Bullwhip effect

This paper revisits the use of trend forecasting to determine ordering policy in supply chains by viewing it as a part of the control process for making the supply responsive to demand. Trend forecasting is often used to assess demand—a tracked variable in the control context, which drives supply—a tracking variable. Used in this way, it is often observed to increase instability creating the so-called bullwhip effect. Trend is used on the other hand with reliability to increase stability in controller control, but with the difference that a trend of a ...

The aim of the paper is to investigate the well-known bullwhip effect of supply chains. Control theoretic analysis of bullwhip effect is extensively analyzed in the literature with the Laplace transform. This paper tries to examine the effect for an extended Holt–Modigliani–Muth–Simon model. A two-stage supply chain (supplier–manufacturer) is studied with quadratic costs functional. It is assumed that both firms minimize the relevant costs. The order of the manufacturer is delayed with a known constant. Two cases are examined: supplier and manufacturer minimize the relevant costs decentralized, and a centralized decision rule. The question is answered, how to decrease the bullwhip effect.

The bullwhip effect (Lee et al, 1997a) is a known supply chain phenomenon where small variations in end item demand create oscillations that amplify throughout the chain. Different price elasticity of demand influence different changes of demand when prices of items are changing on ...

All forecast-driven distribution channels are doomed to the intrinsic characteristic of an oscillating demand pattern leading to a progressively larger swing in inventory levels as moving upstream the supply chain. In supply chain management (SCM), this bullwhip effect is considered as one of the most critical factors that if not controlled appropriately can simply nullify all the efforts done by SCM experts to optimize the overall time and cost of delivering products and/or services.
As the number of intermediates between two extremes of the supply chain increases, monitoring and controlling of demand changes becomes even a more critical managerial issue. Based on Beer Game conceptual framework, in this paper, we will focus on a typical four-component supply chain including: factory, distributor, wholesaler, retailer to simulate and analyze the supply chain behavior during a 24 week period to monitor the system as well as components cost fluctuation trend due to bullwhip effect.

Collaboration in the supply chain has been widely discussed, and a wealth of concepts is at hand. Large-scale projects like the Efficient Consumer Response (ECR) in the fast moving consumer goods sector, for example, or Vendor Managed Inventory (VMI) and Collaborative Planning, Forecasting and Replenishment (CPFR) initiatives more generally provide a rich continuum of strategies for collaborating amongst supply chain partners. While individual successful implementations of the latter have already been reported, there has not yet been the widespread adoption that was originally hoped for. In our research, we looked at implementations across several industries and countries, and our findings show that the slow progress to date may be due to a lack of common understanding of these concepts, and the difficulty of integrating external collaboration with internal production and inventory control. In this paper, we set out to classify collaboration initiatives using a conceptual water-tank...

The Supply Chain Management (SCM) is a socio-technical system designed and managed to deliver products and services from raw materials to end customers through a logistic network of physical, information, financial and human resources. The physical components of a typical supply chain include several production facilities, inventory warehouses, modes of transportation and distribution channels. In order to synchronize demand of end products or services with supply of raw materials cash flow and human resources, it is necessary to have an information system like the popular Enterprise Resources Planning System (ERP) improved with some additional specific modules to strategic planning and corporate management of the Supply Chain. Of course the Supply Chain Management requires an especial organization different from the traditional hierarchy. The paper will describe a recursive special organization for the Supply Chains Management based on the Viable Systems Model (VSM). This model of ...

The amplification of demand as one move up in supply chain is considered as Bullwhip effect. Bullwhip effect creates disturbance in operations and supply chain management (OSCM). Overproduction or underproduction, unmanaged demand, short of cash-in-hand to carry out operations, excessive inventory carrying cost, decrease in service level and profit are the implications of bullwhip effect which result in disturbance of the entire supply chain. Bullwhip effect is experienced among all types of products, all types of sectors and all types of supply chain in varying quantum. The present study computes the bullwhip effect among 10 different Indian sectors from past 12-year data. The study analyzes the various changes that occur within these sectors in terms of bullwhip effect and seek the improvement in the bullwhip effect from first half to second half of data within that sector. Results show that the improvement in bullwhip is not significant. Surprisingly in many sectors, the correlation of bullwhip from first half to second half is negative in nature.

