The Evolution of Workforce Analytics

You’ve probably heard of predictive analytics, where “miners” review historical data to predict future trends and events. Over the last few years, HR has started using the practice to predict employee performance, calculate the impact and ROI of benefit and bonus programs, and even estimate the success of a new manufacturing plant or store.

The goal of these pioneers is to quantify the impact of human capital and help executives make fact-based decisions instead of relying on intuition or perception. For example, Starbucks, Limited Brands, and Best Buy have used data to quantify the value of a one percent increase in engagement among employees at a particular store, and AT&T has discerned that certain traits like taking initiative are a better predictor of a candidate’s success than a degree from a top-notch university.

So what have these pioneers learned? Well, according to Carl Schleyer, director of Workforce Analytics for Sears Holding Corp., the key to a successful analytics program is focusing on behaviors instead of outcomes. Schleyer insists that behavioral metrics bring action to your data and drive change within your organization, as long as someone pays attention to the data and takes corrective action. He also insists that the metrics must be relevant to the end-user and focus on solving a particular problem.

For those embarking on an analytical voyage, here are Schleyer’s other recommendations. Do you agree with his list?

  • Measure behaviors, not outcomes
  • Measure results, not activity
  • Define the key behaviors that drive desired business outcomes
  • Measure less, not more
  • Make measurable what is not