Measuring and Analyzing the Bullwhip Effect in a Two-Product and Two Echelon Supply Chain Using Control Theory Approach

Coordination is very important in supply chain management and it is one of the main factors in supply chain profitability. Bullwhip effect is one of the basic obstacles to achieve coordination in supply chains and reduction of this phenomenon has an important role in supply chain harmony. The other side, costs of supply chain can be mitigated and customer service level can be increased by reducing of bullwhip effect. Because measurement of bullwhip effect is very important in analysing and controlling of it, providing equations to investigate bullwhip effect behaviour based on real world supply chain conditions is necessary. The previous studies mostly concentrate on single product supply chain and few studies have been done on supply chains with more than one product. Here we quantify and investigate the bullwhip effect in a two-echelon supply chain with two products using control theory approach. Due to the relationship between demands of two products in our proposed supply chain, first order vector auto regressive model is used as demand process of the products. We also apply moving average method for lead-time demand forecasting within the "order up to" replenishment policy. We derive a closed form bullwhip measure and then bullwhip effect in a two-product supply chain is discussed and illustrated through a numerical example

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

Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems

As the business environment gets more complicated, organizations must be able to respond to the business changes and adjust themselves quickly to gain their competitive advantages. This study proposes an integrated agent system, called SPA, which coordinates simulated and physical agents to provide an efficient way for organizations to meet the challenges in managing supply chains. In the integrated framework, physical agents coordinate with inter-organizations\' physical agents to form workable business processes and detect the variations occurring in the outside world, whereas simulated agents model and analyze the what-if scenarios to support physical agents in making decisions. This study uses a supply chain that produces digital still cameras as an example to demonstrate how the SPA works. In this example, individual information systems of the involved companies equip with the SPA and the entire supply chain is modeled as a hierarchical object oriented Petri nets. The SPA here applies the modified AGNES data clustering technique and the moving average approach to help each firm generalize customers\' past demand patterns and forecast their future demands. The amplitude of forecasting errors caused by bullwhip effects is used as a metric to evaluate the degree that the SPA affects the supply chain performance. The experimental results show that the SPA benefits the entire supply chain by reducing the bullwhip effects and forecasting errors in a dynamic environment.Supply Chain Performance Enhancement; Bullwhip Effects; Simulated Agents; Physical Agents; Dynamic Customer Demand Pattern Discovery

Judgement and supply chain dynamics

Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and ‘laboratory’ studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

E-logistics of agribusiness organisations

Logistics is one of the most important agribusiness functions due to the idiosyncrasy of food products and the structure of food supply chain. Companies in the food sector typically operate with poor production forecasting, inefficient inventory management, lack of coordination with supply partners. Further, markets are characterised by stern competition, increasing consumer demands and stringent regulation for food quality and safety. Large agribusiness corporations have already turned to e-logistics solutions as a means to sustain competitive advantage and meet consumer demands. There are four types of e-logistics applications: (a) Vertical alliances where supply partners forge long-term strategic alliances based on electronic sharing of critical logistics information such as sales forecasts and inventory volume. Vertical alliances often apply supply chain management (SCM) which is concerned with the relationship between a company and its suppliers and customers. The prime characteristic of SCM is interorganizational coordination: agribusiness companies working jointly with their customers and suppliers to integrate activities along the supply chain to effectively supply food products to customers. E-logistics solutions engender the systematic integration among supply partners by allowing more efficient and automatic information flow. (b) e-tailing, in which retailers give consumers the ability to order food such as groceries from home electronically i.e. using the Internet and the subsequent delivery of those ordered goods at home. (c) Efficient Foodservice Response (EFR), which is a strategy designed to enable foodservice industry to achieve profitable growth by looking at ways to save money for each level of the supply chain by eliminating inefficient practices. EFR provides solutions to common logistics problems, such as transactional inefficiency, inefficient plant scheduling, out-of-stocks, and expedited transportation. (d) Contracting, a means of coordinating procurement of food, beverages and their associated supplies. Many markets and supply chains in agriculture are buyer-driven where the buyers in the market tend to set prices and terms of trade. Those terms can include the use of electronic means of communication to support automatic replenishment of goods, management of supply and inventory. The results of the current applications of e-logistics in food sector are encouraging for Greek agribusiness. Companies need to become aware of and evaluate the value-added by those applications which are a sustainable competitive advantage, optimisation of supply chain flows, and meeting consumer demands and food safety regulations. E-business diffusion has shown that typically first-movers gain a significant competitive advantage and the rest companies either eventually adopt the new systems or see a significant decline in their trading partners and perish. E-logistics solutions typically require huge investments in hardware and software and skilled personnel, which is an overt barrier for most Greek companies. Large companies typically are first-movers but small and medium enterprises (SMEs) need institutional support in order to become aware that e-logistics systems can be fruitful for them as well

