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

OVAP: A strategy to implement partial information sharing among supply chain retailers

This paper analyses the impact on supply chain performance of adopting different strategies to implement partial information sharing among heterogeneous retailers. Supply chains are modelled using a multi-agent systems approach. We find that the strategy adopted to construct the partial information sharing structure (i.e., the retailers who share information) has a significant impact on supply chain performance. We propose a practical strategy, named Order VAriance Prioritization (OVAP), which gives priority to the retailers with higher order variance. OVAP outperforms the worst (i.e. naive) implementation method by 27.2% and 7.8% with respect to the levels of bullwhip and average inventory.Ministerio de Ciencia e Innovación DPI201680750P

Evaluating Obselete Inventory Policies in a Hospital\u27s Supply Chain

Numerous organizations are currently facing inventory management problems including distributing inventory on time and maintaining the appropriate inventory level to satisfy the end user. Organizations understand the importance of inventory accuracy as any error will increase the purchasing and holding costs affecting investment decisions. Lack of information about effective measures that will allow management to make important business decisions motivated this research to identify a decision criterion for warehouse management. A feasible solution of calculating the carrying cost ratio from purchasing and holding cost is the main objective of this thesis. The carrying cost ratio will allow managers to make critical decisions on supply-chain management. Similar to the carrying cost ration, this thesis also provides a methodology for warehouse management using inventory turns that can be used to identify obsolete inventory. Friedman’s Rank test was performed to validate the decision using primary turns for the dataset obtained from a local hospital. Recommendations have been made to the hospital to facilitate their supply chain that will result in the reduction of excessive inventory. A reduced carrying cost ratio demonstrates consolidating commodities into fewer facilities. The future benefits for the current organization include a reduce building and facility costs, decrease in annual operating budgets, reduction in warehouse operational cost, improvement in labor productivity, warehouse space utilization, and establish performance measures. In conclusion, findings from this research will allow organization to move towards the one-echelon model known as Just-In-Time (JIT) system

Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

An Exploratory Study of RFID Implementation in the Supply Chain

The purpose of this paper is to investigate the barriers and motivations for adopting radio frequency identification (RFID), the level of RFID implementation, the processes RFID is utilized in, and issues in the deployment of RFID. A survey instrument was developed based on a literature review. The survey was then distributed to the members of the Association for Operations Management Rhode Island and Boston chapters. The results were then analyzed. It was found that the majority of the surveyed firms are not considering RFID implementation. Lack of a business case and lack of understanding were cited as their main concerns. For firms considering RFID implementation and firms that had implemented RFID, better inventory management, obtaining competitive advantage, and cost reduction were the three most important motivations for adopting RFID. Financial concerns and the lack of a business case were the most prevalent issues. In addition, product tracking (pallets, cases, and items) in shipping was the most cited RFID application. It was also found that considering firms are facing less pressure from customers to adopt RFID and reported a much higher degree of apprehension regarding potential issues than implementing firms reported for actual difficulties faced. One of the limitations is the small sample size (n = 49) which may limit the generalizability of the results. By identifying barriers, motivations, and issues in the implementation of RFID, this study further educates practitioners on the challenges and opportunities of RFID, as well as providing direction to academicians for further research on this area

Impact of RFID information-sharing coordination over a supply chain with reverse logistics

Companies have adopted environmental practices such as reverse logistics over the past few decades. However, studies show that aligning partners inside the green supply chain can be a substantial problem. This lack of coordination can increase overall supply chain cost. Information technology such as Radio Frequency Identification (RFID) has the potential to enable decentralized supply chain coordinate their information. Even though there are research that address RFID on traditional supply chain, few researches address how to coordinate RFID information sharing in a green supply chain. We study, through simulation experiments, two types of RFID information-sharing coordination under different configurations related with their inventory policies: basic and advanced. Statistical analyses show that better results can be presented in advanced RFID configuration given new coordination and inventory policy decisions presented. In addition, these findings shows what are the RFID information-sharing coordination that can provide better system improvement depending on the supply chain scenarios and factors

Reducing inventory by simplifying forecasting and using point of sale data

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.Includes bibliographical references (leaf 69).This thesis assesses the value to vendors of using point of sale data to predict what retailers will order from them. In particular, we look at how The Gillette Company can use point of sale data generated by two of their customers, (Wal-Mart and Target), to predict the orders of all of Gillette's customers combined. The thesis also examines the impact on forecasts of shortening and simplifying the demand planning process. By improving the forecast of orders from their customers, vendors like Gillette can reduce safety stock inventory which is held as protection against unpredictable demand.by Atul Agarwal [and] Gregory Douglas Barton Holt.M.Eng.in Logistic

