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Think Twice: Harnessing the Power of Counterintuition Paperback – November 6, 2012
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"No one wakes up thinking, "I am going to make bad decisions today." Yet we all make them." Think Twice outlines eight common mistakes, tries to help the reader recognize these in context, then provide ideas on how to mitigate your own tendency to repeat these same mistakes. Certain ideas recur throughout the text, including using data and models to inform decisions; viewing many real world situations as complex adaptive systems; as well as appreciating context and luck.
Each chapter focuses on one key error we make:
+Chapter 1: Viewing our problem as unique. Others have usually faced the same decisions we face and we can learn from their results to get to the right answer - for example in corporate M&A, you can look at how other similar deals have performed.
+Chapter 2: We fail to consider enough alternative options under pressure because we have models in our head that oversimplify the world; usually that helps us make quick decisions but often it causes us to leave out alternative choices which could be better. Incentives and unconscious anchoring on irrelevant information contribute to this tunnel vision.
+Chapter 3: An uncritical reliance on experts. Experts are people like us and are subject to all the same bias and error. While this has been covered by Cialdini and others, Mauboussin focuses on the solution - "computers and collectives remain underutilized guides for decision making." We see this idea now in practice in the development of prediction markets for Hollywood movies to who will be the next Senator from North Dakota.
+Chapter 4: "Situation influences our decisions enormously." We all underestimate how much we are influenced not only by others, but by our own feelings.
+Chapter 5: Cause and effect reasoning fails when systems are complex because the whole is greater than the sum of the parts. Focusing on why individuals in a system do something - an investor in the market, an ant in a colony, or birds in a flock - does not help explain how the entire system performs. Understand the rules that govern the entire system, rather than the rules that drive the individual participants.
+Chapter 6: We try to apply general rules in contexts that are not appropriate. In real life, decisions are specific. As Mauboussin says, "it depends".
+Chapter 7: Small changes in a system (or an input) can lead to a large change in output. We mess things up by assuming the same input will always have the same output. One quotation I particularly liked in this chapter was from Peter Bernstein - "Consequences are more important than probabilities."
+Chapter 8: We forget about reversion to the mean. "Any system that combines skill and luck will revert to the mean over time." Ignoring this makes people think they are special and that the rules of probability don't apply to them. This is reinforced by the "halo effect" - when someone is doing well in any field, people and the press lionize that individual and report on the multitude of genius they have ...but when they revert to the mean, all of a sudden that same person is viewed as incompetent. Mauboussin's own colleague Bill Miller faced this same perception cycle, and emerged with a halo in 2009.
Mauboussin concludes the book by summarizing an effective action plan - to put it simply, Mauboussin admonishes us to Think Twice before we make a serious decision to ensure we don't fall victim to any of these pernicious errors.
Perhaps the best way to describe the content of the book is to summarize the key points, roughly in the order they appear in the book:
(1) "Think twice" to avoid errors in judgment and decision making, especially in situations where stakes are high.
(2) Learn from the experiences of others in similar situations (making use of statistics when possible), rather than relying only on your own perspective, and don't be excessively optimistic about expecting to beat the odds.
(3) Beware of anecdotal information, since it can paint a biased picture. Related to this point, don't infer patterns which don't exist, especially when the available data is limited, and avoid the bias of favoring evidence which supports your beliefs while ignoring contradictory evidence (deliberately seek dissenting opinions if necessary).
(4) Avoid making decisions while at an emotional extreme (stress, anger, fear, anxiety, greed, euphoria, grief, etc.).
(5) Beware of how incentives, situational pressures, and the way choices are presented may consciously or subconsciously affect behavior and shape decisions.
(6) In areas where the track record of "experts" is poor (eg, in dealing with complex systems), rely on "the wisdom of crowds" instead. Such crowds will generally perform better when their members are capable and genuinely diverse, and if dissent is tolerated (otherwise the crowd will be prone to groupthink).
(7) Use intuition where appropriate (eg, stable linear systems with clear feedback), but recognize its limitations otherwise (eg, when dealing with complex systems).
(8) Avoid overspecialization, aiming to have enough generalist background to draw on diverse sources of information.
(9) Make appropriate use of the power of information technology.
(10) Overcome inertia by asking "If we did not do this already, would we, knowing what we now know, go into it?"
(11) Because complex systems have emergent properties (the whole is more than the sum of the parts), avoid oversimplifying them with reductionistic models (simulation models are often helpful), remember that the behavior of components is affected by the context of the system, and beware of unintended consequences when manipulating such systems.
(12) Remember that correlation doesn't necessarily indicate causality.
(13) Remember that the behavior of some systems involves nonlinearities and thresholds (bifurcations, instabilities, phase transitions, etc.) which can result in a large quantitative change or a qualitative change in system behavior.
(14) When dealing with systems involving a high level of uncertainty, rather than betting on a particular outcome, consider the full range of possible outcomes, and employ strategies which mitigate downside risks while capturing upside potential.
(15) Because of uncertainties and heterogeneities, luck often plays a role in success or failure, so consider process as much as outcomes and don't overestimate the role of skill (or lack thereof). A useful test of how much difference skill makes in a particular situation is to ask how easy it is to lose on purpose.
(16) Remember that luck tends to even out over time, so expect outcomes to often "revert to the mean" (eventually move close to the average). But this isn't always the case, since outliers can also occur, especially when positive feedback processes are involved (eg, in systems in which components come to coordinate their behavior); in a business context, remember to make a good first impression.
(17) Make use of checklists to help ensure that important things aren't forgotten.
(18) To scrutinize decisions, perform a "premortem" examination. This involves assuming that your decision hasn't worked out, coming up with plausible explanations for the failure, and then revising the decision accordingly to improve the likelihood of a better outcome.
While this book doesn't really present any new material, I still found it to be a good resource, so I recommend it. After all, this subject matter is important and practical, yet also counterintuitive, so it makes sense to read many books to help these insights sink in and actually change one's habits.
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If one considers how to improve his decision making on any level, reading this will only help.