Research findings from Ernest O’Boyle and Herman Aguinis should have rocked the corporate world in 2012. Instead, it was business as usual.
Google, however, was one company that took notice. O’Boyle and Aguinis found that in a number of different fields, human performance followed the power law distribution rather than a normal distribution. This means that in most corporations, there are a small amount of people contributing the bulk of the results rather than a larger band of people with slightly varying degrees of performance.
The conventional wisdom of the normal distribution coupled with conventional pay practices can lead companies to create a vicious talent cycle, especially at the lowest levels of the company.
Picture a highly talented new employee getting hired into a company. They complete 24 projects per year, while the average employee completes six. To reward the top talent, that person gets 10% higher compensation at year end. They are satisfied for now, but start to look towards next year and realize that even if they are much much more efficient and effective than their colleague they know there is not much upside to working so hard.
The choice becomes between mailing it in and putting it on cruise control or quitting. As I’ve seen over and over again, the talented employee ends up leaving. Even more, the average person, due to their tenure and the companies commitment to promotions on a time-based cycle gets promoted. The new top talent they hire is going to be even more frustrated than the last person.
The cycle repeats until the company is full of average people and the company hires a consultant to figure out why it is not successful anymore.
Companies need to take a step back and stop looking at metrics like attrition and ask themselves instead “are the right people staying?” and “are the right people leaving?”
