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The role of the forecasting process in improving forecast accuracy and operational performance

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  • Danese, Pamela
  • Kalchschmidt, Matteo
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    Abstract

    Several 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 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 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 manufacturing 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 should 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.

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    File URL: http://www.sciencedirect.com/science/article/B6VF8-511K3RP-3/2/3b018710b5db10c333f392dc0bc9b0fc
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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 131 (2011)
    Issue (Month): 1 (May)
    Pages: 204-214

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    Handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:204-214

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    Web page: http://www.elsevier.com/locate/ijpe

    Related research

    Keywords: Demand forecasting Global manufacturing research group Hierarchical regression Forecast accuracy;

    References

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    Citations

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    Cited by:
    1. Kalchschmidt, Matteo, 2012. "Best practices in demand forecasting: Tests of universalistic, contingency and configurational theories," International Journal of Production Economics, Elsevier, vol. 140(2), pages 782-793.
    2. Sa-ngasoongsong, Akkarapol & Bukkapatnam, Satish T.S. & Kim, Jaebeom & Iyer, Parameshwaran S. & Suresh, R.P., 2012. "Multi-step sales forecasting in automotive industry based on structural relationship identification," International Journal of Production Economics, Elsevier, vol. 140(2), pages 875-887.
    3. Danese, Pamela & Romano, Pietro & Formentini, Marco, 2013. "The impact of supply chain integration on responsiveness: The moderating effect of using an international supplier network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 125-140.

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