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

The value of coordination in a two echelon supply chain: Sharing information, policies and parameters.

We study a coordination scheme in a two echelon supply chain. It involves sharing details of replenishment rules, lead-times, demand patterns and tuning the replenishment rules to exploit the supply chain's cost structure. We examine four different coordination strategies; naïve operation, local optimisation, global optimisation and altruistic behaviour on behalf of the retailer. We assume the retailer and the manufacturer use the Order-Up-To policy to determine replenishment orders and end consumers demand is a stationary i.i.d. random variable. We derive the variance of the retailer's order rate and inventory levels and the variance of the manufacturer's order rate and inventory levels. We initially assume that costs in the supply chain are directly proportional to these variances (and later the standard deviations) and investigate the options available to the supply chain members for minimising costs. Our results show that if the retailer takes responsibility for supply chain cost reduction and acts altruistically by dampening his order variability, then the performance enhancement is robust to both the actual costs in the supply chain and to a naïve or uncooperative manufacturer. Superior performance is achievable if firms coordinate their actions and if they find ways to re-allocate the supply chain gain.Bullwhip; Global optimisation; Inventory variance; Local optimisation; Supply chains; Studies; Coordination; Supply chain; IT; Replenishment rule; Rules; Demand; Patterns; Cost; Structure; Strategy; Retailer; Policy; Order; Variance; Inventory; Costs; Options; Variability; Performance; Performance enhancement; Firms;

On bullwhip-limiting strategies in divergent supply chain networks

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect. This effect generates a large volume of inefficiencies as it moves a greater number of units than necessary, increases stock and generates stock-outs. There are two different approaches for avoiding and/or limiting this detrimental phenomenon that have received attention in the literature: Collaboration and information sharing in SCNs on one hand, and the adoption of smoothing replenishment rules on the other. The effectiveness of both approaches have been often analyzed only for “serial linked” SCNs, which is a supply network structure rarely found in real-life. In order to give an insight of how these techniques would perform in more generic SCNs, a divergent SCN has been benchmarked against the classical serial SCN. The computational experience carried out show that the bullwhip effect can be considerably reduced by collaboration or the smoothing replenishment rules in divergent SCNs, but it always performs worse than the serial SCN due to its inherent complexity

On the bullwhip avoidance phase: the synchronized supply chain

The aim of this paper is to analyse the operational response of a Synchronised Supply Chain (SSC). To do so, first a new mathematical model of a SSC is presented. An exhaustive Latin Square design of experi- ments is adopted in order to perform a boundary variation analysis of the main three parameters of the periodic review smoothing (S,R) order-up-to policy: i.e., lead time, demand smoothing forecasting factor, and proportional controller of the replenishment rule. The model is then evaluated under a variety of performance measures based on internal process benefits and customer benefits. The main results of the analysis are: (I) SSC responds to violent changes in demand by resolving bullwhip effect and by creating stability in inventories under different parameter settings and (II) in a SSC, long production\u2013 distribution lead times could significantly affect customer service level. Both results have important consequences for the design and operation of supply chains

The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

In 1994, through classic control theory, John, Naim and Towill developed the ‘Automatic Pipeline, Inventory and Order-based Production Control System’ (APIOBPCS) which extended the original IOBPCS archetype developed by Towill in 1982 ─ well-recognised as a base framework for a production planning and control system. Due to the prevalence of the two original models in the last three decades in the academic and industrial communities, this paper aims to systematically review how the IOBPCS archetypes have been adopted, exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains. Using various databases such as Scopus, Web of Science, Google Scholar (111 papers), we found that the IOBPCS archetypes have been studied regarding the a) modification of four inherent policies related to forecasting, inventory, lead-time and pipeline to create a ‘family’ of models, b) adoption of the IOBPCS ‘family’ to reduce supply chain dynamics, and in particular bullwhip, c) extension of the IOBPCS family to represent different supply chain scenarios such as order-book based production control and closed-loop processes. Simulation is the most popular method adopted by researchers and the number of works based on discrete time based methods is greater than those utilising continuous time approaches. Most studies are conceptual with limited practical applications described. Future research needs to focus on cost, flexibility and sustainability in the context of supply chain dynamics and, although there are a few existing studies, more analytical approaches are required to gain robust insights into the influence of nonlinear elements on supply chain behaviour. Also, empirical exploitation of the existing models is recommended

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