (Shields and Young, 1991). Prior to the outsourcing trend that exists today, much of this early focus on life-cycle costing was aimed at equipment and capital purchases, usually examining maintenance and energy costs for two or more alternate equipment purchases (Jackson and Ostrom, 1980). Zero base pricing (ZBP) is a total cost method developed and trademarked by Polaroid in the early 1980s. It is based on the “all-in-cost” concept, in which the all-in-cost equals the acquisition price plus the “all in-house” costs. The all in-house costs are described as all of the costs needed to convert the purchased material to the finished product, including any costs from the field failure of the final product owing to defects in the original purchased materials. In ZBP, each cost area consists of avoidable and unavoidable cost components. ZBP works by identifying the avoidable cost components and eliminating them. The model looks at the supplier cost areas of profit, general and administrative costs, factory overhead, labor, and materials, and at the in-house cost areas of customer returns and lost sales, warranty, service and field failures, scrap, process yield losses, rework, lost production, production, storage, inspection and testing, and incoming transportation. Avoidable cost reduction is carried


Total Cost and Activity-Based Management Process Model 57

out by looking at six cost and quality drivers: tolerances, specifications, materials, the process and requirements placed on it, design for automation, and ease of manufacture. The system places a heavy emphasis on supplier negotiation and early supplier involvement in the design process to maximize cost savings (Burt et al., 1990). Cost management literature of the 1980s defined life-cycle costing (LCC) as all the costs that the producer will incur over the product’s life cycle; Shields and Young (1991) expanded this definition to include all of the costs incurred by the end consumer and called it product life-cycle costing (PLCC). Though they did not go into great detail defining the specific mechanics of the system, Shields and Young pushed the idea from being a mere cost estimating tool to a cost management system. They, describing a product life-cycle cost management (PLCCM) system that takes a productcentric view of costing, focused on creating long-term success in competitive markets through the production of innovative, quality products with short lead and delivery times. As such, the system they describe has a very strategic focus, attempting to align the company structur e and employee behaviors to the PLCCM to maximize its benefit. Cavinato (1991, 1992), whose focus appears to be on supply chains and how the different agents in the supply chain add value to the final product, developed a model called total cost. Similar to TCO, total cost looks at all of the costs associated with a product, but it does so from the perspective of a make/buy type of decision — i.e., comparing the costs at the supplier to the costs at the customer to determine which can make the product for the lowest total cost. It does this by comparing six cost factors: lowest labor rate, most effective process, most capital available, lowest cost of capital, highest tax rate, and most investment tax credits and depreciation available for use (Cavinato, 1991). He later creates a total cost/value model that advocates collecting costs in ten key areas: traditional basic input costs, direct transactional costs, supply relational costs, landed costs, quality costs/factors, operations/logistics costs, indirect financial costs, tactical input factors, intermediate customer factors, and strategic business factors, but he does not discuss any mechanism for actually estimating those costs. Carr and Ittner (1992) codified a cost model, called cost of ownership, that included five main cost items: purchase price, costs of purchasing, costs of holding, costs of poor quality, and costs of delivery failure. Similar to Cavinato, they do not recommend a specific costing mechanism, but instead give examples of four manufacturers’ cost of ownership systems. Each example involves a cost ratio method in which the total of the five cost areas is divided by the purchase price to get a cost index for each supplier. The user can then multiply this index against future purchase prices to estimate the probable cost of ownership (Carr and Ittner, 1992).



Monczka and Trecha (1988) had earlier proposed a similar cost ratio system that they called cost-based supplier performance evaluation system (CBSPES). In CBSPES, the purchased price is added to “nonperformance costs,” mostly quality and logistics costs, and divided by the purchase price to get an index that can be averaged to achieve an overall one for each supplier. CBSPES advocated the use of events with standardized costs to determine nonperformance costs. For example, scrapping a lot of material or returning materials to a supplier has a standard cost to the quality department. CBSPES is unique for a total cost system in that it utilizes a second rating system to capture subjective service factors that might not have an easily identifiable cost such as willingness to share data and responsiveness of communications (Monczka and Trecha, 1988). Originally, Ellram and Siferd (1993) described TCO as “all costs associated with the acquisition, use, and maintenance of an item.” To aid in determining these activities, they break them into six broad categories: quality, management, delivery, service, communications, and price. They differentiated TCO from ZBP by focusing TCO on internal customer costs, whereas ZBP is focused on costs at the supplier (Ellram and Siferd, 1993). It differs from Cavinato’s total cost concept in that it actually provides a more specific method for collecting the costs using activity analysis. Ellram (1993) soon revised TCO to include capital equipment, maintenance, repair, and operating supply (MRO) items and services in addition to purchased components and materials. She also recommended organizing activities into generalized pretransactional, transactional, and posttransactional categories, getting away from the previously described six functional categories. Another change was the suggestion that only significant cost components, those that account for most of the probable TCO, warrant tracking (Ellram, 1993). More recent articles regarding TCO deal not so much with the theory behind it and its importance, but with the disappointing implementation of it. Recent studies (Milligan, 1999; Ellram and Siferd, 1998; Ferrin and Plank, 2002) have indicated that although many companies utilize TCO principles, they currently do not use them systematically or evenly. Often, TCO usage is an informal process in which data has to be collected from numerous sources, often manually or with less-than-optimized IT systems (Milligan, 1999). This informal process often produces vague, untrustworthy, and inaccurate results that inspire less confidence in the TCO system (Milligan, 1999). Many companies do not apply it to all of their purchasing decisions; some apply it routinely, whereas others used it only for highpriority or high-cost items (Milligan, 1999; Ellram and Siferd, 1998). Sometimes, rather than using a general TCO model, companies develop unique TCO models for specific purchasing decisions (Ellram, 1994). There is a great deal of evidence that a single TCO model with a specific set of cost



drivers cannot be applied to all TCO users. Instead, TCO guidelines should be general because they will be customized by the user (Ferrin and Plank, 2002; Ellram and Siferd, 1998). For the remainder of this research study, the term TCO will take the Ellram concept of an all-encompassing cost of ownership, one that attributes cost from many areas of the business to the cost of supplied goods, but it will also include analysis of supplier cost structures and expand beyond purchased components to include services. Understanding supplier costs through ABC can help us determine ways of eliminating costly activities, reducing occurrences of activities, and reducing cost driver rates (Lere and Saraph, 1995). TCO focuses on analyzing supply-chain activities and their associated costs. This requires the use of systematic tools to determine activities, estimate their costs, and manage them. Over time, numerous cost estimation methodologies have developed. Zhang and Fuh (1998) describe six different costing methods: Traditional detailed-breakdown cost estimation — a detailed summation of all the costs (material, direct labor, overhead, etc.) that occur in the manufacturing process. Simplified breakdown cost estimation — simplified cost method for use prior to the development of the detailed process plan. It assumes use of optimum manufacturing method regardless of the equipment and process that will actually be used. Because of its use of empirical equations, it is often difficult to correlate with actual costs. Group technology (GT)-based cost estimation — utilizes a base cost for a group of similar products and a set of cost variables such as size, length, or number of features, and then establishes linear relationships between the final cost and the variable-cost factors. Cost estimation based on cost functions or cost increase functions — useful for a similar group of products, this method combines the technical and economic elements into a single functional equation of the overall cost. Coefficients of this equation are then determined by feeding historical data into a regression analysis. Activity-based cost (ABC) estimation — described in detail in the following text. Neural network approach to early cost estimation — uses a backpropagating neural network (a series of layered algorithms with an input layer, an output layer, and a number of “hidden” layers between them equal to the number of inputs) that can be set up with historical cost data and then adjusted or “trained” as additional cost information becomes available or the manufacturing situation changes.



Historically, use of the traditional costing method prevailed; cost estimates used a cost allocation system in which overhead costs were applied to the manufacturing process on the basis of direct labor hours or direct machine hours. This cost was then added to the direct labor cost and raw material cost to arrive at a total cost for the pr oduct. This produced adequate cost estimates when direct manual labor made up the major portion of the cost. In recent years, however, more production has become automated, reducing the amount of direct manual labor on a product. In the 1990s, conventional wisdom held that direct labor comprised only 5 to 10 percent of a typical product’s cost, and over 50 percent of the cost could be attributed to overheads (Porter, 1993). The continued use of traditional cost systems with a direct labor allocation basis now distorts cost estimates in many situations. Activity-based costing (ABC) is an activity-focused cost estimation and analysis method that seeks to provide a more accurate allocation of indirect overhead costs and complements the activity focus of TCO well (Porter, 1993; Ellram 1995). This methodology can be used to analyze the supplychain-related costs both at the purchasing company and at the supplier. In fact, as companies push to outsource more and more of their components and services, it becomes more important that they apply ABC analysis to their suppliers’ activities and understand their costs. The development of ABC took place in the context of the Harvard Business School in the early and mid-1980s, when American business was under threat from global markets, primarily the Japanese (Jones and Dugdale, 2002). Independent studies by Robin Cooper, Robert S. Kaplan, and H. Thomas Johnson and the Computer-Aided Manufacturing, International (CAM-I) organization all followed along similar threads, looking at revamping cost accounting systems to better account for overhead costs (Jones and Dugdale, 2002). In a series of articles, Kaplan argued that management accounting methods and practices had become irrelevant and obsolete in modern manufacturing. This work cumulated in a 1987 book with Johnson, Relevance Lost, which details the decline in management accounting (Lukka and Granlund, 2002). At the same time, articles by Kaplan and Cooper argued that traditional costing systems were also ineffectual, producing biased information in a modern manufacturing environment. These paved the way for ABC, which Kaplan and Cooper introduced in a Harvard Business Review article in April 1988, based largely on their work with companies such as John Deere, Scovill, Hewlett-Packard, and Siemens, where ABC-type systems were being developed (Lukka and Granlund, 2002). The original definition of ABC, sometimes called “first-wave ABC,” assumes that activities are controlled, allocation of cost is exact and complete, and the results are described as “more accurate” (Jones and Dugdale, 2002). A series of



articles by Cooper outlined the ABC process in detail (Cooper, 1988a, 1988b, 1989a, 1989b). At its central core, the concept of ABC revolves around developing a more accurate cost model of manufactured goods. A traditional volumebased cost system can generate distortions and bias when applied to diverse production volumes, part sizes, complexities, materials, and setup requirements. Use of ABC is aimed at eliminating these biases. Although traditional costing systems focused on the product and usually allocated costs on the basis of direct labor hours, machine hours, and material costs, ABC is focused on activities and how products use activity resources. It generates more accurate results by allocating costs from a wide variety of cost bases (Cooper, 1988a). There are some basic steps to implementing an ABC cost model: 1. 2. 3. 4.

Determine activities. Develop cost pools. Develop cost drivers. Determine pool rates.

Activities must be identified so that they can become the bases for the ABC cost model. This is accomplished by looking at all of the actions involved in the process and combining related ones into activities. It is important because measuring the costs associated with each individual action would be prohibitively expensive and time consuming (Cooper, 1989b). Process mapping is a useful tool in the activity identification process. It consists of devising charts that map the flow of the activities in a process. This often points out wasteful and redundant activities, and can be a useful activity in and of itself. For example, a recent process-mapping case study involving a company that ships parts across the U.S.–Mexico border resulted in 70 percent reductions in transit time and safety stocks. Key activities in developing the process map included visiting all of the locations where activities were taking place, observing them first hand, and having meetings where all of the players in the process met to understand in detail how each step in the process works and how they interact. They then redesigned the process for maximum speed and reliability. Key to this process was seeing activities first hand, conducting face-to-face meetings with every part of the supply chain, and being willing to listen and act on supplier suggestions (Gooley, 2003). Once the types of activities have been determined, these need to be categorized into homogeneous centers of expense, called cost pools. These pools are often broken down into department or function, but care must be given to not group together activities that one wants to allocate separately. For example, there could be a quality department cost pool,



but if inspection and rework were identified as separate activities in the first step, they need to be maintained as separate cost pools. If the cost system developer needs to add more accuracy to their ABC system at a later time, the activity pools can be decomposed into smaller sets of activities (Ben-Arieh and Qian, 2003). Each pool then has an amount of cost assigned to it, often at a periodic rate. For example, a quality department cost pool would consist of the annual cost of the quality department — department wages and benefits, equipment costs, training, etc. This allocation of cost to cost pools is called first-stage allocation (Cooper, 1989b). After the cost pools have been developed, cost drivers need to be determined. Cost drivers are the basis on which each activity cost pool is allocated. In ABC, any basis can be chosen, but the emphasis is on reasonable indicators that are easy to measure. Factors that affect the selection of cost drivers include the cost of measuring the driver, the degree to which the cost driver and the consumption rate of the activity are correlated, and what behaviors one intends to get from selecting a particular cost driver (Cooper 1989a). The number of required cost drivers goes up if the requirements for accuracy, the degree of product diversity, the relative cost of activities, or the degree of volume diversity increase or the cost drivers correlate poorly to consumption rates (Cooper 1989a). Some experts suggest using five or fewer cost drivers to avoid overanalysis, but more sophisticated softwares are allowing companies to measure more. Strong buy-in from IT personnel is required to make these systems work (Marshall, 2002). Babad and Balachandran (1993) developed a model for optimizing the number of cost drivers used in an ABC system through a cost–benefit trade-off between loss of accuracy and the cost of measuring the cost drivers. In this model, multiple activities are merged under single cost drivers, and management can add weight to cost drivers that it feels are more important. The allocation of cost pools into cost drivers is called second-stage allocation (Cooper, 1989b). Once the cost drivers have been determined, the cost pools can be divided by them to determine pool rates. These pool rates are then used to determine the costs of particular products. Early in its history, ABC competed fiercely with E. Goldratt’s theory of constraints (TOC) for hearts and minds of accountants and management (Jones and Dugdale, 2002). TOC deals with identifying the constraint in a process, often called a bottleneck, which limits the throughput of the entire process. TOC advocates removing the constraint and moving on to the next bottleneck that emerges, continually improving the throughput of the process. On a fundamental level, TOC and ABC oppose each other. TOC is focused on immediately removing constraints and thus has a very short-term focus — labor and overhead are fixed-period costs. ABC has



a much more long-term focus, in which labor and overhead are flexible costs that can be adjusted over time. ABC does not include opportunity costs for bottlenecks and fixed-capacity operations (Kee, 2001). Others have argued, similarly, that if an ABC system does not include measures of intangibles such as improved quality, improved cycle times, flexibility, reduced wait times, utilization, and reduction of inventory, ABC analysis of advanced manufacturing systems (AMS) will be as unfairly distorted because it will only include the high overhead and setup costs inherent in such a system (Park and Kim, 1995). First-wave ABC, in which more accurate costs could be determined from exact allocations, led to conflict within the accounting community, and many felt that allocation methods could never be exact. Others felt that allocating certain costs on a per-unit basis was counterproductive when some activities such as R&D and factory tax payments were really aimed at maintaining the overall manufacturing enterprise (Jones and Dugdale, 2002). By 1991, a different interpretation of ABC had emerged. Kaplan and Cooper, in a 1991 article, switched the emphasis of ABC from developing accurate per-unit costing to developing a better understanding of the product cost hierarchy. They divided activities into unit, batch, productsustaining, and facility-sustaining levels. Product cost is then described as a sum of the unit, batch, and product-sustaining costs. In this second definition of ABC (sometimes called second-wave ABC), the focus is on resources instead of activities, costs are “sufficiently accurate” instead of “more accurate,” and estimation and contribution margins are acceptable parts of the model. As it moved into the 1990s, the two differences between the first- and second-wave ABCs caused some confusion among the accounting academic community as some tried to bridge the gap between them, some discounted ABC theory as a whole, and others chose to ignore the redefinition (Jones and Dugdale, 2002). For example, Johnson, one of the originators of ABC literature, soon became a detractor of the system. He argued that controlling activities to control cost via ABC really only works in the short term; it will not help competitiveness or long-term profitability because it places emphasis on altering the product and process mix to the firm’s benefit and not on altering how activities are performed to the customer’s benefit (Johnson, 1991). This growth and change in ABC theory is presented in the format of the ABC literature. During the late 1980s and early 1990s, there was a plethora of consulting research articles, aimed at “selling” ABC to American and European companies. Consulting research accounts for approximately 85 percent of the literature to date. They often include unsystematic research, gross generalization, and selective arguments (Lukka and Granlund, 2002).



Much of the ABC literature in the mid- and late 1990s reflects basic research. These articles look to analyze ABC from an unbiased, scientifically vigorous point of view. Examples include mathematical modeling, statistical surveys, and conceptual clarification articles. This basic research and consulting research is balanced out with critical research articles on ABC that aim to address the sociological ramifications that ABC produces. Oddly, it also tends to use generalizations and less scientifically rigorous arguments. The literature in this field appears to be very asymmetric and fractured between geographic locales (United States and European) and genres (consulting research, basic research, and critical research), with little communication between these groups. This leads to less accumulation of knowledge than would be found in most scientific fields, hindering research in the area (Lukka and Granlund, 2002). During the 1990s, the literature on ABC has gradually switched over into areas such as application possibilities, lessons learned, implementation instructions, and linking ABC to other popular management strategies (Lukka and Granlund, 2002). The early implication of an ABC system (Cooper and Kaplan, 1988) is that if one understands the cost structure behind their manufacturing activities, they can then manage those activities to reduce the overall cost. For example, if one product costs more than other products to make for a similar amount of revenue, that product could be dropped in favor of the more cost-effective ones. If redundant activities occur, doubling the cost to the product, ABC could help identify them, and they could be eliminated for cost savings. Costly processes can be redesigned. Johnson (1991) introduced the term activity-based management (ABM) to describe management based on ABC. Sometimes the combined use of ABC and ABM is abbreviated as ABC/M. Kaplan, Cooper, and Johnson tempered the idea of ABM by stressing the avoidance of automatic decisions (Cooper and Kaplan, 1988) and the limitation of strictly financial-based decisions (Johnson, 1991) in ABM. As the theory unleashed into the environment of management philosophy consultants of the early 1990s, much of this tempering became lost on the general audience, and close, automated links were established between ABC and ABM (Jones and Dugdale, 2002). The emphasis of the ABM literature soon came to identifying and eliminating non-value-adding activities (Jones and Dugdale, 2002; Lukka and Granlund, 2002), often staff functions and similar overhead activities (Armstrong, 2002). There are numerous examples of authors linking ABC with other management strategies. Crance et al. (2001) proposed combining ABC with statistical process control (SPC). Processes naturally experience some amount of variance. ABC and ABM systems that do not take this into consideration may create warning signals whenever there is fluctuation



in a cost activity. SPC can be used to determine normal variance in a cost activity and prevent management from punishing process managers for normally fluctuating costs (Crance et al., 2001). Robert Kee proposes combining ABC with its early archrival TOC. He suggests an “operational ABC,” which uses mixed-integer programming to take into account opportunity costs for bottlenecks and costs of unused capacity. This short-termfocused operational ABC model can be married to a traditional ABC model so that companies can make short- and long-term production decisions that correlate and provide maximum profitability (Kee, 1995, 2001). Letza and Gadd (1994) suggest that because ABC and Total Quality Management (TQM) are both process-oriented philosophies and both deal with employee empowerment, the two methods can complement one another. In their opinion, total quality measures often fail because management cannot prove their effectiveness using traditional cost accounting systems. Clarke and Bellis-Jones (1996) also advocate using ABC and ABM in a TQM environment. Traditional accounting methods can lead to inaccurate cost assumptions, lack of employee empowerment, lack of customer focus, and a reduced ability for management to make effectual changes — all of which is anathema to a TQM organization. They emphasize that ABM is not an accounting technique, but a management process that makes opportunities for improvement apparent (Clarke and Bellis-Jones, 1996). In the early 1990s, in addition to promoting ABC and ABM, Kaplan began developing a management method called balanced scorecard (BSC) with partner David Norton. BSC requires companies to develop key indicators that support their goals and objectives regarding financial performance, customer satisfaction, internal business processes, and innovation and learning (Kaplan and Norton, 1992). These key indicators are used to communicate the strategy and enforce behaviors that support the strategy by tying incentives to those carefully considered key indicators. Organizations within the company can then be further aligned to the goals and strategies by developing their own set of tactical strategies and goals, with their key indicators, which tie into the overall goals and strategies. Results from BSC can be used as feedback to company and unit strategies to test their effectiveness and suggest new strategies (Kaplan and Norton, 2001). BSC examines both financial and operational indicators, differentiating it from ABM, which is strictly focused on cost. This does not mean that the two ideas are incompatible; ABC data can be used to feed and manage BSC systems (Tinkler and Dúbe, 2002; Maiga and Jacobs, 2003). ABC provides critical linkages to BSC by examining operational activity costs and customer profitability, and providing critical budgeting information (Kaplan and Norton, 2001). More recent literature has also been critical of ABC and ABM. Armstrong (2002) believes that ABC and ABM have developed into a method to



challenge staff accountability and suggests that the destruction of the staff department is the heart of ABM. Clearly targeting first-wave ABC allocation principles, he argues that indirect costs, by virtue of being defined as “indirect,” are not directly traceable, and therefore, no method can claim to allocate indirect costs in a more accurate method; they simply choose a more reasonable method. This is okay for ABC, but ABM couples this information with value analysis and uses it to destruct staff activities that cannot tie the value of their activities to individual products, e.g., research and development activities are investments in the future of the whole enterprise, unused capacity is not expended on a product, development of supplier relationships helps the quality of product lines, etc. (Armstrong, 2002). Tsai (1998) gets around this by claiming that an activity is value added if it satisfies an organizational need. Others have simply argued that there may be situations in which ABC is not cost effective to run. Estrin et al. (1994), for example, argue that the benefits of an ABC system may be low if it does not produce results that are significantly different from those of a less costly costing system or if management does not use the information for significant decision making. Cooper (1988b) ties the total cost of operating a cost measurement system to three factors: cost of errors, cost of measurement, and product diversity. A simple cost system has low measurement cost and high cost of errors, whereas a more accurate system has the reverse. This creates an optimal system somewhere between these two, in which the total cost of the system is minimal. Product diversity correlates to the cost of errors that in turn affects the total cost of the system. Any of the three factors can adjust, changing the total cost of the system. The cost system can be changed to meet the new optimal conditions, but there is usually a barrier cost to transferring the systems. If the preexisting, traditional cost system meets the optimal operational cost of the system, there may not be a need to change (Cooper, 1988b). One study suggests that if overhead costs, as a percentage of the overall business, get smaller, ABC implementation may not be profitable if overhead is less than 15 percent of the overall costs of the company (Vokurka and Lummus, 2001). Others have argued that successful use of ABC to increase profits for a firm is not necessarily based solely on implementation, but also on how much manager expertise and private information drives the product or process. In situations in which manager expertise is high and the uncertainty about how much that private information affects the system is low, implementation of ABC may actually lower profits because managers who help implement and operate the ABC system will bias the information to their division’s benefit, passing on almost intangible informational costs to the overall company (Mishra and Vaysmani, 2001).



