Forecast and production order accuracy for stochastic forecast updates with demand shifting and forecast bias correction

Klaus Altendorfer, Thomas Felberbauer

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this paper a general demand model for the supplier is developed based on practically observed customer forecasting behaviours. A rolling horizon information update approach is assumed where customers provide their forecasts for a predefined information horizon. In the basic situation, a MMFE (martingale model of forecast evolution) demand model is assumed where information updates are unbiased. This setting is extended to a situation where updates are biased, i.e., a forecast update does not necessarily imply an information improvement. Furthermore, the model is extended by a demand shifting behaviour, i.e., demands for certain periods may be shifted to other periods. For this practically motivated demand model, the forecast accuracy related to periods before delivery is calculated and a measure for production order accuracy is developed assuming a simplified material requirements planning structure. Finally, a correction method for reducing the negative effects of biased demand forecasts is introduced and its performance is evaluated based on simulation and real company data.

Original languageEnglish
Article number102740
JournalSimulation Modelling Practice and Theory
Volume125
DOIs
Publication statusPublished - May 2023

Keywords

  • Case study
  • Forecast accuracy
  • Forecast updates
  • Material requirements planning
  • Production planning
  • Simulation

Fingerprint

Dive into the research topics of 'Forecast and production order accuracy for stochastic forecast updates with demand shifting and forecast bias correction'. Together they form a unique fingerprint.

Cite this