The last decades, advances in information technologies and increased competition have changed the business environment in the food and beverages industry, particularly in the European Union, which is characterised by the proliferation of small and medium enterprises. Many food companies are now aggressively focusing on logistics management as the last frontier to gain and sustain a competitive advantage.This study describes a model of intelligent food supply chain that improves efficiency within the supply chain. The aim of the paper is to demonstrate that agent technology can optimise food supply chains by (a) reviewing intelligent agents applications for supply chain optimisation and (b) illustrating how a multi-agent system can optimise performance of a beverage logistics network. Firstly, we review and synthesise existing applications in comparison to traditional and Internet-based technologies and critically evaluate agent technology applicability for supply chain management. We model the beer supply network to demonstrate that products can acquire intelligence to direct themselves throughout the distribution network. Optimisation agents can help solve specific problems of beverage supply: reduce inventories and lessen bullwhip effect, improve communication, and enable chain coordination without adverse risk sharing. Further, they gain a capability to be purchased and sold while in transit.Overviews of the supporting technologies that make such a supply chain a reality are fully discussed. In particular, optimisation agents have the characteristics of autonomous action, being proactive, reactive, and able to communicate. We demonstrate that agents enhance the flexibility, information visibility, and efficiency of the supply chain management. Suggestions and recommendations for further research are provided. Simulations of the agent-enabled supply optimisation can be used to benchmark for future research and development associated with building an optimisation agent.

Una supply chain non gestita efficacemente è intrinsecamente instabile. L’evidenza empirica dimostra che la variabilità della
domanda, all’interno della supply chain, cresce man mano che ci si allontana dal consumatore finale. Questo effetto è chiamato effetto “bullwhip”, in italiano “frusta per buoi”, per il tipo di oscillazione della domanda che esso crea; un minimo movimento, ad un estremo della frusta, causa un grande movimento alla sua estremità opposta, si ha dunque un effetto “amplificante” delle fluttuazioni durante il rilancio all’indietro, degli ordini lungo la catena logistica. Questo effetto crea
seri problemi nella pianificazione e nella gestione della supply chain.
L’obiettivo del presente lavoro è di descriverne le cause e proporre soluzioni per contrastarlo.

A review of the past research studies on the causes of bullwhip effect is presented in this paper. This paper is an effective study from the point of view that it presents a detailed classified study of the overall research studies on the effect of both the operational and the behavioral factors on bullwhip effect. A total of 19 causes of bullwhip effect have been shown here. We have identified the various gaps of research in the past research studies. An overview of the steps taken by the industries in order to tackle the bullwhip effect is also provided at the end of this paper. Directions for further research studies are also provided in each subsection of this study and at the end of this paper.

Nowadays, managing global food supply chains is becoming ever more challenging and the increasing complexity in food supply chains calls for awareness in supply chain forecasting. Since forecasting is the starting point of all supply chain activities, its degree of accuracy plays a critical role in supply chain management. The purpose of this study is to examine the importance of forecast accuracy to supply chain performance. By collecting qualitative and quantitative data, a small case study has been conducted at a firm which is active in the FMCG sector. This study indicates that several determining factors influence the accuracy of the forecasts. By analysing three KPIs with significant mismatches between the forecast and actual values, it became clear that the forecast accuracy mainly is influenced by production related factors, information related factors, the human factor and technology & tools. The literature review aligns with these findings, however, the case study shows that organisational culture, new product development and supplier delivery performance must be considered as new determining factors, since their influence is significantly noticeable. Additionally, the literature review and case study have shown that forecasting and planning are both related with each other as well as the importance of forecasting in the decision-making process. It has been restricted in its time and scope, leading to an analysis on only three KPIs. It is advisable to study other KPIs, where significant mismatches between the forecast and actual values occur, with the same depth in order to fully understand the impact of forecast accuracy on supply chain performance.

