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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

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Stability in the inefficient use of forecasting systems : a case study in a supply-chain company. / Fildes, Robert; Goodwin, Paul.

In: International Journal of Forecasting, Vol. 37, No. 2, 01.04.2021, p. 1031-1046.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Fildes R, Goodwin P. Stability in the inefficient use of forecasting systems: a case study in a supply-chain company. International Journal of Forecasting. 2021 Apr 1;37(2):1031-1046. Epub 2020 Dec 17. doi: 10.1016/j.ijforecast.2020.11.004

Author

Fildes, Robert ; Goodwin, Paul. / Stability in the inefficient use of forecasting systems : a case study in a supply-chain company. In: International Journal of Forecasting. 2021 ; Vol. 37, No. 2. pp. 1031-1046.

Bibtex

@article{518c8824407a4d24bb589c408a57f58a,
title = "Stability in the inefficient use of forecasting systems: a case study in a supply-chain company",
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{\textquoteright}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.",
keywords = "behavioural operations;, organizational factors., actor-networks;, forecast adjustments;, task-technology fit;, fjudgmental forecasting;, cognitive biases;, orecasting support systems;",
author = "Robert Fildes and Paul Goodwin",
note = "This is the author{\textquoteright}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",
year = "2021",
month = apr,
day = "1",
doi = "10.1016/j.ijforecast.2020.11.004",
language = "English",
volume = "37",
pages = "1031--1046",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier Science B.V.",
number = "2",

}

RIS

TY - JOUR

T1 - Stability in the inefficient use of forecasting systems

T2 - a case study in a supply-chain company

AU - Fildes, Robert

AU - Goodwin, Paul

N1 - 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

PY - 2021/4/1

Y1 - 2021/4/1

N2 - 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.

AB - 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.

KW - behavioural operations;

KW - organizational factors.

KW - actor-networks;

KW - forecast adjustments;

KW - task-technology fit;

KW - fjudgmental forecasting;

KW - cognitive biases;

KW - orecasting support systems;

U2 - 10.1016/j.ijforecast.2020.11.004

DO - 10.1016/j.ijforecast.2020.11.004

M3 - Journal article

VL - 37

SP - 1031

EP - 1046

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 2

ER -