Supply Chain Performance Improvement Using Vendor Management Inventory Strategy W. Xu, D.P. Song, M. Roe Business School, University of Plymouth, Plymouth, UK (
[email protected]; Dongping@
[email protected];
[email protected])
investigated the role of lead time reduction in improving demand chain performance. Many other studies have confirmed that information sharing is an essential mechanism to reduce the bullwhip effect (e.g. [8], [9], [10]). Ozer [11] discussed the benefits of advanced demand information and its impact on allocation decisions in a one-warehouse-multiple-retailer system. Thonemann [12] analyzed how the values of advanced demand information depend on the characteristics of the supply chain and on the quality of the shared information, and identified conditions under which sharing advanced demand information could significantly reduce cost. Information sharing does not necessarily imply the coordination of decision making in supply chains. A step further from information sharing is the coordinated management for supply chains. In this aspect, a commonly used approach is vendor managed inventory (VMI). Under VMI, the vendor will take responsibility to manage the inventories for downstream entities in the supply chain based on the demand and inventory information provided by downstream entities. There have been sufficient evidences that show that VMI can significantly improve SCM such as reducing total supply chain cost and lead time. For example, Vlist et al. [13] compared non-VMI and VMI in a single buyer and single supplier supply chain system. Song and Dinwoodie [14] quantified the effectiveness of VMI in comparison with retailed management inventory using dynamic programming theory in the context of uncertain replenishment lead-time and uncertain demand. Yu, et al. [15] discussed the interactions between manufacturer and retails and showed that VMI can benefit the entire supply chain eventually although not necessarily to the manufacturer initially. Kiesm and Broekmeulen [16] examined three different VMI strategies and showed their benefits in a stochastic multi-product serial two-echelon system, e.g. reducing the order picking cost and transportation cost. Darwish and Odah [17] developed a VMI model that mainly includes a contractual agreement between a single vendor and multiple retails for global optimal solution. Although a large number of studies on VMI existed in the literature, most of them were characterized by modeling/ simulation approaches and focused on operational efficiency in the grocery industry (e.g. [18], [19]). Few studies concerned with the application of VMI to supply chains including manufacturer and its suppliers using empirical data.
Abstract - This paper considers supply chain performance improvement in a real case study, a Chinese medium-sized aluminum manufacturer. The case supply chain is first described through process mapping. Its inefficiency is analyzed in relation to the associated information flows and material flows. A vendor managed inventory (VMI) strategy is developed and applied to the case supply chain. It is shown that the VMI strategy can significantly improve the supply chain performance such as reducing customer order cycle time and reducing safety inventory costs. Other benefits to the manufacturer and its suppliers and the implications of the VMI implementation are discussed. Keywords - Supply chain performance, information sharing, vendor management inventory, aluminum industry, case study.
I. INTRODUCTION The importance of supply chain performance (SCP) and supply chain management (SCM) has been well recognized regardless of the geographic area and industrial sectors. For example, Gunasekarana et al. [1] studied British companies in order to better understand the importance of supply chain performance measurement and metrics. Bossert et al. [2] argued that centralized control could be more effective than decentralized control in medicine logistics chains in Guatemala and Ghana. Brewer and Speh [3] analyzed different types of supply chains and suggested using the balanced scorecard to evaluate SCM. Slade et al. [4] built a cost comparison model to measure the performance of cellulosic ethanol supply chains in Europe. They divided the costs into different types in accordance with the importance, location and existing market requirements. In the last decade, a lot of research has been done in the area of SCM improvement including reducing information asymmetry, reducing lead time, taming bullwhip effect, and minimizing total costs. A fundamental requirement to achieve that is to share information among the supply chain members. For example, Hsieh et al. [5] stated that information orientation and information collection could effectively reduce information asymmetry. Hou et al. [6] reported that better coordination and revenue sharing could reduce lead time and transaction uncertainty in a two-stage supply chain. De-Treville et al. [7] discussed two perspectives, i.e. supply chain and demand chain, and
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Different industries have their own characteristics and different supply chains may have different types of partnerships between channel members. It would be interesting to investigate the development and application of VMI in real cases. Particularly, in China most mediumsized manufacturers neglect SCM problems and there is lack of research on the development of SCM for these companies. This paper focuses on a real case study, a Chinese Aluminum manufacturer-oriented supply chain, and aims to develop a vendor managed inventory strategy to improve the SCP and discuss the benefits to all entities in the supply chain. The paper is organized as follows. In the next section, the supply chain in the case company is described through supply chain process mapping. The inefficiency of the supply chain performance is analyzed. In section 3, we propose a modified VMI strategy that can be applied to the case supply chain and evaluate its benefits. In section 4, a broad discussion about the implications of VMI in the case context is provided. Finally, conclusions are made in section 5.
