Forced Ranking and the Bell Curve: How Outdated HR Practices Undermine Employee Performance

According to the practice of “forced ranking,” in order to develop, a company has to identify its best and worst performers and then “nurture” the winners and rehabilitate/discard the “losers.” While this concept makes sense, its implementation poses great risks, because many companies use the Bell Curve to plot, and ultimately reward, employee performance. The Bell Curve (also known as normal distribution) assumes there is an equal number of high performers and low performers, and that most employees fall into the average category.

You might be wondering — what’s the point of working for an organization which expects that most of its employees are mediocre performers? This is precisely the problem of using the Bell Curve. By limiting the number of high performers and reducing performance to above/below average, managers undermine employees’ actual contributions and miss potential high performers.

This representation is not only inaccurate, but it can harm an organization’s workforce, as documented by a recent MIT study (Punishing by Rewards: When the Performance Bell-curve Stops Working For You):

As the bottom performers depart, the rigid distribution of the bell-curve forces managers to categorize a high performer (when compared to the rest of the labor market) as a mediocre. A high performer, unmotivated by such artificial demotion, behaves like a mediocre. Further, in a shrinking company, managers find it difficult to differentiate employees. As a result, they begin to reward visible performance over the actual. Beyond a certain point, the erosion of social capital has the potential to cripple the company.

This process:

  • Alienates and demoralizes high performing employees who get labeled as average
  • Encourages “average” employees to be content with being the status quo, because higher rankings are limited
  • Instills fear in your employees, instead of incentives to grow

Here’s an alternative model which better reflects employee performance:

Source

Instead of placing employee performance above or below an average, the Power Law distribution model visualizes more subtle categories such as near-high performers, or potential high performers (the endmost end of the red line) all the way to low performers (the beginning of the red line). These claims are backed by research which compared Power Law (Paretian) and Bell Curve (Gaussian) distribution:

In accordance with a Paretian distribution, the “picture of performance” resembles a ski slope. The typical performer would fall below the mean or average result. So there would be approximately 80% below average, 10% around the middle, and 10% exceeding; meaning that the assumption that the typical performer is average is a myth of the normal distribution assumption. The results lend themselves to the “80 / 20 rule”, which assumes at 80% of the work is done by 20% of the people.

In other words, Power Law distribution is a more accurate performance management tool than the Bell Curve, because it accounts for a much wider variation in low and high performance.

To quote Josh Bersin:

The really big difference between the “bell curve” and the “power curve” is that the power curve reflects the fact that a small number of people deliver an inordinate amount of contribution — hence the “long tail.” This means that “most people” are below the mean. It does NOT imply that most people are lower performers, only the fact that the variability of performance is high and that the curve should not be equal above and below the mean.

Here’s what you can do to escape the average employee nonsense:

a) Consider the outcomes of using a traditional “rank and yank” system. As we’ve seen above, a five point scale couldn’t possibly account for the diversity in employee talent. In fact, according to research by Deloitte, less than 30% of all organizations feel their existing process drives any level of performance or engagement at all.

It’s clear that being ranked against an average is inaccurate and demoralizing (not to mention that it creates a “Game of Thrones” environment). This is why the world’s most successful companies are getting rid of nonsensical rankings and embracing “continuous development.”

b) Rank employees according to what they achieved (competency ranking) — not against each other. A successful performance management process rewards actual over visible performance.

While the Bell Curve model might be sufficient for assembly line workers, whose working conditions cap how well they are able to perform, the Power Law distribution encourages the recognition and development of your best employees — the ones who go above and beyond what’s expected of them. According to Josh Bersin, companies which follow Power Law distribution “focus very heavily on collaboration, professional development, coaching, and empowering people to do great things.”


Originally published at nextlevelwork.com

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