They are often gifted in a certain way (often a combination of skill, passion, drive, and energy) and they actually do drive orders of magnitude more value than many of their peers. These are the people who start companies, develop new products, create amazing advertising copy, write award winning books and articles, or set an example for your sales force.
These "hyper performers" are people you want to attract, retain, and empower.
BELL CURVE PERCENTAGES SOFTWARE
Some software engineers are 10X more productive than the average some sales people deliver 2-3X their peers certain athletes far outperform their peers musicians, artists, and even leaders are the same. Think about how people perform in creative, service, and intellectual property businesses (where all businesses are going). If you think about your own work experience you'll probably agree that this makes sense. (Bill Gates used to say that there were a handful of people at Microsoft who "made" the company and if they left there would be no Microsoft.) In fact the implication is that comparing to "average" isn't very useful at all, because the small number of people who are "hyper-performers" accommodate for a very high percentage of the total business value.
So the concept of "average" becomes meaningless. Roughly 10-15% of the population are above the average (often far above the average), a large population are slightly below average, and a small group are far below average. In the Power Curve most people fall below the mean (slightly). It has very different characteristics from the Bell Curve. Rather these groups fall into what is called a " Power Law" distribution.Ī "Power Law" distribution is also known as a "long tail." It indicates that people are not "normally distributed." In this statistical model there are a small number of people who are "hyper high performers," a broad swath of people who are "good performers" and a smaller number of people who are "low performers." It essentially accounts for a much wider variation in performance among the sample. found that performance in 94 percent of these groups did not follow a normal distribution.
and Herman Aguinis (633,263 researchers, entertainers, politicians, and athletes in a total of 198 samples). Research conducted in 20 by Ernest O’Boyle Jr. Third, most of the people are always in the middle - rated more or less "average." And implicit in this last assumption is the idea that most of the money and rewards go to the middle of the curve.(The "idea" behind this is that we'll continuously improve by lopping off the bottom.) So if your team is all high performers, someone is still at the bottom. Second, we force the bottom 10% to get a low rating, creating "losers" in the group.First, we ration the number of "high performance ratings." If you use a five point scale (similar to grades), many companies say that "no more than 10% of the population gets a rating of 1" and "10% of the population must be rated a 5.".This practice creates the following outcomes: To avoid "grade inflation" companies force managers to have a certain percentage at the top, certain percentage at the bottom, and a large swath in the middle.
In the area of performance management, this curve results in what we call "rank and yank." We force the company to distribute raises and performance ratings by this curve (which essentially assumes that real performance is distributed this way).
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