PERSONNEL PSYCHOLOGY 2012, 65, 79–119
THE BEST AND THE REST: REVISITING THE NORM OF NORMALITY OF INDIVIDUAL PERFORMANCE
ERNEST O’BOYLE JR. Department of Management College of Business and Economics Longwood University HERMAN AGUINIS Department of Management and Entrepreneurship Kelley School of Business Indiana University
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 re- searchers, entertainers, politicians, and amateur and professional ath- letes. Results are remarkably consistent across industries, types of jobs, types of performance measures, and time frames and indicate that in- dividual 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 in- cluding performance measurement and management, utility analysis in preemployment testing and training and development, personnel selec- tion, leadership, and the prediction of performance, among others.
Research and practice in organizational behavior and human resource management (OBHRM), industrial and organizational (I-O) psychology, and other fields including strategic management and entrepreneurship ul- timately build upon, directly or indirectly, the output of the individual worker. In fact, a central goal of OBHRM is to understand and predict the performance of individual workers. There is a long-held assumption in OBHRM that individual performance clusters around a mean and then fans out into symmetrical tails. That is, individual performance is assumed to follow a normal distribution (Hull, 1928; Schmidt & Hunter, 1983;
A previous version of this paper was presented at the Annual Meetings of the Academy of Management, San Antonio, Texas, August 2011. We thank Wayne L. Winston for his insightful comments regarding data analysis issues. Correspondence and requests for reprints should be addressed to Herman Aguinis, De- partment of Management and Entrepreneurship, Kelley School of Business, Indiana Univer- sity, 1309 E. 10th Street, Suite 630D, Bloomington, IN 47405-1701; [email protected].