AI-Driven Replenishment Optimization Case Study

This case study details the implementation of Algonomy's Order Right solution for a leading grocery retailer in South East Asia, addressing significant challenges in demand and replenishment planning. The client faced issues such as frequent stockouts, overstock situations, and difficulties in leveraging retail data due to the need for data science support. The objective was to find a scalable AI/ML-based solution to enhance order planning accuracy and inventory management. The Order Right system utilized custom machine learning algorithms to adapt to hyperlocal demand and supply chain dynamics, resulting in a 63% reduction in out-of-stock instances and a 17% decrease in inventory costs, translating to savings of $1.5 million. The solution enabled automated replenishment based on advanced forecasting techniques, significantly improving demand forecast accuracy for 90% of SKUs and streamlining inventory management across multiple locations. This transformation allowed the client to mitigate supply chain disruptions and optimize inventory levels effectively.