Enterprises have been relying on predictive algorithms to help make critical business decisions for awhile now. They are used in a variety of different areas of business and across multiple industries, however they are highly instrumental in inventory management and control. The problem is that large scale, major events can cause even the best designed and developed algorithms to fail. This is exactly what is happening now as result of the COVID-19 pandemic. The article below describes just how unreliable algorithms can become when not adjusted according to changing external factors.
Even during a pandemic, Walmart’s supply chain managers have to make sure stores and warehouses are stocked with the things customers want and need. COVID-19, though, has thrown off the digital program that helps them predict how many diapers and garden hoses they need to keep on the shelves.
Normally, the system can reliably analyze things like inventory levels, historical purchasing trends, and discounts to recommend how much of a product to order. During the worldwide disruption caused by the COVID-19 pandemic, the program’s recommendations are changing more frequently. “It’s become more dynamic, and the frequency we’re looking at it has increased,” a Walmart supply chain manager, who asked not to be named because he didn’t have permission to speak to the media, told The Verge.
Most retail companies rely on some type of model or algorithm to help predict what their customers will want, whether it be a simple Excel spreadsheet or a refined, engineer-built program. Normally, those models are fairly reliable and work well. But just like everything else, they’re affected by the pandemic.
