Success Leaves Clues, but We Shouldn’t Disregard Luck

A quote popularized by Tony Robbins – “Success leaves clues” – can get us very excited about lofty goals. If we were only to follow the playbook of mega-successful entrepreneurs, sportspeople, politicians and artists, we could (and should) achieve the same results. But what most people are poor at understanding is the role of luck in success.

Daniel Kahneman, the Nobel Prize winner and author of Thinking, Fast and Slow, highlights books like Built to Last by Jim Collins and Jerry I. Porras that describe common characteristics of successful companies that are built for growth and long-lasting success. Kahneman argues that the companies that are chosen for their success are statistical anomalies, rather than the consequence of skill. Many companies run exactly the same way would fail due to the role of luck and chance. Therefore, the conclusions made in these types of books could well be useless.

Although it is difficult to get your head around, Kahneman’s point makes sense. A year after their inception, Google were willing to sell their company for $1m, but the deal didn’t go through because the buyer said the price was too high. There are likely a multitude of other ‘lucky’ events in the company’s history that will have helped Google to get where they are today.

But just because a lot of success is down to luck, doesn’t mean that we should no longer try. The real question is: How can we put ourselves in more positions to get lucky? We are much more likely to get signed by a professional football club if we play in front of scouts and spectators than if we played in our back-garden where nobody saw us.

How UK Government Has Used Statistics to Influence Behaviour During the Covid-19 Pandemic

At the time of writing there are currently 161 cases of Covid-19 per 100,000 in my area, according to a page on the BBC website. That’s the same as 0.161% of the population.

Which statistic sounds more daunting?

Daniel Kahneman writes in Thinking, Fast and Slow that when formatting a probability, a frequency (e.g. 161 per 100,000) elicits a more emotional response than a percentage does. We picture 161 people that are infected, and therefore realize that there’s a threat. It’s much more difficult for us to imagine 0.161% as a threat, and formatting the statistic in this way makes it seem like Covid-19 is much less of an issue.

I believe that the UK government are familiar with this phenomenon, and have chosen to present statistics as total case numbers and frequencies per 100,000 of population (instead of percentages). Amid a national lockdown, the government of course wants compliance and this is a small detail that can influence the public perception of Covid-19.

I am not suggesting that the government have been deviant or unethical in any way, but the fact that the format in which statistics are written does influence the way that we think about things.