Forecasting Case Study: ML-driven forecasts for a manufacturer with promotions

Nicolas Vandeput
5 min readSep 12, 2022

Using cutting-edge machine learning models, SupChains delivered a forecasting model that helped an international manufacturer to reduce their forecast error by 20% compared to the benchmark.

The client is now using this model as a baseline for its monthly demand planning process. On top of the extra forecasting accuracy resulting in fewer lost sales and obsolete inventory, this new model reduced the workload of the demand planning team. The model is also used to generate demand scenarios with and…

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Nicolas Vandeput

Consultant, Trainer, Author. I reduce forecast error by 30% 📈 and inventory levels by 20% 📦. Contact me: linkedin.com/in/vandeputnicolas