External (Supplier)

Information Gathering

ABC Analysis

ABM

Balanced Scorecard

Company Goals, Objectives, & Strategies

Internal (Customer)

Information Gathering

ABC Analysis

Figure 5.1 TCO process model with ABC/M and BSC.

Another complaint about ABC is that it creates a second set of books for accountants to manage because the company must still maintain a traditional set of GAAP accounting measures for external reporting. Recent accounting scandals have made accountants hesitant to embrace ABC (Katz, 2002), and government organizations must be careful that a homegrown, internal ABC accounting system does not interfere with a legally mandated public accounting system (Cone, 2002).

Process Models Given this study’s definition of TCO as an all-encompassing cost of ownership including supplier costs, the following process model, which takes into account these elements (Figure 5.1), is proposed. The proposed process model consists of two parallel ABC cost analysis activities, internal at the customer and external at the supplier. The steps in the process are detailed as follows: 1. Internal a. Information gathering: Prior to the development of cost pool and driver elements, the scope of activities involved in a process



and information about those activities must be determined. For this process model, all activities related to procured components and services need to be determined. Because these activities can be very different at different companies, there is no definitive list of activities to include. Flowcharting and process-mapping techniques can be useful in identifying specific activities. The following list is given as a starting place for these activities: Design and development — What activities are related to developing purchased component specifications? Examples: component selection, supplier research. Logistics — What activities and costs are related to shipping the purchased components? Examples: expediting, carrier costs, tariffs. Quality/engineering — What customer activities are related to ensuring a quality component or service? Examples: audits, communications between the suppler and customer manufacturing personnel, warranty, scrap, rework. Purchasing — What activities and costs are related to supplier development and purchasing administration? Examples: purchase orders, supplier meetings, requests for quotes. MRO — What activities and costs are related to maintaining and repairing purchased items? Examples: inventory maintenance, replacement parts. Disposal — What activities and costs are related to disposing of the product after use? Examples: environmental fees. b. ABC analysis: The information gathered about the internal activities is used to generate cost pools, cost drivers, and pool rates. These are then applied to the components or services in question to determine the internal cost structure that supports them. 2. External a. Information gathering: This is the external version of Substep a. of Step 1. Here, information is gathered about the manufacturing process or outsourced service at the supplier. This may not be as easy as it sounds; many suppliers can only supply manufacturing cost information in a traditional accounting format; others may be reluctant to give up this information without a significant business incentive presented up front. Lere and Saraph (1995) suggest acquiring process flowcharts of the supplier’s activities for the product in question and breakdowns of overhead data for the processes that manufacture those parts. They also suggest asking the following questions: How much is the cost of an average engineering change order (ECO)?



What types and frequencies of setups are performed on the batches of the part or product? How are production control and scheduling activities and their costs allocated to the part or the product? How is initial product development activity charged to the part or product? How are machine maintenance and inspection activities accounted for in part or product cost? How are tooling and other capital expense charges accounted for? (Lere and Saraph, 1995) b. ABC analysis: The information gathered about the supplier activities is used to generate cost pools, cost drivers, and pool rates. These are then applied to the components or services in question to determine the supplier cost structure that supports them. 3. ABM for cost reduction: The results of ABC analysis at the supplier and the customer are combined and analyzed for opportunities to reduce the TCO. This generally drives the three following activities: a. Eliminating non-value-added activities. b. Reducing occurrences of activities. c. Reducing the pool rates for the cost drivers (Lere and Saraph, 1995). 4. Feed ABM data and results into a balanced scorecard (BSC) system: In a BSC system, the company pursues its goals and objectives through the use of key performance indicators, with primary focuses in the financial, customer, internal business process, and learning and growth arenas (Kaplan and Norton, 1992). BSC performance indicators are designed to directly support the goals and objectives and keep a balance of focus between operational and financial goals. The results of the ABM and ABC efforts are important inputs into the company’s BSC system, in which they can be used as part of the key indicator set, be used to easily find the sources of problem issues, and help determine trade-offs in strategic decision making (Kaplan and Norton, 2001; Tinkler and Dúbe, 2002; Maiga and Jacobs, 2003). 5. Feed performance of BSC indicators back into the ABC and ABM processes and the company strategies: The performance of these key indicators feeds back into the ABC and ABM processes to direct attention to TCO evaluation and management activities that directly support the company’s strategic goals and objectives. This also offers a chance to determine the effectiveness of the TCO evaluation and management methods and correct them as necessary or as the supply-chain environment changes. Feedback from



Enabling Factors

Total Life Cycle Costing and Management Using TCO and ABC/M

Suppliers and Customers Sharing Sensitive Information

Potential for Competitive Advantage of Products and Services

H11 +

Total Overall Product Cost H3 +

H4 +

Cost of Procured Services

Cost of Procured Components

H3 + ABM Applied to Procured Components

H1 –

Frequency of Communications between Suppliers and Customers

H2 –

Total Cost of Quality

H4 + H5 +

H7 +

Administrative Cost of Supply Chain Management

ABM Applied to Procured Services H5 +

Number of Suppliers

H10 – Existence of LongTerm Supplier Relationships

H6 – ABM Applied to Procurement Activities

H8 +

H9 +

Procurement Involvement in Design and Development

Common Component Selection

Figure 5.2 Hypothetical model for TCO study.

the BSC is also useful in testing the effectiveness of company strategy and suggesting changes (Kaplan and Norton, 2001).

Hypothetical Model The TCO process model, depicted visually in Figure 5.1, leads to the proposed hypothetical model, depicted visually in Figure 5.2, upon which this TCO study is based. This hypothetical model is discussed and presented in this section. An important part of the TCO process model is analysis of supplier cost structures. Little of the existing ABC literature addresses costs of purchased components and services, and when it does look at procurement, it discusses departmental and administrative costs for procurement activities, not the important cost of procured parts (Ellram, 1995; Lere and Saraph, 1995). Research by Ellram (1995) showed that many ABC-based systems only tracked administrative purchasing costs, generating information that was not sufficient for making good purchasing decisions. Lere



and Saraph (1995) suggest applying ABC to supplier cost analysis. Given the importance of purchased component costs to the overall bottom line of most modern manufacturers, the following hypothesis is proposed: H1: Application of ABM to procured components will reduce the overall cost of procured components and ultimately the total cost of the product. Despite its origins in manufacturing, ABC is not limited to parts and products. Recently, much has been done to apply ABC principles to service industries and services within companies. For example, banks have used ABC to determine the costs of transaction activities, help with customer segmentation, and make outsourcing decisions (Rafiq and Garg, 2002). The U.S. Marine Corps instituted ABC to realize cost savings in nonmilitary functions such as housing and accounting (Cone, 2002). Companies in India have recently used process mapping and ABM to analyze their HR activities, determine non-value-adding steps that do not support strategy and to eliminate them for efficiency and cost savings. It has allowed them to maintain a tighter, constant focus on quality and to better align their HR practices with corporate strategy (Process Mapping, 2002). Given the ability to analyze services using ABC and the importance of outsourced service costs to the overall bottom line of most modern manufacturers, the following hypothesis is proposed: H2: Application of ABM to procured services will reduce the overall cost of procured services and ultimately the total cost of the product. World-class supply chains are dependent on the development of partnership-type supplier relationships, in which customers and suppliers work together to each others’ mutual benefit and to achieve the full potential of the relationship (Carr and Ittner, 1992). Zsidisin and Ellram (2001) find that the critical features of these alliances are continual communication flow and trust between the organizations. These features might be measured by a willingness to share sensitive information, frequency of communication, and willingness to enter lengthy arrangements such as longterm contracts. To support the process model, purchasing personnel will need to get detailed information on activities, cost drivers, cost driver rates, and units of cost drivers at their suppliers. This sensitive information will be much easier to obtain in a partnership-type relationship (Porter, 1993; Ehie, 2001; Zsidisin and Ellram, 2001). Therefore, the following three hypotheses are proposed:



H3: Willingness of suppliers and customers to share information will positively affect the customer’s ability to apply ABM to procured components and services. H4: Frequency of communication with suppliers will positively affect the customer’s ability to apply ABM to procured components and services. H5: Presence of long-term supplier relationship will positively affect the customer’s ability to apply ABM to procured components and services. Every supplier relationship has a number of regular activities that need to go with it: requests for quotes, purchase orders, qualifications and verifications, payments, supplier reviews, etc. If one were to reduce the number of suppliers, consolidating more of its procurement business in a smaller number of key suppliers, then hypothetically there would be a reduction in these activities. One of the primary benefits of ABM is the ability to shift out costly redundant activities and eliminate them. ABM should recommend supplier reduction (Porter, 1993). Therefore, the following two hypotheses are proposed: H6: Application of ABM to procurement activities will lead to a significant reduction in the number of suppliers. H7: Reduction in the number of suppliers will significantly reduce the administrative costs of supply-chain management. If TCO advocates that purchasing must consider the effects of other business functions on the value of a specific purchase (Ferrin and Plank, 2002), and ABM aims to manage these activities and costs, then other areas of the business will be affected by ABM cost reduction efforts. Design and development is a prime target for examination because it is where 70 to 80 percent of the eventual cost is put into a product (Zhang and Fuh, 1998). At that stage, cost reductions can be implemented before much of the actual spending occurs. With more and more components being outsourced, procurement needs to transform its role within the organization from an administrative function where development and manufacturing simply place orders, to an integral advisor in the development and design process. At this stage, supply-chain professionals have the flexibility to consider numerous procurement scenarios to determine the most cost-effective one and can mitigate design issues that will cause future problems (Rink and Fox, 2003), and ABM should recommend



procurement involvement at this level (Porter, 1993). Therefore, the following hypothesis is proposed: H8: Application of ABM to procurement activities will lead to a significant level of procurement involvement in the design and development process. With reductions in the number of suppliers, a natural outgrowth of ABM in the design and development process will be the limiting of common component selection (Porter, 1993). For example, in an assembly, designers would be limited to a small selection of fasteners from a single supplier’s catalog. This has numerous cost advantages: purchasing orders and other administrative paperwork only has to be filed with one supplier, fewer fastener bins need to be filled on the manufacturing floor, and a simpler design means that fewer quality errors occur. Even if the number of suppliers is not reduced, ABM of the procurement activities would suggest the use of a recommended list of common components for design and development. For instance, common component usage across product lines can reduce setup times and facilitate the use of common manufacturing equipment, reducing overhead and cost (Tully, 1994). Therefore, the following hypothesis is proposed: H9: Application of ABM to procurement activities will limit common component selection (fewer suppliers and customer parts) during the design and development process. Application of TCO analysis using ABM principles on procurement activities must include an examination of the costs associated with the quality of the product. These can come from a number of activities: inspections, rework, scrap, warranty, and audits. In a BSC system, the results of these activities can show up in key indicators such as warranty or scrap cost, part defect counts, stop ships, customer dissatisfaction ratings, or field failures. Even though many of these quality activities take place after purchase, they are still associated with the total cost of the component. From an ABM perspective, however, only activities that prevent quality problems and only some activities that ensure conformance are value added; other processes need to be minimized to reduce cost (Tsai, 1998). Suppliers that have a history of producing parts with few quality problems will come out as less expensive in a procurement ABC analysis, and they will be selected over other suppliers. This reduces the total quality costs for the company as scrap, rework, and warranty become less of an issue with the quality supplier. ABM could also be used to



identify redundant activities such as multiple inspections of the same part. Therefore, the following hypothesis is proposed: H10: Application of ABM to procurement activities will reduce total quality costs. Just as a company should apply cost evaluation and management activities to their suppliers, they must realize that their customers will be applying similar activities to the company’s products and services. It is to their advantage to examine the life-cycle costs incurred throughout the entire supply chain, from suppliers to customers, beyond just their TCO. This allows them to develop and offer products and services that are cost effective to the eventual customer, strengthening the competitive advantage of the entire supply chain. Therefore, the following hypothesis is proposed: H11: Cost evaluation and management of the total life-cycle cost of the product or service will strengthen the competitive advantage of the product or service.

Game Theory Game theory is an area of strategic thinking that looks at mathematically predicting strategies in situations in which outcomes are based on the interdependence of the different participants’ actions. It began in 1944, when mathematician John Von Neumann and economist Oskar Morgenstern published Theory of Games and Economic Behavior, and it has become an important tool for business strategists since then (Brandenburg and Nalebuff, 1995). The simplest versions of game theory revolve around two-person games such as rock-paper-scissors or the classic prisoners’ dilemma. In these scenarios, two participants simultaneously choose a strategy without foreknowledge of their competitor’s strategy. With a limited number of strategies available to each player, the outcomes for all of the possible strategy choices can be arranged into a payoff matrix. Table 5.1, for example, shows the payoff matrix for rock-paper-scissors. This rock-paperscissors is an example of a zero-sum game, in which a win for one player results in an equal and opposite loss for the other player. Dominant strategies develop in games when one of the strategies provides an optimal solution regardless of what the other player does (Brickley et al., 2004, pp. 226–254). For example, in Table 5.2, Player 1 and Player 2 will always choose Strategy A because it has the biggest


Total Cost and Activity-Based Management Process Model 75 Table 5.1 Game Theory Payoff Matrix for Rock-Paper-Scissors Game Player 2 Rock

Paper

Scissors

0, 0 1, –1 –1, 1

–1, 1 0, 0 1, –1

1, –1 –1, 0 0, 0

Player 1

Rock Paper Scissors

Table 5.2 Matrix

Sample Game Theory Payoff Player 2

Player 1

Strategy A Strategy B

Strategy A

Strategy B

1, 1 0, 2

2, 0 1, 1

potential payoff. The outcome of rock-paper-scissors exclusively depends on the interaction between the two players, so that game has no dominant strategy. Game theory can get more complex from here, looking at the use of multiple strategies, interactions between multiple players, and sequential strategic decisions in games with multiple rounds (Friedman, 1998). In Chapter 7, we further analyze a number of competitive business scenarios to determine dominant TCO management strategies.

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Total Cost and Activity-Based Management Process Model 77 Gooley T.B. (March 1, 2003), Solving Cross-Border Roadblocks: Step-by-Step Process Mapping Helped One Shipper Speed Shipments across the U.S.Mexico Border, Logistics Management, p. 49. Hayes, R.H. and Wheelwright, S.C. (1984), Restoring Our Competitive Edge: Competing through Manufacturing, New York: John Wiley & Sons. Jackson, D.W. and Ostrom, L.L. (1980), Life cycle costing in industrial purchasing, Journal of Purchasing and Materials Management, 16(4), 8-12. Johnson, H.T. (1991) Activity-based management: past, present, and future, The Engineering Economist, 36(3), 219–238. Jones, T.C. and Dugdale, D. (2002), The ABC bandwagon and the juggernaut of modernity, Accounting, Organizations and Society, 27, 121–163. Kaplan, R.S. and Norton, D.P. (2001), Transforming the balanced scorecard from performance measurement to strategic management: Part II, Accounting Horizons, 15(2), 147–160. Kaplan, R.S. and Norton, D.P. (1992), The Balanced Scorecard — Measures That Drive Performance, Harvard Business Review,70(1), 71–79. Katz, D.M. (December 31, 2002), Activity-Based Costing (ABC), CFO.com. Retrieved April 20, 2003, from LexisNexis Academic database. Kee, R.C. (2001), Evaluating the economics of short- and long-run productionrelated decisions, Journal of Managerial Issues,13(2), 139–158. Kee, R.C. (1995), Integrating activity-based costing with the theory of constraints to enhance production-related decision-making, Accounting Horizons, 9(4), 48–61. Lere, J.C. and Saraph, J.V. (1995), Activity-based costing for purchasing managers’ cost and pricing determinations, International Journal of Purchasing and Materials Management, 31(4), 25–31. Letza, S.R. and Gadd, K. (1994), Should Activity-Based Costing Be Considered as the Costing Method of Choice for Total Quality Organizations, The TQM Magazine, 6(5), 57–63. Lukka, K. and Granlund, M. (2002), The fragmented communication structur e within the accounting academia: the case of activity-based costing research genres, Accounting, Organizations, and Society, 27, 165–190. Maiga, A.S. and Jacobs, F.A. (2003), Balanced scorecard, activity-based costing and company performance: an empirical analysis, Journal of Managerial Issues, 15(3), 283–303. Marshall, J. (2002), More Complex, More Robust: Activity-Based Costing Systems Are Harnessing the Internet and Adding New Functionality, Giving Companies More Horsepower Than Ever, Financial Executive, 18(1), 44–45. Milligan, B. (1999), Tracking Total Cost of Ownership Proves Elusive, Purchasing, 127(3), 22–23. Mishra, B. and Vaysmani, I. (2001), Cost-system choice and incentives — traditional vs. activity-based costing, Journal of Account Research, 39(3), 619–641. Monckza, R.M. and Trecha, S.J. (1988), Cost-based supplier performance evaluation, Journal of Purchasing and Materials Management, 24(1), 2–7. Park, C. and Kim, G. (1995), An economic evaluation model for advanced manufacturing systems using activity-based costing, Journal of Manufacturing Systems, 14(6), 439–451.