suppliers, and also the production planning activities (as shown in dotted lines in Fig. 1): 1. Customers place orders to manufacturer; 2. Manufacturer checks raw materials (RM) inventory; 3. Manufacturer places order to suppliers; 4. Suppliers confirm order to manufacturer; 5. Manufacturer performs production planning; 6. Manufacturer confirms orders to customers. The physical material flows involve the processing and storage of associated raw materials (RM) and finished goods (FG) in the supply chain. They are shown in Fig. 1 in solid lines such as: 7. Suppliers produce raw materials; 8. Transport raw materials from suppliers to manufacturer’s warehouse; 9. Store and transport raw materials from warehouse to production units; 10. Manufacturer produces finished goods; 11. Manufacturer transport and store finished goods in its warehouse; 12. Transport finished goods to customers. In the current practice, information is passed on step by step from customers to manufacturer and to suppliers. The company makes production plans after receiving customer orders, whereas raw materials may be already available or be purchased when receiving customer orders. In that sense, the company is operated in a buildto-order or make-to-order mode.
II. SUPPLY CHAIN IN THE CASE COMPANY The case company is located in Shangdong province in China and has about 900 employees. The company requires four main types of raw materials (RM). Three of them are purchased from a group of suppliers, and the forth is the electrical power that can be supplied continuously. The company produces four key products, aluminum pig A199.90, A199.85, A199.70A and A199.70, which are sold nationwide in China. The supply chain includes suppliers, manufacture, warehouse and customers.
B. Order cycle time in the case supply chain Order cycle time (OCT), also termed as customer lead time, is defined as the duration from the time when a customer places an order to the time that the customer receives the shipment. OCT is a key indicator to measure the supply chain performance. In the case supply chain, the OCT consists two major sequential parts: information lead time (from customer placing an order to the manufacturer confirming the order) and physical lead time (from raw material supply to the delivery of finished goods to customers). According to the data collected from the case company, the lead times for the activities in the case supply chain are shown in Fig. 2.
A. Supply chain process mapping Process mapping is a useful tool to make complex systems visible and facilitate to identify the supply chain problems, e.g. poor coordination of effort, incompatible information systems, long cycle time, etc. A process map is a graphical representation of a system that consists of a sequence of steps that are performed in order to produce some desired outputs [20]. The supply chain in the case company can be illustrated in Fig. 1. 7) Produce RMs
suppliers
10) Produce FGs
8) Transport RMs
suppliers
Place orders to confirm orders >24 hours
9) Store & transport RMs
warehouse
11) Transport & store FGs
manufacturer
warehouse
Production RM1: 24h RM2: 600-720h RM3: 24h RM4: 0h
12) Transport FGs to customers
customers
manufacturer Store & transport 24h
Production 0.064h
warehouse Transport & store 24h
customers Transport 3-11h
Fig. 2. Lead times in the case supply chain.
2) Check inventory 1) Place orders to manufacturer
3) Place orders to suppliers 4) Confirm orders to manufacturer
warehouse Transport 0.5-2h 0.5-6h 2.5h 0h
Place orders to confirm orders >168 hours
5) Production planning
Four types of raw materials have different production lead times and transportation times. For example, raw material 2 requires 600-720 hours to produce while raw material 4 is always available. The manufacturer’s daily production capacity is 375 tons, which indicates 0.064 hour per ton. Depending on whether raw materials are available when receiving customer orders, the order cycle time is calculated differently as follows.
6) Confirm orders to customers
Fig. 1. Information flow and material flow in case supply chains.
