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Published: July 15, 2002


The Folly of Forced Ranking

Mythic leaders like Jack Welch swear by distribution curves to remove low performers. But there are pitfalls in playing the percentage game.

Illustration by Lars Leetaru
General Electric Company’s former CEO Jack Welch is among the most vocal and articulate advocates of performance management systems that force turnover of the lowest-performing employees each year. At GE, it’s the bottom 10 percent of employees who are supposed to be eliminated. Mr. Welch feels so strongly about this practice that he highlighted it in his 1999 letter to GE shareholders and advocated it again in his book Jack: Straight from the Gut (Warner Books, 2001). In addition to arguing that a forced ranking or distribution system is good for organizations, he reasons it is good for individuals because it takes people who are failing out of situations that are bad for them and the company.

GE is not alone in using this system. Similar policies have been adopted by Ford Motor, Conoco, Sun Microsystems, Cisco Systems, EDS, Enron, and a host of other U.S. corporations.

At first glance, it makes sense to systematically identify and remove the worst employees. They can be replaced by better employees, and ridding the organization of poor performers also sends a strong message of low tolerance for poor results. But is using a system that requires the firing of a certain number of underachievers the best way to create a high-performance organization? My research suggests it is not.

Companies certainly need methods and processes to accurately identify people who are not making the grade. But quota systems don’t work for many reasons, including flaws in the normal distribution curve approach that is used to identify poor performers, as well as limitations in human judgment. In fact, systems that force managers to cut a certain percentage of their people often don’t reveal the root causes of problems, often do not elevate performance, and can ultimately be counterproductive.

Potential legal exposure is also a problem with quota systems. Numerous court cases in the U.S. have challenged the use of forced ranking or distribution systems. In 1975, I was an expert witness in a class-action age discrimination suit against the Sandia Corporation that focused on the validity of its forced distribution appraisal system. Sandia lost the case precisely because it couldn’t prove that the forced distributions it created led to valid measures of individual performance. Recently, Ford Motor Company, reacting to the same problem, abandoned its forced distribution system after the company was threatened with lawsuits.

Allowing poor performers to continue as they are in a company isn’t acceptable either. Indeed, doing so can be very destructive, ultimately promoting a culture in which employees believe substandard performance is all right, and good performers leave because they don’t want to be part of an organization that accepts less than the best from its people.

My quarrel isn’t with the premise that companies need to identify and eliminate poor performers. Setting high standards, and dealing with those people who don’t meet or exceed them, is necessary in order to continuously improve organizational performance. The issue is how to do this effectively. What are the best methods for properly and fairly identifying poor performers, for motivating individuals and developing their talents, and for cutting losses for the individual and the company when someone is not working out?

Kinks in the Curve
The notion that the bottom 5 or 10 percent of employees can be eliminated every year assumes that the performance of individuals fits a normal distribution curve (Jack Welch calls it the vitality curve). In a normal distribution of employees, the number of average performers is large and flanked by a small number of outstanding and poor performers. In some work groups or departments, the employees actually do fit a normal distribution; however, there is no reason to assume that this will always, or even frequently, be the case.

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