Impact of Pos Data Sharing on Supply Chain Management: An Experimental Study

Abstract

We examine the impact of point of sale (POS) data sharing on ordering decisions in a multi-echelon supply chain. In particular, we focus on how exposure to POS data may help reduce the "bullwhip effect," the tendency of orders to increase in variability as one moves up a supply chain. Theoretical studies have shown that exposure to POS data can lead to a reduction in the bullwhip effect when suppliers have no prior knowledge of the demand distribution. The benefit of sharing POS data in stable industries, where the demand distribution is commonly known, is less clear. We study this phenomenon from a behavioral perspective in the context of a simple, serial, supply chain subject to information lags and stochastic demand. We find, using a controlled simulation experiment, that sharing POS information does help reduce some components of the bullwhip effect in a stable demand setting, namely the order oscillation of upstream members. We offer one possible explanation for this improvement by examining the relationship between order decisions and demand line information. (BULLWHIP EFFECT; SUPPLY CHAIN MANAGEMENT; POS DATA; EXPERIMENTAL ANALYSIS) *

Modeling Stock-out Loss and Overstocking Loss Generated by Bullwhip Effect

“…In particular, Kim et al [28] used a simulation model ‖SISCO‖ to investigate how stochastic lead times, information sharing and quality of information affect the supply chain under a periodic order-up-to inventory policy. Second approach, -Beer Game‖ pioneered by Sterman [29] and followed by Croson and Donohue [30][31], Haines et al [32] and Sarkar and Kumar [33] has mainly addressed the behavioral aspect of bullwhip effect. The third approach initiated by Lee [4][5] introduced four main causes of bullwhip effect such as demand forecast updating (also [34][35][36][37] provide more elaborate analysis about forecasting methods), order inflation or order rationing, order batching, and price fluctuation and concludes that these factors methodically impair the performance of supply chains.…”

Towards Business Integration as a Service 2.0 (BIaaS 2.0)

“…There is another type of information-based linkage that can improve the visibility of customers' and suppliers' operational activities [12]. Barratt and Barratt [2] present their external and internal supply chain linkages and use a Coffee case study to demonstrate linkages in relationship and business activities between different roles and companies.…”

‘Bullwhip’ and ‘backlash’ in supply pipelines

“…This decision bias caused over ordering and the 'bullwhip' effect for upstream players. The existence of the behavioural causes of the 'bullwhip' effect has been demonstrated in a variety of laboratory settings by many researchers (Chen and Samroengraja, 2000;Croson and Donohue, 2003;Croson and Donohue, 2006;Diana and Katok, 2006).…”

“…Despite being a considerable simplification of reality, it still provides a controlled environment to study the 'bullwhip' effect. It is therefore not surprising to find extensive use of the Beer Game in many 'bullwhip' related studies (Croson and Donohue, 2003;Disney et al, 2004;Croson and Donohue, 2006;Diana and Katok, 2006).…”

“…The Massachusetts Institute of Technology (MIT) Beer Game (Sterman, 1989), a popular method for analysing the 'bullwhip' effect (Chen and Samroengraja, 2000;Croson and Donohue, 2003) which controls for all but the demand signal processing and the behavioural causes was used to get evidence of the 'backlash' effect. We were unable to identify any literature where the Beer Game has been used to study the backlash effect of shipments and this also is a novelty of this paper.…”