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1、The role of the forecasting process in improving forecast accuracy and operational performancePamela Danesea, Matteo Kalchschmidtb,naDepartment of Management and Engineering, University of Padova, Stradella S. Nicola, 3, 36100 Vicenza, ItalybDepartment of Economics and Technology Management, Univers
2、it?a degli Studi di Bergamo, Viale Marconi 5, 24044 Dalmine (BG), Italya r t i c l e i n f oArticle history: Received 15 April 2008 Accepted 7 September 2010 Available online 16 September 2010Keywords: Demand forecasting Global manufacturing research group Hierarchical regression Forecast accuracya
3、b s t r a c tSeveral operations decisions are based on proper forecast of future demand. For this reason, manufacturing companies consider forecasting a crucial process for effectively guiding several activities and research has devoted particular attention to this issue. This paper investigates the
4、 impact of how forecasting is conducted on forecast accuracy and operational performances (i.e. cost and delivery performances). Attention is here paid on three factors that characterize the forecasting process: whether structured techniques are adopted, whether information from different sources is
5、 collected to elaborate forecasts, and the extent to which forecasting is used to support decision-making processes. Analyses are conducted by means of data provided by the fourth edition of the Global Manufacturing Research Group survey. Data was collected from 343 companies belonging to several ma
6、nufacturing industries from six different countries. Results show that companies adopting a structured forecasting process can improve their operational performances not simply because forecast accuracy increases. This paper highlights the importance of a proper forecasting-process design, that shou
7、ld be coherent with how users intend to exploit forecast results and with the aim that should be achieved, that is not necessarily improving forecast accuracy.Armstrong, 2001; Caniato et al., 2002a, b). Forecasting management is a complex issue and companies candecidetoleverondifferentfactorstoredes
8、igntheir forecasting process (Mentzer and Bienstock, 1998; Moon et al., 2003). A plethora of studies have discussed the adoption of forecasting techniques, both quantitative and/or qualitative, as an important opportunity for elaborating accurate forecasts (Mentzer and Cox, 1984; Dalrymple, 1987, Sa
9、nders and Manrodt, 1994; Sanders and Ritzman, 2001). However, several researchers suggested that forecasting technique adoption is not enough to guarantee good forecast accuracy and that studies on forecastingshould consider also other crucial topics linked to how the forecasting process is managed
10、and organized (Armstrong, 1987; Mentzer and Bienstock, 1998; Moon et al., 2003). Forecasting managementincludesdecisionsoninformation-gathering processes and tools (e.g., what information should be collected, how it should be collected), organizational approaches to be adopted (e.g., who should be i
11、n charge of forecasting, and what roles should be designed), interfunctional and intercompany collaboration for developing a shared forecast (e.g., using different sources of information within the company or supply network, joint elaboration of forecasts, etc.) and measurement of accuracy(e.g., usi
12、ng the proper metric and defining proper incentive mechanisms).Thus,theunderstandingofhowimproving forecasting to minimize forecast error requires studying not only the relationship between forecasting techniques and forecast accuracy, but also the impact of other forecasting levers linked to foreca
13、sting process management. In line with these considera- tions,inthispaper,differentelementscharacterizingthe forecasting process will be considered and, in particular, the techniques adopted, the information combined to elaborate forecasts and the role of forecasting in supporting decision making wi
14、thin the company. In literature, these are often mentionedascrucialforecastingvariablesforsignificantly reducing forecast errors (Fildes and Hastings, 1994; Mentzer and Bienstock, 1998; Moon et al., 2003) (see Section 3.1).Contents lists available at ScienceDirectjournal homepage: J. Production Eco
15、nomics0925-5273/$-see front matter fax: +39 035 0252077.E-mail addresses: pamela.daneseunipd.it (P. Danese), matteo.kalchschmidtunibg.it (M. Kalchschmidt).Int. J. Production Economics 131 (2011) 204214Improving the forecasting process is often considered critical in order to obtain more accurate for
16、ecasts. Forecast accuracy is often considered a necessity because large forecast errors usually negatively affect companies operational performance, especially cost and delivery performance (Vollmann et al., 1992; Ritzman and King, 1993; Enns, 2002; Zhao and Xie, 2002; Kalchschmidt et al., 2003). Thus improving the forecasting process can have a positive indirect effect on operational performance through forecast accuracy improvements. However, recent studies
