Getting inventory levels right is one of the hardest things a retailer needs to manage. Now AI has come to the rescue...naturally.
Walmart has been in the forefront of retail technology almost since its founding more than six decades ago. Now it’s once again taking a lead position in using AI tech to help forecast sales and manage its inventory levels. This holiday season will be a big test in gauging how well the system performs.
Initially launched in 2019, the Walmart Inventory Management System, as it’s known internally, is an AI-powered software platform that helps the giant retailer forecast demand based on any number of factors, from the broadest parameters like the overall economy to localized weather predictions. For the 2023 season, the technology has been improved giving Walmart new tools to understand shopping patterns.
“The inventory management system is going to be key, and we are super excited to use it this upcoming holiday season and serve our customers in a much better and improved way,” Parvez Musani, senior vice president of Walmart Global Tech, recently told the online newsletter Retail Brew. He said that in the past the company used historic data to predict upcoming purchasing patterns but that wasn’t enough to know what was likely to happen in the future. He
In addition to predictive indicators like inflation, job numbers and weather forecasts, the systems looks at other factors that might not have previously been able to understand without AI technology.
“Now we are even looking at how people are searching,” he told Retail Brew. “Those types of things will influence [our models] as we get closer to the holiday season, and we will react to them and position inventory accordingly in our stores.”
Of course, any forecasting system, no matter how smart, can never anticipate totally unpredictable factors like COVID or freak weather patterns that impact shopping patterns. Still, the Walmart 7 software represents a real use for AI beyond writing press releases or blog posts. Musani said in the interview that the goal is to make it easier to “constantly tune” its data and use that to make “strong recommendations” to the entire chain.