Vendor Managed Inventory in Practice: Efficient Scheduling and Delivery Optimization

PurposeThe purpose of this paper is to investigate vendor managed inventory (VMI) for the supply of medicines between distributors and hospitals to identify factors that may affect VMI adoption.Design/methodology/approachTwo contrasting VMI initiatives involving five organizations (three hospitals, one distributor and one manufacturer/supplier) are studied. A case study method with semi-structured interviews is used with triangulation in data collection, site visits and document analysis to enhance reliability and validity. The cases are analyzed and compared with respect to hospital, supplier, product and supply chain integration characteristics.FindingsA successful public sector VMI initiative and an unsuccessful private sector VMI initiative are identified. The public sector supplier focuses on improving service level while the private sector supplier seeks to strengthen relationships with a key customer. Hospital characteristics, including type of hospital, top management perspectives and the hospital’s willingness to share information, are critical in decisions on VMI initiation or termination. Relatively stable demand products are preferred for a VMI approach. Hospitals may perceive risks in VMI adoption for medicines as it involves relinquishing control of critical supplies and may result in “lock-in” with a particular supplier.Research limitations/implicationsThe cases have been conducted in one country, which may affect generalization of the findings. Wider empirical evidence from other countries in both developed and less developed regions will be beneficial.Practical implicationsVMI is advocated as being beneficial in many supply contexts. However, it is challenging to implement. The study identifies factors that affect the adoption of VMI for hospital pharmaceuticals and provides guidance on initiating VMI in a hospital context.Social implicationsThe potential for VMI in public health projects to enable greater access to critical medicines is highlighted.Originality/valueThe paper provides supply side and demand side perspectives on VMI adoption in an important sector. It highlights the need for greater understanding of the perceived and actual risks in VMI from the perspective of both the hospital and the supplier and for much clearer advice on which pharmaceutical products are appropriate for VMI control in a hospital context.

Many strategies have been developed to manage supply chain operations effectively. Vendor Managed Inventory (VMI) system is one of the prevalent strategic tools of the supply side logistics based on the electronic data exchange and business process automation among the suppliers and customers to enhance the competitive advantage. VMI is widely used in different industries including automotive sector. The VMI concept is a continuous replenishment program where suppliers are given access to demand and inventory level of customers and they are fully responsible for managing and replenishing the customer’s stock. VMI’s extension on customer satisfaction cannot be perceived sufficiently by decision-makers who are responsible to develop and invest in the customer-supplier relationship. This paper presents a path model using the method of Partial Least Squares (PLS) regression to give insight to decision-makers to understand effect of the VMI adoption on customer satisfaction. This paper investigates both determinants of relative factors of successful VMI adoption and the relationship in the supply chain with an empirical automotive industry case. The results show that the collaboration and coordination between customer and supplier and infrastructure of the information-sharing are the important dimensions to add value to the supply chain and to enhance customer satisfaction.

The vendor managed inventory (VMI) is an efficient coordination policy in supply chain management, in which supplier is responsible to manage inventory at the buyer and decides on replenishment policies. This paper presents a VMI model for a supply chain problem with a single supplier, multi-buyer and multi-product, via a production-inventory system in which shortage is allowed and partially backordered. In order to take into account the concern about environmental issues, the total green house gas emission is also considered as a green constraint. The aim is to find the appropriate values of production quantity and the maximum shortage level for all products of all buyers in such a way that the total cost of supply chain is minimized under VMI. The problem is formulated as a non-linear programming model and then a decomposition based analytical approach is proposed to solve it optimally. At the end, a numerical example is discussed to illustrate the proposed approach.

Supply chain management is well recognised and implemented in private sectors, but the beneficial of supply chain management in public sector is limited shown in the literature. This paper presents a comprehensive supply chain simulation study for a real case of Thai public sector focusing on its material supply network. The supply network consists of four stages in inventory system: head office, regional warehouse, main warehouse and service warehouse. This study aims to propose three different strategies according to the combination of purchasing structure and vendor managed inventory (VMI) with targeting to reduce lead time and cost. The discrete event simulation (DES) is a powerful tool used to reveal the supply chain performances. The three strategies result in shorter lead time and cost reduction. The decentralised purchasing with VMI on each echelon to support continuous replenishment offers the best solution. The managerial implication is provided to enable the enterprise to improve the supply chain performance measures.

A Strategic Approach to Collaborative Inventory Management

Eastern route of south-to-north water transfer project is selected as a study case. Vendor management inventory (VMI) control theory is introduced into the study on water inventory control of the node lake of the project. When the possibility of the flood is taken into account, water inventory control models and water utilization profit models under independent control strategy, centralized control strategy and VMI control strategy are set up. Then VMI and independent control strategies of water resource are compared and restriction conditions of VMI control strategy are deduced. Finally, profit change curves of water buyers and water sellers under different inventory control strategies are obtained in simulation testing. The result shows that VMI control strategy can increase water utilization efficiency and improve the whole profits of water supply chain system. The study can provide guidance for the operations of south-to-north water transfer project and other inter-basin water transfer projects.

