“For decades, teachers, managers and parents have assumed that the performance of students and employees fits what's known as the bell curve—in most activities, we expect a few people to be very good, a few people to be very bad and most people to be average. New research suggests, however, that rather than describe how humans perform, the bell curve may actually be constraining how people perform. Minus such constraints, a new paper argues, lots of people are actually outliers.” – Put Away The Bell Curve: Most Of Us Aren’t ‘Average’ by Shankar Vedantam
In a November post, Risky Business (Part 2), I described how quantitative financial analysts, so-called “quants,” had applied Browian motion from physical sciences—visually described as a bell curve—to market prices. I further described how Benoit Mandelbrot observed that the behavior of prices in financial markets frequently demonstrated huge leaps to the outer edges of the bell curve. When plotted on a chart, the curve produced bubbled out on both ends, and became known as “fat tails.” According to Mandelbrot, the standard bell curve was not applicable to model financial markets because, “Large price changes are much more frequent than predicted.”
Now comes research from Ernest O'Boyle Jr., of Longwood University's College of Business and Economics, and Herman Aguinis at Indiana University's Kelley School of Business that challenges the long-held assumption that the bell curve describes how humans perform. An abstract for the research titled, “The Best and the Rest: Revisiting the Norm of Normality of Individual Performance,” published in the Spring 2012 issue of Personnel Psychology, states, in part, that:
“We revisit a long-held assumption in human resource management, organizational behavior, and industrial and organizational psychology that individual performance follows a Gaussian (normal) distribution. We conducted 5 studies involving 198 samples including 633,263 researchers, entertainers, politicians, and amateur and professional athletes. Results are remarkably consistent across industries, types of jobs, types of performance measures, and time frames and indicate that individual performance is not normally distributed—instead, it follows a Paretian (power law) distribution. Assuming normality of individual performance can lead to misspecified theories and misleading practices. Thus, our results have implications for all theories and applications that directly or indirectly address the performance of individual workers including performance measurement and management, utility analysis in preemployment testing and training and development, personnel selection, leadership, and the prediction of performance, among others.”
An excerpt from an NPR report titled, “Put Away The Bell Curve: Most Of Us Aren’t ‘Average’,” states, "We looked at researchers, we looked at entertainers, we looked at politicians, and we looked at collegiate as well as professional athletes," Aguinis said in an interview. "In each of these kinds of industries, we found that a small minority of superstar performers contribute a disproportionate amount of the output."
If the research is correct, it has huge implications for organizational behavior and human resource management (OBHRM), industrial and organizational (I-O) psychology, and other related fields. Again, quoting from the research:
“Quite simply, if performance is not normally distributed, theories that directly or indirectly build upon individual job performance and its prediction may need to be revisited. In addition, popular practices (e.g., utility analysis of preemployment tests and training and development interventions), which also rely on the assumption of individual performance normality, would also need to be revisited.”
The above graph on the left shows a Gaussian (normal or bell curve) distribution, and the graph on the right shows a Paretian (power law) distribution. The Gaussian distribution indicates that the majority of people in a random sample will be average performers, while a relatively equal minority of people will underperform and overperform the average. The Paretian distribution indicates that a small minority of people, in the random sample, will far outperform the majority.
