Managers often believe their workforce distribution is some kind of bell curve. Research says NO.
There is a long-standing belief in business that people performance follows the Bell Curve. This belief has been embedded in many business practices: performance appraisals, compensation models, and even how we get graded in school. (Remember “grading by the curve?”)
So if you still manage by the old bell curve distribution myth, you might want to consider these facts.
First the Myth
Research shows that this statistical model, while easy to understand, does not accurately reflect the way people perform. As a result, HR departments and business leaders inadvertently create agonizing problems with employee performance and happiness.
A bell curve distribution describes a population as having highs and lows with a large percentage in the middle.
The Bell Curve represents what statisticians call a “normal distribution.” A normal distribution is a sample with an arithmetic average and an equal distribution above and below average like the curve below.
This model assumes we have an equivalent number of people above and below average, and that there will be a very small number of people two standard deviations above and below the average (mean).
The model essentially says that “we will have a small number of very high performers and an equivalent number of very low performers” with the bulk of our people clustered near the average.
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).
To avoid “grade inflation” companies force managers to have a certain percentage at the top, a certain percentage at the bottom, and a large swath in the middle.
I don’t know where it started, but this has been ingrained in the mindset of managers for decades. And it’s blatantly flawed logic.
But Does Reality Work This Way?
The answer is NO.
Research conducted in 2011 and 2012 by Ernest O’Boyle Jr. and Herman Aguinis (633,263 researchers, entertainers, politicians, and athletes in a total of 198 samples). found that performance in 94 percent of these groups did not follow a normal distribution. Rather these groups fall into what is called a “Power Law” distribution.
A “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.
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” account for a very high percentage of the total business value.
(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.)
How the Bell Curve Hurts Performance
Right now there is an epidemic of interest in revamping employee performance management processes, and it’s overdue.
Here are five reasons this old myth does not work.
No one wants to be scored on a 5 point scale.
First, much research shows that reducing a year of work to a single number is degrading. It creates a defensive reaction and doesn’t encourage people to improve. Ideally, performance evaluation should be “continuous” and focus on “always being able to improve.” That’s why I recommend the Big 5 Performance model.
In fact, David Rock’s research shows that when we receive a “rating” or “appraisal” our brain shifts into “fear or flight” mode and shifts to our limbic brain.
Ultra-high performers are incented to leave and collaboration may be limited.
The bell curve model limits the quantity of people at the top and also reduces incentives to the highest rating. Given the arbitrary five-scale rating and the fact that most people are 2,3,4 rated, most of the money goes to the middle.
If you’re performing well but you only get a “2” or a “3” you’ll probably feel under-appreciated. Your compensation increase may not be very high (most of the money is held for the middle of the curve) and you’ll probably conclude that the highest ratings are reserved for those who are politically well connected.
Since the number of “1’s” is limited, you’re also likely to say “well I probably won’t get there from here so I’ll work someplace where I can really get ahead.”
Mid level performers are not highly motivated to improve.
In the bell curve there are a large number of people rated 2, 3, and 4. These people are either (A) frustrated high performers who want to improve, or (B) mid-level performers who are happy to stay where they are.
If you fall into category (B) you’re probably pretty happy keeping the status quo – you know the number of “1’s” is very limited so you won’t even strive to get there. In a sense the model rewards mediocrity.
Compensation is inefficiently distributed.
People often believe the bell curve is “fair.” There is an equal number of people above and below the average. And fairness is very important. But fairness does not mean “equality” or “equivalent rewards for all.”
High performing companies have very wide variations in compensation, reflecting the fact that some people really do drive far more value than others.
In a true meritocracy, this is a good thing, as long as everyone has an opportunity to improve, information is transparent, and management is open and provides feedback.
Incentives to develop and grow are reduced.
In a bell curve model, you tend to reward and create lots of people in the “middle.” People can “hang out” in the broad 80% segment and rather than strive to become one of the high-performers, many just “do a good job.”
This is fine of course, but I do believe that everyone wants to be great at something – so why wouldn’t we create a system where every single person has the opportunity to become a star?
Time to Change the Performance Practices
As I go out and talk with HR leaders about this process I’m finding that almost every major company wants to revamp their current approach. They want to make it simpler, focused on feedback, and more developmental.
But in addition to considering these practices, make sure you consider your performance philosophy. Does your management really believe in the bell curve?
Or do you fundamentally believe there are hyper-performers to be developed and rewarded? If you simplify the process but keep the same distribution of rewards and ratings you may not see the results you want.
Look at how sports teams drive results: they hire and build super-stars every single day. And the pay them richly. If you can build that kind of performance management process in your team, you’ll see amazing results.
Here is another link to an article by the original researchers.
Author’s Note: excerpts contained herein are contributed by Josh Bersin, founder of Bersin, Deloitte