How Finance Executives Aren’t Like Poker Players, and Why it Means We Should Be More Skeptical of Their Expertise
June 27, 2012 4 Comments
Imagine nine poker players seated at the final table of a major tournament. Although they posses a variety of different skillsets and backgrounds, there is one thing they have in common. They have all had the luck necessary to win the majority of the many 50-50 hands that arise during a tournament. Nobody reaches a final table by only gambling as an overwhelming 80-20 favorite.
Now imagine nine random Presidents/CEOs of large finance firms or banks. In some sense, they are also finalists in a tournament. Hordes of smart young people enter the finance industry each year, but only a select few reach the top. Like the pokers players at the final table, the CEOs have benefitted from a perfect combination of skill and luck. Nobody is repeatedly finding risk-free piles of money lying around in a competitive market, and that means each CEO must have successfully gambled on at least a few big ideas. Even if the CEOs repeatedly found major opportunities with a 70% chance of success, they never would have reached the top without beating the odds that they would fail.
Although poker players and finance CEOs rely to some degree on luck, the perception exists that we have identified the ones who are the most skilled. This is where there is a big difference between the two groups. Evaluations of poker players are based on hundreds of thousands of hands, not the outcome of a few tournaments. I won’t venture a guess as to how many risky decisions a finance CEO makes during his first 25 years of employment, but I’m confident the number has substantially less descriptive and predictive power than a poker player’s vast history. Finance CEOs were clearly wise with many gambles — that’s why they are where they are — but the small sample size means we can’t ignore the fact that some of them are CEOs instead of senior managers because they lucked out on bad gambles or a long string of coin flips.
All of this is to say that when we think about the expertise of finance bigwigs we should be more mindful of “outcome bias,” the tendency to focus on the outcome of a decision rather than the decision itself. Imagine LeBron passes up an uncontested dunk but seconds later makes a contested three pointer. Did he make a good decision? The answer is obviously no, but many people might say yes because they fail to understand that good outcomes don’t retroactively create good decisions.1 For example, one recent study found that ethically questionable behavior produces less condemnation when it leads to a positive outcome, even if the outcome is entirely due to chance. In their pioneering work on the issue, Jonathan Baron and John Hershey found that when people were asked about the quality of a medical decision, they said the thinking behind the decision was better when they were told the decision led to a positive outcome.
The lesson is that if a Wall Street CEO rises to his position by making a string of profit-growing decisions, the decisions may not have all been wise given the conditions at the time. That doesn’t mean Jamie Dimon isn’t a smart man who knows a lot about the American financial system, but it does imply that even in a vacuum (i.e. no consideration of political or financial motivation) we should be marginally more skeptical of the the expertise of influential finance people.
In the early days of the internet there was a classic scam where somebody claiming to be an NFL gambling expert would send 800 people a free pick during the first week of the season. The catch is that half the people were told a certain team would cover the spread and the other half were told the team’s opponent would cover the spread. The same thing was repeated the following week among the 400 people who initially received the winning pick. After four weeks 50 people had received four consecutive winning picks, and at that point the scammer asked them to pony up $49.95 to subscribe to the picks for the rest of the season.
The beauty of the scam is that 1/16th of your initial sample will always get the four good picks. Similarly, in a poker tournament nine people will always get lucky enough to make the final table. When it comes to finance, some set of people will always rise to the top of our largest institutions — after all, the banks can’t be leaderless. But when these leaders are annointed, it’s important to be mindful that in an arena full of unpredictability, a rise to the top is not always as indicative of ability as we might think.
1One highlight of my never-heralded sportswriting career was finding a Washington Redskins message board thread that used the outcome bias to take-way-too-seriously a joke I made about Joe Gibbs’ poor decision making. Skins fans need to learn that when Gibbs plays it too conservatively in overtime by kicking a 39-yard field goal on 1st down, the fact that the kick went in doesn’t make it good coaching.
Gino, F., Moore, D.A. & Bazerman, M. (2009). No Harm, No Foul: The Outcome Bias in Ethical Judgments SSRN Electronic Journal DOI: 10.2139/ssrn.1099464
Baron, J. & Hershey, C. (1988). Outcome bias in decision evaluation Journal of Personality and Social Psychology DOI: 10.1037/0022-35184.108.40.2069