Catt’s aim with this paper is to equip forecasters with some cross-disciplinary theory on forecastability and to provide practical techniques for assessing how forecastable a historical time series is. A time series is a sequence of values at equally spaced time intervals: days, weeks, months, quarters, or years. The historical time series can be viewed as an outcome (realization) of an underlying data generating process (DGP). Assessments of forecastability require an understanding of the DGP and its components. Copyright International Institute of Forecasters, 2009
PurposeThe 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/approachThe 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.FindingsThe findings of the study support the adoption of CFE as a more relevant commercial decision‐making measure than commonly applied statistical forecast measures.Practical implicationsThe 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/valueThis study is the first published cost assessment of SAP®'s forecasting models.
Purpose The purpose of this article is to provide a critique of SAP's enterprise resource planning (ERP) (release ECC 6.0) forecasting functionality and offer guidance to SAP practitioners on overcoming some identified limitations. Design/methodology/approach The SAP ERP forecasting functionality is reviewed against prior seminal empirical business forecasting research. Findings The SAP ERP system contains robust forecasting methods (exponential smoothing), but could be substantially improved by incorporating simultaneous forecast comparisons, prediction intervals, seasonal plots and/or autocorrelation charts, linear regressions lines for trend analysis, and event management based on structured judgmental forecasting or intervention analysis. Practical implications The findings provide guidance to SAP forecasting practitioners for improving forecast accuracy via important forecasting steps outside of the system. Originality/value The paper contributes to the need for studies of widely adopted ERP systems to critique vendor claims and validate functionality through prior empirical research, while offering insights and guidance to SAP's 12 million+ worldwide enterprise system practitioners.
PurposeThe purpose of this article is to provide a critique of SAP's enterprise resource planning (ERP) (release ECC 6.0) forecasting functionality and offer guidance to SAP practitioners on overcoming some identified limitations.Design/methodology/approachThe SAP ERP forecasting functionality is reviewed against prior seminal empirical business forecasting research.FindingsThe SAP ERP system contains robust forecasting methods (exponential smoothing), but could be substantially improved by incorporating simultaneous forecast comparisons, prediction intervals, seasonal plots and/or autocorrelation charts, linear regressions lines for trend analysis, and event management based on structured judgmental forecasting or intervention analysis.Practical implicationsThe findings provide guidance to SAP forecasting practitioners for improving forecast accuracy via important forecasting steps outside of the system.Originality/valueThe paper contributes to the need for studies of widely adopted ERP systems to critique vendor claims and validate functionality through prior empirical research, while offering insights and guidance to SAP's 12 million+ worldwide enterprise system practitioners.
Professional doctorate candidates engage in discipline specific investigations linking practical questions with current developments and creating new knowledge in computing and information technology as an outcome. Course content and a constructivist pedagogy is described and exemplified for a professional doctorate in computing and information technology in New Zealand. Both academic and student responses to the program are described. Problems and points of tension are identified, and solutions discussed.
Professional doctorate candidates engage in discipline specific investigations linking practical questions with current developments and creating new knowledge in computing and information technology as an outcome. Course content and a constructivist pedagogy is described and exemplified for a professional doctorate in computing and information technology in New Zealand. Both academic and student responses to the program are described. Problems and points of tension are identified, and solutions discussed.
