In the years following its 2004 IPO, Google needed a way to continue its impressive growth without losing its best people to hot startups like Facebook and Twitter.

Laszlo Bock, who became the SVP of Google's People Operations in 2006, writes in his new book, "Work Rules!" that he and Google's leadership spent years determining how to keep the retention rate of top talent as high as possible.

They decided on a counterintuitive strategy: to "pay unfairly."

As Bock writes (our bold):

At Google, we ... have situations where two people doing the same work can have a hundred times difference in their impact, and in their rewards.

For example, there have been situations where one person received a stock award of $10,000, and another working in the same area received $1,000,000. This isn't the norm, but the range of rewards at almost any level can easily vary by 300% to 500%, and even then there is plenty of room for outliers.

In fact, we have many cases where people at more "junior" levels make far more than average performers at more "senior" levels. It's a natural result of having greater impact, and a compensation system that recognizes that impact.

Bock admits that a policy to "pay unfairly" is provocative, and that it might be better characterized as "pay unequally." In his view, it is actually more fair to pay a top performer significantly more than an employee with the same job title who produces less value.

To follow his logic, you might think of a company like a baseball team. The Detroit Tigers, for instance, pay Justin Verlander $28 million because he's a Cy Young Award-winning pitcher that they don't want to see on the roster of another team.

Bock writes that even though Google prides itself on hiring only elite performers, its employees fall into a power-law distribution (as opposed to a bell curve), in which the large majority of employees are "below average" and its few top performers bring up the average.

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He cites a 2012 report from Longwood University's Ernest O'Boyle and Indiana University's Herman Aguinis that analyzed human performance across various fields, from academia to professional sports. For example, a normal distribution model (in which the median is the average) predicted the number of artists with more than 10 Grammy nominations would be five. In reality, it was 64.

They found that a power law distribution fit almost every field they studied.

"Ten percent of productivity comes from the top percentile, and 26% of output derives from the top 5% of workers," O'Boyle and Aguinis write.

As Bock notes, this means that "the top 1% of workers generated 10 times the average output, and the top 5% more than four times the average."

The exceptions to this observation, O'Boyle and Aguinis explain, include "industries and organizations that rely on manual labor, have limited technology, and place strict standards for both minimum and maximum production" — essentially anywhere there's little opportunity to be exceptional.

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Bock says managers at any company should ask, "How many people would you trade for your very best performer? If the number is more than five, you're probably underpaying your best person. And if it's more than ten, you're almost certainly underpaying."