A Lesson in Using Predictive Analytics to Drive Retention

A Lesson in Using Predictive Analytics to Drive Retention

When we talk to HR leaders about predictive analytics, the first thing they usually want to do with this new advanced tool is improve retention. That’s definitely easier said than done, especially if you want the project to actually drive results, instead of just being an interesting research topic. Aliah Wright at SHRM highlights the success story of one organization that had a strong need to retain its highly skilled employees and used predictive analytics to help meet that goal:

When a top employee at the Anderson Center for Autism, a private school in Staatsburg, N.Y., handed in her resignation, the school’s HR department was expecting her. The HR staff had been using a predictive analytics program to help them gauge retention. “The software is so good that we were developing a retention plan for her as she was preparing to resign,” said Gregg Paulk, director of information technologies for the 92-year-old nonprofit organization. After HR staff spoke with her, “she actually rescinded her resignation,” he added. …

In 2001, the school undertook a new technology initiative spurred and funded by the No Child Left Behind legislation. Using Ultimate Software’s UltiPro, Paulk said the company “grew … and kept head count flat, reduced paper [processes] by 95 percent, and increased the time spent on employee development by 30 percent. The software also allows staff to manage time and attendance from anywhere [and yields] improved reporting and compliance.

“The software also helped us avoid the loss of key talent with predictive tools. It’s really powerful, and it’s astonishing the results we’ve seen,” Paulk said. “[The tools] helped us understand our challenges and put the puzzle pieces together.”

It looks like Anderson has done a couple of things really well, which makes it a great example of how to apply analytics most effectively.

First, they didn’t just choose to focus on retention because it was interesting or they had the data to explore the topic; they were instead trying to solve a problem that was affecting their bottom line. Second, they were focused: They are applying predictive analytic tools to essential employees, not everyone. This hopefully means they can truly understand what is driving their most important employees to leave the organization and stop them. Third, they have gone beyond analysis and numbers to develop clear plans of action when they do discover that a key employee is thinking of leaving.

To be able to take action on insights and data from predictive retention analytics, the most successful organizations think about how they will use those results even before the analysis starts coming in. Who will they share the information with, what steps will HR and managers take to encourage employees to stay, and are those steps the same for all employees?

These best practices apply whether you are managing retention with advanced analytics or with low-tech tools like stay interviews and career conversations. CEB Corporate Leadership Council members can read more about how to measure and mitigate attrition risk here.