Vendor-managed inventory

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Vendor-managed inventory (VMI) is an inventory management practice in which a supplier of goods, usually the manufacturer, is responsible for optimising the inventory held by a distributor.

In traditional inventory management, a retailer (sometimes called buyer) makes his or her own decisions regarding the order size, while in VMI the retailer shares their inventory data with a vendor (sometimes called supplier) such that the vendor is the decision-maker who determines the order size for both. Thus, the vendor is responsible for the retailer's ordering cost, while the retailer has to pay for their own holding cost. This policy can prevent stocking undesired inventories and hence can lead to an overall cost reduction. Moreover, the bullwhip effect is also reduced by employing the VMI approach in a buyer–supplier cooperation.[1] As replenishment frequencies play an important role in integrated inventory models to reduce the total cost of supply chains which many studies fail to model it in mathematical problems.[2]

A third-party logistics provider can also be involved to make sure that the buyer has the required level of inventory by adjusting the demand and supply gaps.[3]

As a symbiotic relationship, VMI makes it less likely that a business will unintentionally become out of stock of a good and reduces inventory in the supply chain. Furthermore, vendor (supplier) representatives in a store benefit the vendor by ensuring the product is properly displayed and store staff are familiar with the features of the product line, all these while helping to clean and organize their product lines for the store. VMI can also decrease the magnitude of the bullwhip effect.

One of the keys to making VMI work is shared risk. In some cases, if the inventory does not sell, the vendor (supplier) will repurchase the product from the buyer (retailer). In other cases, the product may be in the possession of the retailer but is not owned by the retailer until the sale takes place, meaning that the retailer simply houses (and assists with the sale of) the product in exchange for a predetermined commission or profit (sometimes referred to as consignment stock). A special form of this commission business is scan-based trading, where VMI is usually applied but its use is not mandatory.[4]

This is one of the successful business models used by Walmart and many other big box retailers.[5] Oil companies often use technology to manage the gasoline inventories at the service stations that they supply (see Petrolsoft Corporation). Home Depot uses the technique with larger suppliers of manufactured goods. VMI helps foster a closer understanding between the supplier and manufacturer by using electronic data interchange formats, EDI software and statistical methodologies to forecast and maintain correct inventory in the supply chain.

Vendors benefit from more control of displays and more customer contact for their employees; retailers benefit from reduced risk, better store staff knowledge (which builds brand loyalty for both the vendor and the retailer), and reduced display maintenance outlays.

Consumers benefit from knowledgeable store staff who are in frequent and familiar contact with manufacturer (vendor) representatives when parts or service are required. Store staff have good knowledge of most product lines offered by the entire range of vendors. They can help the consumer choose from competing products for items most suited to them and offer service support being offered by the store.

At the goods' manufacturing level, VMI helps prevent overflowing warehouses or shortages, as well as costly labor, purchasing and accounting. With VMI, businesses maintain a proper inventory, and optimized inventory leads to easy access and fast processing with reduced labor costs.[6]

Classes[edit]

1- Bi-Level VMI Mathematical Models

The first class of VMI, bi-level VMI mathematical model, includes two levels (or echelons) in a supply chain: vendor and retailer. There are three types of VMI mathematical models developed from this class, which are single-vendor single-retailer VMI model,[7] single-vendor multi-retailer VMI model,[8] and multi-vendor multi-retailer VMI model.[9] This class has been significantly developing. For example, single-vendor single-retailer VMI model was extended for multi-product case,[10] the consignment stock (CS),[11] and discount.[12]

2- Multi-Level VMI Mathematical Models

The second class is multi-level VMI mathematical model such as a single manufacturer-single vendor multi-retailer (SM-SV-MR) VMI model.[13] Those studies fail to model replenishment frequencies cannot classified here. As replenishment frequencies play an important role in integrated inventory models to reduce the total cost of supply chains which many studies fail to model it in mathematical problems.

