Using confirmed future orders to improve chemical demand forecasting

SupChains reports redesigning Vantage’s demand-planning process, changing forecast granularity and using confirmed future orders as machine-learning features. The case study reports a 19% accuracy improvement and a reduction in planning-cycle time from 15 to six days.

Confirmed orders should be treated as predictive signals rather than added mechanically to a baseline. Governance is needed around order dates, cancellations, missing expected orders, forecast horizons and the risk of double counting.