78 Supply Chain Cost Control Using Activity-Based Management Porter, A.M. (1993) Tying down total cost, Purchasing, 115(6), 38–43. Process Mapping: Adding value to Human Resource Management (September 6, 2002), Financial Express. Retrieved April 20, 2003, from LexisNexis Academic database. Rafiq, A. and Garg, A. (August 2002), Better Performance Is as Simple as ABC, US Banker, 56. Retrieved April 20, 2003, from Business and Company Resource Center database. Rink, D.R. and Fox, H.W. (2003), Using the Product Life Cycle Concept to Formulate Actionable Purchasing Strategies, Singapore Management Review, 25(2), 73–89. Shields, M.D. and Young, S.M. (1991), Managing product life cycle costs: an organizational model, Journal of Cost Management, 5(3), 39–52. Tinkler, M. and Dúbe, D. (September 2002), Strength in Numbers, CMA Management. Retrieved May 9, 2004, from Business and Company Resource Center database. Tsai, W.-H. (1998), Quality cost measurement under activity-based costing, The International Journal of Quality and Reliability, 15(7), 719. Tully, S. (1994), You’ll never guess who really makes … Fortune 130(7), 124–128. Retrieved August 23, 2003 from Business and Company Resource Center database. Vokurka, R.J. and Lummus, R.R. (2001), At what overhead levels does activitybased costing pay off?, Production and Inventory Management Journal, 42(1), 40–49. Zhang, Y.F. and Fuh, J.Y.H. (1998), A neural network approach for early cost estimation of packaging products, Computers and Industrial Engineering, 34(2), 433–450. Zsidisin, G.A. and Ellram, L.M. (2001), Activities related to purchasing and supply management involvement in supplier alliances, International Journal of Physical Distribution and Logistics Management, 31(9/10), 617–634.


Chapter 6

Methodology for Analysis Introduction This chapter presents details on a survey construct used for gathering industry information. This includes the attributes of surveyed subjects, survey instrument design, sample size, profiles of the survey participants’ organizations, and the organization of survey. Survey results were tallied at the macro level.

The Survey Construct To test the hypothetical model, a survey was administered or e-mailed to 255 engineering and business professionals during the months of March and April, 2004. A total of 141 surveys were received, representing at least 62 companies and 3 government and municipal agencies, and resulting in a return rate of 55 percent. Table 6.1 shows the profile of the survey responses by their organizations’ revenue, number of employees, and the tally of respondents that reported whether their organization is an OEM, contract manufacturer, or contracted service provider. The largest number of respondents reported revenues of $100 to $500 million and $1 to $5 billion, employee workforces of 50 to 200, 1,000 to 5,000, and greater than 10,000, and claimed to be OEMs. Industries surveyed included the following: automotive (component manufacturing), medical device (cardiac rhythm management, neurological devices, stents, hearing aids), aerospace (aircraft sensors, military fighter aircraft), industrial (generators,

79


80 Supply Chain Cost Control Using Activity-Based Management Table 6.1 Company Profile of Survey Respondents Tally

Percentage of Surveys

Revenue $0–5M $5–10M $10–25M $25–50M $50–100M $100–500M $500M–1B $1–5B >$5B Missing value

5 3 13 13 13 26 8 31 18 12

3.5 2.1 9.2 9.2 8.5 18.4 5.7 22.0 12.8 8.5

Number of Employees 0–50 50–200 200–500 500–1,000 1,000–5,000 5,000–10,000 >10,000 Missing value

4 27 11 11 37 19 28 4

2.8 19.1 7.8 7.8 26.2 13.5 19.9 2.8

OEM or Contract OEM Contract manufacturer Contract service provider

87 36 11

62 26 8

Category

filters, paints, adhesive products, fluid power distribution, pumps, spraying equipment), home construction and furnishings (windows, porch doors, fireplaces), military (armored vehicles, fighter aircraft, naval guns, submarine repair), heavy machinery (irrigation, harvesting equipment, lawn maintenance equipment), and electronics (hard disk drives, microelectronics fabrication, flexible circuitry, business equipment, electrical enclosures). Table 6.2 tallies the survey respondents by industry and their organizations by industry. The largest numbers of respondents come from the industrial, medical device, and electronics industries, with 28, 24, and 17 surveys, respectively, representing 23 industrial manufacturers, 12 medical device manufacturers, and 11 electronics manufacturers.


Methodology for Analysis 81 Table 6.2 Industry Profile of Survey Respondents Tally


Industry Industrial Medical devices Electronics Home construction and furnishings Military Services Office products Automotive Aerospace Memorabilia Financial services Health Heavy machinery Municipal Research Recreational vehicles Retail fixtures Advertising Utilities Printing Food and beverage Missing value

28 24 17 11 7 6 5 3 3 2 2 2 2 1 1 1 1 1 1 1 1 21

19.9 17.0 12.1 7.8 5.0 4.3 3.5 2.1 2.1 1.4 1.4 1.4 1.4 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 14.9

Respondent Companies by Industry Industrial Medical devices Electronics Home construction and furnishings Military Services Office products Automotive Aerospace Memorabilia Financial services Health Heavy machinery Municipal

23 12 11 2 4 6 3 3 3 1 2 2 2 1

28.0 14.6 13.4 2.4 4.9 7.3 3.7 3.7 3.7 1.2 2.4 2.4 2.4 1.2

Category


82 Supply Chain Cost Control Using Activity-Based Management Table 6.2 Industry Profile of Survey Respondents (Continued) Category

Research Recreational vehicles Retail fixtures Advertising Utilities Printing Food and beverage

Tally


1 1 1 1 1 1 1

1.2 1.2 1.2 1.2 1.2 1.2 1.2

A preliminary survey construct was tested with four known professionals prior to the general survey process to highlight clarity and usability issues, leading to minor alterations in the survey construct. The survey instructions were again altered for clarity after a review of some of the early survey results indicated that not all of the surveys were filled out correctly. A sample of the survey is included in Appendix A. Respondents were asked to rate the frequency of 31 activities within their company or business unit that related to the hypothetical model. Frequency categories were provided as follows:

Never — The activity never occurs. Infrequently — The activity is conducted less than once per year. Sometimes — The activity is conducted once per year. Often — The activity is conducted twice or more per year. Always — The activity is systematically conducted.

Where appropriate, respondents were asked to also provide an approximate percentage increase or percentage reduction of the activity over the previous five-year time span. They were also asked for an approximate percentage of their company’s overall products or services that were outsourced to suppliers. Questions were included to cover both the OEM and supplier points of view because respondents could come from either category or count themselves as both. Definitions of key terms such as TCO, ABC, and ABM were included in the survey for the convenience of the respondent. The survey results were entered into a spreadsheet. Numerous survey respondents did not answer all of the questions, so a number of calculations were added to determine whether each response survey provided enough information to test each hypothesis and calculate the percentage of surveys that supported each hypothesis. This information was then


Methodology for Analysis 83

used to determine which respondents should be targeted with a followup e-mail to fill in the unanswered questions. A total of 59 follow-up emails were sent out, yielding 32 follow-up responses. A tally of the survey results after this follow-up process is presented in Table 6.3 and Table 6.4. Table 6.3 displays all of the frequency responses in the 31 activities on the survey. Table 6.4 displays the quantified percentage reductions or increases over the last five years for ten of the activities on the survey.

Data Analysis Because the survey is designed to test the hypothetical model, the results of questions that indicate proposed causal activities and those of questions that indicate the hypothetical resultant activities are compared to test the hypotheses. Descriptive statistical data and statistical analysis are used to analyze and quantify these comparisons and ultimately test the hypothetical model.

10

9

8

7

6

5

4

3

2

1

Company uses an ABC system to determine the cost of its internal processes Company uses an ABC system to determine the costs of externally supplied components Company uses an ABC system to determine the costs of externally supplied services Customers use an ABC system to determine the cost of the product or services that we provide to them Company uses a cost estimating method other than ABC to determine the TCO of the products or services that it purchases Customers use a cost estimating method other than ABC to determine the TCO of the products or services that they purchase Company uses ABM methods to manage its internal processes Company applies ABM methods to our component suppliers Company applies ABM methods to our service providers Customers apply ABM methods to my products or services

Survey Questions

Table 6.3 Tally of Survey Results — Frequency Data

8

31

45

55

52

14

18

23

17

11

25

40

21

19

19

24

Infrequently

37

53

55

38

Never

21

13

15

31

28

31

14

21

15

22

Sometimes

16

18

19

22

24

23

19

17

15

24

Often

Frequency Data

10

8

6

13

13

27

13

11

18

20

Always

35

29

26

18

37

24

37

20

19

13

Missing Value



22 23

21

20

19

18

17

16

15

14

13

12

11

Company examines and manages the total life-cycle costs of its products or services Customers examine and manage the total life-cycle costs of their products or services Suppliers examine and manage the total life-cycle costs of their products or services Company is positioned competitively in its primary markets Company is willing to enter into nondisclosure agreements and share sensitive information with its suppliers Company is willing to enter into nondisclosure agreements and share sensitive information with its customers Employees communicate frequently with each core supplier Employees communicate frequently with each customer Company enters into long-term relationships with its suppliers Company enters into long-term relationships with its customers Procurement personnel play a significant part in the design and development process Company has reduced its number of suppliers Company has reduced the overall cost of purchased components 19 8

9

1

3

1

2

20 17

23

7

7

17

7

20

13

16

21

2

34

18

23

2

18

21

29

28 25

35

13

25

19

27

32

29

12

25

28

20

26 33

33

53

61

38

52

37

40

37

18

19

29

11 22

33

60

41

62

47

23

34

86

12

23

26

37 36

8

7

4

4

6

8

9

2

34

32

14


Methodology for Analysis 85

31

30

29

28

27

26

25

24

Company has reduced the overall cost of externally contracted services Company has reduced the costs of administrating its supply chain Company has reduced the total cost of quality of its products or services Company has reduced the costs of managing its customer relationships Company has increased the number of long-term relationships with its suppliers Company has increased the number of long-term relationships with its customers Company’s products or service offerings have become more standardized Component set used to design new products has become more standardized

Survey Questions

16

25

10

13

29

15

19

15

Never

Table 6.3 Tally of Survey Results — Frequency Data (Continued)

18

16

13

20

20

15

19

18

Infrequently

19

19

22

31

26

28

26

33

Sometimes

40

41

42

31

19

33

25

22

Often

Frequency Data

14

11

24

14

8

17

9

13

Always

34

29

30

32

39

33

43

40

Missing Value



27

26

25

24

22 23

Company has reduced its number of suppliers Company has reduced the overall cost of purchased components Company has reduced the overall cost of externally contracted services Company has reduced the costs of administrating its supply chain Company has reduced the total cost of quality of its products or services Company has reduced the costs of managing its customer relationships 7

0

1

3

5 0

60

62

56

64

65 72

0–25

=90)

10.00 1 case(s)

Stem & . . . . . . . . .

Leaf 0 5 00000 0000 55 0 (>=50)

10.00 1 case(s)

Always Stem-and-Leaf Plot Frequency 1.00 1.00 .00 1.00 .00 .00 1.00 Stem width: Each leaf:

Stem & 0 0 1 1 2 2 3

. . . . . . .

Leaf 0 5 5 0

10.00 1 case(s)

Sometimes Stem-and-Leaf Plot Frequency .00 3.00 2.00 .00 1.00 .00 .00 1.00 1.00 Stem width: Each leaf:

Stem & 0 0 1 1 2 2 3 3 4

. . . . . . . . .

Leaf 555 00 0 5 0

10.00 1 case(s)

Figure 7.5 Stem-and-leaf plots of reported percent reduction of procured component cost based on frequency of ABM usage.

Never

Infrequently Sometimes

Often

Always

Figure 7.6 Box plots of reported percent reduction of procured component cost based on frequency of ABM usage.

0.00

20.00

40.00

60.00

80.00

100.00

InfrequentABM

RegularABM

Figure 7.7 Box plots of reported percent reduction of procured component cost based on infrequent versus regular ABM usage.

0.00

20.00

40.00

60.00

80.00

100.00

AU8215_C007.fm Page 95 Wednesday, June 14, 2006 1:44 PM

Analysis and Findings 95

Never

11% 10% 40% 0% 40% 10% 36%

Percentage Reduction of Procured Component Costs

Mean Median Range Minimum Maximum Interquartile Range Count

17% 10% 90% 0% 90% 15% 15%

Infrequently (Less than Once per Year)

16% 10% 35% 5% 40% 26.25% 8

Sometimes (Once per Year)

20% 20% 50% 0% 50% 15% 15%

Often (Twice or More per Year)

13% 10% 30% 0% 30% 25% 4%

Always (Systematic)

Uses ABM on Procured Components

11% 10% 90% 0% 90% 20% 51%

Infrequently or Less (Less than Once per Year)

18% 10% 50% 0% 50% 10% 27%

Sometimes or More (at Least Once per Year)

Table 7.2 Descriptive Statistics Pertaining to Percentage Reduction of Procured Component Costs at Varying Frequencies of ABM Application to Procured Component Costs





explanation for this could be that the companies that Always use ABM on procured component costs have already taken much of the cost out and were not able to get the same benefit out of this activity that companies who applied ABM to procured components less frequently were able to achieve. It is important to note that because the survey sample responses fall into five categories for this analysis, the number of observations regarding the percentage reduction in the cost of procured components in each category form small samples, though they do suggest an inclination to accept the hypothesis. H2: Application of ABM to procured services will reduce the overall cost of procured services and ultimately the total cost of the product. Looking at the survey results on cost reductions of procured services for H2 provides a similar set of results as reducing procured component costs (H1). Figure 7.8 shows that the largest group of respondents did not apply ABM to their service providers and that the largest group of respondents reduced the costs of those services at least once per year (Sometimes) over the last five years. Figure 7.9 shows the frequencies by which the company has been able to reduce the cost of procured services grouped by the frequency of ABM usage to achieve that goal. As in H1, there seems to be little correlation between the application of ABM to procured services and the frequency in the reduction of procured service Overall Frequency of Survey Respondents 60

55

50 40

Company applies ABM methods to our service providers

33

30

15

20

18

18

22 13

10

18

13

Often

Sometimes

Infrequently

Never

Always

8

0

Company has reduced the overall cost of externally contracted services over the last five years

Figure 7.8 Side-by-side comparison of survey respondents who use ABM and who have reduced purchased service costs.



14 12 12 Never

99

10 8

Infrequently

77

Sometimes 6

55

5

Often

44

4 4 2

2 1 0

22 2 1

2

1

2

0

1

0

Always

0 s ay w Al

n fte O

im et m So

In

fre

qu

N

en

ev

es

tly

0 er

Number of Survey Respondents

Reduction of Procured Service Costs

Uses ABM on procured services

Figure 7.9 Frequency of procured services cost reductions over the last five years stratified by the frequency of ABM usage.

costs; Figure 7.9 matches Figure 7.8, placing Sometimes reduction in procured service costs as the highest result in any frequency of ABM application to procured services. Figure 7.10 shows the mean percentage reductions of procured service costs for each frequency of ABM application to procured services. This distinctly shows a trend of improved results between the Never and Often applications of ABM to procured services, going from 6 to 20 percent reductions in procured service costs, respectively. As in H1, there was a drop in the Always applies ABM situation, down to 14 percent mean reduction in procured service costs. Again, this may be because companies that Always apply ABM have already gotten much of the value out of this activity; the so-called “low-hanging fruits” are out of the way, and they do not see the results that a company using ABM less frequently would see. Figure 7.11 shows the mean percentage reductions of procured service costs if we broke the results into two categories, Infrequently or less, which represents the nonregular ABM user, and Sometimes or more, which represents the regular user. Here, we see a definite 11 percent procured services cost reduction for those who apply ABM to their procured service costs over those who do not. Although the mean results of the percentage reduction in procured service costs look substantial, they can be biased by a few outlying cases, so Figure 7.12 and Figure 7.13 show the percentage reduction in procured



Mean % Reduction of Procured Service Costs 25% 20% 20% 15%

14%

13% 9%

10% 6% 5% 0% Never

Infrequently

Sometimes

Often

Always

Uses ABM on Procured Services

Figure 7.10 Mean reported percent reduction of procured service costs based on frequency of ABM usage.

Mean % Reduction of Procured Service Costs 18%

17%

16% 14% 12% 10% 8%

6%

6% 4% 2% 0% Infrequently or less

Sometimes or more


Figure 7.11 Mean reported percent reduction of procured service costs based on frequency of ABM usage.



Never Stem-and-Leaf Plot Often Stem-and-Leaf Plot Frequency

Stem &

Leaf Frequency

2.00 Extremes 13.00 0 . 5.00 0 . 7.00 1 . .00 1 . 6.00 2 . 3.00 2 . 2.00 Extremes Stem width: Each leaf:

(==60)

10.00 1 case(s)

Stem &

2.00 0 1.00 0 3.00 1 .00 1 2.00 2 .00 2 1.00 3 .00 3 1.00 4 1.00 Extremes Stem width: Each leaf:

. . . . . . . . .

Leaf 00 5 000 00 0 0 (>=80)

10.00 1 case(s)

Infrequently Stem-and-Leaf Plot Always Stem-and-Leaf Plot Frequency

Stem &

Leaf Frequency

1.00 0 .00 0 1.00 0 .00 0 .00 0 3.00 1 1.00 Extremes Stem width: Each leaf:

. . . . . .

Stem &

Leaf

0 5 000 (>=20)

10.00 1 case(s)

1.00 .00 1.00 1.00 .00 .00 1.00 Stem width: Each leaf:

0 0 1 1 2 2 3

. . . . . . .

0 0 5 0

10.00 1 case(s)

Sometimes Stem-and-Leaf Plot Frequency

Stem &

1.00 Extremes 3.00 1 . .00 1 . 1.00 1 . .00 1 . .00 1 . 2.00 2 . .00 2 . 1.00 2 . Stem width: Each leaf:

Leaf (==40)

10.00 1 case(s)

Often Stem-and-Leaf Plot Frequency

Stem &

1.00 -2 1.00 -1 .00 -0 5.00 0 5.00 1 3.00 2 1.00 Extremes Stem width: Each leaf:

. . . . . .

Leaf 0 0 00155 00005 005 (>=90)

10.00 1 case(s)


Stem &

Leaf Frequency

3.00 0 3.00 0 3.00 1 .00 1 .00 2 .00 2 1.00 3 .00 3 1.00 4 1.00 Extremes Stem width: Each leaf:

. . . . . . . . .

000 555 000

0 0 (>=65)

10.00 1 case(s)

1.00 .00 2.00 .00 3.00 1.00 .00 1.00 Stem width: Each leaf:

Stem & -1 -0 0 1 2 3 4 5

. . . . . . . .

Leaf 5 01 005 0 0

10.00 1 case(s)


Stem &

1.00 Extremes 2.00 0 . .00 0 . 2.00 1 . 1.00 1 . 5.00 2 . 4.00 2 . 2.00 3 . .00 3 . 2.00 4 . 1.00 Extremes Stem width: Each leaf:

Leaf (==100)

10.00 1 case(s)

Figure 7.37 Stem-and-leaf plots of reported percent reduction in supply base based on frequency of ABM usage.



the percentage reduction in supply base results based on the frequency of ABM application to internal processes as stem-and-leaf diagrams. Figure 7.38 and Figure 7.39 plot out the percentage reduction in supply base results based on the frequency of ABM application to internal processes as box plots for all frequencies and for regular (Sometimes or more) and nonregular (Infrequently or less) use, respectively. A detailed summarization of the descriptive statistics for percentage reduction in the supply base is provided in Table 7.6. The difference in the median percentage reduction in supply base results is even more pronounced than that of the mean percentage reduction in supply base results, 10 percent difference in the median results for the percentage reduction in supply base results for the nonregular and regular ABM user versus 4 percent difference for the mean percentage reduction in supply base results between the nonregular and regular ABM user. Because the survey sample responses fall into five categories for this analysis, the number of observations regarding the percentage reduction in the supply base in each category forms small samples, though they can be used in combination with the frequency of activity observations to suggest an inclination to accept the hypothesis. H7: Reduction in the number of suppliers will significantly reduce the administrative costs of supply-chain management. Figure 7.40 shows that the largest number of respondents both reduced their supply base and reduced the administrative costs of supply-chain management at the Sometimes and Often frequencies. Even more notable about Figure 7.40 is that, as in Figure 7.33, most of the frequency categories have a roughly equivalent number of respondents, reducing the size of their supply base and reducing their supply-chain administrative costs at the same frequency. This again suggests that the two may be very closely related. Figure 7.41 groups the frequency with which the company has reduced its supply-chain administrative costs by the frequency of supply base reduction. If a Pearson chi-squared test is performed on this information as was done for the H6 information, the resulting chi-squared probability is 9.55E–8. The frequencies of reduction in supply-chain administrative costs and the reduction of the supply base are rejected as independent, based on a 0.05 probability test. Reduction in supply-chain administrative costs and the reduction of the supply base are therefore accepted as interdependent, based on the survey results. Figure 7.42 shows the mean percentage reduction in supply-chain administration costs based on the frequency with which the supply chain is reduced. The results here are striking with a mean 32 percent reduction in the supply-chain administrative costs for those who Always (systemat-

Never


Often

Always

Figure 7.38 Box plots of reported percent reduction in supply base based on frequency of ABM usage.

