Has the Bell Curve Rung Its Last?
Study debunks the myth of ‘normal distribution’ in employee performance
The dreaded bell curve that has haunted generations of students with seemingly preordained grades has also migrated into business as the standard for assessing employee performance. It appears from a recent study, however, that individual performance unfolds not on a bell curve, but on a “power-law” distribution, with a few elite performers driving most output and an equally small group tied to damaging, unethical, or criminal activity.
The study, by Herman Aguinis from the University of Indiana’s Kelley School of Business and Ernest O’Boyle of the University of Iowa, turns on its head nearly a half-century of plotting performance evaluations on a bell curve, or “normal distribution,” in which equal numbers of people fall on either side of the mean. The researchers predict that the findings could force a wholesale reevaluation of employee recruitment, retention, and performance.
“If, as our results suggest, a small, elite group is responsible for most of a company’s output and success,” says Aguinis, “then it’s critical to identify its members early and manage, train, and compensate them differently from colleagues. This will require a fundamental shift in mind-set and entirely new management tools.”
Study Design and Implications
According to Aguinis and O’Boyle, the entrenched notion of normality: notably in performance evaluations that force managers to assign only numeric or category ratings: is detrimental to individuals, the group, and the larger organization. They suspected that any group, regardless of size or industry, would show a pattern with a few elite performers dominating the rest.
To test their hypothesis, they amassed a database of more than 600,000 individuals and conducted separate studies applying normal and power-law distributions to assess performers in four carefully chosen fields: academics, entertainment, politics, and sports.
“We saw a clear and consistent power-law distribution unfold in each study, regardless of how narrowly or broadly we analyzed the data,” said Aguinis.
Aguinis and O’Boyle also believed that the power-law distribution would identify outliers at the other end of the performance spectrum: those likely to engage in unethical or illegal behavior. Here too, the results conformed to the power law.
“All of our studies suggest that organizational success depends on tending to the few who fall at the ‘tails’ of this distribution, rather than worrying too much about the productivity of the ‘necessary many’ in the middle,” Aguinis says. He admits, however, that such an approach might be difficult for some managers to accept.
“Dedicating extra effort, time, or money toward a handful of employees will seem anathema to managers or human-resource professionals accustomed to thinking in terms of parity, what’s best for all or most, or what’s applicable to a set pay grade or position,” Aguinis says.
Read the entire report here.
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