Managing the bullwhip effect in multi-echelon supply chains

This editorial article presents the bullwhip effect which is one of the major problems faced by supply chain management. The bullwhip effect represents the demand variability amplification as demand information travels upstream in the supply chain. The bullwhip effect research has been attempting to prove its existence, identify its causes, quantify its magnitude and propose mitigation and avoidance solutions. Previous research has relied on different modeling approaches to quantify the bullwhip effect and to investigate the proposed mitigation/avoidance solutions. Extensive research has shown that smoothing replenishment rules and collaboration in supply chain are the most powerful approaches to counteract the bullwhip effect. The objective of this article is to highlight the bullwhip effect avoidance approaches with providing some interesting directions for future research

Mitigating the Bullwhip Effect and Enhancing Supply Chain Performance through Demand Information Sharing: An ARENA Simulation Study

The supply chain is a network of organizations that collaborate and leverage their resources to deliver products or services to end-customers. In today's globalized and competitive market, organizations must specialize and form partnerships to gain a competitive edge. To thrive in their respective industries, organizations need to prioritize supply chain coordination, as it is integral to their business processes.   Supply chain management focuses on the collaboration of organizations within the supply chain. However, when each echelon member optimizes their goals without considering the network's impact, it leads to suboptimal performance and inefficiencies. This phenomenon is known as the Bullwhip effect, where order variability increases as it moves upstream in the supply chain. The lack of coordination, unincorporated material and information flows, and absence of ordering rules contribute to poor supply chain dynamics. To improve supply chain performance, it is crucial to align organizational activities. Previous research has proposed solutions to mitigate the Bullwhip effect, which has been a topic of intense study for many decades. This research aims to investigate the causes and mitigations of the Bullwhip effect based on existing research. Additionally, the paper utilizes ARENA simulation to examine the impact of sharing end-customer demand information. As far as we are aware, no study has been conducted to deeply simulate the bullwhip effect using the ARENA simulation. Previous studies have investigated this phenomenon, but without delving into its intricacies. The simulation results offer potential strategies to mitigate the Bullwhip effect through demand information sharing. Keywords: Supply Chain Management, Bullwhip effect, Inventory management, ARENA simulation, Information sharing, forecasting technique, Demand variability. DOI: 10.7176/JESD/14-14-07 Publication date:August 31st 202

The Impact of Information Sharing on Different Performance Indicators in a Multi-Level Supply Chain

Enterprises can use different methods/principles to obtain competitive advantages. Information sharing (IS) among supply chain (SC) partners is also one of these methods used in enterprises and it has positive effects on overall system performance like reduced inventory level, decreased cost, bullwhip effects and increased profit. In this paper, our aim is to present the impacts of IS on different costs like ordering, holding and penalty costs of each SC member and total system costs in multi SC. We want to show the effects of sharing different types of information simultaneously or separately on SC partners as cost change. Besides, this paper presents the situation of order quantity estimation according to the proximity of actual order quantity in decentralized or centralized demand sharing. A model is developed to determine IS influence on the cost of SC partners. Various IS scenarios are studied in this paper. The customer demand, warehouse order quantity and warehouse-manufacturer lead time are the shared information of scenarios. Results are tested and analysed by using analysis of variance (ANOVA).The findings of this study show that IS especially simultaneously sharing reduces system costs. Lead time sharing provides the lowest cost between other types of sharing. For every system member, holding cost reduces the most during IS. The more accurate demand forecasting is performed in centralized demand sharing compared to decentralized sharing

Centralized - Decentralized Demand Management And The Bullwhip Effect

Information distortion tends to inflate from downstream to upstream, and results in demand planning errors and this is followed by inaccurate forecasting. This situation is referred to as the bullwhip effect phenomenon. Demand management is also determined based on either a centralized or decentralized distribution strategy. Both strategies will influence the accuracy of demand planning and its effect on the bullwhip phenomenon. Unfortunately, research investigating the relationship between centralization and decentralization strategies for demand and the bullwhip effect is still limited. To answer this shortcoming, this paper has two scenarios for its analysis. First, forecasting is done to determine the accuracy of demand planning, indicated by the smallest forecast error value. Based on the results of the analysis, it is known that single exponential smoothing with alpha 0.5 is the best forecasting method. The second step is to measure the bullwhip effect; the results show that the coefficient is less than one. This coefficient indicated that the company underperformed in the fulfillment of its customers’ needs. Theoretically, this paper extends the literature on demand management in the supply chain by considering centralized and decentralized strategies

Smooth is smart: bullwhip, inventory, fill-rates and the golden ratio.

Inventory;

Dampening variability by using smoothing replenishment rules.

A major cause of supply chain deficiencies is the bullwhip effect which can be substantial even over a single echelon. This effect refers to the tendency of the variance of the replenishment orders to increase as it moves up a supply chain. Supply chain managers experience this variance amplification in both inventory levels and replenishment orders. As a result, companies face shortages or bloated inventories, run-away transportation and warehousing costs and major production adjustment costs. In this article we analyse a major cause of the bullwhip effect and suggest a remedy. We focus on a smoothing replenishment rule that is able to reduce the bullwhip effect across a single echelon. In general, dampening variability in orders may have a negative impact on customer service due to inventory variance increases. We therefore quantify the variance of the net stock and compute the required safety stock as a function of the smoothing required. Our analysis shows that bullwhip can be satisfactorily managed without unduly increasing stock levels to maintain target fill rates.Bullwhip effect; Companies; Cost; Costs; Impact; Inventory; Managers; Order; Replenishment rule; Rules; Safety stock; Supply chain; Supply chain management; Variability; Variance; Variance reduction;

Effect of lead-time variations on the operations of supply chain networks.

This thesis focuses on analyzing the value of information sharing on supply chain network. A multi-stage, multi-period, multi-product, inventory-planning model with seasonal demand is used to study the impact of information sharing and lead-time variations on the operational costs of supply chain network. A mixed-integer programming model is used to integrate the production and distribution planning processes throughout the supply chain. The results of the model confirm that using updated demand information may cause a considerable reduction in the forecast errors which has an order-of-magnitude effect on overall cost reduction throughout the supply chain. Paremetric analysis is performed to study the impact of lead-time variations on the operational costs of the supply chain network which leads to the conclusion that lead-time variations have a significant effect on the inventory and safety stock levels, and as a result on the overall system cost in a supply chain network. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .M346. Source: Masters Abstracts International, Volume: 44-01, page: 0508. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005