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2007, Cambridge University Press, 623 p., softcover, US$48.00 list.
ISBN  978-0-262-01672-8

This book should be a standard text for a second or graduate course in decision analysis. Practitioners also will also find a wealth of information inside.

How to Design an "Advances" Book

The editors and the list of contributors reads like a Who's Who of decision science. The editors first decided what topics should be included in an advanced book of decision analysis, then they secured commitments from among the best academics and practitioners.

The book divides 28 chapters among these sections:

Not all chapters will be of high interest for everyone. I skimmed several rather quickly. With 28 topics, there are likely to be many chapters that will apply to the reader. Some sections are more-difficult topics, and I usually required two or three sittings to finish a chapter. It was time well spent.

What's Inside

I always find historical perspectives of special interest. The mathematics needed for decision analysis evolved from the 1400s and earlier through the 1800s. Operation(al) Research emerged during World War II, and many of us consider decision analysis a subset of this broader discipline. One of the classic stories is how Bayes' rule assisted in locating a sunken Russian submarine.

Structuring decision problems is the heart of decision modeling. At least six tools are described as useful. As I'm mostly oriented to maximizing economic-value, it was interesting to read about multi-criteria approaches. Securing support from the stakeholders is often key to project success, and people won't be on board unless their interests and needs are represented.

Methods for representing probabilities continue to be developed. The mathematics are improving, and some recent methods require considerable computer calculations. Practices for eliciting judgments about processes, structures, events and values are described by many contributors.

Several chapters were written by prominent consultants. Descriptions of their approaches and engagements is fascinating. Some examples:

• Probabilistic risk assessment of a nuclear power station

• Risk management to optimize replacement and repair of Space Shuttle tiles

• Assessing terrorism risks and countermeasures

• Decision conferencing for ranking new businesses opportunities

• Nuclear power plant refueling strategies.

Reading this book is an opportunity to learn from the best. I've severely annotated my copy and expect to return to it often. There are thousands of references, and some of these will be pursued. I've acquired several of the earlier book and reprint classics.

Not since the two-volume The Principles and Applications of Decision Analysis (Ronald A. Howard and James E. Matheson, editors, Strategic Decisions Group, 1983) has there been so much about decision analysis in one publication.