Components of VMI[edit]

1. Inventory location

In VMI practice, inventory location depends on the arrangement between the vendor and the customer. The first option is for the inventory to be located both at the customer's and the supplier's premises. For the supplier, this serves as a safeguard against short delivery cycles or unsynchronized production cycles.[14] On the other hand, this arrangement can also infer higher inventory holding costs because of the need for storage of the material, it's tracking and handling, and the threat of inventory obsolescence.[15]

Another option can be for the vendor to deliver to the customer's central warehouse or alternatively, to a third party's warehouse. The latter can be a solution for buyers that have outsourced part or all of their logistics operations. Managing the inventory at the central warehouse enables better optimization of deliveries, lower costs and ultimately enables the buyer to maximize economies of scale.[16] However, it is not always an option, so third-party warehouses are often the solution to many different problems such as the supplier's warehouse being too far away from the buyer's or the buyer's inexperience in storing particular types of goods that are harder to store.[17]

The inventory can also be located directly at the buyer's premises such as the buyer's on-site warehouse, production line or the shop floor itself.[18] However, replenishing inventory levels at these specific locations can be more costly, less organized and overall more difficult to manage for the supplier.[19]

2. Inventory Ownership

Inventory ownership refers to the ownership of the inventory and when the invoice is being issued to the retailer. In vendor managed inventory, there is a number of solutions in terms of payment and transfer of ownership. [18]

In the first alternative, vendor is the owner of inventory at the premises of customer. Invoice is issued when the items are issued from the stock. In the second alternative, retailer assumes ownership of the inventory, but receives an invoice upon delivery. However, the vendor is not paid until the customer issues the items from stock and within a delay according to agreed terms of payment. [18] This enables risk-sharing between both of the parties, as retailer carries risk of obsolescence while vendor would have been accountable for capital costs and fluctuation in prices of the inventory. [19]

In the third alternative, also referred to as a standard process in traditional order delivery, retailer owns the inventory upon delivery, while the vendor invoices the retailer once the shipment has been made. [18] In this setting, retailer is responsible for inventory investment and holding costs, but has an option of protecting themselves against price fluctuations. [19]

3. Level of Demand Visibility

These elements refer to the type of demand information shared by customers to assist the suppliers in controlling their inventory. Many types of demand information are shared in VMI Program. The demand information that are visible to the supplier are: sales data, stock withdrawal, production schedule, inventory level, goods in transit, back order, incoming order and return. It is argued that sharing data and inventory can improve the supplier’s production planning, make it more stable and increase its visibility. It also provides a better understanding of the seasonal changes, and helps figuring out critical times. The supplier can therefore take advantage of this information and adapt its production to the customers’ requests, and respond faster. With the increasing visibility of information, the supplier has longer timeframe for replenishment arrangement [20] The supplier also gets real time visibility, which allows him to have a hand on the inventory for the buyer demand forecast, which allows for projecting inventory based on future demand to target his inventory (minimize or maximize it). [21]. This stability and coordination allows to reduce the Bullwhip effect, [22] as the manufacturer has a clearer visibility on the supply chain and overview of the incoming demand [23].

Data is usually updated every week and is transmitted through an EDI, which allows to forecast actual market trends. The data is based on real quantities of produced and sold items. This agreement to share information is aimed at maintaining a steady flow of necessary goods.

See also[edit]

References[edit]

