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Why do organizations that stack-rank employees force-fit employee rankings to a bell curve? Is there any theoretical or emperical evidence to support a normal or near-normal distribution of performance. My personal experience, which is obviously biased, suggests that if at all there's a general trend in employee performance, it's closer to a power law distribution.

Note: Asking here instead of SO Workplace because I'm looking for any kind of research: papers, books, studies on the topic.

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  • $\begingroup$ There's no content or meaning to "curving" rankings, because it's purely a mathematical operation that always can be done on any dataset: what matters is how the results are used. Could you elaborate? $\endgroup$ – whuber Jan 16 at 14:52
  • $\begingroup$ I meant assigning ratings following bell curves. So most of the employees get average ratings, few get good or bad and still fewer get great or terrible ratings and the distribution of ratings is made to follow a normal curve. $\endgroup$ – farhanhubble Jan 16 at 15:01
  • $\begingroup$ Where I'm struggling is that even without curving the ratings, the top ones will be good and the bottom ones will be bad when the ratings are compared to each other. It doesn't matter what numbers are attached to them. So what would be useful to know is exactly how the organization interprets and acts on the ultimate numerical values that might be assigned by the rating process. $\endgroup$ – whuber Jan 16 at 18:53
  • $\begingroup$ I think my use of "force-fit" is causing the confusion since the ratings are being computed from a normal distribution. What I meant by force-fitting was changing the data (ratings) to fit a hypothesis (normal distribution). $\endgroup$ – farhanhubble Jan 17 at 2:38

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