Omnitracs introduced its Omnitracs ELD Driver Retention Model, a predictive modeling solution that allows companies to identify and retain truck drivers who are most likely to voluntarily leave their jobs.
“The Omnitracs ELD Driver Retention Model allows fleets of all sizes to reap the benefits of predictive modeling to prevent driver turnover and address the root causes of voluntary termination,” said Brad Taylor, Omnitracs vice president of data and IoT solutions. “In a 500 driver fleet, preventing just half of the voluntarily turnover in the most at-risk group of drivers saves nearly $29,000 per month in direct hiring costs.”
Omnitracs ELD Driver Retention Model uses the data that companies are already collecting through electronic hours-of-service (HOS) applications to detect subtle changes in driver habits, which can then be key indicators of their desire to voluntarily leave their jobs, according to the company. These individual driver logs produce more than a thousand pieces of data related to hours worked, customer site delays, lack of hours and amount of activity on the clock. According to Omnitracs, the ELD Driver Retention Model can leverage not just Omnitracs’ own HOS data, but HOS data generated by competitive solutions.
“The ELD Driver Retention Model is the first of a suite of solutions from Omnitracs to help the fleet management industry capitalize on the Interstate of Things—Omnitracs’ vision for the industry to capture, understand and manage data created from the connected devices in the entire transportation industry, including trucks, streetlights and toll roads, in order to make more efficient, data-driven decisions,” the company said.
“Omnitracs also arms users with the knowledge and techniques to enable fleets to manage fatigue at the driver and organizational level,” the company added. “Users can proactively engage drivers through training and intervention programs to increase driver safety and satisfaction, improve driver-manager relationships and ultimately prevent driver turnover.”