After creating predictive models for drivers of so many HR outcomes in the past 20+ years, there is one fundamental truth that has stood the test of time. The most actionable models require as much art as they do science.
Earlier in our careers in people analytics, we were preoccupied by creating the “best possible” predictions. After all, organizations were asking us where their greatest risks were in hiring, engaging, developing, promoting and retaining talent. What would be more important than the accuracy of those predictions?
Here’s the problem. Generally, albeit not always, the best predictions may not provide sufficient