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on January 10, 2010
Think Twice represents the next step in Mauboussin's beneficial quest to help all of us identify the mistakes we make and provide the tools to fix them. It takes many of Mauboussin's past ideas, condenses a vast array of additional sources, and puts them in a manifesto on how to dodge the pitfalls of poor decision making. Mauboussin has managed to write a book that is interesting for everyone. Deceptively short at 143 pages (with 33 pages of notes and references), I recommend readers slow their pace to digest this book and internalize the tools and countless real world examples used to clarify and illustrate.

"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.
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on February 21, 2010
There are now many good books available on why we make errors in judgment and decision making. This book represents Michael Mauboussin's contribution to this genre, and I think he has done a good job in pulling together a lot of information from a diverse range of credible sources. The information he presents has broad application, though he has a slight emphasis on business and investing applications (his own area of specialization). The book is also a fairly easy and quick read.

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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on April 25, 2015
This is a thought-provoking book, supposedly a business book but one that offers insights to people like me who only have to make the decisions of everyday life. Since reading it, I keep seeing examples of the inside view and the outside view in making decisions both by myself and by others. I live in a hurricane-prone area. After a natural disaster, we have to deal with property damage, insurance companies, and scam artists posing as contractors. How to sort it all out? Those who take the inside view are trusting to luck, while the cautious people who examine the situation by taking the outside view are more likely to recover from the catastrophe. How about investment decisions? It's the same thing. Those who take the inside view may get lucky, or maybe they'll end up cursing their "luck." What's this business about the inside and outside view? Read the book.
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on September 1, 2013
I am not going to delve in too much detail about the contents of the book, other reviewers have done a very good job of that. Instead, I am interested in understanding a few things in greater detail; sort of pose the questions to the author if I could. Indeed, the book raises many interesting points.

The author has picked up many cognitive biases and woven a nice little story around them. To make the 'package' more attractive, he has also thrown in the tagline of the book being for 'investors', the implicit assertion being that we can make more money if we could eliminate some of the biases (as if we are already making millions in markets and could suddenly make billions!). I found nothing useful here for traders or investors (full disclaimer: I did not buy the book for that purpose, my sole interest was cognitive bias only). If you can separate the marketing hype and take out the 'trader/investor' framework, it is a mediocre book on cognitive biases at best, simply because it does not cover all of them, or even the most important ones. If you want some hard hitting stuff on biases, you are better off reading Kahneman, Tversky, et. al., directly. This book is a nice filler if heavy and comprehensive tomes are not your thing (though Kahneman happens to be very readable).

Ok, with the disclaimer done, some questions and possibilities.

1. There are too many implicit statements in the book, with the author neither making open statements, nor taking them to their logical conclusion. For instance, the episodes related to portfolio managers doing worse than the market are mentioned numerous times. Each time, it is implicitly stated that the investors would well to invest in index funds rather than go with portfolio managers. Hmmm...

One of the major themes on crowdsourcing posits that markets run up and become ripe for crashes as diversity gets eliminated from the market and all agents start conforming to the dominant view of the market. That issue has been known in the financial literature in many forms for decades. It is the reason behind once successful trading strategies becoming useless in addition to causing market cycles (in fact, the famed Eugene Fama paper on Efficient Market Hypothesis hinges on this very feature, you cannot have a lasting advantage or a trading strategy in the market). The "Index Fund Strategy" also has to be viewed in this light. After all, Index Funds do not invest in 10,000 assets. Most leading indices comprise of 30, 40, 50 or 100 stocks or securities at best. If everyone starts to follow and invest in these indices only, diversity would get knocked out of this decision. And very rapidly too. Logically, stock pickers who were investing outside the indices would do better than indices. All of a sudden, index funds will start looking bad and money managers will start looking good, for some time...

So am not so sure what the blinding insight here is. That investors should start investing in index funds? That would start a different cycle, at least some money managers will start outperforming indices significantly. Go with the money managers, index funds will get better. It is a forever oscillating system.

More than that, different chapters conflate a lot of concepts. For example, a baseball team owner venting on the team because it loses 8 out of its first 12 games... The author argues that the owner was wrong because there WAS real skill involved. Why wouldn't the same thing apply to the big pension funds firing their money managers because they had a bad year or quarter? Simply pointing out that the fired folks suddenly outperformed the ones who replaced them proves neither mean reversion nor lack of skill.

This conflation continues throughout the book, though I am not complaining about it. In fact, I quite enjoyed it because it put the same conflicting positions in juxtaposition as the incident of 'global oil supply debate' that the author has listed in the book.

2. Again, the idea of crowdsourcing has 'second order effect' questions that the book neither raises nor answers. We are seeing a situation where the crowd is better than experts, for the time being. I have no problem with computer based predictive systems being better than the experts. But there is a bit of a problem with overall crowdsourcing paradigm.

