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The Application Of Power Law Distribution Theory To HR?

Published by on November 1, 2012

My wife is reading What the Dog Saw by Malcolm Gladwell (Amazon).  She brought the book to my attention because of the potential implications of power law distribution theory to human resources.  (How’s that for a mouthful?)  You have to click thru to learn more. A power law distribution looks like this: (Source:  Wikipedia.)  Unlike […]

My wife is reading What the Dog Saw by Malcolm Gladwell (Amazon).  She brought the book to my attention because of the potential implications of power law distribution theory to human resources.  (How’s that for a mouthful?)  You have to click thru to learn more.

A power law distribution looks like this:

(Source:  Wikipedia.)  Unlike the bell curve distribution that everyone is familiar with — and apparently assumes is a normal distribution for just about everything — recent studies have shown that performance is more accurately reflected on a power law distribution.  So what are the implications of that for HR?

One recent study challenges the long-held view that employee performance is measured on a bell curve and looks at the implications of that for HR.  The author of the study is quoted as saying that “All five of our studies suggest that organizational success depends on tending to the few who fall at the ‘tails’ of this distribution, rather than worrying too much about the productivity of the ‘necessary many’ in the middle.”  SHRM references the study here.

One blog post discusses the issue with respect to employee value:

Is employee value described by a power law distribution or a normal distribution? I was struck by a recent Zuckerberg quote, “Someone who is exceptional in their role is not just a little better than someone who is pretty good,” he said. “They are 100 times better.” Even Paul Allen, the cofounder of Microsoft, wrote in his autobiography, “A great programmer can outproduce an average one by ten to one; with a genius, the ratio might be fifty to one.” I would reinterpret this as a ‘Power Law view of employee value’. I’ve argued for some time that employees with scalable skill sets are worth more than those with unscalable skill sets (an idea I picked up from Dr. Lester Thurow in Zero Sum Society), but I’ve never seen this reflected in salary information. What is the value of someone (Jeff Bezos) who builds a company (Amazon) of 33,700 employees that will soon surpass Wal-mart (572,000 employees) in revenues? Blockbuster laughed when Reed Hastings tried to sell them his patent, and instead created Netflix. What is the value of his insight and that patent now? I would argue that the abnormal returns that entrepreneurs can and have earned over the past three centuries are proof that employee value is a power law distribution. This in turn indicates that most companies seek abnormal returns by paying employees according to a normal distribution, and that Zuckerberg just wants to arbitrage the market inefficiency.

Evaluate Individuals Rather Than Populations Capital One was the first credit card company to use microsegmentation and they were the fastest growing stock on the SP500. Progressive Insurance regularly targets low-risk individuals within unattractively risky populations such as elderly motorcycle owners vs the general motorcycle owner market. If microsegmentation has been fine tuned for customer application, then why have no governments applied it to social problems, or companies applied it to recruiting? It seems like HR would would be an ideal area of application, especially considering it’s already been done in professional sports… so what’s the hold up?

(Competitive Advantage via Quantitative Methods)

It is easy to see how the implications of power law theory in the area of employee value, performance management, training and compensation will be significant.  The question, however, is whether the data can be used to move away from the status quo.  As the author of the above study notes, “[d]edicating extra effort, time or money toward a handful of employees will seem anathema to managers or human-resource professionals accustomed to thinking in terms of parity, what’s best for all or most, or what’s applicable to a set pay grade or position.”

What about employee discipline (or the flip-side of value)?  The same blog post summarizes one of Gladstone’s examples:

Excessive Force in the LAPD and the Power Law Distribution

The LAPD has endured numerous accusations of excessive force over the years. The unwritten assumption has been that the majority of officers earned the same number of accusations and that they clustered around an average. In fact though, accusations of excessive force per officer obey a power law distribution:

  • 6,700 officers had zero accusations of excessive force over a four year period
  • 1,400 officers had one or two accusations over a four year period
  • 183 officers had four or more complaints
  • 44 officers had 6 or more complaints
  • 16 officers had 8 or more complaints
  • 1 officer had 16 complaints

Absent this data, “you’d propose solutions that would raise the performance of the middle—like better training or better hiring—when the middle didn’t need help.” The Christopher commission (responsible for investigating the systematic nature of the excessive force allegations) “gives the strong impression that if you fired those forty-four cops the L.A.P.D. would suddenly become a pretty well-functioning police department.” Think about the significance of this statement… firing 0.5% of the LAPD would instantly convert it into an exemplary law force whereas training programs would doubtfully produce concrete results. Isn’t the immediate, concrete solution a powerful tool for improvement? Doesn’t this tool arise directly because we’ve challenged the normality assumption?

What are the implications of these studies for the current normative way of thinking in human resources?  Is power law theory relevant to diversity training (the value of which has already been questioned)?  For example, should employers be devoting significant resources to train the “vast middle” on principles of nondiscrimination — or should employers be devoting those resources to training employees who have demonostrated a lack of sensitivity in this area (and who, according to power law distribution theory, are most likely to be repeat offenders)?

This is certainly a topic worth keeping an eye on.

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