Watch: How AI Is Influencing Last-Mile Operations

Artificial intelligence isn’t just in the conversation throughout the supply chain. It’s delivering real, measurable value in fleet and last-mile operations, says James Wee, senior vice president and general manager of fleet at Descartes.

Ask fleet operators what’s top of mind today, and expense reduction in last-mile delivery may be at the head the list, Wee says. Not far behind are higher expectations in customer service and on-time delivery. Then, complying with regulations in driver safety and sustainability measures must be taken into account.

As for that number-one consideration, expense reduction, it’s no longer a cyclical issue, Wee says. “It’s a structural issue. Fleet operators need to develop business plans and design their business operations to account for rising costs of fuel and labor, all exacerbated by driver shortages. They’re not cyclical anymore. They’re just part of the day-to-day expectations.”

Historically, planning systems have depended on operational assumptions, but route planning solutions are compromised when underlying assumptions are incorrect, as actual performance often shows. “So the opportunity in the marketplace is to leverage the actual operational execution data to be fed back into the planning system to get highly accurate business route plans,” Wee says.

As it happens, fleet operators have been sitting on lots of data for the last decade or so, but the amount isn’t important, he says. “It’s the signal that data represents, and what issues can be surmised from the data that’s collected.” 

High-performing fleets in the near term will leverage all the data in their business operations, Wee says. That allows them to apply machine learning and analytics to generate the right insights into their business operations, so that they can be data-driven to make good business decisions. “That’s really one of the things that will separate strong fleet operators versus the rest of the pack.”