Inventory management or warehouse management is a bigger challenge than it appears to be. But, it’s not impossible to minimize the losses that occur due to over/under-stocking.

Real-time data allows grocery stores and supermarkets to forecast the potential sales and demand of their items through predictive analytics, highlighting which items are in demand and those to discard. This removes the problem of stock that’s just taking up space on shelves and not selling; this solution reduces overall inventory costs, ensures high-demand items are always in stock, and increases potential revenue.
Some older forecasting techniques work on products as clusters and can’t take the local dynamics into account. A good AI model can make predictions about products at a granular level considering local and regional trends.