A shopper fills her virtual cart with the items she wants, goes to check out, confirms the details, and clicks a button to complete the purchase.
Then what happens? The question is fundamentally important for retailers. Efficiently fulfilling customer orders—sending them from the right place at the right time—can generate huge savings.
One tactic that has emerged to capture these savings is a brief delay between when a customer completes a purchase and when the merchandise is actually picked from the shelf and prepared for shipment. Missing, though, has been a theoretical foundation to explain how and why this practice makes sense. Using data from one of China’s largest online retailers, JD.com, Chicago Booth PhD student Yaqi Xie, Columbia’s Will Ma, and Booth’s Linwei Xin built a model and conducted a series of experiments to estimate the benefits of delay.
They find that the potential savings can be attributed to more information about future demand: the longer a company waits to fulfill one customer’s order, the more it learns about other orders as they arrive.
Xin offers a hypothetical example of three Chicago-based consumers placing separate orders with Amazon. The first customer orders shoes and a jacket. Ten minutes later, one customer buys toothpaste and the same shoes, and the other purchases the jacket and candy.
Amazon has the choice of filling the first order from a smaller local warehouse or a bigger distant one. However, the local warehouse stocks only one unit of each item. Therefore, if it fills the first order locally, it has no choice but to route the second and third orders to the faraway warehouse.
“If you instead wait for a short period, then you can route the first order to a more distant warehouse and fill more orders locally,” he says, noting that this would reduce shipping costs. “The benefits of delay are about making better decisions with more information.”