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I just finished reading the most enjoyable business book I’ve read in a long time – although relegating “The Success Equation,” by Legg Mason Chief Investment Strategist Michael J. Mauboussin to this category would be a grave disservice, significantly understating its sophistication and selling short its achievement.
Mauboussin’s specific focus is understanding the relative contribution of luck vs skill in a range of endeavors, from sports to business; he brings not only an unusually broad, multidisciplinary approach to this question (especially for a finance guy), but also a willingness to look with unsparing frankness at the role of luck in his own field, investing.
(Disclosure: I don’t have a business or personal relationship with Mauboussin; we had a brief exchange several months ago related to a Washington Post piece I wrote about the fragility of science, a topic he touches upon in “The Success Equation,” and I am among those included in his “Acknowledgements” section.)
Mauboussin starts out with a story about the role of luck at the start of his career. He describes interviewing for his first job (at Drexel Burnham): after a series of unremarkable discussions with mid-level staffers, he went in for a short, high-stakes interview with a senior executive. Mauboussin happened to notice a Washington Redskins trash can peeking out from behind the desk, and complemented the man on his taste – Mauboussin, a huge sports fan, had previously spent four years in DC and attended a number of football games. This led to an impassioned conversation about DC sports, and ultimately a job offer.
Mauboussin later learned that the other six interviewers hadn’t been especially impressed, and he won the job solely on the strength of the final interview. “My career was launched by a trash can,” he writes. “That was pure luck, and I wouldn’t be writing this if I hadn’t benefited from it.”
Mauboussin launches into an engaging discussion of luck and skill, and their relative importance in sports, business, investing, and life. He first seeks to identify domains where either luck or skill is unquestionably dominant – e.g. lotteries involve luck, checkers involve skill. Most other activities, he recognizes, lie somewhere in between, and the challenge is to figure this out without falling into the many cognitive traps that conspire to overemphasize skill and underrepresent the contribution of luck.
A common mistake, Mauboussin points out, is evaluating the wisdom of a strategy by the outcome generated, since due to the powerful effect of luck, bad strategy can still lead to good outcomes, and good strategy can result in bad outcomes. Mauboussin highlights the example of the Sony Mini-Disk – a product associated with a fantastic strategy, yet according to consultant Michael Raynor (author of “The Strategy Paradox), was brought down by bad luck.
“Not only did everything that could go wrong for Sony actually go wrong, everything that went wrong had to go wrong in order to sink what was in fact a brilliantly conceived and executed strategy. In my view, it is a miracle that the MiniDisc did not succeed.”
Conspicuously widely-read, Mauboussin touches upon the work of Taleb (randomness and black swans), Tetlock (expert fallacy), Rosenzweig (importance of negative evidence), Gladwell (especially the concept of cumulative advantage), Sims (value of small exploratory efforts), Ioannidis (fragility of science) and of course Kahnemen. (The interested reader might enjoy these WSJ book reviews of Taleb’s “The Black Swan,” Gladwell’s “Outliers,” Sims’ “Little Bets,” as well as this short discussion of Tetlock and Rosenzweig, this critique of “Good to Great” [a sacred business text Mauboussin tackles head on], and this discussion of Ioannidis. As for Kahneman – I continue to recommend his Nobel address, and well as this recent commentary about overconfidence in the NYT – with a particular focus on investors.)
I especially appreciated Mauboussin’s emphasis on the need for relevant outcome measures, in a chapter titled “What Makes for a Useful Statistic?” He explains why ideal metrics should be both reliable (persistent) and valid (predictive), and points out how difficult it can be to find measures of performance in business, investing – and sports – that are either. (Again, I’ve recently discussed this exact issue in context of healthcare worker certification – professional societies charge steep premiums to administer certification exams despite a dearth of evidence linking test performance with clinically meaningful outcomes – see here and here.)
Mauboussin is especially effective invoking examples from sports, especially Sabermetrics, to introduce or demonstrate a particular point; at the same time, he is careful to avoid what Taleb calls the ludic fallacy, and to recognize the difference between the relative simplicity of sports and games, and the comparative complexity of most other areas of life.
While Mauboussin appropriately acknowledges the role of skill in a range of domains, and provides several familiar suggestions (deliberate practice, use of checklists), he is at his best when discussing the contribution of luck to success in a range of endeavors – including those closest to his own heart, business and investing.
In business, he writes, luck is far more important than most appreciate, although there seems to be emerging evidence that sustainable success in business exceeds what chance alone would have predicted. Even so, he explains, we don’t know what aspects of “management’s actions, or skill can lead to success,” so “all we can really say today is that we cannot explain results by luck alone, and that it appears that skill plays a role when companies earn a high return on their assets.” At the same time, he notes that “it is very easy to confuse superior performance with the results you would expect from luck.”
