This is a "must-read" book. It's a category starter. It's full of innovative ideas. It's entertainingly written, and it has great case studies. The category the book starts is the category of risk intelligence, in the sense of one's capability to learn about the risks one will face in an area of endeavor and so cope with and reduce them. In the past, risk intellgence hasn't really referred to intelligence in the sense of the capability to learn about risks. Instead, it's been about a category of business intelligence, which generally refers to information of better quality than ordinary information. So this slight shift in orientation opens up an entirely new and important field, one that can emphasize anew the practical importance of the capacity for organizations and people to learn.
This book also provides innovative ideas in every Chapter. In Chapter 1 the idea of relative risk intelligence, or the gap between self and others in ability to learn about risk, is introduced and we are given a set of four myths about risks, and four accompanying rules countering the myths. The distinction between random and learnable risks is also introduced, and definitions of risk and risk intelligence are provided. With this as background, Chapter 2 then discusses the difference between random and learnable risks in order to help readers learn how to distinguish them, and expands a bit on the idea of relative risk intelligence. The chapter ends by emphasizing the need for a way of comparatively scoring risk intelligence. Chapter 3, the pivotal chapter of the book, then immediately turns to filling that need. It offers a method of measuring one's relative "Risk IQ" through a simple test based on five elements focusing on experiences in the risk area in question. The five elements of the test focus on the frequency, relevance, impact, unexpectedness, and diversity of one's experiences, and on the extent to which one is methodical about tracking what one learns. Someone doing the assessment compares organizations, or other actors, on each of the five elements using a simple scaling method. The scores on each element are then summed to get the relative risk IQ score. The score is then used to triage risks, diagnose one's risk intelligence, and classify oneself or one's organization as a risk assessor. The chapter then illustrates classification by using the At & T case, while introducing three patterns of risk assessor: encyclopedists, impressionists, and amnesiacs. The chapter then uses these patterns to develop some ideas about the life cycle of risk assessment skills in organizations, how teams can be used to enhance risk intelligence, how risk intelligence scores value information (involving use of a Bayesian approach), and about relevance as the missing link between information and learning.
Having offered a basic tool to assess risk intelligence, in Chapter 4, the book turns to risk strategy auditing, risk strategy, and "pipelines of learning challenges." The idea of the learning pipeline is critical idea that addresses us to the importance of sequencing risks. It's not just the risk portfolio that's important in risk strategy. Chapter 4 argues persuasively that "the pipeline in the portfolio" is just as important as the portfolio itself and that the sequencing of risk is just as important in risk strategy as the diversification of risk. The chapter also offers us tools to assess and formulate risk strategy. These include the risk strategy matrix, the risk strategy audit tool, and a guide to who should conduct risk strategy audits in organizations. The chapter also shows how risk strategy audits complement analyses based on the BCG's growth-share matrix, explains four key risk strategy patterns: winter, spring, summer, and fall strategies, and relates the life cycle of risk to business cycles. Chapter 5 focuses on how important it is to to join with partners to manage one's risks. Tools offered in the chapter include risk-role matrices and risk role measures. Roles such as "customer umbrella," "classic borrowers," "shock absorbers," and risk distributors are discussed, among others. The discussion then turns again to random risks and to emphasize that when risks are random, no one has an inherent advantage, re-labels them "flat-field" risks, and uses the Mexico debt case study to show how creating flat-field risks can be a good thing. The chapter ends by exploring the idea of risk ecology and its relation to open market economies. Chapter 6 provides a great ending to the Book by summarizing its analysis and advice in 10 steps "that distill the implications of the story of risk intelligence." While you're reading the book, relatively short as it is, one tends to lose track of the number of new ideas and tools it presents. But Chapter 6 is the perfect antidote to diffusion. Its effect is to coalesce the book's impact for you and to bring home the importance of its innovations.
In the category of "entertainingly written," the book's frequent anecdotes enhance the presentation. A typical example begins this way: ". . . suppose blue smoke starts to billow from under the hood of your car any time you drive over 60 mph. You also notice, for the first time, a mysterious green liquid collect under your car when it's parked. So you call the guys at Car Talk . . . " In the category of case studies the book covers cases like Toyota, Tokyo's Tsukiji Fish Market, the Boeing - Airbus rivalry over stretch jumbo jets, the Nokia - Ericsson competition in mobile phone manufacturing, and AT & T's growth decisions in the years prior to its merger with SBC -- principles in every chapter are illustrated with important cases.
No book is perfect, and this one does have some problems in the areas of conceptualizing risk intelligence, the risk intelligence test, and also in its scaling methodology. But these problems hardly weigh at all against the fact that if you're interested in risk intelligence as a category, you really need to read this book.
