Introduction To Decision Analysis

"This book is the most practical and thought-provoking step-by-step guide to making better decisions that is available today! Proven techniques and solid experience are the foundation for this classic text, which was written for the manager and for the decision analysis practitioner!"--

A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels.

This best-selling and up-to-date survey of decision analysis concepts and techniques is accessible to students with limited mathematical backgrounds. It is designed for advanced undergraduate and MBA-level courses in decision analysis and also for business courses in introductory quantitative methods. (Prerequisites: college algebra; introductory statistics.)

Everybody has to make decisions—they are unavoidable. Yet we receive little or no education or training on how to make decisions. Business decisions can be dif_ cult: which people to hire, which product lines or facilities to expand and which to sell or shut down, which bid or proposal to accept, which process to implement, how much R&D to invest in, which environmental projects should receive the highest priority, etc. This book gives you all the tools you need to... • clarify and reach alignment on goals and objectives and understand trade-offs in reaching those goals, • develop and examine alternatives, • systematically analyze the effects of risk and uncertainty, and • maximize the chances of achieving your goals and objectives. Success (getting what you want) depends on luck and good decision making. You can’t control your luck, but you can maximize your odds by making the best possible decisions, and this book gets you there. Broadly speaking, this book organizes and presents otherwise formal decision-making tools in an intuitively understandable fashion. The presentation is informal, but the concepts and tools are research-based and formally accepted.

This book presents an introduction to MCDA followed by more detailed chapters about each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research. Worked examples as well as the software featured in the book are available on an accompanying website.

The purpose of this book is to provide readers with an introduction to the fields of decision making, location analysis, and project and machine scheduling. The combination of these topics is not an accident: decision analysis can be used to investigate decision seenarios in general, location analysis is one of the prime examples of decision making on the strategic Ievel, project scheduling is typically concemed with decision making on the tactical Ievel, and machine scheduling deals with decision making on the operational Ievel. Some of the chapters were originally contributed by different authors, and we have made every attempt to unify the notation, style, and, most importantly, the Ievel of the exposition. Similar to our book on Integer Programming and Network Models (Eiselt and Sandblom, 2000), the emphasis of this volume is on models rather than solution methods. This is particularly important in a book that purports to promote the science of decision making. As such, advanced undergraduate and graduate students, as weil as practitioners, will find this volume beneficial. While different authors prefer different degrees of mathematical sophistication, we have made every possible attempt to unify the approaches, provide clear explanations, and make this volume accessible to as many readers as possible.