Fig. 1 shows the information flows and material flows between suppliers, manufacturer, warehouse and customers in the supply chain. The information flows mainly included six processes associated with order processing between customers, manufacturer and
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If raw materials are not available when receiving customer orders, the minimum OCT is given by: OCT1 = TMC + Min{TP1+TT1, TP2+TT2, TP3+TT3, TP4+TT4} + TST + Q*TP + TTS + TC, Where TMC denotes the information lead-time from customer placing an order to the manufacturer confirming the order; TPi is the production lead-time of raw material i per ton (i=1, 2, 3, 4). However, as multiple suppliers are used and the production lead-time can be regarded as independent of order quantity from the manufacturer; TT1 is the transportation time of raw material 1 from suppliers to the manufacturer’s warehouse; TST denotes the time that raw materials spend at warehouse and transportation; TP is the manufacturer’s production time per ton of finished goods; Q is the total order quantity in tons to be produced in the schedule including the current customer order; TTS is the transportation and storage time of final goods in the manufacturer’s warehouse; TC is the delivery lead-time from warehouse to the customer. If raw materials are available when receiving customer orders, the minimum OCT is given by: OCT2 = TMC – TSM + TST + Q*TP + TTS + TC, Where TSM denotes the information lead-time from the manufacturer placing an order to the suppliers confirming the order. Given the data in Fig. 2, it can be calculated that the minimum order cycle time is: 168 + 600.5 + 24 + 0.064Q + 24 + 3 = 819.5+0.064Q hours in situations with unavailable raw materials, and 168 – 24 + 24 + 0.064Q + 24 + 3 = 195.5+0.064Q hours in situations with available raw materials. As we can see there is a huge difference of the order cycle times between raw material unavailable and available situations (i.e. OCT1 and OCT2). There is also a very significant part of information lead-time that could be reduced in both situations. Therefore, it is believed that an appropriate re-engineering of the SCM could greatly improve the supply chain performance.
decision up to the upstream entity. In return, upstream keeps inventory and bears the risk of demand uncertainty. A. Vendor-hub VMI This paper aims to adjust the vendor-hub concept and apply it to the case supply chain. Here the raw material inventory will still be held in the manufacturer’s warehouse, but its suppliers are allowed to access the inventory information at any time and the management of raw material inventory replenishment is delegated to the suppliers. There is an agreed two-week stock of raw materials in the warehouse. Under such arrangement, whenever the manufacturer pulls raw materials out of the warehouse, this information will be immediately passed on to the suppliers. The suppliers can then make decisions on scheduling production and arranging deliveries to maintain the agreed inventory level at the manufacturer’s warehouse. More specifically, the activities in the case supply chain under the vendor-hub VMI can be described in a diagram shown in Fig. 3. The manufacturer is assured by the suppliers that raw materials are always available at a two-week inventory level. Therefore, as soon as it receives customer orders, it can start production planning. This is followed by the order confirmation to customers and updating inventory in the raw material warehouse. The manufacturer can then start moving raw materials from warehouse to the production units and initiate producing finished goods, followed by transportation and storage at warehouse, and finally delivery to customers. On the other hand, because suppliers can access raw material inventory at any time, the information of inventory change can be picked immediately after the manufacturer updates the inventory at the raw material warehouse. This will then trigger the suppliers’ production and delivery of raw materials to replenish the inventory at the manufacturer’s warehouse. 1. Customers place orders 2. Manuf. production planning
III. APPLICATION OF VMI IN CASE SUPPLY CHAIN There are many forms of VMI from basic replenishment systems to more complex computerized approaches. Lee and Chu [21] reviewed a few common forms of VMI including VMI with full refund, consignment VMI, and the vendor-hub. For example, the vendor-hub approach has been used in automotive industry, in which the manufacturer requests a supplier to keep a minimum stock (usually two weeks of buffer) in supplier’s warehouse or hub and only pays the supplier when goods are pulled and consumed. The common characteristics of the VMI approaches are: downstream entities provide demand and/or inventory information to the upstream entity and leave the inventory management
3a. Manuf. confirm orders
3b. Manuf. update inventory
4a. Store & transport RMs
4b. Suppliers access inventory
5a. Manuf. produce FGs
5b. Suppliers produce RMs
6a. Transport & store FGs
6b. Suppliers transport RMs
7. Transport FGs to customers Fig. 3. The sequence of activities under VMI.
The activities in Fig. 3 can be linked back to the case supply chain to show the information flows and material flows under the vendor-hub VMI in Fig. 4, which can be more clearly compared to the original supply chain in Fig. 1.
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5b) Produce RMs
suppliers
C. Inventory cost reduction
5a) Produce FGs
6b) Transport RMs
4a) Store & transport RMs
warehouse
6a) Transport & store FGs
manufacturer
7) Transport FGs to customers
warehouse
customers
3b) Update inventory 1) Place orders to manufacturer
4b) Inventory information 2) Production planning
3a) Confirm orders to customers
Fig. 4. Information flow and material flow under VMI.