First and foremost, all the successful predictive market and crowd wisdom experiments have needed to be well controlled and well set up. You suddenly don't go asking people on the street what the price of crude oil six months later will be. As listed by the author, people need to have right kind of incentives, they need to know about the subject well enough and so on. Question: if crowdsourcing is so effective, why is a survey of 50 or 100 economists about economic indicators usually wrong and typically wide off the mark? If expertise is such a hindrance, then what level of familiarity with the subject is the right level for getting crowdsourcing right?

Next order question, of course, is the same as what tanked the likes of LTCM. If experts also typically end up creating crude mental models while predicting (simple extrapolation), wouldn't the same thing apply to all the participants? May be in a stable system (the world where LTCM's models predicted everything accurately, till the normal distributions worked), the crowd would be right. What about fundamental shifts in the market (what caused LTCM to fail and other such major turning points in financial history)? Will the crowds be able to effectively pick those? Not so sure again, as we simply don't have enough evidence. And I am not even touching upon the diversity issue here.

3. At some point, the author makes a really tired point about 'the market being more accurate than the individual trader or investor'. If you are a seasoned trader or investor, I am sure you would probably get a bemused chuckle at best. If individual biases do not add up, then why do we have bubbles at all? I know he has conveniently laid the blame at the door of market losing diversity. But if all or most of the participants in the collective are the same, just change their opinion (as it often happens in bubbles), at what point do you say the market has lost diversity? The collective argument simply means that the trend following systems of the '80s and the madness of the last decade were actually legitimate. The collective consciousness of the market WAS driving everything up after all. And that too for multiple years.

4. I think the financial crisis has been just a favorite horse to flog for too many writers. No harm in analyzing it one more time and earning some quick bucks. But for every Taleb who made money in the crisis, there are many who bet against the 'madness' in 2003, 2004 or 2005, and lived to the rue the day. And there have been plenty, just that those with the staying power eventually triumphed. There have been cassandras at all times, just that the crisis happened and the cassandras of the day (Roubini, et. al.) collected the accolades.

5. Laying all the blame for the last financial crisis at the doorstep of 'bad modelling' or 'cognitive biases' alone is probably too narrow a view anyway. Probably the biggest factor was the incentive built into the system. Unprecedented amount of liquidity pumped into the system without any apparent reason (why did Greenspan keep pumping money even when the global economy was on the boil is a question no one has an answer to), no financial oversight, individual incentives adding up to collective disaster (the author is right about this); these are probably bigger reasons for it than anything else. If your model is right and you are predicting disaster, but listening to you would force the corporation to forgo billions in profit for next few years and its bosses to lose millions in bonuses; there is only one logical outcome possible, you get fired. If you are lucky enough to be able to raise money and bet against the system, you may have the last laugh. Otherwise, you don't stand a chance. I don't think cognitive bias has a lot to do with it.

6. Coming back to the investor / trader premise, what about automated systems? Much of the trading on the exchanges today is carried out by automated systems. Occasional glitches do bring the problems to the surface. But how do you trade / invest in markets that pit sophisticated algorithms and computers against you? Market information may also be getting less transparent with dark pools, etc., emerging in a big way. How do these affect the collective wisdom of the market? If half the participants in the market are computers and algorithms, what shape would investor biases take then? Will the market stop having bubbles (since the computers will beat the biased humans in a big way, all of us humans will go bankrupt and there will be no bubble)? Again, I am not holding the author to it, as the book is not really addressing investing in any serious manner.

Okay, with the questions over, now let us turn to why I think this book is worth four stars. One, it is a thoroughly enjoyable book with exhaustive research, a great bibliography and good anecdotes interspersed. Two, the book may not delve too deep in the topics, but at least asks the right questions. If you stay with the thoughts and are willing to push the questioning further on your own, the book gives you enough material for doing that too. Three, there are some things that you can use in day to day decision making. Ideas like the collective, etc., are difficult to deploy without going through elaborate processes and large scale organizational buy-in. But the checklists at the end of the chapters are handy in case of some of the biases. Finally, the book is a nice and light read. I would prefer it any day over a fiction book for its sheer reading pleasure.

Overall, worth a read. Just don't expect it will help you make 'more money', and be happy with some research being quite dated.

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on November 4, 2014
I borrowed this book title and some of the author's advice in a speech to accounting students. My speech title was Think Twice ... ten illogical actions to have a successful accounting career.

Author Michael Mauboussin states on page 143 that almost everyone agrees decision-making is important yet we don't teach students how to make good decisions. I recommended Think Twice plus Decisive by Chip & Dan Heath to the students.

