A supermarket chain was failing to match the inventory stock of its products with customer demand during peak seasons. It would manually estimate the sales for a peak season, including identifying fast and slow moving products.

These estimates were consistently wrong and led to overstocked warehouses with devaluing inventory, limiting liquidity and working capital.

By deploying AI, the company developed actionable insights in real-time, which predicted and identified where items sold best. This took the guesswork out of inventory allocation to match product performance and demand requirements.

Based on these improvements, the merchants could procure more of the right inventory for the specific locations to meet demand while reducing inventory levels and improving working capital utilisation.