It’s graduation season. Scores of students leaving high school and college (and kindergarten, for that matter) are being told they can do anything, accomplish anything, achieve anything. They’re the best and the brightest, we say.
But what if most of us are simply average … or below?
“The Best and the Rest,” co-authored by Herman Aguinis of the IU Kelley School of Business in Bloomington and published in the Spring 2012 issue of Personnel Psychology, has attracted a lot of attention. A story and interview this week on NPR’s Morning Edition program brought the research into the news in this season of commencements.
Essentially, Aguinis, a Dean’s Research Professor and professor of organizational behavior and human resources, and Ernest O’Boyle, of Longwood University, have debunked the “norm of normality” regarding individual performance, as expressed in the familiar bell curve. Their “remarkably consistent” results, they say, offer a strong challenge to the long-held assumption that most of us cluster in the middle.
In fact, the researchers conclude that “most performance outcomes are attributable to a small group of elite performers.” Aguinis and O’Boyle say the data on individual performance is best represented not by the peaked bell curve that bulges up in the middle (called a Gaussian curve), but rather by a Paretian curve, which looks something like a very steep ski-jump that flattens out at the end.
The researchers carried out five separate studies using 198 samples that included 633,263 researchers, entertainers, politicians, and athletes. In each of the five studies, the steep-slope curve yielded a “superior fit” for the data, meaning that most performers fell into a lower category:
Based on Study 1, we discovered that nearly two thirds (65.8%) of researchers fall below the mean number of publications. Based on the Emmy-nominated entertainers in Study 2, 83.3% fall below the mean in terms of number of nominations. Based on Study 3, for U.S. representatives, 67.9% fall below the mean in terms of times elected. Based on Study 4, for NBA players, 71.1% are below the mean in terms of points scored. Based on Study 5, for MLB players, 66.3% of performers are below the mean in terms of career errors.
In other words, a small number of “top performers account for the majority of results.” In each of the different groups, superstars account for most of the success, with everyone else performing below the mean, or mathematical average.
As Aguinis and O’Boyle point out, their results call into question “the usual definitions of fairness and bias, which are based on the norm of normality” and lead to some “thorny and complicated” issues in the workplace and beyond. For example:
- How does the demonstrated impact of top individuals affect the ubiquitous belief that teamwork improves performance?
- Is the productivity of teamwork “negated by the loss of individual output of the elite worker [who is] slowed by non-elites?”
- Is it ethical for organizations “to allocate most of their resources to an elite group of top performers to maximize firm performance?”
- Should “separate policies be created for top performers, given that they add greater value to the organization than the rest?”
In his interview with NPR’s Morning Edition, Aguinis said the study’s findings were “descriptive, not prescriptive” and “should not be interpreted to mean that managers and teachers should only focus on the superstars and ignore everyone else.” Still, he suggests, some organizations may choose to focus on the small minority of superstars “who contribute a disproportionate amount of the output.”
As they discussed Aguinis’s work, NPR correspondents David Greene and Shankar Vedantam called themselves “disturbed” by the notion that most of us are below-average performers. In a society where we standardize-test students to exhaustion and demand a higher metric for every move, such disturbance is understandable.
But …could striving for average be OK? If 70 or 80 percent of us fall short of the norm, then perhaps being average is an acceptable goal. What’s wrong with average?