In an era when same-day delivery is table stakes for retailers and manufacturers, pressure on profit margins is also a given. Consumers have come to expect less and less delay between ordering and delivery, and shipping fees have become a cost of doing business. Buy-online-pick-up-in-store (BOPIS) fulfillment relieved some of the pressure, but that has given way to curbside pickup, forcing retailers to shift back-end delivery costs to front-end labor costs.
As more goods and materials are bought exclusively online, retailers and manufacturers are optimizing their approach to inbound and outbound logistics. They are also dealing with the reverse logistics of customer returns. Timely data about supplier performance, outbound shipping, and parcel routing becomes a competitive advantage.
Most logistics and shipping teams still juggle spreadsheet models in their quest to shave small percentages off shipping costs. Although spreadsheets are easy to use, they’re rarely up to the task of quickly bringing together data from multiple sources covering supply chains, shipping, and delivery. Automated workflows can collect and blend data sets in areas as diverse as the transportation performance of suppliers, the effect of shipping costs on profits, and optimal routes for delivery. Instead of cobbling data from multiple sources together in spreadsheets, logistics staff can let analytics perform the heavy lifting while they take actions based on the results.