Smarter Stock Management with Demand Forecasting & Dynamic Re-ordering
Too many items were selling out, while slow-movers sat on shelves tying up cash. In four weeks we proved that AI-driven demand forecasting plus a dynamic re-order engine could halve stock-outs, cut inventory holding cost by 17 %, and lift GMROI nearly 30 %—all without swapping out the client’s existing ERP.
The
Challenge
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Stock-outs - lost revenue and unhappy customers
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Over-stock - cash locked in slow items and occupying space in warehouse
Traditional rule-of-thumb safety stock wasn't keeping up with noisy demand, promotions and seasonality.
The POC Approach
Results from the 3-Month Backtest
“This model didn’t just predict demand—it told us exactly what to order and when. Stock-outs halved and our cash finally started working for us.”
- CEO & Founder, Cat Store
Why This Proof of Concept is Successful
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SKU-specific intelligence - Fast movers, seasonal items, and slow lines each get bespoke forecasts and buffers.
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Real-world uncertainty baked in - Monte-Carlo safety stock protects against promo spikes and supplier delays.
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Zero new infrastructure - Runs off nightly CSV drops; results feed straight back into the client’s ERP purchasing module.
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Clear, actionable output - Buyers get a simple “buy this many, now” sheet—no black-box stats required.