I was not wow'ed by this book (therefore 4, not 5, stars) but had several Aha's:
1. A crowd of partially informed is more accurate than a handful of experts.
2. Peter Drucker's question to Campbell Soup leaders : "If we did not do this (promote tomato soup) already, would we, knowing what we do now, go into it?" Drucker was one of the best at posing questions instead of giving answers.
3. To improve a team or organization, don't rely on bringing in a star. Instead improve the whole instead of adding or subtracting one person.
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on April 9, 2010
This short and easy-reading book packs a real wallop when it comes to identifying and explaining common mental tendencies that can impair our judgment. These tendencies may be hard-wired into our DNA as a result of events thousands of years ago. For example, suppose that while two cavemen were walking down a path, they both heard a sound in a nearby bush. One caveman bolts immediately, while the other stops and thinks to himself, "I wonder what that is?" While he's thinking, a rattlesnake strikes out and bites him--and he dies shortly thereafter. That caveman's DNA didn't get passed on to future generations, while the DNA of the caveman who ran first and thought later does. So it may make sense that in uncertain or stressful situations, we have a tendency to react quickly. But modern society's situations may call for careful thought more than immediate reaction, so at times even smart people can be led by their instinctive responses into poor decisions. As author Michael Mauboussin puts it, "Smart people make poor decisions because they have the same factory settings on their mental software as the rest of us."

This book is filled with interesting examples of how our instinctive first responses can lead to less than optimal choices. I'll relate two of the book's examples, so you can get a feel for what's in the book, and then you can hopefully decided better whether you want to buy it. The first example that comes to mind may be called the "inside versus outside" view. To illustrate "inside" thinking, consider the case of race horse Big Brown in 2008. He won the Kentucky Derby by four and three-quarters lengths, and then he won the Preakness Stakes by five and one-quarter lengths. Prior to Big Brown's attempt to win the Belmont Stakes (and thus capture racing's Triple Crown), he looked great, and his owner expressed a lot of confidence. On race day for the Belmont, Big Brown's odds were 3 - 10, making him the easy (75% likelihood of winning) favorite. That's the details-oriented "inside" view. The "outside" view is that of the 29 prior horses to compete in the Belmont after winning both the Kentucky Derby and the Preakness, only 11 won the Belmont (about 38%). Further, since 1950 (perhaps when better training methods were more commonly practiced) only 3 of 20 horses (15%) with a chance to win the Triple Crown won the Belmont. In short, the inside view was optimistic, but the outside view wasn't. It turns out that Big Brown finished ninth in the Belmont.

A briefer second example of how our "mental models" affect our thinking and decision making, concerns French and German wines available for sale in a store. When French music was played, customers chose French wine 77% of the time, yet when German music was played in the store, customers chose German wine 73% of the time. The customers were asked whether they heard the music and whether it affected their choices. Most customers recalled hearing the music, but they denied that it had anything to do with their choices.

Okay, perhaps these examples will help you understand the kind of reasoning processes that author Mauboussin examines and discusses in Think Twice. Indeed, the book's title is the shortest advice he has to give to people facing situations where instinctive responses may impede the best decisions. As they say, forewarned is for forearmed.
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on February 28, 2010
"Think Twice" was wonderfully eye-opening and a joy to read.

And Mauboussin's points are all the more credible because there is further supporting evidence of the principles he describes well outside the domains where he proposed they be used. The principles in "Think Twice" fit perfectly with W. Edwards Deming's work that led to Japan's postwar resurgence and became the foundation of today's Lean Manufacturing practices and the Toyota Production System.

Unlike Mauboussin, Deming did not use the phrase "mean reversion," but Deming's view that manufacturing defects were evidence of inherent variability in manufacturing systems rather than evidence of lapses in a particular worker's effort fits perfectly with Mauboussin's work: "In a probabilistic environment, you are better served by focusing on the process by which you make a decision than on the outcome" (p.xx) could just as easily have come from Deming if Deming had been as good a writer as he was a statistician.

Again, Mauboussin's points are all the more compelling because they can be successfully applied to situations far beyond those where he proposed they be used. "Think Twice" is a must-read for anyone who wants to make well-informed, insightful decisions.
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on February 26, 2013
I am licensed MFT specializing in working with court ordered domestic violence perpetrators and writing evaluations in high confilct civil cases. In both endeavors, I am continuously making decisions that could have critical impact on marriages and intimate relationships. Often the stakes are high for every party involved. This is especially true in custody cases.
Even though this book is aimed more at business and political decision making, it was very useful for me to avoid mistakes in my profession, which often entailed cross examination by the attorneys for both parties in court.
First, the author brings together the fragmented research into the psychology of decision making, then he analyzes the mistakes made in recent critical decisions. Among these are the mistakes that stalled the delivery of Boeing's new aircraft.
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on September 21, 2016
Great aggregation of steps how to improve our natural biases.
If one considers how to improve his decision making on any level, reading this will only help.
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on November 26, 2015
This book is packed full of insights into the dysfunctional ways in which we think. It points to many other resources relevant to the topic and was a very valuable source in preparing for an assignment on 'Improving Management Decision Making' as part of an MBA course.

A great companion piece to Daniel Kahneman's "Thinking, Fast and Slow".
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