The Ripple Effect Caused by Judgmental Forecast Adjustments
Access status:
USyd Access
Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Hurley, Jason KyleAbstract
Demand forecasting is essential for businesses to effectively plan and manage their supply chain (SC) operations. Judgmentally adjusting statistically derived forecasts is common industry practice and some evidence suggests that this process can improve forecast accuracy; particularly ...
See moreDemand forecasting is essential for businesses to effectively plan and manage their supply chain (SC) operations. Judgmentally adjusting statistically derived forecasts is common industry practice and some evidence suggests that this process can improve forecast accuracy; particularly in the presence of retail promotions. Research pertaining to the bullwhip effect (BWE) suggests that accurate forecasting can improve SC stability by reducing demand distortion and order/inventory amplification. However, this stream of research has overlooked that forecasts are often adjusted by demand planners and very little is known about the impact that it has on the SC holistically. In this thesis, an experiment is designed to assess the effects that judgmental forecast adjustments have on upstream SC operations including production and inventory replenishment decisions. An empirical investigation is also undertaken at Coca-Cola Amatil, Australia, consisting of observations of operations and semi-structured interviews with management. Archival data is collected and utilised to generate experiment parameters and enhance the external validity of findings. The results from 240 participants indicate that forecast adjustments can improve SC performance, but their efficacy is dependent on the level of information sharing. When adjusted forecasts are only available to the retailer, SC costs increase while service levels decrease. However, costs reduce and service levels increase when adjusted forecasts are transparently shared across the SC. The most significant benefits are realised in the presence of promotions. In contrast to the demand/inventory variability amplification often observed in SCs, smoothing behaviour and improved SC stability is found to occur when adjusted forecasts are shared. The findings of this study narrow the current gap between judgmental forecasting and BWE streams of research and provide theoretical and managerial insights for more informed SC decision making.
See less
See moreDemand forecasting is essential for businesses to effectively plan and manage their supply chain (SC) operations. Judgmentally adjusting statistically derived forecasts is common industry practice and some evidence suggests that this process can improve forecast accuracy; particularly in the presence of retail promotions. Research pertaining to the bullwhip effect (BWE) suggests that accurate forecasting can improve SC stability by reducing demand distortion and order/inventory amplification. However, this stream of research has overlooked that forecasts are often adjusted by demand planners and very little is known about the impact that it has on the SC holistically. In this thesis, an experiment is designed to assess the effects that judgmental forecast adjustments have on upstream SC operations including production and inventory replenishment decisions. An empirical investigation is also undertaken at Coca-Cola Amatil, Australia, consisting of observations of operations and semi-structured interviews with management. Archival data is collected and utilised to generate experiment parameters and enhance the external validity of findings. The results from 240 participants indicate that forecast adjustments can improve SC performance, but their efficacy is dependent on the level of information sharing. When adjusted forecasts are only available to the retailer, SC costs increase while service levels decrease. However, costs reduce and service levels increase when adjusted forecasts are transparently shared across the SC. The most significant benefits are realised in the presence of promotions. In contrast to the demand/inventory variability amplification often observed in SCs, smoothing behaviour and improved SC stability is found to occur when adjusted forecasts are shared. The findings of this study narrow the current gap between judgmental forecasting and BWE streams of research and provide theoretical and managerial insights for more informed SC decision making.
See less
Date
2019-01-31Licence
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
The University of Sydney Business School, Institute of Transport and Logistics Studies (ITLS)Awarding institution
The University of SydneyShare