Recently, I found some strange statistics on BigThink. It suggested that to be successful, one needs to fail 16% of the time.

The article mixed three different strands of activity: creativity, learning, and work. To describe creativity, the author described how Einstein and Mozart dealt with performance. Both had individual strategies to deal with it as it appeared and disappeared. Talking about learning, they tried to explain how finding a sweet spot between effort and letting go would allow for the fastest possible learning. To end the article, they wrote about the way organizations tolerate failure. In doing so, they settled with one organization that had failed and had chosen a zero-error tolerance approach. These descriptions might highlight how different these activities are.

In essence, the article seems to search for a way to define and measure performance.

To do so, the authors assumed that performance can be measured using failures and what they considered its opposite: success. What the article doesn’t do is consider how the context of the activity influences the result and how the perception of the individual shapes its interpretation.

This may be natural, as most such statistics serve an objective of reassuring the individual and describe an assumption that is considered to be helpful. The idea is that the statistics will help individuals transform their perception of how well they are performing.

It tries to counteract the natural tendency to judge oneself and interpret something that feels good as success and something that feels bad as failure. However, such judgment usually is based on what one sees others do. It’s the result of comparing oneself with their results. It’s an unfair comparison as it uses results as a measure without consideration of the input it required or of the circumstances helping such a result to occur.

But to me, the real problem with such statistics is that they seek to establish predictability where it doesn’t exist.