""The bullwhip effect is defined as the distortion of demand information as one moves upstream in the supply chain, causing severe inefficiencies in the whole supply chain. Although extensive research has been conducted to study the causes of the bullwhip effect and seek mitigation solutions with respect to several demand processes, less attention has been devoted to the impact of seasonal demand in multi‐echelon supply chains. This paper considers a simulation approach to study the effect of demand seasonality on the bullwhip effect and inventory stability in a four‐echelon supply chain that adopts a base stock ordering policy with a moving average method. The results show that high seasonality levels reduce the bullwhip effect ratio, inventory variance ratio, and average fill rate to a great extent; especially when the demand noise is low. In contrast, all the performance measures become less sensitive to the seasonality level when the noise is high. This performance indicates that using the ratios to measure seasonal supply chain dynamics is misleading, and that it is better to directly use the variance (without dividing by the demand variance) as the estimates for the bullwhip
effect and inventory performance. The results also show that the supply chain performances are highly sensitive to forecasting and safety stock parameters, regardless of the seasonality level. Furthermore, the impact of information sharing quantification shows that all the performance measures are improved regardless of demand seasonality. With information sharing, the bullwhip effect and inventory variance ratios are consistent with average fill rate results.""

With the development of Information and communication technologies (ICT), the supply chain performance and its management techniques have significantly transformed. The internet revolution has bought the surge in online shopping platforms attracting millions of small size manufactures to engage in the nascent business models. The research attempts to identify the factors influencing the supply chain performance for small size manufacturers under e-shopping scenario. The system dynamics simulation approach is attempted to assess the impact of replenishment strategies on supply chain performance indicators. The results reveal the existence of bullwhip effect in the e-shopping supply chains due to backlogged orders and management decisions. The comparison between two different inventory control strategies with replenishment patterns indicates that the target stock level method performs better over economic order quantity method under e-shopping scenario.

Bullwhip effect represents the amplification and distortion of demand variability as moving upstream in a supply chain, causing excessive inventories, insufficient capacities and high operational costs. A growing body of literature recognizes ordering policies and the lack of coordination as two main causes of the bullwhip effect, suggesting different techniques of intervention. This paper investigates the impact of information sharing on ordering policies through a comparison between a traditional (R, S) policy and a coordination mechanism based on ordering policy (a combination of (R, D) and (R, S) policies). This policy relies on a slow, easy to implement, information sharing to overcome drawbacks of the effect, in which replenishment orders are divided into two parts; the first is to inform the upstream echelons about the actual customer demand and the second is to inform about the adjustment of the inventory position, smoothing at the same time the orders of the different levels of the supply chain. A simulation model for a multi-echelon supply chain quantifies the supply chain dynamics under these different policies, identifying how information sharing succeeds to achieve an acceptable performance in terms of both bullwhip effect and inventory variance.

A major cause of supply chain deficiencies is the bullwhip effect, which implies that demand variability amplifies as one moves upstream in supply chains. Smoothing inventory decision rules have been recognized as the most powerful approach to counteract the bullwhip effect. Although several studies have evaluated these smoothing rules with respect to several demand processes, focusing mainly on the smoothing order-up-to (OUT) replenishment rule, less attention has been devoted to investigate their effectiveness in seasonal supply chains. This research addresses this gap by investigating the impact of the smoothing OUT on the seasonal supply chain performances. A simulation study has been conducted to evaluate and compare the smoothing OUT with the traditional OUT (no smoothing), both integrated with the Holt-Winters (HW) forecasting method, in a four-echelon supply chain experiences seasonal demand modified by random variation. The results show that the smoothing OUT replenishment rule is superior to the traditional OUT, in terms of the bullwhip effect, inventory variance ratio and average fill rate, especially when the seasonal cycle is small. In addition, the sensitivity analysis reveals that employing the smoothing replenishment rules reduces the impact of the demand parameters and the poor selection of the forecasting parameters on the ordering and inventory stability. Therefore, seasonal supply chain managers are strongly recommended to adopt the smoothing replenishment rules. Further managerial implications have been derived from the results.

The current study examines the effect of the Bullwhip phenomena in both manufacturing and services industry based on a literature survey. The cause and impact of the bullwhip effect have been determined, besides the methodology is determined to mitigate this effect. For this purpose, Mcdonald's case has been considered to better understanding the reasons for the bullwhip for the product. The way forward has been proposed to cope with the bullwhip problem. The study also reviews the literature on the service sector, especially in the health sector. Moreover, the difference between the services and manufacturing industry is determined in this study so that both kinds of firms can get benefit by making it part of their system to mitigate the bullwhip effect. The study concludes by pointing out the roadmap for future studies based on the previous reviews done in this regard.