Demand sharing inaccuracies in supply chains: A simulation study

We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand error has a negative impact on SC performance, which is exacerbated by the magnitude of the error and by low demand variability scenarios. In contrast, demand delay produces a nonlinear behavior in the supply chain response (i.e., a short delay may have a negative impact and a long delay may have a positive impact), being influenced by the supply chain configuration.Ministerio de Universidad e Investigación (Italia)Universidad de Sevilla V PPIT-USMinisterio de Ciencia e Innovación PROMISE DPI201680750

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

Promise and problems with supply chain management approaches to health care purchasing

Background: Double-digit health care inflation, coupled with widespread reports of poor care quality and deadly medical errors, has caused private sector employers to reevaluate their health benefits purchasing strategies, with a focus on supply chain management approaches. In other industries, this strategy has proven to be an effective method for simultaneously reducing costs and increasing quality. Purpose: This article describes four current applications of supply chain management network methodologies to health care systems and identifies potential ways to improve purchasers‘ return on investment. In particular, information exchanges, purchase decision, and payment agreement components of integrated supply chains are described. Approach: First, visual depictions of the health care supply chain are developed from a purchaser‘s perspective. Next, five nationwide programs designed to realign incentives and rewards across the health care supply chain are described. Findings: Although several nationwide efforts are gaining traction in the marketplace, at this time, no cost reduction and quality improvement program initiative appears to systematically align the entire health care supply chain from providers to purchasers, raising doubt about the ability of supply chain management network techniques to significantly impact the health care marketplace in the short run. Practice Implications: Current individual efforts to coordinate the health care supply chain do not act on all of the actors necessary to improve outcomes, promote safety, and control costs. Nevertheless, there are indications that several of the individual efforts are coming together. If national efforts touching on all critical elements can coordinate with purchasers, then the health care supply chain‘s performance may improve significantly

Patient Risk and Data Standards in Healthcare Supply Chain

Patient safety is one of the most important health care challenges. It is a big concern since 1 in every 10 patients around the world is affected by healthcare errors. The focus of this study is given to preventable adverse events that caused by the errors or system flaw that could have been avoided. In this study, simulation models are developed using Arena to evaluate the impact of GS1 data standards on patient risk in healthcare supply chain. The focus was given to the provider hospital supply chain operations where inventory discrepancy and performance deficiencies in recall, return, and outdate management can directly affect patient safety. Simulation models are developed for various systems and scenarios to compare different performance measures and analyze the impact of GS1. The results indicates that as the validation points are closer to the point of use, the number of recalled or outdated products administered to a patient are still reduced significantly so checking at the bedside or PAR is critical. But validation only at these points may cause some problems such as stock outs; therefore, validating in other locations is also needed

Accessing Antecedents and Outcomes of RFID Implementation in Health Care

This research first conceptualizes, develops, and validates four constructs for studying RFID in health care, including Drivers (Internal and External), Implementation Level (Clinical Focus and Administrative Focus), Barriers (Cost Issues, Lack of Understanding, Technical Issues, and Privacy and Security Concerns), and Benefits (Patient Care, Productivity, Security and Safety, Asset Management, and Communication). Data for the study were collected from 88 health care organizations and the measurement scales were validated using structural equation modeling. Second, a framework is developed to discuss the causal relationships among the above mentioned constructs. It is found that Internal Drivers are positively related to Implementation Level, which in turn is positively related to Benefits and Performance. In addition, Barriers are found to be positively related to Implementation Level, which is in contrast to the originally proposed negative relationship. The research also compares perception differences regarding RFID implementation among the non-implementers, future implementers, and current implementers of RFID. It is found that both future implementers and current implementers consider RFID barriers to be lower and benefits to be higher compared to the non-implementers. This paper ends with our research implications, limitations and future research

The Influence of Managerial Forces and Users’ Judgements on Forecasting in International Manufacturers: a Grounded Study

Despite the improvements in mathematical forecasting techniques, the increase in forecasting accuracy is not yet significant. Previous research discussed various forecasting issues and techniques without paying attention to users’ forces and behaviours that influence the construction of forecasts. This research investigates this gap through examining the managerial forces that influence the judgements of different users and constructors of forecasts in international pharmaceutical companies. A qualitative research applying Grounded Theory methodology is used to explore the concealed forces in forecasting processes by interviewing different constructors and users of forecasts in international contexts. Using the Coding Matrices, the research identifies the forces which induce users’ judgements, and consequently lead to conflicts. The research adds value by providing assessment criteria of forecasting management in future research

Empirical Evidence of RFID Impacts on Supply Chain Performance

Purpose - The purpose of this paper is to investigate the actual benefits of radio frequency identification (RFID) on supply chain performance through the empirical evidence. Design/methodology/approach - The research reviews and classifies the existing quantitative empirical evidence of RFID on supply chain performance. The evidence is classified by process (operational or managerial) and for each process by effect (automational, informational, and transformational). Findings - The empirical evidence shows that the major effects from the implementation of RFID are automational effects on operational processes followed by informational effects on managerial processes. The RFID implementation has not reached transformational level on either operational or managerial processes. RFID has an automational effect on operational processes through inventory control and efficiency improvements. An informational effect for managerial processes is observed for improved decision quality, production control and the effectiveness of retail sales and promotions coordination. In addition, a three-stage model is proposed to explain the effects of RFID on the supply chain. Research limitations/implications - Limitations of this research include the use of secondary sources and the lack of consistency in performance measure definitions. Future research could focus on detailed case studies that investigate cross-functional applications across the organization and the supply chain. Practical implications - For managers, the empirical evidence presented can help them identify implementation areas where RFID can have the greatest impact. The data can be used to build the business case for RFID and therefore better estimate ROI and the payback period. Originality/value - This research fills a void in the literature by providing practitioners and researchers with a better understanding of the quantitative benefits of RFID in the supply chain

The drug logistics process: an innovation experience

Purpose - The purpose of this paper is to present the latest innovations in the drug distribution processes of hospital companies, which are currently dealing with high inventory and storage costs and fragmented organizational responsibilities. Design/methodology/approach - The literature review and the in-depth analysis of a case study support the understanding of the unit dose drug distribution system and the subsequent definition of the practical implications for hospital companies. Findings - Starting from the insights offered by the case study, the analysis shows that the unit dose system allows hospitals to improve the patient care quality and reduce costs. Research limitations/implications - The limitations of the research are those related to the theoretical and exploratory nature of the study, but from a practical point of view, the work provides important indications to the management of healthcare companies, which have to innovate their drug distribution systems. Originality/value - This paper analyzes a new and highly topical issue and provides several insights for the competitive development of a fundamental sector

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