B. Order cycle time reduction Under the VMI control, customer’s order cycle time consists of the activities 1, 2, 3a, 4a, 5a, 6a and 7 (see Fig. 3). The first three activities represent the information flow between customer and manufacturer, while the remaining four activities represent the physical material flow. The OCT can be calculated by OCTVMI = TMC(VMI) + TST + Q*TP + TTS + TC, Where TMC(VMI) denotes the information lead time from customer placing an order to the manufacturer confirming the order under the VMI strategy. It is expected that TMC(VMI) would take about 8 to 24 hours. Therefore, the minimum order cycle time becomes: 8 + 24 + 0.064Q + 24 + 3 =59.5 + 0.064Q hours, which is substantially shorter than OCT1 and OCT2. Table 1 compares the customer OCT (in days) between the current practice and the VMI approach with different total order quantity to fill. The first column of table 1 represents different scenarios, i.e. the manufacturer has total 1 day, 7 days, 14 days, 21 days and 28 days of work (in tons) to do in order to meet the current customer. It can be seen that VMI can reduce order cycle time by 50%~90% from the situations with unavailable raw materials, and by 16%~62% from the situations with available raw materials. TABLE I OCT COMPARISON (IN DAYS) WITH DIFFERENT SCENARIOS Q 375 2625 5250 7875 10500
OCT1 35.15 41.15 48.15 55.15 62.15
% reduction % reduction OCT2 OCTVMI from OCT1 from OCT2 9.15 3.48 90.10% 61.96% 15.15 9.48 76.96% 37.41% 22.15 16.48 65.77% 25.59% 29.15 23.48 57.42% 19.44% 36.15 30.48 50.96% 15.68%
TABLE 2 INVENTORY COST COMPARISON (IN GBP) Current practice VMI Safety stock Inventory Safety stock (ton) cost (GBP) (ton) RM1 20000 342000 10132.5 RM2 5000 135600 2782.5 RM3 20 840 171.15 Total 478440
Inventory cost (GBP) 173265.8 75461.4 7188.3 255915.5
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In the current practice, the case company holds 20000 tons of raw material 1, 5000 tons of raw material 2 and 20 tons of raw material 3 that are served as safety stock. The purchase prices for raw material 1, 2 and 3 are 285, 452 and 700 GBPs respectively. With the implementation of VMI, it can reduce the safety stock to two weeks’ production quantity. To produce one ton of finished goods, it requires 1.93 tons RM1, 0.53 tons RM2 and 0.0326 tons RM3. As raw material 4 has no inventory, it is omitted here. Assume the inventory carrying charge is 6% per year. Table 2 compares the annual inventory holding costs (in GBPs) under the current practice and under the VMI approach. The cost reduction achieved by using VMI from the current practice is 46.51%. IV. DISCUSSION Through the re-engineering of the SCM in the case company, the supply chain performance can be significantly improved. The benefits to the manufacturer of using VMI strategy include: (i) reducing customer order cycle times; (ii) reduce safety stock inventory costs and also saving storage spaces; (iii) eliminating or simplifying the documentation and information flow since there are no longer order placing and confirmation processes between the manufacturer and its suppliers; (iv) as the manufacturer delegates the management of raw material inventory to its suppliers, it can save administration costs as well. The suppliers can also benefit a lot from the use of VMI. For example, the suppliers can directly access the inventory information at the manufacturer’s site, which reflects the end-customers’ demands more accurately. The demand information will not be distorted and the bullwhip effect can be reduced. Secondly, the close and long-term relationship with the manufacturer can stabilize the demands and sales of the suppliers’ products, and smooth the production and delivery planning; Thirdly, the simplification of order processing procedure between the manufacturer and the suppliers can also reduce suppliers’ order processing costs. However, to implement the proposed VMI, trust and partnership should be established between the manufacturer and its suppliers. The possible issue is the risk of exposing sensitive data, e.g. financial status, identity of end customers. In addition, an electronic data interchange (EDI) system is necessary to facilitate the data exchange. Nevertheless, both issues could be solved for Chinese medium-sized companies. Note that under VMI the manufacturer’s raw material warehouse serves as an interface or hub to exchange demand and inventory information between the manufacturer and the suppliers. Therefore, the information about the end customers is not directly accessible to the suppliers, neither the financial
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information about the manufacturer. Moreover, the manufacturer can still keep its own raw material warehouse within the controllable distance. As for the technology, since Internet and EDI are mature technologies, it is feasible for the case company to implement Internet based EDI from both financial and technical perspectives.