  1. ^ Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan (2016-08-01). "Optimizing an inventory model with fuzzy demand, backordering, and discount using a hybrid imperialist competitive algorithm". Applied Mathematical Modelling. 40 (15–16): 7318–7335. doi:10.1016/j.apm.2016.03.013. ISSN 0307-904X.
  2. ^ Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan; Sadeghi, Saeid (2014-10-01). "Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm". Transportation Research Part E: Logistics and Transportation Review. 70: 274–292. doi:10.1016/j.tre.2014.07.007. ISSN 1366-5545.
  3. ^ "What Is Vendor Managed Inventory?", Datalliance, Retrieved Aug. 16, 2016
  4. ^ "Vendor Managed Inventory: Three Steps in Making it Work", NC State University Supply Chain Resource Cooperative, Retrieved Aug. 16, 2016
  5. ^ Sila Çetinkaya & Chung-Yee Lee, "Stock Replenishment and Shipment Scheduling for Vendor-Managed Inventory Systems ", Management Science, Volume 46 Issue 2, February 2000, pp. 217-232. Accessed 9 June 2014
  6. ^ "Insider's Tips to Packaging Issues", CGR Products, Retrieved Aug. 16, 2016
  7. ^ Yao, Yuliang; Evers, Philip T.; Dresner, Martin E. (2007). "Supply chain integration in vendor-managed inventory". undefined. Retrieved 2018-10-15.
  8. ^ Sadeghi, Javad; Sadeghi, Saeid; Niaki, Seyed Taghi Akhavan (2014-07-10). "Optimizing a hybrid vendor-managed inventory and transportation problem with fuzzy demand: An improved particle swarm optimization algorithm". Information Sciences. 272: 126–144. doi:10.1016/j.ins.2014.02.075. ISSN 0020-0255.
  9. ^ Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan; Sadeghi, Saeid (2013-09-01). "Optimizing a multi-vendor multi-retailer vendor managed inventory problem: Two tuned meta-heuristic algorithms". Knowledge-Based Systems. 50: 159–170. doi:10.1016/j.knosys.2013.06.006. ISSN 0950-7051.
  10. ^ javad, sadeghi; ahmad, sadeghi; mohammad, Saidi mehrabad (2011-09-29). "A parameter-tuned genetic algorithm for vendor managed inventory model for a case single-vendor single-retailer with multi-product and multi-constraint". Journal of Optimization in Industrial Engineering. 0 (9). ISSN 2251-9904.
  11. ^ Zavanella, Lucio; Zanoni, Simone (2009-03-01). "A one-vendor multi-buyer integrated production-inventory model: The 'Consignment Stock' case". International Journal of Production Economics. 118 (1): 225–232. doi:10.1016/j.ijpe.2008.08.044. ISSN 0925-5273.
  12. ^ Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan (2016-08-01). "Optimizing an inventory model with fuzzy demand, backordering, and discount using a hybrid imperialist competitive algorithm". Applied Mathematical Modelling. 40 (15–16): 7318–7335. doi:10.1016/j.apm.2016.03.013. ISSN 0307-904X.
  13. ^ Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan; Sadeghi, Saeid (2014-10-01). "Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm". Transportation Research Part E: Logistics and Transportation Review. 70: 274–292. doi:10.1016/j.tre.2014.07.007. ISSN 1366-5545.
  14. ^ Radzuan, Kamaruddin; Abdul Rahim, Mohd kamarul Irwan; Moohd Nawi, Mohd Nasrun; Mazri, Yaakob (January 2018). "Vendor managed inventory practices: A case in manufacturing companies". International Journal of Supply Chain Management. 7 (4): 196–201.
  15. ^ Elvander, Mikael; Sarpola, Sami; Mattsson, Stig-Arne (November 2007). "Framework for characterizing the design of VMI systems". 37 (10): 782–798. doi:10.1108/09600030710848914. Cite journal requires |journal= (help)
  16. ^ Elvander, Mikael; Sarpola, Sami; Mattsson, Stig-Arne (November 2007). "Framework for characterizing the design of VMI systems". 37 (10): 782–798. doi:10.1108/09600030710848914. Cite journal requires |journal= (help)
  17. ^ Radzuan, Kamaruddin; Abdul Rahim, Mohd kamarul Irwan; Moohd Nawi, Mohd Nasrun; Mazri, Yaakob (January 2018). "Vendor managed inventory practices: A case in manufacturing companies". International Journal of Supply Chain Management. 7 (4): 196–201.
  18. ^ a b c d Elvander, Mikael; Sarpola, Sami; Mattsson, Stig-Arne (November 2007). "Framework for characterizing the design of VMI systems". 37 (10): 782–798. doi:10.1108/09600030710848914. Cite journal requires |journal= (help)
  19. ^ a b c Radzuan, Kamaruddin; Abdul Rahim, Mohd kamarul Irwan; Moohd Nawi, Mohd Nasrun; Mazri, Yaakob (January 2018). "Vendor managed inventory practices: A case in manufacturing companies". International Journal of Supply Chain Management. 7 (4): 196–201.
  20. ^ Elvander, Mikael; Sarpola, Sami; Mattsson, Stig-Arne (November 2007). "Framework for characterizing the design of VMI systems". 37 (10): 782–798. doi:10.1108/09600030710848914.
  21. ^ https://www.scmr.com/wp_content/e2open_wp_building_effective_vmi_020216.pdf
  22. ^ Guillaume Marquès, Jacques Lamothe, Caroline Thierry, Didier Gourc. Vendor Managed inventory, from concept to processes, for an unified view. ILS 2008 - 2nd International Conference on Information Systems, Logistics, and Supply chain, May 2008, Bordeaux, United States. p.536-546. hal-00444174
  23. ^ https://ctl.mit.edu/sites/ctl.mit.edu/files/library/public/theses_2008_Kou_ExecSumm.pdf

Literature[edit]

  • Tempelmeier, H. (2006). Inventory Management in Supply Networks—Problems, Models, Solutions, Norderstedt:Books on Demand. ISBN 3-8334-5373-7.
  • Franke, P. D. (2010). Vendor-Managed Inventory for High Value Parts—Results from a survey among leading international manufacturing firms. ISBN 978-3-7983-2211-0

External links[edit]