Demand-Driven Replenishment – Grocery Distribution
The Challenge:
A grocery distributor serving 85 retail stores used static reorder points resulting in 22% stockout situations on high-velocity items and 31% of inventory aged over 60 days. Manual replenishment planning consumed 15 hours weekly per planner, limiting responsiveness to demand changes and promotional activities.
The Solution:
Deployed Azure AI forecasting models on Fabric analyzing POS data, weather patterns, local events, and promotional calendars to predict store-level demand. Power Automate generated recommended replenishment orders reviewed via Power Apps. Power BI tracked forecast accuracy and inventory turnover by category and store.
Result:
Stockouts reduced from 22% to 4.5%, aged inventory decreased from 31% to 9%, and overall inventory turns improved from 18 to 27 annually. Planner productivity increased 60%, and improved product availability drove 6.2% increase in retail sales for participating stores.