The inventory glut that U.S. retailers experienced after the covid pandemic has left them cautious about over-ordering for the 2023 holidays, according to an analysis from C.H. Robinson, the transportation and third party logistics provider (3PL).
Many retailers accumulated mounds of safety stock in recent years to ensure they could handle pandemic spikes in demand despite supply chain disruptions like travel bans, port closures, and container backups. But that excess inventory has filled warehouses to the rafters, driving up storage fees and rental rates in the industrial real estate sector.
So now they’re ordering merchandise in smaller amounts – just what they need, as they need it. And with many retailers expecting same-store sales to be down because of inflation-weary shoppers, they’re also hiring less holiday help to keep shelves stocked, C.H. Robinson said. But the downside of following that just in time (JIT) strategy is that it relies on expedited—and often expensive—shipments to meet immediate needs.
“To maximize holiday sales with less inventory and less staff means you need to know with more precision where your inventory is,” Noah Hoffman, head of retail logistics at C.H. Robinson, said in a release. “Before, a retailer would bring in 50 truckloads of TVs in October to make sure all their stores were covered for the holidays. This year, they’re more likely to pull from existing inventory to start and then replenish only if, when and where they need to. If that TV sells fast in Philadelphia but not in Chicago, they’ll order more just for that city or transfer inventory there. Without safety stock lying around, the timing of a retailer’s inbound freight really matters.”
In response, the Eden Prairie, Minnesota-based company says it has increased the accuracy of the predictive estimated time of arrival (ETAs) data it generates for its shipments. C.H. Robinson has now reached 98.2% accuracy in predicting that a truckload shipment will arrive within the appointment window and 92% accuracy in predicting that a less-than-truckload shipment will be on time, the company claims.
- It reached that level by taking a closer look at the data it collects on transportation operations, and making three changes. The company say it:
- Determined which tracking data makes the greatest contribution to accurate ETAs
- Stopped collecting data that is unreliable but typically required of carriers across the industry
- Instituted rules for carriers to provide tracking data at different, more meaningful points in time
Another element in C.H. Robinson’s approach to predictive ETAs is historical data on 20 million shipments a year in 3 million shipping lanes, taking into account things like dwell time at specific warehouses, and allowing the model to make educated guesses about driver behavior, the company said.
“Scale matters when it comes to data science and artificial intelligence, and C.H. Robinson moves more truckload freight than anyone,” Hoffman said. “Other companies providing real-time visibility can notify a retailer that merchandise has arrived late. What retailers actually need is an accurate prediction of whether their merchandise will be on time or not, and people who can do something about it.”