-50.00

-25.00

0.00

25.00

50.00

75.00

100.00

InfrequentABM

RegularABM

Figure 7.39 Box plots of reported percent reduction in supply base based on frequency of ABM usage.

-50.00

-25.00

0.00

25.00

50.00

75.00

100.00



Never

11% 10% 70% –20% 50% 17.5% 25%

Percentage Reduction in supply base

Mean Median Range Minimum Maximum Interquartile range Count

15% 7.5% 65% 0% 65% 23.75% 12


21% 20% 150% –50% 100% 17.5% 20


12% 10% 100% –20% 90% 18.5% 16


16% 20% 65% –15% 50% 28.5% 8

Always (Systematic)


13% 10% 85% –20% 65% 17.5% 37


17% 20% 150% –50% 100% 23% 44%


Table 7.6 Descriptive Statistics for Percentage Reduction in Supply Base at Varying Frequencies of ABM Application to Procured Service Costs





Overall Frequency of Survey Respondents

30

28 26

25

19

20

19

2625

20 19

Company has reduced its number of suppliers over the last five years

15 10

119

5 Company has reduced the co st s of administrating its supply chain over the last five years

Alway s

Often

Sometimes

Infr equently

Never

0

Figure 7.40 Side-by-side comparison of survey respondents who have reduced their supply base and who have reduced the costs of administering their supply chain.

Reduced Cost of Administering the Supply Chain


16

15

14 12 10

Never 9

Infrequent ly

8 7

8

Sometimes 6 6

6

5

6

6

5

Often Always

4

3

33 3 2

2

1 00

2 1 11

2

1

0 wa ys Al

n O fte

et im es So m

In fre qu en t ly

Ne ve r

0

Reduces supply base

Figure 7.41 Frequency of reductions in the cost of administering the supply chain over the last five years stratified by the frequency of supply-chain reductions.



Mean % Reduction of Supply Chain Administration Costs 35%

32%

30% 25% 20%

19%

17%

15% 8%

10% 5%

4%

0% Never

Infrequently

Somet imes

Often

A lway s

Reduces Supply Base over last five years

Figure 7.42 Mean reported percent reduction of supply-chain administration costs based on frequency of supply-chain reductions.

ically) reduced their supply base versus a mean 4 percent reduction in mean reduction in the supply-chain administrative costs for those who Never reduced their supply base. Figure 7.43 shows the mean percentage reduction in supply-chain administration costs for those who reduced their supply base Sometimes or more versus those who reduced their supply Mean % Reduction of Supply Chain Administration Costs 20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8. 0% 6. 0% 4. 0% 2. 0% 0. 0%

17.3%

10.0%

Infrequently or less

Sometimes or more

Reduces Supply Base over last five years

Figure 7.43 Mean reported percent reduction of supply-chain administration costs based on frequency of supply-chain reductions.



Never Stem-and-Leaf Plot Frequency 1.00 .00 5.00 2.00 1.00 2.00 Stem width: Each leaf:

Stem & -0 -0 0 0 1 1

. . . . . .

Leaf 5 00000 55 0 55

10.00 1 case(s)


Infrequently Stem-and-Leaf Plot Frequency 2.00 1.00 1.00 .00 3.00 .00 .00 .00 2.00 Stem width: Each leaf:

Stem & 0 0 1 1 2 2 3 3 4

. . . . . . . . .

Leaf 00 5 0 000

00

10.00 1 case(s)


Stem &

6.00 0 .00 0 6.00 1 1.00 1 1.00 2 1.00 Extremes Stem width: Each leaf:

. . . . .

Leaf 000002 000000 5 0 (>=30)

6.00 3.00 3.00 5.00 1.00 1.00 Stem width: Each leaf:

Stem & 0 1 2 3 4 5

. . . . . .

Leaf 005555 000 005 00000 0 0

10.00 1 case(s)

Always Stem-and-Leaf Plot Frequency 2.00 1.00 1.00 1.00 .00 .00 .00 1.00 1.00 Stem width: Each leaf:

Stem & 0 1 2 3 4 5 6 7 8

. . . . . . . . .

Leaf 00 5 7 0

5 0

10.00 1 case(s)

10.00 1 case(s)

Figure 7.44 Stem-and-leaf plots of reported percent reduction in supply-chain administration costs based on frequency of supply base reduction over the last five years.

base Infrequently or less and presents a mean 7.3 percent supply-chain administrative cost reduction advantage to those who regularly reduced their supply base. The differences in the median percentage reductions in supply-chain administrative costs, as presented in Figure 7.44, Figure 7.45, Figure 7.46, and Table 7.7, are also sizeable. Figure 7.44 shows the percentage reduction of supply-chain administration costs based on the frequency of supply base reductions as stem-and-leaf diagrams. Figure 7.45 and Figure 7.46 plot out the percentage reduction of supply-chain administration costs based on the frequency of supply base reductions as box plots for all

Infrequent Reduct

Regular Reduct

Figure 7.46 Box plots of reported percent reduction in supplychain administration cost based on frequency of supply base reduction.

-20.00

-20.00

Figure 7.45 Box plots of reported percent reduction in supplychain administration cost based on frequency of supply base reduction.

0.00

0.00

Always

20.00

20.00

Often

40.00

4000.


60.00

60.00

Never

80.00

80.00



Never

4% 0% 20% –5% 15% 10% 11%

Percentage Reduction in Supply-Chain Administration Costs


17% 20% 40% 0% 40% 27.5% 9


8% 10% 30% 0% 30% 10% 15%


19% 20% 50% 0% 50% 25% 19%


32% 27% 80% 0% 80% 75% 7%

Always (Systematic)

10.0% 5% 45% –5% 40% 18.75% 20


Has Reduced the Supply Base over the Last Five Years

17.3% 10% 80% 0% 80% 26.5% 41


Table 7.7 Descriptive Statistics for Reductions in the Cost of Administrating the Supply Chain at Varying Frequencies of Supply Base Reduction over the Last Five Years





frequencies and for regular (Sometimes or more) and nonregular (Infrequently or less) use, respectively. Table 7.7 summarizes the percentage reduction of supply-chain administration costs based on the frequency of supply base reductions results. They show a median 27 percent reduction in the supply-chain administrative costs for those who Always (systematically) reduced their supply base versus a median 0 percent reduction in mean reduction in the supply-chain administrative costs for those who Never reduced their supply base. The difference between the median percentage reduction in supply-chain administrative costs for those who have reduced their supply base Sometimes or more over the last five years and those who reduced their supply base Infrequently or less over the last five years is only 5 percent. Because the survey sample responses fall into five categories for this analysis, the number of observations regarding the percentage reduction in the supply-chain administrative costs in each category form small samples, though they can be used in combination with the frequency of activity observations to suggest an inclination to accept the hypothesis. H8: Application of ABM to procurement activities will lead to a significant level of procurement involvement in the design and development process. Figure 7.47 shows that the largest number of respondents do not use ABM to manage the internal processes, such as procurement activities, at their company and that the majority of the respondents reported that procurement personnel play a significant part in the design and development process at their companies at a Sometimes or greater frequency with almost an equal number reporting procurement involvement at the Sometimes, Often, and Always (systematically) frequency levels. Figure 7.48 shows the survey results for procurement involvement in design grouped by the frequency of ABM application to internal processes. There is a noticeable trend here; as the frequency of ABM application to internal processes increases, the number of Always has procurement involvement increases as a proportion of the responses for each frequency category. H9: Application of ABM to procurement activities will limit common component selection (fewer suppliers and customer parts) during the design and development process. Figure 7.49 shows that the largest number of respondents standardized their component set at an Often frequency over the last five years, and the largest number of respondents Never apply ABM to their internal




40

40

35 30

23 20

9

10

33

31

33 Company uses ABM methods to manage its internal processes

22

17

13 Procurement personnel play a significant part in the design and development process

Always

Of ten

Sometimes

Infrequently

Neve r

0

Figure 7.47 Side-by-side comparison of survey respondents who use ABM and whose procurement personnel are involved in the design process.

13

14

11

12

Never

10 77

8 6

7 6 6

666

6

7

Often

4

4 3

4


55 2 1

2

22

Always

11

1

0 s ay

n

Al

w

fte O

im et m So

In

fre

qu

N

en

ev

es

tly

0 er

Numb er o f Survey Respondents

Procurement Involvement in Design

Uses ABM on internal processes

Figure 7.48 Frequency of procurement involvement in design stratified by the frequency of ABM usage.




40

40

40 31

30 18

16

20

19

17

Company uses ABM methods to manage its internal processes

22 14 13

10

Always

Often

Sometimes

Infr equently

Never

0

Component set used to design new products has become more standardized over the last five years

Figure 7.49 Side-by-side comparison of survey respondents who use ABM and who have increased the standardization of their component set.

processes, including their procurement activities. Figure 7.50 groups the component set standardization frequency results by the frequency of ABM application to internal processes. As the frequency of ABM application increases, the frequency of component set standardization becomes greater because Never, Infrequently, and Sometimes become less prominent as the ABM application frequency moves from Never to Always. Figure 7.51 and Figure 7.52 show the mean percentage increase in component standardization on the basis of the frequency of ABM application to internal processes. Figure 7.51 does not display any particular trend, and Figure 7.52 displays a mere 0.5 percent difference in the mean percentage increase in component standardization between those who apply ABM Infrequently or less and those who apply ABM Sometimes or more. Looking at the stem-and-leaf diagrams and box plots of the percentage increase in component standardization based on the frequency of ABM application to internal processes, shown respectively in Figure 7.53 and Figure 7.54, it becomes clear that the lack of trend in Figure 7.51 and the closeness of the mean percentage increases in component standardization in Figure 7.52 are most likely the result of an outlier in the Never applies ABM category. As shown in Figure 7.53 and Figure 7.54, the median values of the percentage increase in component standardization increase as the frequency of ABM application to internal processes increases. Figure 7.55 shows the percentage increase in component standardization between those who apply ABM Infrequently or less and those who apply ABM Sometimes or more as box plots. The



12 10 10

9 8

8

Never

7 6 66

Infrequently

6

Sometimes

6 4

4 4

4

Often

33 3

3 2

2

3 3 2

1

Always 2 1

1 0 0

Al w ay s

n fte O

im et m So

In

fre

qu

N

en

ev

tly

es

0

er

Numb er o f Su rvey Respondents

Increased Standardized Component Set


Figure 7.50 Frequency of increases in component standardization over the last five years stratified by the frequency of ABM usage.

Mean % Increase of Standardized Component Set 30% 26% 25%

22%

21%

20% 16%

14%

15% 10% 5% 0% Never

Infrequently

Somet imes

Often

A lway s

Uses ABM on Internal Processes

Figure 7.51 Mean reported percent increase in standardized components based on frequency of ABM usage.


132 Supply Chain Cost Control Using Activity-Based Management Mean % Increase of Standardized Component Set 19.9%

19.8%

19.8% 19.7% 19.6% 19.5% 19.4%

19.3%

19.3% 19.2% 19.1% 19.0% Infrequent ly or less

Sometimes or more


Figure 7.52 Mean reported percent increase in standardized components based on frequency of ABM usage.

descriptive statistics from these charts are summarized in Table 7.8. Because the survey sample responses fall into five categories for this analysis, the number of observations regarding the percentage increase in component standardization in each category form small samples, though they do suggest an inclination to accept the hypothesis. H10: Application of ABM to procurement activities will reduce total quality costs. Figure 7.56 shows again that the largest number of respondents Never uses ABM to manage their internal activities, including their procurement activities, and that the largest numbers of respondents have managed to reduce their total costs of quality over the last five years on an Often and Sometimes basis. The frequency of reduction in total cost of quality responses are also shown in Figure 7.57, grouped by the frequency of ABM application to internal processes. No trends are apparent here on the basis of the frequency of ABM application to internal processes. Figure 7.58 and Figure 7.59 show the mean percentage reductions in the total cost of quality based on the frequency of ABM application to internal processes. There is a noticeable difference between the mean percentage reductions in the total cost of quality results when ABM is used Infrequently or less and when ABM is used Sometimes or more; the



Never Stem-and-Leaf Plot Frequency

Stem &

1.00 -2 .00 -1 .00 -0 7.00 0 6.00 1 4.00 2 2.00 3 .00 4 1.00 5 2.00 6 1.00 7 1.00 Extremes Stem width: Each leaf:

. . . . . . . . . . .

Leaf 5 0000025 000005 0555 00 0 02 0 (>=100)

10.00 1 case(s)


Stem &

1.00 -1 1.00 -1 .00 -0 .00 -0 2.00 0 .00 0 2.00 1 1.00 1 4.00 2 1.00 2 2.00 Extremes Stem width: Each leaf:

. . . . . . . . . .

Leaf 5 0 02 00 5 0000 5 (>=50)

10.00 1 case(s)


Stem &

Leaf Frequency

5.00 0 1.00 0 1.00 1 .00 1 2.00 2 1.00 2 1.00 3 1.00 Extremes Stem width: Each leaf:

. . . . . . .

00000 5 0 00 5 0 (>=60)

10.00 1 case(s)

1.00 2.00 2.00 .00 .00 1.00 1.00 Stem width: Each leaf:

Stem & 0 1 2 3 4 5 6

. . . . . . .

Leaf 0 00 55 0 0

10.00 1 case(s)


Stem &

4.00 0 1.00 0 3.00 1 3.00 1 1.00 2 1.00 2 .00 3 .00 3 2.00 4 2.00 Extremes Stem width: Each leaf:

. . . . . . . . .

Leaf 0000 5 000 555 0 5 00 (>=70)

10.00 1 case(s)

Figure 7.53 Stem-and-leaf plots of reported percent increase in standardized component set based on frequency of ABM usage.

Never


Often

Always

Figure 7.54 Box plots of reported percent increase in standardized component set based on frequency of ABM usage.

-25.00

0.00

25.00

50.00

7.005

100.00

Infrequent ABM

Regular ABM

Figure 7.55 Box plots of reported percent increase in standardized component set based on frequency of ABM usage.

-25.00

0.00

25.00

50.00

75.00

100.00



Never

22% 10% 125% –25% 100% 29% 25%

Percentage Increase in Standardized Component Set


14% 7.5% 60% 0% 60% 23.75% 12


21% 20% 80% 0% 80% 30% 17%


16% 17.5% 65% –15% 50% 19.75% 14


26% 25% 60% 0% 60% 40% 7%

Always (Systematic)


19.3% 10% 125% –25% 100% 27.5% 37


19.8% 15% 95% –15% 80% 20.75% 38


Table 7.8 Descriptive Statistics for Percentage Increase in Standardized Component Set at Varying Frequencies of ABM Application to Procured Service Costs





Overall Frequency of Survey Respondents 40

40

33 31 28

30 15

20

22

17 15

Company uses ABM methods to manage its internal processes

17 13

10

Company has reduced the total cost of quality of its products and/or services over the last five years

Always

O ften

Sometimes

Infr equently

Never

0

Figure 7.56 Side-by-side comparison of survey respondents who use ABM and who have reduced their total cost of quality.

12 10 10

9 8

Never

8

7

7

Infrequently

6 6

5

Sometimes

5 4

4

3

4

4 3

3

3

3

2 2 2

Often 3

2

22

Always

2 0

0

Al w

ay

s

n fte O

im m et So

In

fre

N

qu en

tly

es

0 ev er

Numb er of S urvey Respondents

Reduced Total Cost of Quality


Figure 7.57 Frequency of total cost of quality reductions over the last five years stratified by the frequency of ABM usage.



Mean % Reduction of Total Cost of Quality 25% 20%

20% 15% 10%

19%

18%

12% 9%

5% 0% Never

Infrequently

Somet imes

Often

A lway s


Figure 7.58 Mean reported percent reduction in total cost of quality based on frequency of ABM usage.

Mean % Reduction of Total Cost of Quality 18. 8%

20. 0% 18. 0% 16. 0% 14. 0% 12. 0%

10. 1%

10. 0% 8. 0% 6. 0% 4. 0% 2. 0% 0. 0% Infrequently or less

Sometimes or more


Figure 7.59 Mean reported percent reduction in total cost of quality based on frequency of ABM usage.



more frequent ABM usage presents a mean 8.7 percent reduction in the total cost of quality advantage. Figure 7.60 shows the percentage reduction of the total cost of quality based on the frequency of ABM application to internal processes as stemand-leaf diagrams. Figure 7.61 shows the percentage reduction of the total cost of quality based on the frequency of ABM application to internal processes as box plots. Figure 7.62 shows the percentage reduction of the total cost of quality based on the frequency of ABM application to Never Stem-and-Leaf Plot


Frequency 9.00 2.00 5.00 1.00 4.00 1.00 1.00 Stem width: Each leaf:

Stem & 0 0 1 1 2 2 3

. . . . . . .

000000000 56 00000 5 0000 5 0

10.00 1 case(s)

Infrequently Stem-and-Leaf Plot Frequency

Stem &

5.00 0 2.00 0 .00 0 .00 0 .00 0 1.00 1 .00 1 1.00 1 2.00 Extremes Stem width: Each leaf:

. . . . . . . .

Stem &

Leaf

Leaf

Leaf 00001 23

0 5 (>=35)

6.00 0 2.00 1 3.00 2 2.00 3 .00 4 1.00 5 1.00 Extremes Stem width: Each leaf:

. . . . . .

000225 05 000 05 0 (>=75)

10.00 1 case(s)

Always Stem-and-Leaf Plot Frequency .00 1.00 2.00 1.00 2.00 .00 2.00 Stem width: Each leaf:

Stem & 0 0 1 1 2 2 3

. . . . . . .

Leaf 5 00 5 00 00

10.00 1 case(s)

10.00 1 case(s)


Stem &

3.00 0 .00 0 2.00 1 2.00 1 1.00 2 4.00 2 2.00 Extremes Stem width: Each leaf:

. . . . . .

Leaf 003 00 55 0 5555 (>=50)

10.00 1 case(s)

Figure 7.60 Stem-and-leaf plots of reported percent reduction in total cost of quality based on frequency of ABM usage.

Often

Always

Figure 7.61 Box plots of reported percent reduction of total cost of quality based on frequency of ABM usage.

Infrequent ABM

Regular ABM

Figure 7.62 Box plots of reported percent reduction of total cost of quality based on frequency of ABM usage.

0.00

0.00 Infrequently Sometimes

20.00

20.00

Never

40.00

60.00

80.00

40.00

60.00

80.00





internal processes grouped into those who apply ABM to internal processes Infrequently or less and those who apply ABM to internal processes Sometimes or more as box plots. The descriptive statistics from these charts are summarized in Table 7.9. From them, it can be seen that the median values of the percentage reduction of the total cost of quality increase as the frequency of ABM application to internal processes increases, a 9.5 percent difference between those who use ABC Infrequently or less and those who use ABM Sometimes or more. Because the survey sample responses fall into five categories for this analysis, the number of observations regarding the percentage reduction in the total cost of quality in each category form small samples, though they do suggest an inclination to acceptance the hypothesis. H11: Cost evaluation and management of the total life-cycle cost of the product or service will strengthen the competitive advantage of the product or service. Figure 7.63 shows that a large majority of the survey respondents felt that their company was Always positioned competitively in their primary markets and that the distribution of those who use TLCC to manage the cost of their services and pr oducts was relatively even between all of the frequency categories. The competitive positioning results are shown grouped by frequency of TLCC usage in Figure 7.64. The large response of Always positioned competitively from the survey makes it hard to pick out any trends on the basis of frequency of TLCC usage. This may be a perception issue; when asked about their company’s competitive position, many respondents may have felt compelled to rate their company, which they identify themselves with, very highly. It is notable, however, that the three respondents who rated their company as Never or Infrequently positioned competitively in their primary markets also reported that their company never used TLCC to manage its costs.

