Actions Taken

·      Implemented machine learning forecastingmodels (ARIMA, ARIMAX, ensemble approaches) at both SKU and aggregated producthierarchy levels.

·      Automated generation of replenishment orders,in-stock, and stock-out reports.

·      Developed analytics dashboards to compareactual vs forecasted sales and inventory across dimensions.

Outcomes Achieved

·      Achieved 90+% accuracy at store leveland 85+% accuracy at product level.

·      Automated inventory replenishment across 1,500+stores.

·      Significantly reduced merchandiseredeployment costs.

·      Improved inventory control and planningefficiency at scale.

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