Decision Bias, Problem Solving, and Training
During WW2 the United States Navy had a problem to solve, aircraft were not returning home at an adequate rate and the military was hemorrhaging money on aircraft and pilot losses. In order to remedy this they brought in a team of expert engineers to assess the planes that had managed to return home in order to discover what they needed to do differently. The entire Center of Naval Analyses engineering team looked at the firing damage pattern and quickly jumped to the conclusion that they should add armor to the planes where the damage had been done.
Of this entire team only one man recommended differently; The Jewish-Hungarian mathematician Abraham Wald noted that the only planes the team was basing decisions off of were the survivors. Notably, the planes returning with the firing pattern in the picture were returning home and thus were not casualties but successes. He suggested that planes were already robust to lethal damage in the shot up areas meaning that the planes should be armored extra in the places where there were no signs of damage in the survivors. He posited that the planes that were going down were suffering critical damage at those unseen locations.
Sometimes the information or data we DON’T see is just as, if not more, important than the information we do see, and sometimes the immediate evidence in front of us can blind us to more fruitful solutions.
When we fail to see the whole picture we can jump to unfruitful conclusions such as:
Elon Musk is a high school drop out who became a millionaire therefore if I drop out of high school and just “work hard” I too will become a millionaire. This quick conclusion overlooks the overwhelming data that shows that people who drop out of high school overwhelmingly have poorer long term health outcomes and lower lifetime incomes – these people represent the majority. Elon is a survivor (and someone born into substantial wealth) not evidence that dropping out will guarantee someone a millionaire career.
In this case, survivorship bias obscures the real odds of the situation and can lead individuals astray, preventing them from examining all the data, and blinding them to the real odds of a decision in critically dangerous ways.
When Survivorship Bias become Sunk Cost
In sport, survivorship bias can be dangerous – over emulating the greatest athletes of all time can lead people into training in ways that are not fruitful for them.
Much of the popular rhetoric in the sport world focuses on the individuals who are already elite – the survivors. On one hand, focusing on the greatest athletes can feel emotionally inspirational albeit temporarily, and it makes killer sales for a magazine to show you the current training program of this or that elite athlete but neither emotional fervor nor emulating the elite guarantees success! In fact, over focusing on the people who become great ignores the larger portion of the data – the athletes that stay average or never become very good represent a majority of people who have played sports at one point or another. We likely have just as much to learn if not more to learn about what prevented those people from being successful than from what made a select few successful.
In another example, we probably have just as much if not more to learn about what makes successful and unsuccessful running training from those who failed to complete their first marathons and those who scored below average, average, and slightly above average times than we do from exclusively the David Goggins of the world.
The unfortunate thing is that over emulating the greatest athletes or the most extreme performers can become something people become emotionally attached to – “I run until I pee blood and my toe nails fall off just like David Goggins does!” This behavior can create another mind trap known as the sunk cost fallacy where folks decide to double down on a decision or investment purely because they’ve already dedicated previous efforts to it even when the cost of continuing is far higher than the cost of changing strategies.
Being blinded by both of these biases prevents individuals who could become better from leaving the path they are on, assessing what is best, and pivoting to more successful individualized strategies.
Avoid the trap!
So, how do we as coaches and athletes avoid the above situations from hampering our performance?
- Examine the unseen data, if a conclusion feels easy to jump to – think opposite and see if you discover something new.
- Accept that there are often multiple correct ways to achieve success and what is right for one person may not be right for another.
- Assess needs and deficits regularly and make choices based on those things rather than arbitrarily on what worked for one person or what worked in the past.