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  • Case study paper on FSS -revised Jan2021

    Rights statement: 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

    Accepted author manuscript, 690 KB, PDF document

    Embargo ends: 17/12/22

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>1/04/2021
<mark>Journal</mark>International Journal of Forecasting
Issue number2
Volume37
Number of pages16
Pages (from-to)1031-1046
Publication StatusPublished
Early online date17/12/20
<mark>Original language</mark>English

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.

Bibliographic note

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