Investing, it appears, is, if anything, subject to even more luck than business – not because skill doesn’t matter, but precisely because it does. When there are so many highly skilled individuals, Mauboussin explains, luck plays a disproportionate role in determining the best and the rest.
Remarkably, he writes that “investing, especially over relatively short perioids of time, is more a matter of luck than of skill,” and while “research shows that most active managers generate returns about their benchmark on a gross basis,” these “excess returns are offset by fees, leaving investors with net returns below those of the benchmark.” Powerful words from the Chief Strategist of a leading financial services company!
He also point out that experts are “notoriously poor at predicting the outcomes of political, social and economic systems.” The problem, he writes, is that these “systems are complex adaptive systems; the results you see, such as boom and busts in the stock market, emerge from the interaction of lots of individual agents. Complex adaptive systems effectively obscure cause and effect. You can’t make predictions in any but the broadest and vaguest terms.” Nevertheless, he observes, “what’s surprising isn’t [experts’] abysmal record of prediction, but rather that society continues to believe them.”
There seem to be few good ways to deal with the role of luck – which may be another reason its contribution is functionally de-emphasized in the day-to-day work of most businesses.
One approach, Mauboussin suggests, is to listen to Nassim Taleb, particular when contemplating activities in the “Fourth Quadrant,” where “events of small and incomputable probability [can] have significant consequences.
“When it comes to managing luck,” Mauboussin writes,
” Taleb has two very useful messages. The first is to understand the limits of your knowledge about events that have probabilities that you can’t compute and consequences that are significant. In other words, know what you don’t know. The second is to take steps to make sure that whatever exposure you do have in the Fourth Quadrant is the result of buying, or acquiring, options and not the result of selling options. Selling options is the more profitable strategy most of the time. But you don’t define your ultimate success by the frequency of gains, but rather by how much you make when you are right versus how much you lose when you are wrong.”
Mauboussin also suggests that in situations where you are the underdog, it’s in your interest to maximize complexity, to increase the opportunity for exposure to chance; however, if you are dominant, than you should try to simply the contest as much as possible, so your superior skill, minimally impeded, will drive your success.
In the many situations where luck and skill both play major roles, Mauboussin advises focusing on the process of decision making, rather than the consequences, since you can’t assess (and improve) skill based on any individual outcome. The analogy he uses is blackjack; if you want to see whether someone is a good blackjack player, you don’t analyze her performance on any given hand, or any given evening; rather, the most efficient way is to look at her approach, the way she plays her hands. The challenge, of course, is that in blackjack, you can confidently define the ideal strategy, and benchmark again it; for most areas of business and investing, the ideal process is appreciably less clear.
The one question Mauboussin didn’t ask was also the one that interested me most: knowing what he knows about luck, prediction, and forecasting, how does he get up every day and go to work at his financial services business?
In particular, while he highlights the supposed benefits of being aware of the role of luck, I suspect the benefits of such awareness may be significantly overstated. Phrased differently: What is the competitive advance of recognizing the role of luck and the limitations of skill?
I am reminded of a searing experience I had as a management consultant, when I described to an extremely earnest, rapidly rising colleague historical data (from consultants) I had seen back when I was near the end of my medical training, demonstrating convincingly an absolute lack of correlation between peak drug sales as estimated by wall street analysts at the time a drug was FDA approved and the ultimate peak sales achieved by these same drugs.
These data always stood out in my mind as emphatically highlighting the futility of long-term (even medium-term) prediction; yet, to my colleague, the issue was equally clear: this analysis must have missed a crucial variable – if only the consultants had been more thorough in their treatment, they would have achieved the correct results.
All of my experience in the business world suggests that my colleague’s mindset is carrying the day. Although Taleb, as Mauboussin writes,
“argues that having no theory or model of events in the fourth quadrant is preferable to having a theory or model, because the errors we make are huge and often lead to bad results. In practice, we try to use policy and models to manage a part of the world that defies control and understanding.”
The world – policy, business, investing – demands structure, models, and forecasts even when these have little to no validity. As I’ve written, it seems to be in everyone’s interest to effectively disregard the overwhelming impact of luck, and assume you truly can make long-term predictions – and in no one’s interest to assert such predictions are likely worthless.
Mauboussin, and many other authors discussing cognitive baises, highlight the value of awareness, of recognition, of not being fooled. These are great conclusions for academic observers, and authors – but what I’d really like to know is what does such clarity get you in the real world?
My suspicion: not very much – though I’d dearly loved to be proven wrong.
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