This web page contains the preface from

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.

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.

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.

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 craig.kirkwood@asu.edu)

Department of Management

Arizona State University

Tempe, AZ 85287-4006

- Making Decisions Strategically
- Structuring Objectives
- Developing Alternatives
- Multiobjective Value Analysis
- Thinking About Uncertainty
- Decisions with Uncertainty
- Multiple Objectives and Uncertainty
- Resource Allocation
- Multiattribute Preference Theory

- Case: Computer Networking Strategy
- Scenario Planning for Decision Making
- Probability Elicitation Interview
- Interdependent Uncertainties

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*Last August 25, 2008.*