Getting Predictive With AI
Can emerging technology help predict operational risks so distributors can head off problems?
The answer is yes, and transportation is a case in point.
Dot Foods is leveraging an AI-powered solution that employs predictive analytics to boost driver safety and efficiency. It proactively identifies risky driver behaviors and helps modify patterns before negative incidents take place.
“The solution creates a risk score for the driver,” based on factors such as speed, harsh braking and accidents, said Tim Eckhardt, senior director of Safety for the distributor. “We then follow up with a personal development plan for coaching, training and monitoring. The goal is for scores to improve in the coming months.”
Eckhardt said this data-driven strategy has enabled the company to lower accident rates by record levels in three out of the past four years. He will be outlining Dot’s journey in an education session at the IFDA Solutions Conference called “Harnessing Predictive Analytics and AI in Transportation.”
“We operate with multiple locations across the U.S. and in Canada, so the progress is different by location,” he said. “But this solution has put us in really good shape overall.”
Predictive capabilities are useful for other transportation applications as well, such as to better understand maintenance needs for tractors and trailers, Eckhardt observed. “We are focusing on solutions for transportation both inside and outside the cab.”
One of the most important success prerequisites is the need for ample amounts of data. “The predictive AI works best when you have a lot of good data to input,” he emphasized.
Dot is excited about the future potential for predictive capabilities in its business.
“We’re just getting started,” he said.
IFDA’s 2025 Foodservice Distribution Industry Technology Report shows that 37% of companies in this industry use or plan to use AI for driver behavior monitoring. Among companies employing truck-related automation, 57% use automated driver behavior alerts (audio, sensory or visual alerting to distractions, eye movement, head-angle, etc.), and 42% use driver safety features (collision avoidance, lane departure, etc.).
Article authored by freelance writer David Orgel.
