Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Assessing forecast model performance in an ERP environment

Assessing forecast model performance in an ERP environment 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Management & Data Systems Emerald Publishing

Assessing forecast model performance in an ERP environment

Loading next page...
 
/lp/emerald-publishing/assessing-forecast-model-performance-in-an-erp-environment-BuSXSx1PPx
Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0263-5577
DOI
10.1108/02635570810876796
Publisher site
See Article on Publisher Site

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.

Journal

Industrial Management & Data SystemsEmerald Publishing

Published: May 23, 2008

Keywords: Manufacturing resource planning; Demand forecasting; Error analysis

References