Assessing forecast model performance in an ERP environment

Abstract

Purpose

The paper aims to describe and apply a commercially oriented method of forecast performance measurement (cost of forecast error – CFE) and to compare the results with commonly adopted statistical measures of forecast accuracy in an enterprise resource planning (ERP) environment.

Design/methodology/approach

The study adopts a quantitative methodology to evaluate the nine forecasting models (two moving average and seven exponential smoothing) of SAP^®'s ERP system. Event management adjustment and fitted smoothing parameters are also assessed. SAP^® is the largest European software enterprise and the third largest in the world, with headquarters in Walldorf, Germany.

Findings

The findings of the study support the adoption of CFE as a more relevant commercial decision‐making measure than commonly applied statistical forecast measures.

Practical implications

The findings of the study provide forecast model selection guidance to SAP^®'s 12+ million worldwide users. However, the CFE metric can be adopted in any commercial forecasting situation.

Originality/value

This study is the first published cost assessment of SAP^®'s forecasting models.

Citation

Catt, P.M., Barbour, R.H. and Robb, D.J. (2008), "Assessing forecast model performance in an ERP environment", Industrial Management & Data Systems, Vol. 108 No. 5, pp. 677-697. https://doi.org/10.1108/02635570810876796