Reduced supply chain and credit risks across 20K customers with machine learning
Food & Beverages
The client is a leading global QSR that owns multiple fast-food brands and a chain of stores worldwide. Their supply chain network setting was very complex with 30+ distribution centers and 10,000+ store locations. Their existing inventory strategy was to set a static number on Safety Stock. However, the demand and supply variability were never the same. As a result, inadequate Safety Stock often led to severe backlog or out-of-stock scenario, which in turn impacted the company’s revenue.
ElectrifAi’s ML-powered inventory optimization product helped the client in identifying demand and supply patterns, and recommend the optimal Safety Stock for each SKU. Not just that—as new data came in, our ML model continuously learned itself and improved, enabling the client to optimize their inventory management operations significantly.