Stay Metrics creates new predictive driver turnover model

Stay Metrics, providers of an evidence-based driver engagement platform, research, and analytics that enable motor carriers to retain more of their best drivers, announces the next generation of its predictive driver turnover model.

Stay Metrics company logoWith the new Predictive 2.0 model, Stay Metrics is providing motor carriers with insights on why drivers leave their companies. The model’s computer algorithms extrapolate data from the company’s full product suite, which has been integrated into a single database.

The full product suite of Stay Metrics includes:

  • 7-day orientation and 45-day onboarding interviews to identify driver expectations, experiences, and satisfaction levels at critical periods for preventing early turnover.
  • The Driver Satisfaction survey, an in-depth annual survey and report that identifies areas of strength and weakness for clients using peer group and year-over-year trend analysis.
  • Exit interviews that capture the reasons why drivers leave in their own words.
  • Custom research.
  • A privately branded online rewards, recognition and driver engagement platform. The online platform doubles as a data collection tool for driver turnover by tracking driver activations and deactivations.

To date, Stay Metrics has collected more than 5 million individual driver responses from more than 50,000 completed annual Driver Satisfaction surveys. Predictive 2.0 uses each carrier’s survey responses to correlate the factors that are causing driver dissatisfaction — home time, dispatchers, or pay among many other possibilities — with their turnover data.

The Predictive 2.0 model was developed by Dr. Timothy Judge, Stay Metrics’ director of research who is the Joseph A. Alutto Chair in Leadership Effectiveness at the Ohio State University’s Fisher College of Business.

“The typical approach is to lump all data together and then extrapolate the overall prediction to a carrier. This would work well if all carriers were alike, but we know that they are not,” said Judge. “Our Predictive 2.0 model does often identify common denominators in terms of what attitudes predict turnover, but I am generally struck by how the results differ fundamentally across carriers. One size definitely does not fit all.”

Stay Metrics delivers insights to clients from its Predictive 2.0 model, from the Driver Satisfaction survey and ongoing research on a quarterly basis through consultation sessions.

“During our quarterly consultations, we translate results from the model into practical strategies and prescriptions that will reduce turnover. We hold our clients accountable for acting on their data to increase driver engagement, satisfaction and to move their needle for driver retention,” said Tim Hindes, chief executive officer of Stay Metrics.