Retail

Retail Demand Forecasting

25%Inventory cost reduction

The Opportunity

A national retailer with 500+ SKUs was struggling with overstock and stockouts. The company was losing $5M annually to inventory inefficiency. Existing forecasting relied on spreadsheets and gut instinct, missing seasonal patterns and trends.

Our Solution

We implemented time-series forecasting using ensemble models that combine Prophet with custom gradient boosting. Automated reorder triggers integrate with the ERP system, and an executive dashboard provides real-time visibility into demand signals.

The Results

25%

Cost reduction

15%

Fewer stockouts

3 months

Payback period

500+

SKUs optimized

Tools & Technologies

PythonProphetSparkDatabricksTableau

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