
AI Meets Logistics:
The Untapped Goldmine in Retail Backhaul Optimization
With all the hype surrounding AI retailers are often distracted from the core business fundamentals that made them successful in the first place. No where is this more evident than supply chain and getting the product to the store. With transportation for example, the main goals never change, reduce transportation costs wherever possible, and improve service levels to the retailers. Easier said than done. While saving money isn’t necessarily as flashy as increasing sales, the impact to the bottom line is magnified when you reduce costs vs. increasing sales.
Most retailers use round-trip fleets, which fundamentally changes the route optimization challenge, and while technology for getting product to the store has evolved, there’s significant opportunity in leveraging AI to optimize return hauls and store clean-out returns. Those who manage to crack the code on backhaul optimization stand to gain substantial cost savings and service improvements.
In my view, the smartest technology investments are those that tackle these intricate logistics challenges, where artificial intelligence isn’t just flashy, but truly practical in reducing costs and improving operational efficiency. That’s where the biggest gains (and competitive advantages) will come for retailers aiming to stay relevant beyond 2025.