Results Table 7.10 summarizes the results of the previous hypothesis-testing discussions, including the verdicts of each test. H1, H2, H3, H5, H6, H7, H8, H9, and H10 are inclined to be accepted, and H4 and H11 ar e inclined to be rejected on the basis of the survey results. Figure 7.65 redisplays the TCO study hypothetical model with the rejected hypotheses removed.

Never

9% 10% 30% 0% 30% 20% 23%

Percentage Reduction of Total Cost of Quality


12% 2% 65% 0% 65% 15% 11%


20% 17.5% 50% 0% 50% 16.75% 14


19% 15% 75% 0% 75% 28% 15%


18% 17.5% 25% 5% 30% 17.5% 8

Always (Systematic)


10.1% 5.5% 65% 0% 65% 16.25% 34


18.8% 15% 75% 0% 75% 20% 37


Table 7.9 Descriptive Statistics for Percentage Reduction of Total Cost of Quality at Varying Frequencies of ABM Application to Internal Processes






100 86

80

Company examines and manages the total life cycle costs of its products and/or services.

60 40

37

29 23

2

20

2

29

20 12

26

Company is positioned competitively in its primary market(s). Always

Of ten

Sometimes

Infrequently

Neve r

0

Figure 7.63 Side-by-side comparison of survey respondents who use TLCC and who are competitive in their primary markets.

25

22 18

20 15

13

7

Someti mes

7

6

5

4 2

3

1

2

00

0 00

Never Infrequently

12

9

10 5

12

00

Often Always

2 00 ay s w Al

fte n

So

m

et im

en qu fre In

O

tly

es

0 N ev er


Company Is Positioned Competitively

Uses Total Life Cycle Costing

Figure 7.64 Frequency of competitive market positioning stratified by the frequency of TLCC usage.

H3: Willingness of suppliers and customers to share information will positively affect the customer’s ability to apply ABM to procured components and services. H4: Frequency of communication with suppliers will positively affect the customer’s ability to apply ABM to procured components and services.

Frequency: No observable trends.

Frequency: No observable correlation. Percentage reduction: Observable benefit when looking at mean percentage reduction of procured component costs, particularly at Often application of ABM. Median results favorable only when looking at the Often application of ABM. Frequency: No observable correlation. Percentage reduction: Observable benefit when looking at mean percentage reduction of procured service costs, particularly at Often application of ABM. Median results also favor ABM. Frequency: Companies that Often enter into information-sharing agreements displayed slightly higher frequencies of ABM application.

H1: Application of ABM to procured components will reduce the overall cost of procured components and ultimately the total cost of the product.

H2: Application of ABM to procured services will reduce the overall cost of procured services and ultimately the total cost of the product.

Observed Results

Hypothesis

Table 7.10 Summary of Hypothesis-Testing Results

Inclined to reject on basis of frequency observations.

Inclined to accept on basis of frequency observations.

Inclined to accept on basis of percentage reduction of procured service cost results.

Inclined to accept on basis of percentage reduction of procured component cost results.

Verdict



Observed Results

Verdict

Frequency: Companies that enter into Inclined to accept on basis of frequency long-term relationships Always observations. (systematically) with service providers show slightly higher frequencies of ABM application. Customers that enter into long-term relationships Sometimes with survey respondents show slightly higher frequencies of ABM application. H6: Application of ABM to procurement Frequency: Chi-squared test indicates Inclined to accept on basis of chiactivities will lead to a significant interdependence. squared test and percentage reduction reduction in the number of suppliers. Percentage reduction: Mean and median of supply base results. percentage reduction of supply base indicate higher reduction of supply base with increased frequency of ABM application. H7: Reduction in the number of suppliers Frequency: Chi-squared test indicates Inclined to accept on basis of chiwill significantly reduce the interdependence. squared test and percentage reduction administrative costs of supply-chain Percentage Reduction: Mean and median of supply-chain administration costs. management. percentage reduction of supply-chain administration costs indicate higher reduction of supply-chain administration costs with increased reduction of supply base.

H5: Presence of long-term supplier relationships will positively affect the customer’s ability to apply ABM to procured components and services.

Hypothesis

Table 7.10 Summary of Hypothesis-Testing Results (Continued)



Frequencies: Always (systematically) involvement of procurement personnel in design and development process increases with frequency of ABM application to internal processes. H9: Application of ABM to procurement Frequency: Standardization of activities will limit common component component set increases as frequency selection (fewer suppliers and customer of ABM application to internal parts) during the design and processes increases. Percentage increase: Mean percentage development process. increases in component set standardization do not appear to be significant. Median percentage increases in component set standardization increase with increases in the frequency of ABM application to internal processes. H10: Application of ABM to procurement Frequency: No observable correlation. activities will reduce total quality costs. Percentage reduction: Mean and median percentage reduction of total cost of quality indicate higher reduction of total cost of quality with increased the frequency of ABM application to internal processes. H11: Cost evaluation and management of Frequency: No observable trends. the total life-cycle cost of the product or service will strengthen the competitive advantage of the product or service.

H8: Application of ABM to procurement activities will lead to a significant level of procurement involvement in the design and development process.

Inclined to reject on basis of frequency observations.

Inclined to accept on basis of percentage reduction of total cost of quality results.

Inclined to accept on the basis of frequency observations and median percentage increase in component set standardization observations.

Inclined to accept on basis of frequency observations.





Enabling Factors

Results for BSC System

Total Life Cycle Costing and Management using TCO and ABC/M

Suppliers and Customers Sharing Sensitive Information Total Overall Product Cost H3 + Cost of Procured Services

Cost of Procured Components

H3 + ABM Applied to Procured Components

H1 –

H2 –

Total Cost of Quality H7 +

H5 +

Administrative Cost of Supply Chain Management

ABM Applied to Procured Services H5 +

Number of Suppliers

H10 – Existence of LongTerm Supplier Relationships

H6 – ABM Applied to Procurement Activities

H8 +

H9 +

Procurement Involvement in Design and Development

Common Component Selection

Figure 7.65 Hypothetical model for TCO study after hypothesis testing.

Game Theory Analysis When looking at the strategic importance of adopting cost evaluation and management methods based on TCO and TLCC, it becomes necessary to examine how interaction with competitive players in the marketplace will affect the adoption of these business methods. Game theory can provide us with tools to examine these interactions. In a saturated and competitive worldwide market, market share can be modeled as a zero-sum game, i.e., where a gain in market share for one company represents an equal loss for its competitors. Table 7.11 is a zero-sum game matrix that represents potential strategies that two competing companies could employ. One of these companies, Company A, wants to use an activity-based approach to evaluating and managing its TCO. The other company, Company B, is employing either no method of evaluating and managing its TCO, or it is employing a nonactivity-based method such as traditional costing or GT-based costing. Each number in the matrix indicates a percentage cost advantage that Company


Analysis and Findings 147 Table 7.11 Game Theory Matrix — Procured Component Cost Advantage Based on Survey Results Company B Potential Strategies Competitive Cost Advantage for Company A Based on Cost of Procured Components

Company A potential strategies

A1. Systematically employs ABC to analyze TCO A2. Systematically employs ABM to analyze and manage TCO A3. Systematically analyzes and manages TLCC (including TCO)

B1. Makes no active effort to understand or manage costs

B2. Systematically employs some method to analyze TCO other than ABC

0%

1%

2%

3%

0%

1%

A will get if Company A and Company B pick the corresponding strategies; Company B loses an amount of cost advantage equal to Company A’s gain. The values in the matrix were derived from the survey results. Each one represents the difference between the mean percentage reduction in the cost of procured components of those survey respondents who used the corresponding strategy regularly (Sometimes or more, i.e., at least once per year) and the mean percentage reduction in the cost of procured components of those survey respondents who used the opposing strategy. According to game theory, each competing company will decide what to do based on their own self interest. Both will pick a strategy that maximizes their potential cost advantage while simultaneously minimizing the potential cost advantage of the competitor. Company A will determine the minimum value in each row of the matrix, which represents the minimal result for each of its strategies based on Company B’s potential strategies, and then choose the strategy that corresponds to the largest of those minimum values. In this way, Company A is picking the best of its worst-case scenarios. In Table 7.11, based on the survey results, Company A would pick strategy A2. Company B, on the other hand, will choose the strategy that potentially produces the most minimal result if Company A realizes the maximum result of that strategy. Company B will determine the maximum value in each column of the matrix, which represents the maximal result for each



of its strategies based on Company A’s potential strategies, and then choose the strategy that corresponds to the smallest of those maximum values. In Table 7.11, based on the survey results, Company B will choose strategy B1. This game theory payoff matrix results in a “saddle point,” a single strategy for each company that will produce a single value for the matrix, in this case 2 percent. If the individual resultant values for Company A’s and Company B’s strategies had been different from one another, i.e., if the maximum value of all of the minimum row values (the maximin) or the minimum value of all of the column maximum values (the minimax), it would indicate that there is a range of values in the system. In such a case, either competitor might be able to optimize the value of its outcome by proportioning out its efforts between two or more strategies. The survey instrument gives us three additional cost parameters that can be examined in this way: percentage reduction in procured service costs, percentage reduction in supply-chain administration cost, and percentage reduction in total cost of quality. Table 7.12, Table 7.13, and Table 7.14 show the game theory matrices for these cost reduction parameters based on the survey results. Table 7.15 summarizes the Company A results of these game theory matrices. All of them settle on saddle points. In three of the four cost reduction parameters, the strategy of choice for Table 7.12 Game Theory Matrix — Procured Services Cost Advantage Based on Survey Results Company B Potential Strategies Competitive Cost Advantage for Company A Based on Cost of Procured Services





5%

5%

8%

8%

4%

4%


Analysis and Findings 149 Table 7.13 Game Theory Matrix — Supply-Chain Administration Cost Advantage Based on Survey Results Company B Potential Strategies Competitive Cost Advantage for Company A Based on Cost of Supply-Chain Administration





8%

1%

8%

1%

7%

0%

Table 7.14 Game Theory Matrix — Total Cost of Quality Advantage Based on TCO Strategies in Competitive Environment Company B Potential Strategies

Competitive Cost Advantage for Company A Based on Total Cost of Quality





8%

2%

11%

5%

8%

2%


150 Supply Chain Cost Control Using Activity-Based Management Table 7.15 Results of Game Theory Matrices Cost Advantage Analysis Cost Advantage Procured components cost Procured services cost Supply-chain administration cost Total cost of quality

Strategy Solution Company A A2 A2 A1 or A2, either strategy equally advantageous A2

Company A is the application of ABM to control costs, based on the survey results. The game theory matrix can be adjusted to test a great variety of potential situations and strategies, given a reasonable set of data such as the survey results. For example, a large Company A and a small Company C are competing in similar markets with similar products at similar costs. Both companies want to use TCO methods to reduce the cost of administering their supply chains. Because of the relative sizes of their infrastructures, however, they will not be able to get the same results from the same strategy. Table 7.16 is a game theory matrix for such a scenario using the results of the survey, in which any company of over 1000 employees is regarded as large and any company of less than 1000 employees is considered small. In this scenario, the solution is for the large Company A to apply ABM to its supply-chain administration costs and for the small Company C to only use ABC to study its supply-chain administration costs. This suggests that smaller companies cannot capitalize on ABM or overall TLCC to reduce supply-chain administration costs as easily as a larger company, which may have either more resources to send at the problem or more nonvalue activities to trim from their procurement operations. Again, this data can be reconfigured and weighted in different ways, depending on the competitive situation, e.g., different competitors could be differentiated by revenues, size, geographies, industries, etc., and different strategies. However, as the examples from Table 7.11, Table 7.12, Table 7.13, Table 7.14 and Table 7.16 show, ABM is an effective tool when compared to other TCO methods for achieving cost reductions.

Large Company A potential strategies

A1. Systematically employs some method to analyze TCO other than ABC A3. Systematically employs ABC to analyze TCO A4. Systematically employs ABM to analyze and manage TCO A5. Systematically analyzes and manages TLCC (including TCO)

Competitive Cost Advantage for Company A Based on Supply-Chain Administration Costs

C3. Systematically employs ABC to analyze TCO

–1%

–4%

0%

–2%

C2. Systematically employs some method to analyze TCO other than ABC

8%

5%

9%

9%

5%

7%

3%

6%

C4. Systematically employs ABM to analyze and manage TCO

Small Company C Potential Strategies

5%

7%

3%

6%

C5. Systematically analyzes and manages TLCC (including TCO)

Table 7.16 Game Theory Matrix — Supply-Chain Administration Cost Advantage Based on TCO Strategies; Large versus Small Company Example





Chapter 8

Conclusions and Recommendations Ultimately, the goal of each company is to remain competitive and stay in business. As cost management through outsourcing and supply-chain management becomes a more prevalent strategy, strategic management methods such as BSC require more accurate TCO data and better ways of managing their TCO. This study has proposed the use of ABC and ABM to accomplish this and meet the strategic needs and objectives of the company. The results of this study show that the ability to apply ABM to suppliers is affected by the existence of long-term relationships and willingness to share sensitive information, both signs of partnership-type relationships, but that it is not affected by the frequency of communication with the supplier. This leads to a number of conclusions. As companies look to employ more accurate systems of managing their supplier costs, it will be necessary for them to develop these partnerships. Coming fr om the opposite direction, as companies develop partnerships with their suppliers to manage issues such as delivery and access to special technologies and skills, they will have a greater opportunity to try employing ABM to their supply chain and reduce their costs and their suppliers’ costs as well. Frequency of communication may have been too broad an indicator of partnerships when compared to sensitive information sharing and longterm relationships; it is just an important general requirement for business, partnership or not.

153



In this study, application of ABM to procured components and services led to reductions in their costs. As established in Chapter 1, these costs represent over half of the cost of the manufactured product. As indicated by the survey results, many of the respondents did not report using ABM on their procured components or services, but those that do have seen substantial reductions in the costs of those procured components or services, lowering their bottom lines and increasing their profits and ability to invest. Similarly, the total cost of quality, the reduction of which this study strongly correlates with increased ABM application to procurement activities, also affects the bottom line. ABM application to procurement activities led to increases in procurement involvement in design and development activities and increases in the amount of component standardization. The effects of ABM can be seen here in an area other than manufacturing or procurement, acknowledging the effect that other areas of the business have on the overall cost of the product. This, of course, is one of the central points of ABC and ABM, determining how the traditional overhead activities affect cost and effectively using that knowledge to control costs. It also suggests an organizational model made popular by concurrent engineering circles, in which the compartmentalized “over-the-wall” mentality is replaced by a more holistic whole business point of view. In this study, ABM application to procurement activities led to reductions in the number of suppliers, and reductions in the supply base corresponded with reductions in the cost of administering the supply base. This shows the value of ABM to achieve cost reductions, but it is also interesting because reductions in the size of supply base increase dependency on the suppliers who are selected for continued business. This in turn creates the need for partnership arrangements with these suppliers to ensure the dependability of delivery and price from the customer’s point of view and dependability of sales from the supplier’s point of view. It is just this sort of relationship that supports and allows the application of detailed TCO costing and management methods such as ABC and ABM to supplier operations. As a whole, competitiveness was not shown to be affected by the overall use of TLCC. As mentioned earlier, the survey response regarding the company’s competitiveness within its primary markets seems to be affected by a great deal of personal bias, with the vast majority of the respondents reporting that their company was positioned positively. It is also possible that TLCC, despite the relatively large number of respondents who reported some usage of TLCC, is just not perceived as a factor in companies’ competitive positioning when compared to other possible factors such as product and service offerings, flexibility, stock performance, quality, and dependability.


Conclusions and Recommendations 155

Some flaws in the survey instrument and procedure came to light during the study that future studies should take into account. Many of the respondents to this study’s survey felt that they did not have exact answers to the questions as they were unfamiliar with their company’s accounting and cost management structures. Hence, future studies could be focused on specific employees who have direct knowledge about a company’s accounting methodology and cost management strategies, such as accounting and procurement managers. The survey only received minimal testing (3 individuals) prior to wide distribution; future surveys should receive a more thorough predistribution screening. The Never–Infrequently–Sometimes–Often–Always scheme for reporting the frequency of various activities was useful and easy for survey respondents to understand, but it did not always apply equally to all activities. As the data was all self-reported, some bias undoubtedly crept in, particularly when asked about their company’s competitive posture; future studies should implement a method of independently verifying questions that might involve a high degree of bias. Future studies in the area of TCO and supply-chain integration might be taken in several directions. All of the participants in this study are from within the United States, but the future surveys could be expanded to compare results in other geographical locations such as Asia-Pacific and Europe. A topical area of inquiry might be into whether TCO is being utilized in international outsourcing arrangements and, if not, whether TCO analysis would still recommend this activity. The TCO activities of surveyed companies in future studies could be compared with the process model presented in this study to determine whether they are using a similar model and using the model outputs to generate key indicators for BSC systems. Future studies should examine the role of TCO data in strategic decision making and goal setting. With the continued trends toward globalization, productivity-measurement tools such as learning curve, outsourcing, and competitive supply chains, the management of cost in this environment is only going to become a more important facet of competitive strategy in the years to come.



Appendix A

Survey Instrument ABC/M in Outsourced Supply-Chain Survey Name: Date: Company and business unit (if applicable): Company Web site: $0–$5 million Annual revenue: (Place an X next to the $5–$10 million most appropriate $10–$25 million selection.) $25–$50 million $50–$100 million 0–50 Number of employees: 50–200 (Place an X next to the 200–500 most appropriate 500–1,000 selection.) Construction Industry: (Place an X next to the most appropriate Education and sector.) health services Financial activities Government

$100–$500 million $500 million–$1 billion $1–$5 billion > $5 billion 1,000–5,000 5,000–10,000 >10,000

Manufacturing Natural resources and mining Other services Professional and business services Continued.

157


158 Supply Chain Cost Control Using Activity-Based Management Information Leisure and hospitality Main product lines or service offerings:

Transportation and utilities Wholesale and retail trade

1. 2. 3. 4.

Job title: E-mail address: Work phone: Note: All answers will be treated as confidential and are for academic purposes only. All survey participants will be sent a copy of the results.

Background definitions (to be read prior to filling out the survey): Activity-based costing (ABC): A cost estimation methodology that attempts to directly determine the cost contribution of all activities related to a product or service. It stands in contrast to traditional costing methods in which the costs of overhead and administration activities are allocated on the basis of another, more easily measured activity such as direct labor time or machine operation time. Activity-based management (ABM): Management of activities for the purpose of reducing overall costs using ABC information. Typical ABM actions include eliminating redundant activities and determining unprofitable product offerings. Original equipment manufacturer (OEM): A company that produces complex equipment (as a computer system) from components usually sourced from other manufacturers. Total cost of ownership (TCO): All costs associated with the acquisition, use, and maintenance of a product or service. It includes costs incurred at the supplier but not costs incurred at a customer or end user if those costs are not charged back to the producer. Total cost of quality: All costs associated with product quality. It traditionally includes costs for proactive prevention and inspection activities and reactive internal and external failure mitigation activities; can be included in the TCO. Total life-cycle cost: All costs attributed to a pr oduct or service throughout its entire life cycle. It encompasses the entire supply chain, from raw material supplier to end user, including field use and end-of-life costs; includes the TCO.


Survey Instrument 159

I regard my company or business unit as (check all applicable): ___ An original equipment manufacturer (OEM) ___ Contracted supplier of components/materials/subassemblies to OEMs ___ Contracted service provider to OEMs Amount of your company’s (or business unit’s) overall products or services outsourced to suppliers or subsuppliers: ____ percent. Instructions: Place an X in the correct space next to each question. Skip any questions that are not applicable, but please try to answer as many as you can. Only mark one response per question. If you are part of a large multiunit company, please respond for just your business unit. Terms such as activity-based costing and total cost of ownership are defined on the first page of the survey.

