Effects of multiple adjustments in supply chain forecasting on forecast accuracy

Abstract

Behavioral supply chain management is a subdiscipline within behavioral operations management that is growing rapidly. Judgmental adjustments of forecasts are considered part of this domain given the salience of forecasts to the smooth functioning of a supply chain. System-generated forecasts are frequently modified in the industry by forecasting professionals for numerous purposes. Accurate forecasts are significant to supply chain management and efficient organizational planning. Multiple adjustments occur when forecasts are subjected to more than one adjusted in its life cycle. Multiple adjustments are one of the key forecasting issues which impact forecast accuracy. Despite this, multiple adjustments to forecasts remain a not well-addressed research gap in academia. There are very few preliminary studies that investigate multiple adjustments to forecasts. Thus, to investigate the effect of multiple adjustments to forecasts to enhance forecast accuracy in the SC, the researcher employed a laboratory experiment with four different treatments to measure the forecasters’ behavior specifically on multiple adjustments to forecasts. 194 undergraduate and MBA students were recruited as participants for the experiment. In the Control Group, forecasts with first adjustments were observed while other treatments investigate how the participants would perform when they do subsequent adjustments with different levels of information availability. The authors found that multiple adjustments to forecasts significantly improve forecast accuracy. This expands the knowledge of multiple adjustments to forecasts to industry and academic professionals. Moreover, the provision of relevant information related to the previous adjustment allows the forecasters to perform better. The authors suggest the industries to increase information visibility among supply chain partners to have accurate forecasts and subsequent results in supply chain optimization. The results emphasize the importance of industry exposure and understanding the practical situations for a forecaster to improve his/her decision-making regarding judgmental adjustments. This study stresses the supply chain management-related degree programs to provide industry exposure to students to understand the practical implications of forecasting and other supply chain issues. Further works in this avenue, such as developing a forecasting model by integrating multiple adjustments and investigating the impact of the black-box effect in multiple adjustments are encouraged.