It’s a long-held assumption that human performance fits a normal (or Gaussian) distribution — a bell curve in which only a very small number of people are outliers.
Consequently human resource managers usually work from the idea that in most activities, although there are a few people that are very good and a few people that are very bad, most are about average.
A new study provides evidence that individual performance doesn’t fit on a bell curve (with its stable average and limited variance), but follows a distribution in which the average is unstable, the variance is infinite and the prevalence of outliers is much higher.
Statisticians called it a power law (or Paretian) distribution.
Researchers Ernest O’Boyle Jr. and Herman Aguinis conducted five studies involving 633,263 researchers, entertainers, politicians, and athletes. Of a total of 198 samples of performers, 186 (a whopping 94 per cent) followed a power law distribution more closely than a normal distribution.
That is, there was consistently a sizable number of elite performers (i.e. outliers) in each profession that accounted for the lion’s share of output while a majority of workers performed below the mathematical average.
For example, one study found that two-thirds of Major League Baseball players commit more errors in their careers than the average for a fielder. Another involving 490,185 researchers — who produced 943,224 publications across 54 academic disciplines between January 2000 and June 2009 — found that the performance of researchers follows a power law distribution.
The findings imply that performance measurement would benefit from identifying superstars who account for the majority of results (as opposed to disregarding outliers and examining slight differences in non-elite workers).
The authors state that new theories are needed “to address the identification and motivation of elite performers” because leadership theories that avoid elite workers will fail to positively influence overall output in a meaningful way.
Managers, the researchers suggest, should realise that the individual performance of workers follows a power law distribution so that they can properly recognise and develop the superstars that will make or break their organisation.
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