1. My company (or business unit) uses an activity-based costing (ABC) system to determine the cost of its internal processes. 2. My company (or business unit) uses an ABC system to determine the costs of externally supplied components. 3. My company (or business unit) uses an ABC system to determine the costs of externally supplied services. 4. My customers use an ABC system to determine the cost of the product or services that we provide them. 5. My company (or business unit) uses a cost estimating method other than ABC to determine the total cost of ownership (TCO) of the products or services that we purchase.

Never

Infrequently (Less than Once per Year) Sometimes (Once per Year)


Continued.

Always (Systematically)



6. My customers use a cost estimating method other than ABC to determine the TCO of the products or services that they purchase. 7. My company (or business unit) uses ABM methods to manage its internal processes. 8. My company (or business unit) applies ABM methods to our component suppliers. 9. My company (or business unit) applies ABM methods to our service providers. 10. My customers apply ABM methods to my products or services. 11. My company (or business unit) examines and manages the total life-cycle costs of its products or services. 12. My customers examine and manage the total life-cycle costs of their products or services. 13. My suppliers examine and manage the total life-cycle costs of their products or services. Continued.



14. My company (or business unit) is positioned competitively in its primary markets. 15. My company (or business unit) is willing to enter into nondisclosure agreements and share sensitive information with its suppliers. Examples of sensitive information could include intellectual property, product roadmaps, and production and sales figures. 16. My company (or business unit) is willing to enter into nondisclosure agreements and share sensitive information with its customers. 17. Employees in my company (or business unit) communicate frequently with each of our core suppliers. 18. Employees in my company (or business unit) communicate frequently with each of our customers.

Never



Continued.




22. Over the last five years, my company (or business unit) has reduced its number of suppliers. 23. Over the last five years, my company (or business unit) has reduced the overall cost of purchased components.

Percentage Reduction Never




Continued.


For the following questions, place an X in the correct space next to each question, and also give an approximate percentage reduction if applicable. Estimate to the best of your knowledge.

19. My company (or business unit) enters into long-term relationships with its suppliers. 20. My company (or business unit) enters into long-term relationships with its customers. 21. Procurement personnel (supply/materials management, procurement engineering buyers, etc.) play a significant part in the design and development process in my company (or business unit).



24. Over the last five years, my company (or business unit) has reduced the overall cost of externally contracted services. 25. Over the last five years, my company (or business unit) has reduced the costs of administrating its supply chain. 26. Over the last five years, my company (or business unit) has reduced the total cost of quality of its products or services. 27. Over the last five years, my company (or business unit) has reduced the costs of managing its customer relationships.

Percentage Reduction Never



Continued.




28. Over the last five years, my company (or business unit) has increased the number of longterm relationships with its suppliers. 29. Over the last five years, my company (or business unit) has increased the number of longterm relationships with its customers. 30. Over the last five years, my company’s (or business unit’s) products or service offerings have become more standardized. 31. Over the last five years, the component set used to design new products has become more standardized.

Percentage Increase Never




For the following questions, place an X in the correct space next to each question and also give an approximate percentage increase, if applicable. Estimate to the best of your knowledge.





Appendix B

Survey Data

167

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Survey Response

$25–50M $10–25M

$50–100M $50–100M $25–50M $1–5B $50–100M $100–500M $100–500M $100–500M $100–500M >$5B $0–5M >$5B >$5B >$5B $25–50M $10–25M >$5B $100–500M $100–500M >$5B

Education and health Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Financial services Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing

Annual Revenue

Manufacturing Manufacturing

Industry

1,000–5,000 200–500 500–1,000 50–200 >10,000 50–200 1,000–5,000 1,000–5,000 1,000–5000 500–1,000 >10,000 0–50 >10,000 >10,000 >10,000 50–200 50–200 >10,000 50–200 50–200 >10,000

50–200 50–200

Percentage of Employees

x

x x

x x

x x

x x x

x

x x x x

OEM?

x x

x

x

x

x

x

CM? CSP?

5

25 30 5 10 10

1

50

70

5 5

0 0 30

Percentage Outsourced



25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Transportation and utilities Manufacturing Manufacturing Manufacturing Transportation and utilities Manufacturing Manufacturing Manufacturing Manufacturing $50–100M $5–10M $25–50M

>$5B >$5B $25–50M $25–50M $1–5B $10–25M $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B $1–5B >$5B $10–25M $50–100M $0–5M $10–25M >10,000 >10,000 50–200 200–500 1,000–5,000 200–500 5,000–10,000 1,000–5,000 5,000–10,000 5,000–10,000 5,000–10,000 5,000–10,000 5,000–10,000 5,000–10,000 500–1,000 >10,000 1,000–5,000 >10,000 50–200 1,000–5,000 0–50 50–200 500–1,000 1,000–5,000 0–50 50–200 x x x x

x x

x x x

x x x

x x x x x x

x x

x

x

20 25 10 10 50 30 18 75 30 0.5

10 0

10 0 10 5 10

0 0

15


Survey Data 169

51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

Survey Response

Manufacturing Other services Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Other services Manufacturing Manufacturing Manufacturing

Manufacturing Financial services Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Other services Manufacturing Manufacturing Other services

Industry

$100–500M $25–50M $50–100M $100–500M $1–5B $1–5B >$5B $1–5B $50–100M $100–500M $100–500M $100–500M $100–500M $500M–$1B

$100–500M $1–5B $1–5B $10–25M $10–25M $10–25M $1–5B

$25–50M

Annual Revenue

200–500 50–200 200–500 5,000–10,000 5,000–10,000 50–200 50–200 50–200 >10,000 200–500 1,000–5,000 50–200 50–200 1,000–5,000 1,000–5,000 1,000–5,000 >10,000 >10,000 1,000–5,000 1,000–5,000 1,000–5,000 1,000–5,000 200–500 1,000–5,000


x x

x x

x

x x

x x

x

x x

x x x

x

x

CM?

x

x x x

x x x

x

OEM?

x

x x

CSP?

5

10 25 30 80 10 50 30 10

5 100 30

20 1 5

40 5 80 20




75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Professional and business services Wholesale and retail trade Manufacturing Manufacturing Manufacturing Manufacturing Government Professional and business services Manufacturing Manufacturing Manufacturing $500M–$1B $100–500M $10–25M $1–5B $1–5B $10–25M $100–500M $100–500M >$5B $25–50M >$5B $100–500M $500M–$1B $100–500M $500M–$1B $100–500M $100–500M >$5B $10–25M >$5B $1–5B $500M–$1B $500M–$1B $25–50M $1–5B $1–5B 1,000–5,000 50–200 500–1,000 1,000–5,000 5,000–10,000 50–200 500–1,000 1,000–5,000 >10,000 500–1,000 >10,000 500–1,000 1,000–5,000 5,000–10,000 5,000–10,000 1,000–5,000 1,000–5,000 >10,000 50–200 >10,000 >10,000 1,000–5,000 1,000–5,000 200–500 >10,000 >10,000 x

x x x x

x

x

x x x

x x

x

x

x

x x x

x x

x

x

10 0 10 0 50 90 30 20 50 50 30 30 5

30 20 10 50 20

15 100 70


Survey Data 171

101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120

Survey Response

200–500 1,000–5,000 1,000–5,000 0–50 500–1,000 5,000–10,000 1,000–5,000 5,000–10,000 >10,000 200–500 50–200 500–1,000

$25–50M $100–500M $100–500M $5–10M $50–100M $1–5B $500M–$1B

Manufacturing Manufacturing Government Manufacturing Manufacturing Other services Manufacturing Manufacturing Information Manufacturing Manufacturing Professional and business services >$5B $25–50M $0–5M $50–100M

1,000–5,000 >10,000 >10,000 1,000–5,000 >10,000 >10,000 >10,000


$100–500M $1–5B $1–5B $50–100M >$5B >$5B $1–5B

Annual Revenue

Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing

Industry

x x

x

x x x x

x x x x x x x

OEM?

x

x

x

x

CM? CSP?

10 5 5

0 10 50 5 0 99 30

4 20

25 50 10




121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 $0–5M $0–5M $1–5B >$5B $100–500M

Financial services Government Government Manufacturing Manufacturing Other services

$1–5B $1–5B $50–100M $25–50M $50–100M

$500M–$1B

$100–500M $100–500M $5–10M $10–25M $10–25M

Manufacturing Manufacturing Manufacturing Manufacturing Manufacturing Education and health Manufacturing Other Services Manufacturing Manufacturing Manufacturing Professional and business services Government Government 5,000–10,000 5,000–10,000 5,000–10,000 5,000–10,000 >10,000 1,000–5,000

1,000–5,000 1,000–5,000

1,000–5,000 1,000–5,000 50–200 50–200 50–200 50–200 5,000–10,000 1,000–5,000 500–1,000 50–200 200–500

x

x x

x

x x

x x

x

x x x

x

x

x x

x

x

x x x

x

10 20 30 3

0

5 2 30 75 10

20

15 20 25 5 10


Survey Data 173

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Survey Response

Sometimes Sometimes Sometimes Sometimes Sometimes Often Often Infrequently Infrequently Never

Sometimes Often Sometimes Sometimes Sometimes Always Often Infrequently Infrequently Infrequently

Always Always Often Sometimes Never Always Always Never Sometimes Infrequently Infrequently Sometimes Never Sometimes

Often Infrequently Often Often Never Often Sometimes

Often Never Always Sometimes

Sometimes Infrequently

Never Never Often Sometimes

Infrequently Always Never Sometimes

Sometimes

Often Never Never Often

Often Never Never Always

Often Never Never Often Never Often

Never Sometimes

Never Infrequently

4. Customer Applies ABC

Never Infrequently

3. ABC Applied to Procured Services

Never Sometimes

2. ABC Applied to Procured Components

Sometimes Sometimes

1. Internal Use of ABC

5. Use of TCO on Procured Components/ Services

Never Always Never

Never Sometimes Sometimes Sometimes Never Often Often

Never Sometimes

Sometimes

Never Sometimes

6. Customer Applies TCO on Procured Components/ Services



22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 Often Never Never Never Never Never Infrequently Never Never Never Sometimes Infrequently

Often Never Never Never Never Never Infrequently Never Never Never Sometimes Never Often Often Often Never Never Never Infrequently Infrequently

Sometimes Often Sometimes Often Never Never Infrequently

Infrequently

Infrequently

Often Sometimes Sometimes Never Never Never Never

Infrequently Infrequently Infrequently


Often Infrequently Often Sometimes Sometimes Never Never Never Never Infrequently Sometimes Infrequently Never Never Sometimes Infrequently

Never Infrequently

Never Often Sometimes Never Infrequently

Infrequently Never Never Never Sometimes Sometimes

Never Infrequently Never Never


Never Sometimes

Often Often Never Never Often

Always Often

Sometimes Often

Often Sometimes Never Never Often Never Always Sometimes

Never Infrequently Never Never Sometimes Often Sometimes Never

Sometimes Always Always Often

Sometimes Never Never Never Always Sometimes Often Often Never

Sometimes Always Always


Survey Data 175

48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68

Survey Response

Sometimes Always Infrequently Sometimes

Sometimes Always Sometimes Sometimes Infrequently Always Often Never Sometimes Often Always Always

Often Never Infrequently Never Never Often Sometimes Never Sometimes Often Often

Never Never Never Never Never Never Sometimes Never Infrequently Often Often

Never Never Infrequently Never Never Never Never Never Infrequently Infrequently Often Always

Never Never Never Infrequently Never Infrequently Often Always Infrequently

Never Sometimes

Always Sometimes Never Sometimes

Often Never Often Often Never Often Never

Infrequently Never Sometimes Often Sometimes Always Sometimes

Infrequently Never Never Infrequently Never Never Infrequently


Sometimes Never Never Never Never Infrequently Infrequently


Never Never Never Infrequently Never Sometimes Sometimes



Often Never Never Infrequently Infrequently Infrequently Often Often Sometimes Never Sometimes





69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 Always Infrequently Never Sometimes Infrequently Never Always Sometimes Always Often Never Sometimes Often Sometimes Never Often Never Never Never Never Never Often Often Never

Always Infrequently Never Infrequently Infrequently Never Always Often Always Often Never Sometimes Often Often Never Always Never Never Never Never Never Often Never Never

Always Infrequently Never Never Often Never Always Often Always

Often Sometimes Often Always Often Never Always Infrequently Never Never Never Never Sometimes Never Never Never Sometimes Often

Sometimes Never Sometimes Never Never Never

Always Never Infrequently

Always Infrequently Always

Always Often Sometimes Infrequently Never

Never Never Sometimes Often Infrequently Never Sometimes Always Never Never Sometimes Always Infrequently Always Often

Always Often Always Always Never Always Always

Always

Always Never Never Sometimes Always Infrequently Sometimes Often

Never Sometimes Often Sometimes Never Never

Never Infrequently Never

Sometimes Often


Survey Data 177

95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115

Survey Response

Often Always Always Never Never Never Infrequently Often Always Never Never Infrequently Never Sometimes Never Never Never Never

Infrequently

Infrequently Never Often Infrequently Never Often Never


Often Always Often Infrequently Never Never Infrequently Often Always Sometimes Never


Infrequently Never Sometimes Never Never Infrequently Never

Never

Infrequently Never Always

Infrequently

Infrequently

Always Sometimes Sometimes Infrequently Always Never Sometimes

Never

Infrequently Always Never

Often

Never

Often Often

Never

Never

Never Often Always

Sometimes Never Sometimes

Never Often Often Often

Sometimes Infrequently Sometimes

Often Often Often

Often Always Always



Often Always Often Never Never Never Infrequently Sometimes Always





116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 Always Always Always

Often Often Never Often

Always Sometimes Always Always Always Often Infrequently Never Sometimes

Always Sometimes Sometimes Never Always

Always Often Sometimes Sometimes Sometimes

Never Sometimes Never

Never Sometimes Never Never Always Always Always Always

Sometimes Sometimes Infrequently Always Always Always Always Always Never Sometimes Sometimes Always

Never

Sometimes Sometimes Never Always Never Never Infrequently Never Always

Sometimes Sometimes Never Always Never Never Infrequently Never Always

Sometimes Often Never Often Always Never Infrequently Never Always

Infrequently Infrequently Often Never Never Often Always Never

Often

Infrequently

Sometimes Always Infrequently Always Infrequently

Never Sometimes

Sometimes Often Often Never Sometimes

Often Often Often Always Always Sometimes Never Always Often Infrequently

Infrequently Sometimes Infrequently Often Always

Often Infrequently Often Sometimes Always Sometimes Sometimes Never Sometimes

Always Always Sometimes Never

Often


Survey Data 179

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Survey Response

Infrequently Never Never Often Never

Sometimes Infrequently Never Infrequently Often Never

Always Never Never Never Often Never

Infrequently

Sometimes

Infrequently Never Never Sometimes

Infrequently Sometimes Sometimes

Sometimes Sometimes Often Sometimes Never Infrequently Always Never Often Infrequently Always Sometimes Often Never


Never Sometimes

10. Customer Applies ABM

Often Sometimes Sometimes Sometimes



Never Sometimes

9. ABM Applied to Procured Services

Often Sometimes Sometimes Sometimes Never Infrequently Sometimes

Never Sometimes

8. ABM Applied to Procured Components

Never Often

7. Internal Use of ABM

Sometimes Sometimes Never Infrequently Sometimes Sometimes Often Often Often

Always Often Sometimes Infrequently

Infrequently Sometimes Never Always

Never Often

11. Use of TLCC



24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Often Often Infrequently Never Never

Infrequently Infrequently Sometimes Never

Never Sometimes Often Often Sometimes Never Never

Infrequently Infrequently Infrequently Never

Sometimes Sometimes

Always Often Often Often Sometimes Sometimes Infrequently Sometimes Infrequently Sometimes Never

Never Infrequently

Often Never Never Never Never Infrequently Sometimes Never Never

Never Never Never Never Infrequently Sometimes Never Never

Infrequently

Infrequently Infrequently Often Never Never Never Never Infrequently Sometimes Never Never

Often Sometimes

Infrequently Infrequently Often Never

Never Sometimes Never Sometimes

Never Sometimes

Never Infrequently Never Never Infrequently Sometimes Never Never


Infrequently Sometimes Infrequently Infrequently Never

Often Often Often Never

Never Never Infrequently Often

Infrequently Always Sometimes Never Never Sometimes Always Never


Survey Data 181

50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72

Survey Response

Always Sometimes Never

Always Infrequently Never

Often Often

Infrequently Never

Often Always

Always Sometimes Infrequently

Often Often

Sometimes Never Never Sometimes Never Never Often Often Infrequently

Never Never Never Infrequently Never Never

Never Never Infrequently Never Never Infrequently

Sometimes Never Never Never Never Infrequently

Sometimes Never

Infrequently Never

Infrequently Never

Never Never Never Never


Never Never Always Never Sometimes


Never Never Always Never Sometimes


Never Never Always Infrequently Sometimes Sometimes Sometimes Never


Often Infrequently Infrequently Often Sometimes Infrequently Never Often Sometimes Often Never Never Often Sometimes Often Sometimes Sometimes Always Always Always Always Often Often

11. Use of TLCC



73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 Always Often Always

Always Often Always Never Never Often Always Often Never Often Never Never Never Never Never Often Never Never Sometimes Often Always Infrequently

Always Often Often

Never Sometimes Often Always Always Never Sometimes Infrequently Never Never Never Never Infrequently Never Never Often Always Always Sometimes Never Never Never Sometimes Never Often Never Never Infrequently Often Always Never

Never Never Often Always Often Never

Never Never

Never Never

Sometimes Sometimes

Always Always Sometimes

Never Often Often Always Never Often Never Never Never Sometimes Never Infrequently Never Never

Often Often Always


Never Never Infrequently Always Often Never Always Never Sometimes Infrequently Infrequently Never Infrequently Never Always Often Always Always Never

Sometimes Infrequently Always Always Always Always


Survey Data 183

99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118

Survey Response

Never

Never


Never Never Never Infrequently Infrequently Never Never Never Often Infrequently

Infrequently

Infrequently Never Often Sometimes Never Often Infrequently Often Sometimes Never Never Sometimes Never Often Never

Never

Never

Infrequently Infrequently

Never Sometimes Always

Often Often

Never

Never


Never Never Never Often Often


Never Never Infrequently Often Often


Never Never Infrequently Often Often Sometimes Never


Often Infrequently Often Infrequently Never Sometimes Infrequently Often Sometimes Often

Never

Never Never Sometimes Often Always Always Always

11. Use of TLCC



119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 Never

Never Often Never Infrequently Often Infrequently Always Always Infrequently Often Infrequently Never Infrequently

Never Often Never Sometimes Often Infrequently Always Infrequently Sometimes Infrequently Never Infrequently

Never Often Never Infrequently Often Sometimes Always Always

Never Often Sometimes Never Infrequently

Sometimes Never Sometimes Never Never

Sometimes Never Often Never Never

Sometimes Never Often Never Never Sometimes Sometimes

Infrequently Often Often Never Often

Never Often Sometimes Always Sometimes Sometimes Always Always

Never Never Often Never Never Sometimes

Always Infrequently Infrequently Sometimes Often

Always Often Often Often Never Always Always Always Always

Never Infrequently Infrequently Never Never Often Never


Survey Data 185

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Survey Response

Never Infrequently Infrequently Often Never Often Often Infrequently Sometimes Sometimes Sometimes Infrequently

Sometimes Infrequently Infrequently Infrequently

Infrequently Often Never Sometimes

Always Infrequently Sometimes Infrequently

Often Sometimes

Infrequently Sometimes Sometimes Sometimes Often

13. Supplier Use of TLCC

Never Often

12. Customer Use of TLCC

Always Often Sometimes

Always Often Always Always Often Always Never Often Often Sometimes Always Often Sometimes Always Often Always Always Always

14. Competitive Positioning in Primary Market

Sometimes Often Infrequently Often Never Always Often Infrequently

Sometimes Infrequently Sometimes Sometimes Sometimes Never Never Often Infrequently Never Always Always Often

15. Sensitive Information Sharing with Suppliers

Often Often Sometimes Often Never Sometimes Sometimes Infrequently

Infrequently Infrequently Sometimes Sometimes Infrequently Never Never Often Often Never Always Often Often

