HOUSTON. It’s no question that driver retention is a problem facing all fleets, no matter how big or small. During a session at Trimble’s in.sight user conference, Chris Orban, vice president of data science in the Trimble Transportation Division and Onavie Boyce, BI consultant for DAWG alerting system for data warehouse, dove into driver turnover and solutions on how to overcome it.
“Wouldn’t it be nice to treat drivers as human beings and not numbers?” started Orban. “Going back many years ago, it was not possible for the safety manager I was working with to get the first and last name of the driver in the system. They could get the truck number that the driver was assigned to, and they can get the driver ID number, but not their first and last name. That’s kind of crazy, right? We have to remember that drivers are people, too.”
Orban explained how expensive it is to replace a driver when they leave – anywhere from $8,000 to $10,000 depending on the company. Some of these costs include advertising, staff labor costs, testing fees, recruitment fees, orientation fees, cost of safety, training fees, referral/sign on bonus, costs for idle equipment and more.
But what drives turnover? Orban suggested money, hometime, freight type, work load and respect all play a role in driver turnover with each reason having its own solution. Paying drivers for performance, guaranteed home time, accessorial pay and fatigue monitoring were all potential solutions presented by Orban. But what solutions are out there for respecting the driver?
According to Orban, understanding your driver’s career path, hearing their voice while at the same time making your voice heard as well, being committed to doing what you say you’re going to do as a fleet because trust is a two-way street are all possible solutions to respecting the driver.
Boyce, on the other hand, suggests that recognizing a driver’s age when they leave the fleet matters just as much as the length of that driver’s service, their performance, the organizational structure of the fleet as well as the understanding of the marketplace all matter in realizing a fleet’s retention rate.
Enter Vusion Driver Analytics, a driver retention software integrated within the TMW Suite, a transportation management program.
Through Vusion, fleet managers can use these factors to determine whether or not a driver is more or less likely to leave their fleet:
- Driver predictive score: single point for dispatchers to see if a driver is in danger of leaving the company
- Retention predictor: field that indicates the predictor that is most influential on the driver’s predictive retention score.
- View driver’s trip history, driver pay, expiration, accidents, HOS, and provide driver coaching records.
For example, if a driver is unhappy because he’s driving too many cross-country trips and not being able to see his family as much, a fleet manager could see that noted in the coaching records and maybe assign that driver to some trips closer to home. Making a simple change like that could make the difference between the driver staying or leaving the fleet.
“For me, it’s about having the right conversation with the right driver at the right time,” Orban said. “Over the time I’ve been doing predictive driver retention, I have seen that if you have the right conversation with the driver before they make that decision to leave, you can change that turnover rate by 50%. That’s a pretty powerful number.”