Over the past several decades, the bell curve that has haunted generations of students with seemingly pre-ordained grades migrated into business as the standard for assessing employee performance in the U.S. But in an expansive study, academic researchers found that individual performance unfolds not on a bell curve (or "normal distribution," in which equal numbers of people fall on either side of the mean) but on a power-law distribution with a few elite performers driving most output and an equally small group tied to damaging activity.
The study, "The Best and the Rest: Revisiting the Norm of Normality of Individual Performance," published in the Spring 2012 issue of Personnel Psychology, challenges nearly a half-century of rating employees and could prompt employers to re-evaluate how employee performance is measured and compensated, the researchers concluded.
“How organizations hire, maintain and assess their workforce has been built on the idea of normality in performance, which we now know is, in many cases, a complete myth,” said lead author Herman Aguinis, professor of organizational behavior and human resources at Indiana University’s Kelley School of Business. “If, as our results suggest, a small, elite group is responsible for most of a company’s output and success, 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 mindset and entirely new management tools.”
It's critical to identify elite performers early
and manage, train and compensate them
differently from their colleagues.
According to Aguinis and his co-author, Ernest O’Boyle of Longwood University, who is soon to join the University of Iowa, the entrenched notion of normality—notably in performance evaluations that force managers to assign only numeric or category ratings (for instance, “above average”) —is detrimental to individuals, the group and the organization. They suspected that any group, regardless of size or industry, would show a pattern with a few elite performers (“the best”) dominating the many (“the rest”).
The researchers 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 in 50 disciplines, based on publishing frequency in the most pre-eminent discipline-specific journals.
• Entertainers (actors, musicians, writers) and the number of prestigious awards, nominations and distinctions received.
• Politicians in 10 nations and election/re-election results.
• Collegiate and professional athletes looking at the most individualized measures available (home runs or receptions in team sports, total wins in individual 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. “For example, with the athletes we could look at performance within leagues, within teams or specific positions, but the shape of the distribution was constant.”
Aguinis and O’Boyle expected 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. “Counterproductive work behaviors” often are covert and thus challenging to assess, so they again used sports samples, examining such elements as yellow cards in soccer and first-base errors in baseball to find negative performance attributable largely to an individual. Here, too, the results conformed to the power-law distribution.
“All five 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,’” said Aguinis.
Implications for Pay Structures
Aguinis noted that the power-law approach has applications for rewarding employees at organizations of all types and sizes. However, changing theory and practice will be challenging because of deeply entrenched notions of fairness and equality in society and business. Further, it could pose ethical dilemmas because it requires rewarding the “superstars” first within the context of treating everyone fairly.
“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,” said Aguinis. “Similarly, an educator may struggle with the notion of investing more time in top students—who would bring up overall class scores—rather than trying to improve everyone a little bit, which won’t move the needle.”
Aguinis cautioned that top performers can exhibit personality traits such as narcissism and selfishness that could have a negative impact on an organization. “When we recommend looking for ‘superstars,’ we mean those who don’t just do their jobs well but also create a good work environment and enhance productivity for the entire team, unit and organization,” he said.
The bottom line, according to Aguinis, is that everything about individual performance has to be re-evaluated so managers can identify and go after lead performers. “These people will be desirable to outside firms, so success means thinking about excellence and improvement all the time, talking with top performers continuously to find out what they need to grow and advance,” he said. “Rating them once a year, based on a bell curve, will send top performers—and profits—right out the door.”
Stephen Miller, CEBS, is an online editor/manager for SHRM.
For whom the bell curve tolls
Unlike the children of Lake Wobegon, all employees are not above average; in fact, according to this research, they don't even perform along a "normal distribution" as represented by the famous bell curve. Instead, it's "the best" and then "the rest," the researchers contend. Do they have a point? Comment on SHRM Connect, here.
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