16. Sensitive Information Sharing with Customers

Always Infrequently Often Often Always Sometimes Never Often Often Often Always Sometimes Often Never Sometimes Always Sometimes Always Often Often Often Always

17. Communication with Suppliers



23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Infrequently Infrequently

Never Infrequently Sometimes Infrequently Infrequently Sometimes Infrequently Infrequently Sometimes

Sometimes Infrequently Sometimes Never

Infrequently Sometimes Infrequently

Infrequently Infrequently Always

Never Infrequently Never Infrequently Never

Sometimes Sometimes

Never Infrequently

Often Infrequently Often Never Never

Never Infrequently Sometimes Sometimes Always Often Sometimes

Always Always Always Often Always Often Always Often Often Always Always Always Often Always Always Always Often Always Always Always Always Often Sometimes Sometimes Often

Sometimes Always Always Sometimes Sometimes Sometimes

Sometimes Always Often Often Often Sometimes Sometimes Always Never Often Often Always Often Always Sometimes

Sometimes Infrequently Often

Sometimes Infrequently Sometimes Always Sometimes Infrequently

Sometimes Sometimes Often Sometimes Often Infrequently Never Never Never Often Sometimes Always Often Never Sometimes Always Sometimes Sometimes Sometimes Often Often Often Infrequently Always Always Often Always Often Sometimes Often Always Often Always Often Always Often Sometimes Infrequently Infrequently Often Sometimes


Survey Data 187

49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70

Survey Response

Never Often Often Often Sometimes Infrequently Sometimes Often Always Always

Always Sometimes Sometimes Sometimes Sometimes Always Often Always Always

Infrequently Often Often

Infrequently Infrequently Never Sometimes Infrequently


Sometimes Sometimes Sometimes Never Never

Never Often Sometimes Never Often Sometimes


Often Sometimes Sometimes Always Always Always Always Often Always Always Always Infrequently Often Often Often Always Often Always Always Always Often Always


Sometimes Sometimes Sometimes Sometimes Often Sometimes Never Often Often Infrequently Always Infrequently Often Often Always Never Often Always Sometimes Often Always Always


Infrequently Sometimes Sometimes Never Often Sometimes Infrequently Often Sometimes Infrequently Often Often Often Often Never Never Often Always Infrequently Infrequently Always Always


Often Often Often Infrequently Always Often Often Always Often Sometimes Sometimes Often Often Often Often Sometimes Sometimes Often Sometimes Often Always Always




71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 Never Infrequently Always Sometimes Never Always Sometimes Sometimes Infrequently Often Infrequently Sometimes Infrequently Infrequently Often

Never Infrequently Often Infrequently Never Always Sometimes

Always Always

Never Sometimes Often Sometimes Often

Never Infrequently Infrequently Never Always Always Always Always

Often Infrequently Sometimes Never Always Always Always Always Often Always Often Often Always Always Always Often Always Never Often Always Always Always Always Often Always Often Always Often Always Often Always Always Always Always Always Often Often Always Never Infrequently Often Never Never Always Often Always Often Always Never Always Often Often Always Always Often Never Always Always Often

Often Always Always Often Often Never Infrequently Often Never Never Always Often Always Often Always Always Always Sometimes Sometimes Sometimes Sometimes Often Often Always Always Sometimes Always Always Always Always Often Always Often Always Infrequently Sometimes Always Always Sometimes Always Always Always Often

Often Always Sometimes Always Always Always Sometimes Sometimes


Survey Data 189

97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118

Survey Response

Often Sometimes Sometimes Never Infrequently Infrequently Never Never

Infrequently

Often Sometimes

Often

Never

Often

Infrequently Never

Often

Never

Often Sometimes Never Never


Always


Always Often Always Always Always Always Always Always Always Always Always Infrequently Always Often Always Always Sometimes Always Always Always Always Often


Always Infrequently Always Infrequently Sometimes Infrequently Never Often Never Often

Sometimes Sometimes Always

Often Always Always

Always Infrequently


Never Sometimes

Infrequently Sometimes Always Never

Always Never


Often Infrequently Infrequently Infrequently Sometimes Often Infrequently


Infrequently Often Sometimes Sometimes

Always Often Often Often Often Often Always Often Sometimes

Often Sometimes Sometimes Often

Always Often




119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 Never Infrequently Sometimes Never Often

Often Sometimes Often Sometimes Never Sometimes Always Always Often Always Always Sometimes Infrequently Often

Never Infrequently Infrequently Always

Often

Always Sometimes Often Sometimes Infrequently Always Always Always Always

Always Always Sometimes Sometimes Always

Always Always Always Always Sometimes Often Sometimes Sometimes Always Always Always Always Sometimes Always Often Sometimes Always Always Always Always Often Always Always Always Always Sometimes Always Always Often Sometimes Always Always Always Always Often Always Often Often Always Often Never Often Often Often Often Often Often

Always Always Often Always Often Often Often

Never Often Often Never Sometimes Never Sometimes Sometimes Always Often Sometimes Always Often Infrequently Always Often Always

Never Sometimes Often Always Sometimes Never Sometimes Sometimes Always Often Sometimes Always Often Infrequently Often Infrequently Always


Survey Data 191

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Survey Response

Always Often Often Sometimes Always Sometimes Never Often Often Often Always Infrequently Often Never Always Always Always Often Always Often Often Always

Always Always Always Always Often Always Often Always Often

19. Long–Term Relationships with Suppliers

Always Infrequently Always Always Always Always Never Often Always Infrequently Always Infrequently Always

18. Communication with Customers

Always Always Often Often Always Often Never Often Always Often Always Often Often Always Often Always Always Always Often Always Often Always Often

20. Long–Term Relationships with Customers

Sometimes Sometimes Never Sometimes Sometimes

Always Always Never Sometimes Sometimes Infrequently Often

Sometimes Always Often Often Sometimes Sometimes Infrequently Often Sometimes

Often

Infrequently

22. Reduced Supplier Base

Often Sometimes Never Always Often Sometimes Always Sometimes Sometimes

Never Sometimes Sometimes

21. Procurement Involved in Development

1 30

–15

0 20

20

25

10 50

5 20

22. Percentage Reduction of Supplier Base



24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

Often Always Sometimes Often Infrequently Often Always Always Always Always Sometimes Always Sometimes Often Often Always Always Sometimes Often Often Often Often Infrequently Often Infrequently Infrequently Often Often Often Often Sometimes Often Sometimes Always Sometimes Often Often Often Often Always Always Always Often Always Often Often Often Infrequently Infrequently Often Sometimes Often

Often Always Often Often Sometimes Often Always Always Sometimes Often Infrequently Often Often Often Always Always Often Often Always Always Often Sometimes Always Often Infrequently Infrequently Sometimes Often Often Always Infrequently Infrequently Infrequently Infrequently Often Often Sometimes

Infrequently Always Often Infrequently Often Often Sometimes Always Often Sometimes Always Often Often Infrequently

Infrequently Sometimes Infrequently Often Infrequently

Always Sometimes Infrequently Infrequently

Often Often Infrequently

Sometimes

Often Infrequently Often Often Sometimes Infrequently Sometimes Sometimes Never

100

90 5 10 1 20 5

20 30

20 5 15 10 20 50 5

10


Survey Data 193

50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72

Survey Response

Often Sometimes Always Always Always Sometimes Always Often Always Always Always Sometimes Often Always Often Infrequently Sometimes Sometimes Infrequently Often Always Always Always


Infrequently Often Sometimes Always Often Always Often Always Often Often Never Often Often Always Often Infrequently Often Often Often Often Always Often Always


Often Always Often Infrequently Often Sometimes Infrequently Often Often Often Always

Often Often Often Always Always Always Often Always Always Often Often


Infrequently Infrequently Never Always Always Sometimes Often Often Sometimes Never Sometimes Infrequently Sometimes Always Always Infrequently Often Infrequently Always Always Always Infrequently Infrequently


25 5

20 20

Often Sometimes Sometimes Sometimes

65

0

10 25

40

25 0 0


Often Often

Infrequently Infrequently Never

Infrequently Often Sometimes

Sometimes Never Infrequently Always Always




73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 Sometimes Often Always Always Often Always Often Always Often Always Sometimes Often Always Always Sometimes Often Always Often Often Often Often Sometimes Sometimes Always Often

Always Infrequently Sometimes Always Often Infrequently

Always Often Often Always Always Often Infrequently Always Often Always Often Sometimes Often Always Always Always Sometimes Always Always Always Always Always

Always Often Always Always Often Always Always Often Always Sometimes Infrequently Often Always Always

Often Often Often Always Often Always Never Often Sometimes Always Often Sometimes Sometimes Always Sometimes Sometimes Infrequently Never Sometimes Often Often Always Always Always Always

Infrequently Always Often Always Always Always

Sometimes Often Always Sometimes Always Never Infrequently Often Often Never Sometimes Sometimes Always

Never Sometimes Never Often

Sometimes Always Always Infrequently Never Infrequently

50 25

0 0 10 10 0

10 –10 30 25 10 20 40 10

20 40 25 1 0 5


Survey Data 195

99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118

Survey Response

Sometimes Sometimes Often Infrequently Always Sometimes Often

Always Often Always Often Always Always

Always Sometimes Infrequently Often Infrequently


Often Often Sometimes Often Always Often Sometimes Often Infrequently Often Sometimes Always Sometimes Sometimes Sometimes Often Often Sometimes


Sometimes Sometimes Often Sometimes Often Often Always

Always Often Always Always

Always

Always Often Sometimes Often Often Always Always Always Sometimes Always Sometimes Sometimes Sometimes Never Infrequently Sometimes Often Often Sometimes Never Often

Often Often Often



15

Sometimes

Never Always Often

10 10 0 25 10 –20 30 25

0

10


Often Sometimes Never Sometimes

Sometimes





119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141

Always Always Sometimes Always Infrequently Often Often Often Always Sometimes Sometimes Always Always Often Often Always Always Infrequently Often Always Always Always Often Always Always Often Always Infrequently Often Often Sometimes Always Sometimes Sometimes Always Often Always Sometimes Always Always Sometimes Always Always Always Sometimes Often Always Infrequently Sometimes Sometimes Sometimes Often Always Sometimes Always Always Always Always Always Always Often Always Always Always Always Often

Always Always

Always Sometimes Sometimes Infrequently Always

Always Sometimes Never Infrequently Infrequently Sometimes Always Always Sometimes Often Often Always Infrequently Often Infrequently

Often

Sometimes Infrequently Often Often Often

20 0

Never Infrequently Never Often

15 10 30 40 5

15

0

15 10 0

Often Never Never Never

Never Infrequently


Survey Data 197

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Survey Response

Always Always Never Sometimes Often

Always Often Sometimes Sometimes Infrequently Infrequently Often

Infrequently

23. Reduced Purchased Component Costs

5

30 10

25

10 40

0 10

23. Percentage Reduction of Purchased Component Cost

Always Always Infrequently Sometimes Sometimes

Often Never Sometimes Never Never Sometimes Sometimes

Never

24. Reduced Purchased Service Costs

20 0

0 10

0

5

0 10

24. Percent Reduction of Purchased Service Cost

Always Sometimes Infrequently Sometimes Often

Never Infrequently Infrequently

Sometimes Sometimes Sometimes

Never

25. Reduced Supply-Chain Management Costs

15 0

0 20

5 5

30

0 5

25. Percentage Reduction of Supply-Chain Management Costs



22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Often Sometimes

Always Often Often Often Sometimes Sometimes Often Sometimes Infrequently Infrequently

Often Often Often Infrequently Often Always Always Often Sometimes Always Always

20 20 5 10 3 0

10 20

20 15

40 5 5 10

50 40 5

20 10 25 4 5

Sometimes Infrequently Sometimes Infrequently Infrequently Often Sometimes

Never Often Often Sometimes

20 10 0

Often Always Sometimes Often Never Infrequently Often 10 20 0 90 20

30 70 5

Often Always Sometimes


Always Often Never Never

Always Often Sometimes

Often

Never

Often Always Never Often Never

Often Often Often

75 30 0 0 30

20 30

5 20 20

10 –5 0

40 50 5


Survey Data 199

48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68

Survey Response

0

90

40

Often Sometimes

Always

20 15

35

0 20 0

30


Never

Infrequently

Sometimes Sometimes Often

Often Infrequently Infrequently Sometimes Infrequently Always Always


Often Sometimes Sometimes Always

Infrequently Never Never

Infrequently Sometimes Often

Sometimes Infrequently Infrequently Never Infrequently Always Often


10 40

60

0

10 10

25

0 0 0

20


Sometimes Sometimes Infrequently Often

Infrequently

Infrequently

Often Infrequently Often

Infrequently Infrequently Sometimes Never Sometimes Always Often


30

30

10

40 5

27

10 0 10

30




69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94

Infrequently Often Always Sometimes Always Often Often Often Often Never

Never Always Often Often

Often Sometimes Sometimes Infrequently Always Always Sometimes Sometimes Infrequently

15 10 10 3 0

25 5 15 10 5 20 15 10

10 5

10 5 5 10 4

Infrequently Often Infrequently Sometimes Always Often Often Often Sometimes Infrequently

Never Always Sometimes Often

Sometimes Sometimes Always Always Sometimes Infrequently Infrequently

Always

20 10 10 1 5

20 10 15 0 5 0 –100 5

5 10

10 25 20 4

Never Sometimes Always Sometimes Always Never Sometimes Often Often Never

Never Never Sometimes Often

Always Sometimes Infrequently Infrequently Never Infrequently Sometimes Infrequently Sometimes

0 20 10 5 0

30 0 20 80 10

0 5

5 20

10 2 10 0 0


Survey Data 201

95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115

Survey Response

Infrequently Always

Sometimes Often Sometimes Never Never

Sometimes


Infrequently Sometimes Always


5 5 20 0 10 0 25

10

10

30 6


Often Infrequently

Sometimes Never Infrequently Never Sometimes

Sometimes

Often Often Often



Never

25 10 15 0



Sometimes

Sometimes Often Often

Sometimes Often Always


0 5

0

80

30 1


15

0 5

0

10

30

30 0




116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141

Sometimes Always Always Always

Infrequently Infrequently Often Always Often

20 15 5

Often Never Often Sometimes

5 5 5 15 15

15

10 20 0 5 10

Sometimes Sometimes Often Always

Sometimes


Often Never Sometimes Sometimes

10

10 20

100

–10 20 0 10 10

Sometimes Sometimes Often Never Often

Never Infrequently Never Often

Often Never Infrequently Infrequently

Often Sometimes

5

5

Sometimes Sometimes Sometimes Sometimes

Often

25

Often

0 10

10 20

0 40

15

8 10 0

15

25


Survey Data 203

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Survey Response

Always Often Never Often Often

50 10

Often Often Sometimes Sometimes

20

0 10

10

15

Often Sometimes

Never

26. Reduced Total Cost of Quality Costs

26. Percentage Reduction in Total Cost of Quality Costs

Never Sometimes Sometimes

Always

Sometimes Sometimes Infrequently Sometimes

Sometimes Sometimes

Never

27. Reduced Customer Management Costs

–5

20 20

25

5 50

10

27. Percentage Reduction in Customer Management Costs

Always Always Always Sometimes Infrequently


Often Infrequently Sometimes

Sometimes

Often

28. Increased Long-Term Supplier Relationships

25 –5

0 20

25 25

20 5 5

10

28. Percentage Increase of LongTerm Supplier Relationships



22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Often Always Sometimes Infrequently Often Always Always Infrequently Sometimes Never Infrequently Infrequently

Always Infrequently Often Never

Sometimes Always Infrequently Always


0

30 30 35 75 3

25

20 6 5 1 0 30 0

5 10 2


Infrequently Infrequently Sometimes Never Never Infrequently

Never Sometimes Never Often Often Often

Sometimes Always Infrequently Always

Never Sometimes Infrequently

20 10 15 0 0

15

10 1 2 0 –5 50 0

0 10 2

0 15 25 2 5


5 30

10

0 15 0 5

5 30 5

Infrequently Often Sometimes Infrequently

Infrequently Often Always

Always Sometimes Sometimes Often

Sometimes Always Infrequently Often



Survey Data 205

48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68

Survey Response

Sometimes Sometimes Often Always

Sometimes Sometimes Sometimes

Often Never Sometimes

Sometimes Infrequently Sometimes Sometimes Infrequently Often Often


Never

Sometimes Often

35 20 20

Infrequently

Infrequently

Never Infrequently Sometimes

Infrequently Sometimes Sometimes Never Never Often Often


20

20 0

25

10 20 10

10


–10

20

10

0 10

15

10 0 0

0


Often

Sometimes Sometimes

Never Often

Infrequently Never Infrequently Infrequently Sometimes Always Sometimes Always Sometimes Often Often


20

35

70 30

20 40

10

10 5 5

0




69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94

Never Sometimes Always Often Often Often Never Often Always Never

Never Always Never Often

Infrequently Sometimes Often Always Often Often Sometimes

Often Always

20 0 10 15 0

65 25

15 0 15 5 0

10 20

2 25 15 5

Never Often Never Often Infrequently Infrequently Never Often Never Never

Never Sometimes Sometimes Often

Never Infrequently Never Always Never Often Never

Often Always

10 0 10 0 0

–20 15

10 0 10 0 0

10 –25

0 10 0 5

Never Often Never Sometimes Often Sometimes Infrequently Often Often Infrequently

Sometimes Never Sometimes Often

Infrequently Infrequently Never Always Always Often Sometimes

Often

10 0 10 15 10 0 25 50 5 25 30 0 20 5 30

10 20

10 5 0 50

20


Survey Data 207

95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115

Survey Response

Never Infrequently

Infrequently Often Infrequently Never Always

Always

Sometimes Sometimes Always Often



0 50 10 0 0

15

0

50

30 0


Never Infrequently

Never

Sometimes Sometimes Infrequently

Always

Sometimes Sometimes Always Often



0 5 –10 5

0

0

20

20 0


Never Sometimes

Sometimes Never Infrequently Often Never

Sometimes

Never Often Often Infrequently

Always Often Always


0 5 50 0 10 0 2

0

20 10




116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141

Never Often Often Sometimes Often

Sometimes Sometimes

Sometimes Sometimes Never Often

Often Never Infrequently

Often Often Sometimes Often

0 3

0 20

25

0

2 10 0

15

Never Infrequently Sometimes Sometimes Infrequently

Often

Sometimes Infrequently Never Sometimes

Often Never Never Never


0

0 5

15

–10

5 10 0

0

Often Infrequently Sometimes Often Often

Often Sometimes

Always Sometimes Often Never Infrequently Sometimes

Often Never Often Infrequently

Sometimes Sometimes Sometimes Always

45 5 5 20 10

15

20 5

4 20 0 10 5

15


Survey Data 209

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Survey Response

Always Always Always Often Often Sometimes

25 25

Always Often Infrequently Often

10

50 10

15 10

20 20 300

10

29. Percentage Increase of LongTerm Customer Relationships

Often Always Often

Sometimes

Always

29. Increased Long-Term Customer Relationships

Always Always Always Often Sometimes Sometimes

Never Often Infrequently Sometimes

Often Sometimes Always

Sometimes

Often

30. Increased Standardization of Offerings

5

25 5

0 20

0 70

25 5

0

30. Percentage Increase in Standardization of Offerings

Always Always Always Often Often Infrequently

Never Often Often Sometimes

Often Never Always

Never

31. Increased Standardization of Component Set

10

25 10

60 0

0 80

15 0

15

31. Percentage Increase in Standardization of Component Set



23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Infrequently Sometimes Infrequently Never

