Supply Chain Management relies heavily on forecasts, e.g. of future demand or future prices. Most applications, however, use static forecasting models in the sense that past data is used for model construction and evaluation without being updated adequately when new data becomes available.We propose a dynamic forecasting methodology and show its effectiveness in a real-world application.