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

Robert Fildes, Paul Goodwin

Research output: Contribution to journalArticle

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 based on 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.
Original languageEnglish
Article numberINTFOR4858
JournalInternational Journal of Forecasting
Publication statusAcceptance date - 12 Nov 2020

Keywords

  • behavioural operations
  • forecast adjustments
  • forecasting support systems;
  • judgmental forecasting
  • cognitive biases
  • task-technology fit
  • actor-networks
  • organizational factors.

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