It is tempting to say that, for a very long time, supply chain management has been a central topic in the field of management science and operations management. In fact, however, it has evolved from the seminal work done in the 1960s on multiechelon inventory models to recent studies of various mechanisms for coordinating supply chain decisions. In this evolution, one sees a clear shift from studying centralized planning models, in which a central planner makes all the decisions to optimize a systemwide objective, to focusing on decentralized systems with independent decision makers. This is no trival change, for it is one step closer to many real life situations, it has brought about another layer of complexity, and it often requires the use of new analytical tools. The department of supply chain management was created to recognize, emphasize, and encourage this change, and it will continue to do so. Organizing supply chain activities is about determining who does what (in the case of managers, who decides what), who knows what, and the economic incentives motivating supply chain members. This suggests that the management of supply chains can be addressed along three dimensions: allocation of decision rights, information elicitation and sharing, and incentive alignment. This framework matches what we observe in practice: vendor-managed inventory is a supply chain partnership to reallocate stocking decision rights; the creation of corporate communication networks is an example of information sharing; and the myriad of contracts signed among supply chain partners are attempts to align incentives. Moreover, the above three dimensions are likely to characterize the research frontier in supply chain management for the years to come. The Department of Supply Chain Management welcomes papers that are motivated by real-world operations problems and contribute to the understanding of supply chain management issues. The contributions can be methodological, conceptual, empirical, application-oriented, etc. The department especially welcomes papers that present novel models that may open up new directions of research. Needless to say, all submitted manuscripts must follow the guidelines of Management Science, and they will be rigorously refereed according to the normal standards of the journal. Please send four copies of the paper to the departmental editor of supply chain management at the address printed above. The associate editors for the department are: Sven Axsater, Lund University Gerard P. Cachon, University of Pennsylvania Gary Eppen, University of Chicago Stephen C. Graves, MIT Albert Y. Ha, Yale University Martin A. Lariviere, Northwestern University Evan L. Porteus, Stanford University Ananth Raman, Harvard University Kaj Rosling, Lund University Jeannette Song, University of California, Irvine Sridhar Tayur, Carnegie Mellon University Seungjin Whang, Stanford University

Numerous studies show that the application of Vendor Managed Inventory (VMI) provides benefits for members of the supply chain. This research considers the application of VMI in a supplier-buyer relationship and develops an analytical model to prove the benefits obtained from the VMI collaborative initiatives. A mathematical model is developed for a two-level supply chain consists of single supplier and single buyer in a probabilistic demand situation. The analytical model shows that the VMI implementation in the probabilistic inventory model, considering leadtime as a decision variable, has the ability to reduce the supply chain expected total cost, reduce the leadtime, therefore increase the frequency of replenishment and improve the service level. Numerical examples are given to prove these results analytically.

As an inventory management model, VMI (Vendor Management Inventory) has gradually become the main way for dot-companies on the supply chain to improve their relationships between each other and the overall competitive advantages. Aiming at a two-level supply chain with demand uncertainty, this paper analyzes the impact of the VMI model on supply chain inventory management from the aspect of inventory control. The results show that the implementation of VMI model can effectively reduce the railway fastener inventory and the total cost of the supply chain.

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

A supply chain model of vendor managed inventory

Despite the importance of transport within the supply chain, it has traditionally been treated as a separate functional silo within businesses. More recently, there has been increased recognition that transport needs to be integrated into the supply chain. This chapter considers the role of vendor managed inventory and demonstrates how it can be used to improve both transport and supply chain performance. With VMI control, inventory across the supplier/customer interface (including transport) is managed holistically. Scenario analysis is carried out via simulation and through a case study from the U.K. grocery sector. Among the benefits identified are control of the bullwhip effect, improved customer service, lower transport costs, and improved vehicle fill. In addition, it is found that VMI is particularly effective during times of pressure within the supply chain.

PurposeTo identify the key determinants of successful vendor managed inventory (VMI) and strategic supply chain relationships in the New Zealand (NZ) food industry.Design/methodology/approachThe research primarily used action research, supported by a literature review, triangulation and case studies from other industries and countries.FindingsEight key factors impacting the success of organisation‐level VMI and strategic supply chain relationships were identified. These were integrated into a framework that provides a model for practitioners to follow when establishing VMI and strategic supply chain relationships in the NZ food industry.Research limitations/implicationsThis research was conducted using action research in the NZ food industry. As a result, these research findings may need to be modified and further adapted before applying to less concentrated food industries in other countries.Practical implicationsPractical guidelines are provided for practitioners who wish to improve their organisation's supply chain activities through VMI and strategic supply chain relationships.Originality/valueThe key outcome was a working model that identifies the key determinants of successful VMI and strategic supply chain relationships in the NZ food industry, at an organisation‐level. A secondary outcome was the contribution to knowledge from an action research perspective.

Supply chain coordination mechanisms under flexible contracts

Inventory management is one of the key functions in any supply chain. Since inventory cost occupies a significant portion of supply chain cost, it is essential to employ a good inventory policy in order to reduce the supply chain cost while improving the service level. This paper presents a vendor managed inventory (VMI) policy with emergency orders for a supply chain with a single vendor and two independent retailers. A mathematical model is developed using the concept of demand rate, assuming Poisson demand for the retailers. The formulated model is used to help determine the optimal system base stock level, delivery quantities to retailers and the cycle length such that the total expected inventory cost of the system is minimised. Numerical experiments and sensitivity analysis are then conducted to examine the effect of model parameters on total inventory cost and optimal solution.