Exploring the bullwhip effect by means of spreadsheet simulation.

One of the main supply chain deficiencies is the bullwhip effect: demand fluctuations increase as one moves up the supply chain from retailer to manufacturer. The Beer Distribution Game is widely known for illustrating these supply chain dynamics in class. In this paper we present a spreadsheet application, exploring the two key causes of the bullwhip effect: demand forecasting and the type of ordering policy. We restrict our attention to a single product two-echelon system and illustrate how tuning the parameters of the replenishment policy induces or reduces the bullwhip effect. We also demonstrate how bullwhip reduction (dampening the order variability) may have an adverse impact on inventory holdings and/or customer service. As such, the spreadsheets can be used as an educational tool to gain a clear insight into the use of inventory control policies and forecasting in relation to the bullwhip effect and customer service.Bullwhip effect; Replenishment rules; Forecasting techniques; Spreadsheet simulation; Beer distribution game;

Exploring the bullwhip effect by means of spreadsheet simulation.

An important supply chain research problem is the bullwhip effect: demand fluctuations increase as one moves up the supply chain from retailer to manufacturer. It has been recognized that demand forecasting and ordering policies are two of the key causes of the bullwhip effect. In this paper we present a spreadsheet application, which explores a series of replenishment policies and forecasting techniques under different demand patterns. It illustrates how tuning the parameters of the replenishment policy induces or reduces the bullwhip effect. Moreover, we demonstrate how bullwhip reduction (order variability dampening) may have an adverse impact on inventory holdings. Indeed, order smoothing may increase inventory fluctuations resulting in poorer customer service. As such, the spreadsheets can be used as an educational tool to gain a clear insight into the use or abuse of inventory control policies and improper forecasting in relation to the bullwhip effect and customer service. Keywords: Bullwhip effect, forecasting techniques, replenishment rules, inventory fluctuations, spreadsheet simulationBullwhip; Bullwhip effect; Forecasting techniques; Inventory fluctuations; Replenishment rule; Simulation; Spreadsheet simulation;

Supply chain uncertainty:a review and theoretical foundation for future research

Supply-chain uncertainty is an issue with which every practising manager wrestles, deriving from the increasing complexity of global supply networks. Taking a broad view of supply-chain uncertainty (incorporating supply-chain risk), this paper seeks to review the literature in this area and develop a theoretical foundation for future research. The literature review identifies a comprehensive list of 14 sources of uncertainty, including those that have received much research attention, such as the bullwhip effect, and those more recently described, such as parallel interaction. Approaches to managing these sources of uncertainty are classified into: 10 approaches that seek to reduce uncertainty at its source; and, 11 approaches that seek to cope with it, thereby minimising its impact on performance. Manufacturing strategy theory, including the concepts of alignment and contingency, is then used to develop a model of supply-chain uncertainty, which is populated using the literature review to show alignment between uncertainty sources and management strategies. Future research proposed includes more empirical research in order to further investigate: which uncertainties occur in particular industrial contexts; the impact of appropriate sources/management strategy alignment on performance; and the complex interplay between management strategies and multiple sources of uncertainty (positive or negative)