The language of “average” is pervasive. Reservation centers calculate the “average” number of calls a customer service representative can handle in an hour. Restaurant chains project staffing needs by estimating how many servers are needed to staff the “average” restaurant. In sales organizations, territories are divided up based on how many prospects the “average” salesperson can handle. “Average” is everywhere.
The best managers wouldn’t necessarily disagree with this kind of “average thinking.” They would admit that the effective management of a company requires some way of approximating what is going on every day within the company. However, they disagree vehemently when this “average thinking” bleeds into the management of people. Unfortunately it happens all the time.
They might not be aware of it, but many managers are fixated on “average.” In their mind they have a clear idea of what they would consider to be an acceptable level of performance; what sales organizations often call a “quota.” This quota, this performance “average,” serves as the barometer against which each individual’s performance is assessed. So, for example, a manager may give her employees a rating based upon how far above or below “average” their performance lies. She may calculate her employees‘ bonuses by figuring out the correct proportion of the “average” bonus each should receive. And, probably the most obvious symptom of “average thinking,” she may well spend most of her time trying to help her strugglers inch their performance up above “average,” while leaving her above average performers to their own devices.
This kind of “average thinking” is very tempting. It seems so safe and so practical—by focusing on your strugglers you are protecting yourself, and the company, from their inevitable mistakes. Nonetheless, great managers reject it.
Here are a couple of reasons why. First, they don’t use average performance as the barometer against which each person’s performance is judged. They use excellence. From their perspective, average is irrelevant to excellence.
Second, they know that the only people who are ever going to reach excellence are those employees who are already above average. These employees have already shown some natural ability to perform the role. These employees have talent. Counterintuitively, employees who are already performing above average have the greatest room for growth. Great managers also know that it is hard work helping a talented person hone his talents. If a manager is preoccupied by the burden of transforming strugglers into survivors by helping them squeak above “aver‑
Age,” he will have little time left for the truly difficult work of guiding the good toward the great.
Jean P.’s story illustrates both the irrelevance of average and the growth potential of talent.
For data entry roles, the national performance average is 380,000 keypunches per month, or 19,000 per day. Many companies use an average performance measure like this to determine how many data entry employees they need to hire. Upon hiring these data entry folk, a good manager should probably be able to raise his employees‘ performance higher than this national average. How much higher? Using this average as your measure, what should a good manager’s goal be-25 percent higher? 35 percent higher? 50 percent higher? Fifty percent higher would put you over 500,000 keypunches per month. In fact, the top- performing data entry employees make a mockery of the national average. They outperform it almost tenfold.
Jean P. is one such employee. When she was first measured, she averaged 560,000 punches per month, already 50 percent above the national average. She was recognized for her performance, then she and her manager set out some individual goals that could help her improve and track her performance. Three months later she hit a million keypunches. A couple of weeks after that milestone, Jean checked her total at the end of the day and saw that she had managed 112,000 keypunches in one day. She approached her manager and said, “You know what? If I average over 110,000 for the whole month, then I’ll hit the 2 million mark.” They put a plan together, and six months later she soared past 2 million.
Jean became a model for the role. Her manager spent time watching her, asking her why she loved her work so much—”I’m real competitive; I love counting”—and why she seemed to make fewer mistakes the more keys she punched—”I have more practice.” He designed a talent profile to find more like her and a compensation plan to reward her excellence. Today Jean’s personal best is 3,526,000 keypunches in a month, and the average of all the data entry employees working around her is over a million.
The lessons from Jean’s story are applicable to almost any role. Don’t use average to estimate the limits of excellence. You will drastically underestimate what is possible. Focus on your best performers and keep pushing them toward the right-hand edge of the bell curve. It is counterintuitive, but top performers, like Jean P., have the most potential for growth.
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