Strategic Decision Making Preface

This web page contains the preface from Strategic Decision Making. The bibliographic citation for this book is Craig W. Kirkwood, Strategic Decision Making: Multiobjective Decision Analysis with Spreadsheets, Duxbury Press, Belmont, CA, 1997, ISBN 0-534-51692-0.
This book presents methods for strategically making decisions using quantitative, spreadsheet-based, decision analysis methods. The intended audience is anyone responsible for decision making in an organizational setting, and the book provides a framework for thinking about decisions strategically, as well as practical tools that the reader can immediately apply. The book is suitable for use in classes on decision making, as well as for self-study.

Rules of thumb, intuition, tradition, and simple financial analysis are often no longer sufficient for addressing such common decisions as make-versus-buy, facility site selection, and process redesign. In general, the forces of competition are imposing a need for more effective decision making at all levels in organizations. The ongoing restructuring of businesses and other organizations increases the usefulness of the material in this book for a wide range of managers, analysts, and engineers. Traditionally, strategic decisions involving multiple competing objectives and significant uncertainties have been considered primarily the concern of top executives. However, with the current emphasis on downsizing and flattening organizations, individuals at lower levels in organizations must be concerned with such tradeoffs as cost versus quality, cost versus timeliness, or market share versus short-term return on investment.

The methods in this book have been applied for over twenty-five years, and they have a demonstrated capability to improve decision making. The methods have traditionally been considered advanced, in part because early presentations were framed in a mathematical terminology that is not familiar to many managers, and in part because early implementations of the methods required specialized software. This book brings the methods to a broader audience by explaining the intuitive basis for the methods, as well as how to implement them using spreadsheets.


I wrote this book to make strategic decision making methods accessible for those who are making the decisions. The approaches in this book can help you to improve your decision making processes. The decision structuring methods in the first three chapters provide a framework for thinking about virtually all decisions ranging from those that are relatively tactical to corporate strategy. Numerous examples are included to give you a starting point for your own decision analyses. Later chapters of the book present detailed procedures for quantitatively analyzing decisions using spreadsheets. The methods are based on intuitively appealing principles, which are discussed as the methods are presented. There are no mysterious procedures. You can understand, implement, and explain these methods without the need for specialized consultants or software.

Focus and approach:

The focus is on decisions where there are multiple competing objectives that require consideration of tradeoffs among these objectives. This book brings the tools to analyze these decisions to a wider range of decision makers through the use of spreadsheet methods. The approach is to provide a structured, quantitative process for making such decisions by using spreadsheet analysis methods. We take the view that decisions should be made strategically, that is, in a skillful manner that is adapted to the ends that the decision maker wishes to achieve. While there is probably little argument that such an approach is desirable, the methods to actually carry out this type of analysis have often been considered beyond the resources of managers below the top level in large organizations.

Audience and prerequisites:

The only prerequisite for much of the book is an understanding of elementary algebra. The sections that consider computer-based computational procedures also require an elementary understanding of electronic spreadsheets. Microsoft Excel, Version 5.0 or later, is used in the book, including some use of Visual Basic, Applications Edition, which was first included with Excel in Version 5.0. However, the reader does not need to be familiar with Visual Basic or to learn anything about that programming language to apply the methods.

Classes using the material in this book have included students in business administration, engineering, health policy and administration, and public policy. Most of these students have had practical experience in business, government, or the not-for-profit sector. The quantitative and computer backgrounds of the students in each class have generally varied substantially.


The book can be used in a variety of ways for either class instruction or self-study. It is self-contained and can be used for a first course in decision making which focuses on decisions with multiple objectives. It can be used in conjunction with a text such as Robert T. Clemen's Making Hard Decisions: An Introduction to Decision Analysis, Second Edition, Duxbury Press, Belmont, California, 1996, in a first decision analysis course which places less emphasis on decisions with multiple objectives. It can also be used as the text for a course in multiobjective decision analysis which follows a traditional first decision analysis course.

An instructor's manual is available with solutions to the exercises.

Chapters 1, 2, and 3 address decision problem structuring (formulating). Chapter 4 addresses evaluation of alternatives with multiple objectives and no uncertainty. Chapters 5, 6, and 7 address evaluation of alternatives with uncertainty. Chapter 8 reviews procedures for analyzing resource allocation decisions with multiple objectives in the face of budget or other constraints. Chapter 9 presents theory that underlies the methods in earlier chapters. You do not have to understand this chapter to make practical use of the methods in the earlier chapters.

