Improved forecasting considering dynamic properties within the time series of customer demands
Bernd Scholz‐Reiter, Mirko Kück, Christian Toonen · International Conference on Signal Processing · 2011
Increasing complexity and dynamics of today's markets involve volatile customer demands. These conditions complicate a company's sales forecast. However, high-quality data on future sales is of eminent importance for a substantiated long- and middle-term planning of production programs, schedules and resources. Common forecasting methods are mostly based on quantitative and stochastic characteristics. Methods of nonlinear dynamics enlarge the supply of classical and specialized methods by considering deterministic structures within the customer-related time series. The paper at hand presents the research approach of a project which links quantitative and qualitative characteristics of customer demands with the selection and application of suitable forecasting methods emphasizing methods of nonlinear dynamics.