“In a textbook case of naive empiricism, the author also looked for traits these millionaires had in common and figured out that they shared a taste for risk taking. Clearly risk taking is necessary for large success—but it is also necessary for failure. Had the author done the same study on bankrupt citizens he would certainly have found a predilection for risk taking.” | Nassim Taleb in Fooled by Randomness.
The quote highlights the danger of cognitive bias by assuming that a single trait or behaviour can determine success or failure, without taking into account the broader context and the role of luck and chance.
Let’s say there are two entrepreneurs, John and Sarah, who both have a taste for risk-taking.
John takes a big risk by investing heavily in a new technology that ends up being a huge success, and he becomes a millionaire as a result.
Sarah takes a similar risk, but unfortunately, the technology she invests in fails and she loses all her money, eventually declaring bankruptcy.
In this example, both John and Sarah shared the same trait of risk-taking, but the outcome was different for each of them.
Risk-taking alone does not guarantee success [or failure]. Timing, market conditions, competition, and luck can also affect the outcome.
It’s important that we don’t oversimplify interrelated aspects that determine success or failure to a single characteristic or action.
Risk-taking can be a double-edged sword, while it may be necessary for success, it can also lead to failure, and is not a sufficient condition for success.
This is a good reminder to look beyond the data and think more carefully about our findings.