Overview
This engagement focused on transforming the supply chain operations of a global retail giant. By unifying fragmented data sources and deploying a custom AI forecasting engine, we optimized replenishment decisions across 500+ stores, directly impacting the bottom line.
The Challenge: Inventory Fragmentation
A leading retail chain struggled with legacy inventory management systems that resulted in:
- Frequent Stockouts: High-demand items were often unavailable, leading to lost sales.
- Excess Overstock: Millions of dollars were tied up in slow-moving inventory.
- Manual Replenishment: Store managers spent hours manually adjusting orders based on intuition rather than data.
Our Approach: AI-Driven Demand Forecasting
Sterlites implemented a multi-layered AI solution to modernize the retail chain’s operations:
- Unified Data Feature Store: Consolidated POS, ERP, and external signals (weather, local events) into a clean, real-time feature store.
- Hierarchical Forecasting: Built a demand forecasting model per SKU x store with hierarchical reconciliation to ensure consistency across regions.
- Automated Order Recommendations: Implemented a system that auto-suggests ordering quantities based on predicted demand and lead times.
- Control Tower Visibility: Enabled a centralized dashboard for executive visibility with proactive alerting and “what-if” simulations.
The Results
The transformation delivered immediate and measurable value within the first six months:
- 37% Reduction in Stockouts: Significantly improved product availability and customer satisfaction.
- $15M Working Capital Freed: Decreased excess inventory by 42% through precision ordering.
- 3.5% Gross Margin Improvement: Optimized pricing and reduced markdowns on overstocked items.
- Rapid ROI: The project achieved full return on investment within the first two quarters of deployment.