Big Promise, Big Peril in Big People Data
Firms can use analytics in Machiavellian ways that might boost the bottom line in the short run but bruise workers and harm reputations over the long haul.
The analytics knife cuts both ways.
That is, the reams of data around employees—what I propose to call Big People Data—can be used for good or for ill. I was reminded of this by a story I just heard from Brian Kelly, a partner at advisory firm Mercer.
A Mercer client in the retail industry was concerned about turnover, and suspected that its full-time employees were the most valuable to its bottom line. But the numbers showed otherwise. It turned out that the most productive employees were part-timers who were given a certain amount of overtime. And who had been working for less than 12 months.
As a result, the client became less concerned about turnover among part-timers after a year on the job.
To me, this is something of a hair-raising tale. It seems like a case of taking advantage of workers desperate for jobs and hours. And it seems like an unsustainable model for the long run. What happens to the client’s employment brand over time, if it becomes clear the retailer cares mostly for newcomers and doesn’t care much about a long-term relationship with employees? Will it continue to attract good workers if and when the economy picks up? Will its sales droop as a result?
Kelly, a leader of Mercer’s analytics practice, saw this point of view. And he suggested ways that smart data analytics can point the way to a better situation for both employees and employers. In particular, Kelly said the client should seek to elongate that period of top performance for part-time employees, and could experiment with different hypotheses. Could longer manager tenure make a difference in stretching out peak performance? What about moving employees into new roles? Maybe a fresh start in a job is key to workers’ enthusiasm and productivity?
Knowing how to pose such questions and then find the data to answer them highlights the way Big People Data is really both “an art and a science,” Kelly says.
Kelly’s proposals also get at the way that hard-headed analysis can result in soft-hearted actions toward employees. But not necessarily. As the retailer in this story suggests, companies can use analytics in Machiavellian ways that might boost the bottom line in the short run but bruise workers and harm reputations over the long haul. Make no mistake—the era of Big People Data is going to be bloody at times.
Ed Frauenheim is senior editor at Workforce Management. Comment below or email email@example.com.