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.
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.
The findings of the study support the adoption of CFE as a more relevant commercial decision‐making measure than commonly applied statistical forecast measures.
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.
This study is the first published cost assessment of SAP®'s forecasting models.
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/10.1108/02635570810876796Download as .RIS
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