[7] S. De-Treville, R.D. Shapiro, and A.P. Hameri, “From supply chain to demand chain: the role of lead time reduction in improving demand chain performance.” Journal of Operations Management, vol. 21, no. 6, pp. 613627, 2004. [8] H.L. Lee, V. Padmanabhan, and S. Whang, “Information distortion in a supply chain: the bullwhip effect,: Management Science, vol. 43, pp. 546-558, 1997. [9] X. He, “See the Supply Chain Management Information Technology Support System from the View of Beer Game,” The Eighth Wuhan International Conference on E-Business, 1-111, pp. 462-465, 2009. [10] Y. Ouyang, “The bullwhip effect in supply chain networks,” European Journal of Operational Research, vol. 201, no. 3, pp. 799-810, 2010. [11] O. Ozer, “Replenishment strategies for distribution systems under advance demand information,” Management Science, vol. 49, no. 3, pp. 255-272, 2003. [12] U.W. Thonemann, “Improving supply-chain performance by sharing advance demand information,” European Journal of Operational Research, vol. 142, pp. 81-107, 2002. [13] P.V.D. Vlist, R. Kuik, and B. Verheijen, “Note on supply chain integration in vendor-managed inventory,” Decision Support Systems, vol. 44, pp. 360-365, 2007. [14] D.P. Song, and J. Dinwoodie, “Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands,” Production Planning & Control, vol. 19, no. 6, pp. 590-600, 2008. [15] H.S. Yu, A.Z. Zeng, and L.D. Zhao, “Analyzing the evolutionary stability of the vendor-managed inventory supply chains”, Computers & Industrial Engineering, vol. 56, pp. 274-282, 2009. [16] G.P. Kiesm, and R.A.C.M. Broekmeulen, “The benefit of VMI strategies in a stochastic multi-product serial two echelon system,” Computers & Operations Research, vol. 37, pp. 406-416, 2010. [17] M.A. Darwish, and O.M. Odah, “Vendor managed inventory model for single-vendor multi-retailer supply chains,” European Journal of Operational Research, vol. 204, pp. 473–484, 2010. [18] G. Kuk, “Effectiveness of vendor-managed inventory in the electronics industry: determinants and outcomes.” Information & Management, vol. 41, pp. 645-654, 2004. [19] J. Kauremaa, J. Småros, J. Holmström, “Patterns of vendormanaged inventory: findings from a multiple-case study.” International Journal of Operations & Production Management, vol. 29, pp. 1109-1139, 2009. [20] S.E. Fawcett, L.M. Ellram, and J.A. Ogden, Supply chain management : from vision to implementation, Upper Saddle River, NJ, Pearson Prentice Hall, 2007. [21] C.C. Lee, and W.H.J. Chu, “Who should control inventory in a supply chain,” European Journal of Operational Research, vol. 164, pp. 158-172, 2005.
V. CONCLUSION This paper focuses on a Chinese aluminum manufacturer-oriented supply chain. The inefficiency of the supply chain performance is identified through processing mapping and the analysis of the associated information flows and material flows. A vendor-hub type of VMI strategy is then developed and applied to the case supply chain. It is found that within a reasonable range of scenarios, VMI can reduce order cycle time by 50%~90% from the current situations with unavailable raw materials, and by 16%~62% from the current situations with available raw materials. The inventory holding cost could be reduced by 46% if two-week inventory level is maintained under the VMI strategy. Although the realization of VMI requires long-term partnership between supply chain members and the implementation of EDI, it is argued that the proposed vendor-hub VMI is feasible to Chinese medium-sized companies. Further research will consider the dynamic aspects of the supply chain and use simulation to quantify the impact of different coordinated management strategies on the supply chain performance. REFERENCES [1] A. Gunasekarana, C. Patelb, and R.E. McGaughey, “A framework for supply chain performance measurement,” International Journal of Production Economics, vol. 87, no. 3, pp. 333-347, 2004. [2] T.J. Bossert, D.M. Bowser, and J.K. Amenyah, J.K., “Is decentralization good for logistics systems? Evidence on essential medicine logistics in Ghana and Guatemala,” Health Policy and Planning, vol. 22, no. 2, pp. 73-82, 2007. [3] P.C. Brewer, and T.W. Speh, “Using the balanced scorecard to measure supply chain performance,” Journal of Business Logistics, vol. 21, no. 1, pp. 75-93, 2000. [4] R. Slade, A. Bauen, and N. Shah, “The commercial performance of cellulosic ethanol supply-chains in Europe,” Biotechnology for Biofuels, vol. 2, p. 3, 2009. [5] C.T. Hsieh, F.J. Lai, and W.H. Shi, “Information orientation and its impacts on information asymmetry and e-business adoption: Evidence from China's international trading industry,” Industrial Management & Data Systems, vol. 106, pp. 825-840, 2006. [6] J. Hou, A.Z. Zeng, and L.D. Zhao, “Achieving better coordination through revenue sharing and bargaining in a two-stage supply chain,” Computers & Industrial Engineering, vol. 57, no. 1, pp. 383-394, 2009.
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