Often Often Always Infrequently Often Often Always Infrequently

Always Infrequently Often Never

Often Always Infrequently Often

Infrequently Often

0

5

30 50 5 75 3

5

0

5 5 100 –10

20 15

Infrequently Sometimes Infrequently

Infrequently Infrequently Never Never

Never Never Often Never Often Never Sometimes Often

Often Infrequently Infrequently Often

Often Sometimes

0

0 3 0 0

25 10

0

0

20 10

25

Sometimes Sometimes Infrequently Never

Sometimes Often Never Sometimes

Always Sometimes Often Often Often Often Often

Often Infrequently Sometimes Often

Always Often

0

20

20 20 0 10

15 10

20

10 25 25 5

70 25


Survey Data 211

49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70

Survey Response

5 50

Sometimes

Often

30

70

20 30

25

20 10 25


Sometimes Sometimes

Never Often

Never Often Infrequently Often Always Often Always Sometimes Often Always


Sometimes Often Sometimes Infrequently Often Sometimes

Infrequently Often

Often Infrequently Never Often Often Always Often Never Infrequently Often


50

35

70 30

0 20

30

10 0 25


Sometimes Often Often Always Often Often


Often Sometimes Often

Often Infrequently Never Always Always Often


50 60

20

50 0

40 30

25

10 0 50




71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96

Never Often Always Never Always Sometimes Never Often Often Infrequently Always Often

10 0 15 15 15 0 20 50 0 50 10 0 20 5 30

10 20

Often Often Sometimes

Sometimes Never Sometimes Often

15 15 20

Sometimes Sometimes Often

Never Sometimes Never Infrequently Often Often Never Often Always Never Never Sometimes

Often Never Often

Sometimes Never Never Never Never Always Often

20 –15 25 40 0 50 0 0 25 30 0 30 10 0

10

0 0

10 0

Never Often Never Sometimes Sometimes Often Always Often Sometimes Infrequently Sometimes Often

Always Never Often

Sometimes Never Sometimes Infrequently Infrequently Infrequently Often

40 –15 25 10 0 70 0 5 25 62 100 30 2 10

10

10 0 15 0 20


Survey Data 213

97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116

Survey Response

Always Infrequently Often

Sometimes

Sometimes Never Sometimes 15 5 25 0

0 10

10

Never Infrequently Often

Often Never Sometimes Often Often

Sometimes Always

Sometimes Often

Often


Often Sometimes Sometimes Often Sometimes

0 10


Often Sometimes Often Always Often

Sometimes


0 5 20 10 10 –10 0

20

50

25 5


Never Infrequently Often

Sometimes Never Infrequently Often Infrequently

Infrequently

Never Sometimes Often Sometimes

Often


20 0 10 –10 0

0

0

20

25 5




117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141

Often Infrequently Often Always Often

Always Always

Always Sometimes Often Often Often Often

Often Never Sometimes Infrequently

Often Sometimes Always Always

30 30

50 5

50

20 20

2 8 20 0 15 5

10

Often Always Often Never Often

Often Often

Always Often Infrequently Never Never Often

Often Never Often Infrequently

Often Infrequently Always

60 50 15 0 30

0

–25

20 10 0 5 5

10

Often Often Infrequently Never Infrequently

Often Often

Always Always Infrequently Never Never Often

Infrequently Often

Often

Often Infrequently Always

0 10

60 50

20

–25

15

2 10 30

5


Survey Data 215



Index A Acceleration principle, ix, 14–15 Accountability, 6 Activity-based costing (ABC), vii, ix, 1, 59, 60 complaints about, 66–67 expense of implementing, 2 long-term focus of, 63 model of, 2 relative accuracy of, 61 steps in, 61 U.S. Marines use of, 71 Activity-based management (ABM), vii, 3, 64 application and cost reductions, 69, 154 and component set standardization, 129–132 and frequency of communication with suppliers, 106–109, 110 game theory and, 74–75 hypothetical model, 70–74 importance of partnerships to, x integration with TCO, ix limiting common component selection through, 73, 128–132 literature review, 56–67 and long-term supplier relationships, 109–114 process model with integrated TCO, 55, 67–70

and procurement involvement in design process, 129 and reduced supplier base, 114–120 reducing TCO and procured components through, 89–97 and TCO, ix, 1 and total quality costs, 132–138 vs. traditional cost accounting, viii Activity frequency, measurement of, 82 Activity identification process, 61 Activity resources, 61 Administrative costs, 148 frequency of cost reductions, 123 game theory matrix of cost advantage, 149, 151 mean reported percent reduction based on frequency of supply base reductions, 124 reduction with reduced supply base, 120–128 of supply-chain management, 72 Advanced manufacturing systems (AMS), 63 Aerospace industry, survey of, 79 Aggregate decreased production cost, due to learning curve impact, 23 Analysis methodology, 79 hypothesis testing, 89–140 Automatic decisions, avoiding, 64 Automation, in business processes, 40 Automotive industry, 6 survey of, 79 Avoidable cost components, 56

217



B Baby boomers, and upcoming labor shortages, 38 Back office jobs, offshoring opportunities, 37 Balanced scorecard (BSC), ix, 1, 2, 4, 65 categories of, 5 feeding ABM data and results into, 69 requirement for more accurate TCO data, 153 Batch activities, 63 Beer Game, 14 Benchmarking, 2, 3 Benefits, savings through offshoring, 43 Best Buy DuPont financial analysis, 50–52 offshoring practices, 36 Best practices, 3 Bias, in survey results, 155 Bottlenecks, 62 inevitability of, 32 Box plots component set standardization and ABM usage, 134 percent reduction in administrative costs based on frequency of supply base reduction, 126 percent reduction in supply base based on ABM usage, 121 percent reduction of procured component cost based on ABM usage, 95 percent reduction of procured services cost based on ABM usage, 101 total quality costs reductions based on frequency of ABM usage, 139 Brain drain, 37 Buffer stocks, 27 Bureau of Labor Statistics, employment projections, 41 Business environment, as evaluation metric for offshoring, 47 Business process outsourcing (BPO), 37 Buyer passivity/proactivity, 18

C Capacity variables, 30

Case studies, offshoring knowledge work, 48–52 Channel efficiency, 7 Chi-squared probability, 117 China, computer science and college graduates in, 42 College graduates, international comparisons, 42 Commitment, and successful partnership alliances, 19 Common component selection, limiting through ABM, 73, 128–132 Communication, and successful partnership alliances, 19 Communication frequency, 71, 153 with suppliers, 106–109 Communications responsiveness, 58 Company age, and benefits from learning curves, 26 Company size, and supply-chain administration cost advantage, 151 Competition, engendering through outsourcing, 45 Competitive advantage as corporate goal, 153 with cost analysis and management, 1 factors ensuring, 55 no effect by use of TLCC, 154 strategies for enhancing, 7 strengthening through TCO evaluation, 74 and total life-cycle cost, 140, 142 Component set standardization, 130–132 based on frequency of ABM usage, 134 frequency of increases and ABM usage, 131 percent increase based on frequency of ABM usage, 131 Computer science graduates, international comparisons, 42 Continuous improvement, 3, 4 Contract manufacturers, as survey respondents, 80 Corporate models, changes in, 41 Cost accounting, traditional vs. ABM, viii Cost-based supplier performance evaluation system, 56, 58 Cost control, through outsourcing, 42 Cost driver rates, reducing, 59 Cost drivers, 61, 62


Index 219 Cost Cost Cost Cost Cost

focus, six stages of, 7 functions estimation, 59 measurement systems, 66 objectives, 2 of ownership, 56, 57. See also Total cost of ownership (TCO) Cost pools, 61, 62 Costing methods, 59 Costly activities eliminating, 59 redesigning, 64 Creative swiping, 3 Critical materials/resources, worldwide allocation of, 18 Customer contact jobs benefits of offshoring, 43 offshoring opportunities, 37 Customer dissatisfaction ratings, 73 Customer relationships, reducing costs of managing, 86, 87 Customer responsiveness, 7 Customer satisfaction, 4 measures of, 65 Cycle times, 30, 63 balancing in production lines, 27–28

D Data analysis, 83–88 Data center services, offshoring of, 37 Data sharing, willingness, 58 Davenport, Thomas, 4 Dedicated suppliers, 16 Degrees of freedom, 117 Delayed information, 14 Delivery failure costs, 57 Dependability, as competitive advantage, 55 Descriptive statistics administrative costs reductions at varying frequencies of supply base reduction, 127 component set standardization and frequency of ABM application, 135 percent reduction in supply base by ABM application, 122

percent reduction of procured component costs by ABM application, 96 percent reduction of procured services costs by ABM application, 102 total quality cost reductions and ABM usage, 141 Design and development, 68 application of IBM and procurement involvement in, 73 as prime target for ABM, 72 procurement role in, 85, 128, 129 Direct labor, as share of product cost, 60 Direct savings, ix through offshoring, 35 Distorted demand data, 14 Dominant game strategies, 74–75 DuPont financial analysis model, ix Best Buy, 50–52 return on net work (RONW), 36 Staples case study, 48–50

E Economic unrest, 46 Economies of scale, vs. learning, 26 Electronics industry, 6 survey of, 80 Elemental capacity, and learning curves, 32 Elemental task learning curves, ix and line balance, 28–32 in production line, 23 Employed populations, by country, 39 Employee numbers, of survey respondents, 80 Employment projections, 41 English-language skills, and offshoring opportunities, 38 Enterprise value-added costs of sales, 7 Equilibrium point, 28 Errors, cost of, 66 European labor costs, 42 Experience, role in lower cost and production speed, 24 External cost analysis activities, 67, 68–69, 84, 86 Externally contracted services, cost reductions for, 87



F

I

Facility-sustaining activities, 63 Fiber-optic cables, role in offshoring trend, 38 Field failures, 73 Financial-based decisions, 64 Financial performance measures, 65 Financial structure, as evaluation metric for offshoring, 47 First-stage allocation, 62 Flexibility, 63 as competitive advantage, 55 Forester’s Effect, 14 Frequency data, survey results, 84–86 Frequency of communication, 71 affect on customer ability to apply ABM, 72 Functional cost minimization, 7

IBM, xiii India computer science and college graduates in, 42 offshoring of knowledge work to, 35 Indirect savings, ix through offshoring, 35 Industrial surveys, 79–80 Industry profile, of survey respondents, 81–82 Information flows, 14 Information gathering, 67–68 Information sharing. See also Data sharing ABM application by frequency of willingness, 104 and customer ability to apply ABM to procured components and services, 103–106 with customers, 105 effect of willingness on customer ability to apply ABM, 72 frequency of, 103 willingness, 71 Infrastructure, as factor in offshoring decisions, 46 Innovation as competitive advantage, 55 measures of, 65 Intangibles, ABC measures of, 63 Interenterprise value-added cost, 7 Internal cost analysis activities, 67 Internal processes, 4 costing with ABC systems, 84 crosstabular count of reduced supplier base and ABM application to, 115 measures of, 65 Internet use, by country, 39 Inventory reduction syndrome, 14–15

G GAAP accounting measures, 67 Game theory analysis, vii, viii, x, 74–75, 145–151 matrix cost advantage analysis, 150 GDP per capita, by country, 39 Global Crossing, 38 Group technology (GT)-based cost estimation, 59

H Hammer, Michael, 4 Heavy machinery industry, survey of, 80 Holding costs, 57 Home construction and furnishings, survey of, 80 Hypothesis testing procured components cost reduction with ABM usage, 89–97 procured services cost reduction with ABM use, 97–103 results summary, 143–145 Hypothetical models, TCO with ABM, 70–74

J Just-in-time systems, learning curve theory and, 24


Index 221

K

M

Knowledge work, 37 benefits of offshoring, 42–44 drawbacks and risks of offshoring, 45–46 drivers for offshoring, 37–42 economic implications of offshoring, 44–45 increasing shareholder value by offshoring, 35–36 offshore locations for, 46–48 offshoring case study, 48–52 offshoring of, ix, viii, 35–36 opportunities for offshoring, 37 Kumar, Sameer, xiii

Maintenance and repair operations (MRO), 68 Management accounting, decline in, 60 Manufacturers, as service providers, 6 Manufacturing environment, influencing, 14–15 Manufacturing expense, purchasing as percentage of, 8 Manufacturing sector, job loss in, 36 Margin potential, 13 Market maturity, 16 Material flows, 14 Measurement, cost of, 66 Medical device industry, survey of, 79 Methodology for analysis, 79 Military, survey of, 80 Mobile telephone use, by country, 39 Morgenstern, Oskar, 74

L Labor costs, international comparisons, 44 Labor shortages, as driver of offshoring, 38 Lead time syndrome, 14–15, 15 Learning and growth activities, 4 Learning curves, ix, 23, 24–27. See also Elemental task learning curves as capacity variable, 30 and elemental capacity, 32 elemental task, ix multiple elemental tasks with, 29 rate of learning, 25 recommendations, 33–34 vs. economies of scale, 26 Life-cycle costing (LCC), 57 Line balance, 23 and elemental task learning curves, 28–32 objectives gained from, 27 Line design, 31, 32 Literacy rates, 38 Logistics, 68 Long-term supplier relationships, 71 and customer’s ability to apply ABM, 109–114 frequency of entering into, 111–112 increased, 86, 88 Lowest delivered cost, 7 Lowest end-user delivered supply-chain cost, 7 Lowest-price pressure, 16

N Net new job growth, 44, 45 Neumann, John Von, 74 Neural network cost estimation, 59 Non-value-added activities, 3 eliminating, 64 Nondisclosure agreements, 85

O Occurrence rates, reducing, 59 OEM manufacturers, as survey respondents, 80 Offfshore locations, 46–48 top 20 countries for, 47 Offfshoring opportunities, by job type, 37 Offshore Location Attractiveness Index, 46–47 Offshoring. See also Outsourcing business benefits of, 42–44 drivers for knowledge work, 37–42 economic implications, 44–45 evaluation metrics for, 47 of knowledge work, viii number of U.S. jobs affected by, 36 rationales for, 42, 43


222 Supply Chain Cost Control Using Activity-Based Management Operational indicators, in balanced scorecard measures, 65 Organizational learning, 24, 32–33 Outsourcing defined, 6 of knowledge work, 35–36 as predominant practice, vii rationales for, 42–43 reasons for, 6 Overheads, as share of product costs, 60

P Part defect counts, 73 Partnerships, 153 dependence of world-class supply chains on development of, 71 elements of successful, 19 importance in applying ABM principles, x Payoff matrix, game theory, 75 People skills, as evaluation metric for offshoring, 47 Performance measures, traditional and SCM, 21 Plan, Do, Check, Act, 4 Pool rates, 61 Population growth, by country, 39 Predistribution screening, 155 Process improvement, 2, 3 Process mapping, 61 by U.S. Marines, 71 Process models, TCO with ABM, 67–70 Process-oriented philosophies, 65 Process performance, 5 Process reengineering, 2, 3–4 Procured components contribution to overall cost, 56 cost reduction through ABM, 89–97 and frequency of communications with suppliers, 107 frequency of cost reductions, 92 game theory matrix and cost advantage, 147 and long-term relationships with suppliers, 112–114 mean reported percent reduction based on ABM usage, 92, 93 percentage cost reductions, 93

Procured services and component set standardization, 135 cost advantage in game theory matrix, 148 cost reduction with ABM usage, 97–103 and frequency of communications with suppliers, 108–109 frequency of cost reductions by frequency of ABM usage, 98 percent cost reduction based on frequency of ABM usage, 99 and willingness to share information with suppliers, 105 Procurement involvement in design and development, 73, 85, 128 results of ABM application to, 154 Procurement organizations, critical role of, 8 Product diversity, 66 Product life-cycle costs (PLCC), 56, 57 Product offerings, standardization of, 88 Product-sustaining activities, 63 Production costs impact of experience on, 24 reductions with line balance, 27 Production line balancing cycle times in, 27–28 elemental task learning curves in, 23 learning curves in, 25 Profit margin, Best Buy vs. Staples, 52 Public accounting, legally mandated, 67 Purchased components crosstabular count of reduced costs and ABM application, 91 reduced overall costs of, 85, 87 side-by-side survey respondents comparison, 90 Purchasing, 68 critical role in supply chain, 8 Purchasing costs, 57 Purchasing excellence, vs. supply-chain management, 17

Q Quality as competitive advantage, 55


Index 223 costs of poor, 57 reducing total cost of, 87 Quality/engineering, 68

R Rate of learning, 25 Redundant activities, 64 eliminating through ABM, 72 Repetitive tasks, and production speed, 24 Research and development, offshoring opportunities for, 37 Residuals, 116–117 Resources assigning to cost objectives, 2 as focus in second-wave ABC, 63 Responsiveness, 58 Return on Assets, Best Buy vs. Staples, 52 Return on Net Worth (RONW), 36 Staples vs. Best Buy, 48, 52 Revenue, of survey respondents, 80 Reverse marketing, 18 Risks, of offshoring knowledge work, 45–46 Rock-Paper-Scissors Game, 75

S Saddle points, 148 Safety stock syndrome, 15 Scrap costs, 73 Second-stage allocation, 62 Second-wave ABC, 63 Security breaches, 45 through offshoring of knowledge work, 37 Sensitive information frequency data, 85 willingness to share, 71 Service offerings, standardization of, 88 Service sector, job losses in, 36 Shareholder value increasing by offshoring knowledge work, 35–36 and offshoring knowledge work, ix, viii Short, J.E., 4 Simplified breakdown cost estimation, 59 Six Sigma, 2, 5

Small companies, product performance advantages and, 16 Software developers, offshoring of, 37 Software engineers, offshoring of, 37 Staff departments, destruction of, 66 Staples DuPont financial analysis, 48–50 offshoring practices, 36 Statistical analysis, 4 Statistical process control (SPC), 64 determining normal variance with, 65 Stem-and-leaf plots component standardization and frequency of ABM usage, 133 percent reduction in supply base based on ABM usage, 119 percent reduction in supply base based on frequency of supply base reduction, 125 percent reduction in total quality costs based on ABM usage, 138 percent reduction of procured component cost based on ABM usage, 94 percent reduction of procured services cost based on ABM usage, 100 Stop ships, 73 Supplier-customer relationships, increasing complexity of, 17 Supplier dependencies, 154 Supplier management reducing administrative costs of, 72 as target of outsourcing, 6 Supplier numbers, reduction by ABM application, 72, 87 Supplier-owned technology, access to, 6 Suppliers, dedicated, 16 Supply base frequency of reduction by frequency of ABM usage, 116 percent reduction of, 118, 121 and reduction in administrative costs, 120–128 and use of ABM, 114–120 Supply-chain cost evaluation, vii Supply-chain innovations history of, 12 trends in, ix, 11–13 Supply-chain management performance measures, 21 vs. purchasing excellence, 17


224 Supply Chain Cost Control Using Activity-Based Management Supply-chain structure, 15–22 Supply chains, 7 extending TCO into, viii world-class, 71 Survey bias, 155 Survey construct, 79–83 flaws in, 155 Survey respondents company profile of, 80 industry profile of, 81–82 Survey results frequency data, 84–86 percentage data, 86–87

T Technical skills, need for workers with, 40 Telephone use, by country, 39 Theory of constraints, 32, 62 Theory of Games and Economic Behavior, 74 Throughput time, 27 Time-to-market goals, 18 benefits of offshoring, 43–44 Total cost of ownership (TCO), vii, viii, 7 and ABM, ix, 1 disappointing implementation, 58 extending to supply chain, viii game theory and, 74–75 hypothetical model, 70–74, 146 integrated with ABM process model, ix, 55 literature analysis, 56–67 process models, 67–70 purchase price share of, 56 reducing through ABM, 89–97 Total life-cycle cost, 85 and competitive advantage, 140, 142 strengthening competitive advantage through management of, 74 Total quality costs and ABM application, 132–140 and advantage with game theory matrix, 149 frequency of reductions, 136

percent reduction based on frequency of ABM usage, 137 reducing by ABM application, 74 Total Quality Management (TQM), 2, 4, 65 Traditional cost estimation, 59 distortion by, 60 ineffectual nature of, 60 Trust, and successful partnership alliances, 19

U Unavoidable cost components, 56 Unemployment rate, by country, 39 University of St. Thomas, xiii U.S. Department of Defense (DOD), use of TCO by, 56

V Value, defined, 19–20 Value-added activities, 3 Value web management (VWM), 16 Value webs, 16 Virtual supply chains, 15–16 vs. rigid supply chains, 16–17

W Warranty costs, 73 Win-win scenarios, supplier-customer, 20 Working age population, U.S. decline in, 40 Workstation numbers, 27–28 World-class customers, 21 World labor force, 42

Z Zander, Matthew, xii Zero base pricing (ZBP), 56 Zero-sum game matrix, 146

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