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Retail Chain

Smarter Demand Forecasting Across 120 Stores

Turning point-of-sale noise into store-level forecasts the merchandising team could actually trust.

Smarter Demand Forecasting Across 120 Stores — platform overview

24%

Less Excess Inventory

120

Stores Onboarded

99.9%

Pipeline Uptime

This retail chain's planning team was fighting a losing battle against spreadsheets. We helped them replace manual forecasting with a self-service platform their merchandising team could actually trust.

The Challenge

Forecasting demand was a manual, spreadsheet-driven process maintained by a small team, with no way to account for seasonality, promotions, or local store trends. The result was chronic overstock in slow-moving categories and stockouts on bestsellers — tying up working capital while leaving revenue on the table.

Our Approach

We designed a demand forecasting and inventory optimization platform that ingests point-of-sale, supplier, and promotional calendar data, and generates store- and SKU-level forecasts automatically. A self-service layer lets merchandising and supply chain teams adjust assumptions and see the forecast update in real time.

  • Automated ingestion of POS & supply chain data
  • Store-level & SKU-level demand models
  • Promotion & seasonality-aware forecasting
  • Self-service adjustment layer for merchandising teams

Technologies Used

dbtSnowflakePythonPower BIAirflow

The Results

Inventory allocation became a data-driven process instead of a guessing game, freeing up working capital and improving on-shelf availability across the chain.

For the first time, our merchandising team trusts the forecast enough to act on it without double-checking it in a spreadsheet.

VP of Supply Chain, Retail Chain client

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