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Retail · Regional retail chain (placeholder)

Cutting stockouts with demand forecasting

Replaced spreadsheet-based ordering with a demand-forecasting pipeline, reducing stockouts and excess inventory across 40+ locations.

AI InnovationAI Implementation

28% reduction in stockouts

15% lower excess inventory

Forecasts refreshed daily instead of weekly

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The challenge

The client managed ordering for 40+ locations using spreadsheets and intuition. Popular items sold out while slow movers tied up cash in overstock. Leadership wanted a data-driven approach without a multi-year platform project.

What we did

We ran a two-week discovery to prioritize the highest-impact SKUs, then built an incremental forecasting pipeline:

  • Consolidated point-of-sale and inventory data into a single warehouse.
  • Established a baseline forecast and layered in seasonality and promotions.
  • Delivered store-level order recommendations to managers through a simple dashboard.

The outcome

Within one quarter, the pilot regions saw a 28% reduction in stockouts and 15% less excess inventory. Just as importantly, store managers trusted the recommendations because the process was transparent and explainable.

Why it worked

We focused on a narrow, measurable problem first, shipped quickly, and expanded only after the approach proved itself — the same pattern we apply to every engagement.

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