Machine Learning · Retail
Demand Forecasting & Inventory Planning
A forecasting model that cut stock-outs and freed working capital.
−30%
Stock-outs
+15%
Inventory turnover
Weekly
Automated plans
The challenge
Planning relied on spreadsheets and gut feel, leading to frequent stock-outs on fast movers and overstock on slow ones.
Our solution
We unified sales, promotions and seasonality data into a warehouse, trained gradient-boosted forecasting models per product group, and surfaced weekly order recommendations in a dashboard.
PythonXGBoostPostgreSQLPower BI
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