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 - Funding Information:
The authors would like to thank the anonymous contributors to this case study for giving their time to explaining the processes in the case organization. They would also like to thank researchers who were involved with aspects of the case at an early stage, Dr Stavros Asimakopoulos, Andrea Franco and Professor Konstantinos Nikolopoulos. The research was supported by grants GR/60181/01 and GR/60198/01 from the Engineering and Physical Sciences Research Council (EPSRC), United Kingdom .
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 15-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 using the system's facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of a sales & operations planning (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 15-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 using the system's facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of a sales & operations planning (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 - Actor–networks
KW - Behavioural operations
KW - Cognitive biases
KW - Forecast adjustments
KW - Forecasting support systems
KW - Judgmental forecasting
KW - Organizational factors
KW - Task-technology fit
UR - http://www.scopus.com/inward/record.url?scp=85099501290&partnerID=8YFLogxK
U2 - 10.1016/j.ijforecast.2020.11.004
DO - 10.1016/j.ijforecast.2020.11.004
M3 - Article
SN - 0169-2070
VL - 37
SP - 1031
EP - 1046
JO - International Journal of Forecasting
JF - International Journal of Forecasting
IS - 2
ER -