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

被引:38
|
作者
Danese, Pamela [2 ]
Kalchschmidt, Matteo [1 ]
机构
[1] Univ Bergamo, Dept Econ & Technol Management, I-24044 Dalmine, BG, Italy
[2] Univ Padua, Dept Management & Engn, I-36100 Vicenza, Italy
关键词
Demand forecasting; Global manufacturing research group; Hierarchical regression; Forecast accuracy; DEMAND UNCERTAINTY; SUPPLY CHAIN; IMPACT; FAMILIARITY; SERVICES; ERRORS; COST;
D O I
10.1016/j.ijpe.2010.09.006
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:204 / 214
页数:11
相关论文
共 50 条
  • [31] Macroeconomic forecasting in the EMU - Does disaggregate modeling improve forecast accuracy?
    Ruth, Karsten
    JOURNAL OF POLICY MODELING, 2008, 30 (03) : 417 - 429
  • [32] Impact of augmented reality on operational performance: the mediating role of process innovativeness
    Turkcan, Hulya
    Imamoglu, Salih Zeki
    Ince, Huseyin
    JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT, 2023, 34 (08) : 1313 - 1331
  • [33] THE ROLE OF JUDGMENT IN MACROECONOMIC FORECASTING ACCURACY
    MCNEES, SK
    INTERNATIONAL JOURNAL OF FORECASTING, 1990, 6 (03) : 287 - 299
  • [34] Improving Operational Water Quality Forecasting with Ensemble Data Assimilation
    Riazi, Hamideh
    Kim, Sunghee
    Seo, Dong-Jun
    Shin, Changmin
    Kim, Kyunghyun
    JOURNAL OF WATER MANAGEMENT MODELING, 2016, 25
  • [35] Initial conditions estimation for improving forecast accuracy in exponential smoothing
    Vercher, E.
    Corberan-Vallet, A.
    Segura, J. V.
    Bermudez, J. D.
    TOP, 2012, 20 (02) : 517 - 533
  • [36] Combine to compete: Improving fiscal forecast accuracy over time
    Carabotta, Laura
    Claeys, Peter
    JOURNAL OF FORECASTING, 2024, 43 (04) : 948 - 982
  • [37] Striving for Improvement: The Perceived Value of Improving Hurricane Forecast Accuracy
    Molina, Renato
    Letson, David
    McNoldy, Brian
    Mozumder, Pallab
    Varkony, Matthew
    BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2021, 102 (07) : E1408 - E1423
  • [38] Study on improving peak flood forecast accuracy with SVM model
    2005, Tsinghua University Press, Beijing, China (24):
  • [39] Initial conditions estimation for improving forecast accuracy in exponential smoothing
    E. Vercher
    A. Corberán-Vallet
    J. V. Segura
    J. D. Bermúdez
    TOP, 2012, 20 : 517 - 533
  • [40] Improving Deep Learning for Forecasting Accuracy in Financial Data
    Lin, Shih-Lin
    Huang, Hua-Wei
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2020, 2020