Judgmental Adjustments to Demand Forecasts: Accuracy Evaluation and Bias Correction

Davydenko, A and Fildes, R A and Trapero Arenas, J R (2010) Judgmental Adjustments to Demand Forecasts: Accuracy Evaluation and Bias Correction. Working Paper. The Department of Management Science, Lancaster University.

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Abstract

Judgmental adjustments to statistically generated forecasts have become a standard practice in demand forecasting, especially at a stock keeping units level. However, due to the subjective nature of judgmental interventions this approach cannot guarantee optimal use of available information and can lead to substantial cognitive biases. It is therefore important to monitor the accuracy of adjustments and estimate persistent systematic errors in order to correct final forecast. This paper presents an appropriate methodology for such analysis and focuses on specific features of source data including time series heterogeneity, skewed distributions of errors, and generally nonlinear patterns of biases. Enhanced modelling and evaluation techniques are suggested to overcome some imperfections of well-known standard methods in the given context. Empirical analysis showed that a considerable proportion of final forecast error is formed by a systematic component which can be pre- dicted. Proposed bias correction procedures allowed to substantially improve the accuracy of final forecasts. In particular, one-factor mod- els of the relationship between forecast error and adjustment were found to be a simple, robust and efficient tool for the given purpose.

Item Type:
Monograph (Working Paper)
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/aacsb/disciplinebasedresearch
Subjects:
ID Code:
48981
Deposited By:
Deposited On:
11 Jul 2011 21:26
Refereed?:
No
Published?:
Published
Last Modified:
03 Jul 2020 07:01