The appendices provide supplemental and background material. Appendix A presents a case that illustrates the application of the methods in Chapters 2, 3, and 4. Appendix B presents scenario planning approaches to analyzing decisions with uncertainty. These approaches can be used in conjunction with, or as an alternative to, the probability analysis methods in Chapters 5, 6, and 7. Appendix C presents a transcript of a probability elicitation session with a senior executive. Appendix D presents basic concepts of conditional probabilities, including use of influence diagrams and decision trees.

Chapter 9 is more abstract and requires somewhat more technical background than the other chapters and appendices. It can be assigned as optional reading or used as the primary reading for a more theoretical course. The material in Chapter 8 has also traditionally been considered more advanced, but with the current general availability of spreadsheet optimization features, these methods are now more widely used.

The latter parts of Chapters 4, 6, and 7, as well as Chapter 8, make use of electronic spreadsheets, and readers studying this material need to be familiar with elementary spreadsheet concepts. Some specific features of Excel, Version 5.0 or later, are used, although the approaches can be translated to other advanced spreadsheets. The Appendix A case study does not specifically require spreadsheet computations, but the calculations needed to complete the case will be tedious without a spreadsheet. A reader wishing to understand the methods presented in this book but not how to implement them can skip the spreadsheet material without loss of continuity. Some readers may wish to use specialized multiobjective decision analysis software, and an appropriate package is Logical Decisions for Windows, available from Logical Decisions, 1014 Wood Lily Drive, Golden, Colorado 80401.

All chapters include both Review Questions and Exercises. While either of these can be assigned as homework, the review questions are more open-ended and sometimes do not have a unique answer. Thus, these questions may be more suitable for in-class review purposes.

The diagram following this preface shows the primary precedence relationships among the chapters and appendices. In addition, Section 8.4 requires background provided in Section 7.7.

For readers who are familiar with multiobjective decision analysis methods, note that this book uses multiattribute value and utility analysis methods, including probabilistic analysis of decisions with uncertainty. A measurable value approach is taken, although an instructor who is so inclined can easily take a more traditional approach.


Special thanks to Curt Hinrichs at Duxbury Press for supporting this project. Thanks are also due to Donald L. Keefer and Jeffrey S. Stonebraker for many helpful comments on drafts of much of the book, and to Nancy A. Houston for reviewing several chapters. James L. Corner also provided helpful comments. I~owe a substantial debt to the reviewers, whose comments helped me greatly improve the quality of the book. These include Richard H. Bernhard, North Carolina State University; Alan J. Brothers, Battelle, Pacific Northwest Laboratories; Robert T. Clemen, Duke University; L. Robin Keller, University of California, Irvine; Don N. Kleinmuntz, University of Illinois at Urbana-Champaign; Abu S. M. Masud, Wichita State University; H. V. Ravinder, University of New Mexico; Rakesh K. Sarin, University of California, Los Angeles; James E. Smith, Duke University; Donald N. Stengel, California State University, Fresno; L. James Valverde A., Jr., Massachusetts Institute of Technology; James N. Vedder, Syracuse University; and Robert L. Winkler, Duke University. I also wish to thank Ruth Cottrell for patiently guiding me through the preparation of this book and Charles Cox for correcting my sometimes fractured grammar. Thanks also to Lura Harrison for catching some longstanding errors. This book was typeset by the author using PCTeX for Windows.

Please write, phone, or e-mail me if you have questions, corrections, or ideas for improvements to this book.

Craig W. Kirkwood (602-965-6354; e-mail
Department of Management
Arizona State University
Tempe, AZ 85287-4006

Quick Contents

  1. Making Decisions Strategically
  2. Structuring Objectives
  3. Developing Alternatives
  4. Multiobjective Value Analysis
  5. Thinking About Uncertainty
  6. Decisions with Uncertainty
  7. Multiple Objectives and Uncertainty
  8. Resource Allocation
  9. Multiattribute Preference Theory
  1. Case: Computer Networking Strategy
  2. Scenario Planning for Decision Making
  3. Probability Elicitation Interview
  4. Interdependent Uncertainties

Precedence Diagram

Return to ASU decision analysis resources page.

Last August 25, 2008.