Salvatore Cannella

On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothing

This paper provides an assessment of the impact of collaboration and smoothing replenishment rules on supply chain operational performance and customer service level. Three supply chain configurations (i.e. Traditional, Information Exchange and Synchronised) in which orders are generated by smoothing (S, R) inventory control policies are studied for different proportional controllers. A supply chain stress test is performed through a sudden and intense change in demand. A structured and extended supply chain assessment framework is adopted. The main conclusions of this paper are the following. (i) The impact of Supply Chain Collaboration on overall supply chain performance is greater than that of order smoothing. Order smoothing mitigates the bullwhip effect, but it may have a negative impact on customer service. Supply Chain Collaboration mitigates the bullwhip effect, provides inventory stability, limits lumpy orders and enhances customer service level. (ii) The negative effect on customer service level of order smoothing is almost eliminated in synchronised supply chains.

Metrics for Bullwhip Effect Analysis

A bullwhip measurement system based on a two-criterion assessment—‘internal process efficiency’ and ‘customer service level’—is developed in this paper. The framework is designed to assess both individual (single member) and systemic (whole supply chain) performances. Data collection and calculation methods, update and monitoring mechanisms, as well as related procedures for each metric used, are detailed. A comparative analysis with a recent work by Barlas and Gunduz is performed, showing that the adoption of the proposed performance measurement system can help academics and practitioners to better understand, study and avoid the bullwhip effect. Such analysis also provides evidence on the relevance of considering when analysing the bullwhip effect in supply chains, the ‘customer importance’ aspect that is often forgotten in the published literature.

Impact of reverse logistics on supply chain performance

Purpose – The purpose of this paper is to analyse the impact of reverse logistics on order and inventory variance amplification in a single-echelon supply chain (SC) and to propose a new order policy for dampening such amplification. Design/methodology/approach – A general review of the literature on sustainable operations and on the impact of reverse logistics on SC performance provides the foundation for the study. The authors use difference equation math approach for modelling and analysing a closed SC. A proper design of experiment and data collected from the European Union statistics validate the obtained numerical results. Findings – The variability of reverse flow in a closed loop SC increases the serviceable inventory variance. However, a proper design of the reverse flow considerably improves the global performance. To this purpose, the authors propose a new order policy, namely R-APIOBPCS, which explicitly considers the reverse flow of products. Research limitations/implications – The paper pres...

On the Bullwhip Avoidance Phase: The Synchronised 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 experiments 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–distribution lead times could significantly affect customer service level. Both results have important consequences for the design and operation of supply chains.

Inventory policies and information sharing in multi-echelon supply chains

The aim of this article is to show how to modify a replenishment rule in relation to the operational information shared by suppliers. More specifically, we present a model of an Automatic Pipeline Variable Inventory and Order-Based Production Control System rule for a multi-echelon supply chain characterised by different increasing levels of shared information. A numerical study is presented to underline the performance differences for three variants of the smoothing order rule in terms of bullwhip reduction, inventory stability and operational and customer responsiveness. Results show how the effectiveness of a smoothing replenishment rule depends on the level of information sharing.

The effect of Inventory Record Inaccuracy in Information Exchange Supply Chains

The goal of this paper is to quantify the impact of Inventory Record Inaccuracy on the dynamics of collaborative supply chains, both in terms of operational performance (i.e. order and inventory stability), and customer service level. To do so, we model an Information Exchange Supply Chain under shrinkage errors in the inventory item recording activity of their nodes, present the mathematical formulation of such supply chain model, and conduct a numerical simulation assuming different levels of errors. Results clearly show that Inventory Record Inaccuracy strongly compromises supply chain stability, particularly when moving upwards in the supply chain. Important managerial insights can be extracted from this analysis, such as the role of ‘benefit-sharing’ strategies in order to guarantee the advantage of investments in connectivity technologies.

Capacity constrained supply chains: a simulation study

This paper explores the relationship between constrained capacity and supply chain performance. Six capacity constraint levels are studied under different inventory policies and information sharing strategies. The results suggest that an increment of production capacity, used in industry as local approach to manage increasing incoming orders, does not necessarily imply an improvement in customer service. In presence of information distortions, the strategy of augmenting production capacity can lead to satisfy at a higher cost an over-estimated market demand. The collaborative practices provide bullwhip effect dampening and inventory stability, and increase the ability of the structure to avoid this risk.

On bullwhip-limiting strategies in divergent supply chain networks

Abstract 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.

Serial vs. divergent supply chain networks: a comparative analysis of the bullwhip effect

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect, which creates inefficiencies due to high variation in the order quantities placed between companies, leading to a flow of a larger number of units than the actual need, increasing stock and generating stock-outs. Since this phenomenon has been recognised as one of the main obstacles for improving SCN performance, recently it has received a lot of attention by SCN managers and researchers. One of the most common simplifying assumptions in the literature is to assume that the SCN adopts a serial structure. The present work addresses a comparative analysis of the bullwhip effect between a serial SCN and a more complex divergent SCN. To do so, we analyse the response of both SCNs under two different input demands: a stationary demand and an impulse demand. The results reveal that there are not significant differences in terms of bullwhip effect between both SCNs for a stationary demand. Nevertheless, we show how for a violent disturbance in customer demand there is a great different between the two SCNs.

An IT-enabled supply chain model: a simulation study

During the last decades, supply chain collaboration practices and the underlying enabling technologies have evolved from the classical electronic data interchange (EDI) approach to a web-based and radio frequency identification (RFID)-enabled collaboration. In this field, most of the literature has focused on the study of optimal parameters for reducing the total cost of suppliers, by adopting operational research (OR) techniques. Herein we are interested in showing that the considered information technology (IT)-enabled structure is resilient, that is, it works well across a reasonably broad range of parameter settings. By adopting a methodological approach based on system dynamics, we study a multi-tier collaborative supply chain. Results show that the IT-enabled supply chain improves operational performance and customer service level. Nonetheless, benefits for geographically dispersed networks are of minor entity.