Optimising Supply Chain Performance via Information Sharing and Coordinated Management

Supply chain management has attracted much attention in the last decade. There has been a noticeable shift from a traditional individual organisation-based management to an integrated management across the supply chain network since the end of the last century. The shift contributes to better decision making in the supply chain context, as it is necessary for a company to cooperate with other supply chain members by utilising relevant information such as inventory, demand and resource capacity. In other words, information sharing and coordinated management are essential mechanisms to improve supply chain performance. Supply chains may differ significantly in terms of industry sectors, geographic locations, and firm sizes. This study was based on case studies from small and medium sized manufacturing supply chains in People Republic of China. The study was motivated by the following facts. Firstly, small and medium enterprises have made a big contribution to China’s economic growth. Several studies revealed that most of the Chinese manufacturing enterprises became aware of the importance of supply chain management, but compared to western firms, the supply chain management level of Chinese firms had been lagging behind. Research on supply chain management and performance optimisation in Chinese small and medium sized enterprises (SMEs) was very scarce. Secondly, there had been plenty of studies in the literature that focused on two or three level supply chains whilst considering a number of uncertain factors (e.g. customer demand) or a single supply chain performance indicator (e.g. cost). However, the research on multiple stage supply chain systems with multiple uncertainties and multiple objectives based on real industrial cases had been spared and deserved more attention. One reason was due to the lack of reliable industrial data that required an enormous effort to collect the primary data and there was a serious concern about data confidentiality from the industry aspect. This study employed two SME manufacturing companies as case studies. The first one was in the Aluminium industry and another was in the Chemical industry. The aim was to better understand the characteristics of the supply chains in Chinese SMEs through performing in-depth case studies, and built models and tools to evaluate different strategies for improving their supply chain performance. The main contributions of this study included the following aspects. Firstly, this study generalised a supply chain model including a domestic supply chain part and an international supply chain part based on deep case studies with the emphasis on identifying key characteristics in the case supply chains, such as uncertainties, constraints and cost elements in association with flows and activities in the domestic supply chain and the international supply chain. Secondly, two important SCM issues, i.e. the integrated raw material procurement and finished goods production planning, and the international sales planning, were identified. Thirdly, mathematical models were formulated to represent the supply chain model taking into account multiple uncertainties. Fourthly, several operational strategies utilising the concepts of just-in-time, safety-stock/capacity, Kanban, and vendor managed inventory, were evaluated and compared with the case company's original strategy in various scenarios through simulation methods, which enabled quantification of the impact of information sharing on supply chain performance. Fifthly, a single objective genetic algorithm was developed to optimise the integrated raw material ordering and finished goods production decisions under (s, S) policy (a dynamic inventory control policy), which enabled the impact of coordinated management on supply chain performance to be quantified. Finally, a multiple objectives genetic algorithm considering both total supply chain cost and customer service level was developed to optimise the integrated raw material ordering and finished goods production with the international sales plan decisions under (s, S) policy in various scenarios. This also enabled the quantification of the impact of coordinated management on supply chain performances

The application of discrete event simulation and system dynamics in the logistics and supply chain context

Discrete event simulation (DES) and system dynamics (SD) are two modelling approaches widely used as decision support tools in logistics and supply chain management (LSCM). A widely held belief exists that SD is mostly used to model problems at a strategic level, whereas DES is used at an operational/tactical level. This paper explores the application of DES and SD as decision support systems (DSS) for LSCM by looking at the nature and level of issues modelled. Peer reviewed journal papers that use these modelling approaches to study supply chains, published between 1996 and 2006 are reviewed. A total of 127 journal articles are analysed to identify the frequency with which the two simulation approaches are used as modelling tools for DSS in LSCM. Our findings suggest that DES has been used more frequently to model supply chains, with the exception of the bullwhip effect, which is mostly modelled using SD. Based on the most commonly used modelling approach, issues in LSCM are categorised into four groups: the DES domain, the SD domain, the common domain and the less common domain. The study furthermore suggests that in terms of the level of decision making involved, strategic or operational/tactical, there is no difference in the use of either DES or SD. The results of this study inform the existing literature about the use of DES and SD as DSS tools in LSCM