Stability in the inefficient use of forecasting systems:a case study in a supply-chain company

Fildes, Robert and Goodwin, Paul (2021) Stability in the inefficient use of forecasting systems:a case study in a supply-chain company. International Journal of Forecasting, 37 (2). pp. 1031-1046. ISSN 0169-2070

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Abstract

Computer-based demand forecasting systems have been widely adopted in supply chain companies, but little research has studied how these systems are actually used in the forecasting process. We report the findings of a case study of demand forecasting in a pharmaceutical company over a fifteen-year period. At the start of the study managers believed that they were making extensive use of their forecasting system that was marketed on the basis of the accuracy of its advanced statistical methods. Yet most forecasts were obtained by using the system’s facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of an S & OP process, yet these often only served to reduce forecast accuracy. This study uses observations of the forecasting process, interviews with participants and data on the accuracy of forecasts to investigate why the managers continued to use non-normative forecasting practices for many years despite the potential economic benefits that could be achieved through change. The reasons for the longevity of these practices are examined both from the perspective of the individual forecaster and the organization as a whole.

Item Type:
Journal Article
Journal or Publication Title:
International Journal of Forecasting
Additional Information:
This is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, 37, 2, 2021 DOI: 10.1016/j.ijforecast.2020.11.004
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1400/1403
Subjects:
ID Code:
150963
Deposited By:
Deposited On:
21 Jan 2021 11:18
Refereed?:
Yes
Published?:
Published
Last Modified:
08 Sep 2021 06:07