AI-Driven Supply Chain Automation for National Retailer
Automating supply chain workflows and reducing stock-outs by 41%
The Challenge
A national retailer with 380+ stores across Australia was managing demand forecasting, purchase orders, and supplier coordination through a patchwork of spreadsheets and disconnected systems. Stock-outs were costing an estimated $12M annually, while overstock in other categories tied up working capital.
Our Approach
We built an intelligent supply chain automation platform that integrates demand forecasting ML models with automated purchase order generation and supplier communication workflows. The system ingests POS data, seasonal patterns, promotional calendars, and external signals like weather data to optimise inventory levels dynamically.
The Outcome
Stock-outs reduced by 41% across all categories. Overstock levels decreased by 28%, freeing $8.6M in working capital. Purchase order processing that previously took 3 days per cycle now completes in under 4 hours, and the forecasting model achieves 91% accuracy at the SKU-store level.
Stock-outs
Forecast Accuracy
Capital Freed
Technology Stack
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