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Increasing demand for automobile sector has forced to move international automotive enterprises to move towards India for sale and manufacturing of their products as well as export to global market. Globalization has enhanced domain of the Indian automotive sector which also has increased competition in this sector. This has become more diversify and includes product variety as well as demand uncertainty which leads to many managerial problems at every level of supply chain (SC). For sustainability of enterprise, it is very-much significant to manage the supply chain in an effective manner to reduce the level of inventory and hence the item cost as well as enhances customer satisfaction level. One of the important issues in supply chain is purchasing strategy. Vendor managed inventory (VMI) policy is the innovative and effective to control the inventory especially in the context of automotive industry. Some of the Indian automotive industries start implementing the VMI. But small and medium industries and even big players still found it difficult to understand what is VMI, how it can be implemented, what the benefits are and how it can be evaluated. In our paper, we propose theoretical benefits of VMI policy relevant to Indian automotive industries and identify some challenges as well.
Keywords- VMI, Automotive Supply Chain,
The automotive industry is the world's largest single manufacturing activity [Suthikarnnarunai]. It is one of the most important and widespread industries in the world. The current turnover of the automobile industry is around Euro 2 trillion and is equivalent to the size of 6th largest economy in the world. The global automotive industry has been evolving through different phases characterized by its own developments. Over a period of time, the industry has witnessed several ups and downs, only to emerge stronger and better equipped to take on the challenges (EXIM Report, 2008).
The automotive industry has a vital role in Indian economy. It has the immense potential to promote the economy by further development of technological capabilities (Humphrey, 2000). The Indian automotive industry have a huge range of products e.g. Two and Three wheelers, passenger vehicles, light, medium and heavy commercial vehicles, agricultural vehicles (tractors and combines), Construction machineries/vehicles and ancillary (component segment for all these categories). Based on the information from Society of Indian Automobile Manufactures (SIAM) and Automotive Component Manufacturers Association of India (ACME), a modified classification of Indian automotive industry has been proposed in the paper (figure 2).
It is nearly impossible particularly for those organizations that spend a major portion of their revenues in materials and parts supplies. The experts believe that inventory policy selection is the most important activity of any organization's purchase department. Most inventory management models are based upon rather restrictive assumptions, e.g. unit sized demands and the normal distribution for total demand during replenishment time. In a majority of inventory management systems, circumstances seem to allow these simplifications, and inventory policies based upon these assumptions yield satisfying results. However, in some particular cases, these simplifications differ fundamentally from the actual conditions and particle. Therefore, application of the models mentioned above can result in an overinvestment in inventory or in an unacceptable low service level (Matheus, 2000).
The objective of this paper is to recognize the hindrances in achieving a higher level of economic growth in the Indian automotive industry and also to evaluate the benefits of VMI policy in the Indian automotive industry. The idea of selection of this industry is that it play a vital role in Indian economy as well generate employment in the bulk. The sustainability and profitability of this sector is directly and indirectly connected with Indian economy.
Indian Automotive Supply Chain
The Indian automotive industry has experienced the various phases of growth since independence. After independence the growth of the industry is almost stagnant. Telco, Ashok Leyland, Mahindra & Mahindra, Hindustan Motors, Bajaj auto and such others have play a vital role in accelerating the automotive sector growth. The liberalization in industrial policy in 1990s has attracted international automobile manufactures. They started their manufacturing plants in India. The growth of automotive sector has floated for automobile component manufactures. Components manufactures also started joint venture with global partners. The globalization
INDIAN AUTOMOTIVE INDUSTRY
Vehicle Manufacturing Industry
Component Manufacturing Industry
Three - Wheeler
SUV/ MUV Van
Figure 2 A proposed classification of Indian automotive industry (Based on information from SIAM and ACME)
has provided the new dimension to automotive industries in terms of transfer of technology and link with global markets. Today the automotive industry plays an important role in the Indian economy. Growths in economy, increasing demand for cars and industry favourable conditions have forced the international automobile manufacture to move toward India. With the passage of time, India is now considered hub for automotive sector. In today scenario of globalization, the Competitiveness of the company is entirely depends on its ability to reduce inventory cost, lead-times and enhance customer service levels, product quality (Singh & Kumar, 2011, 13). Traditionally, all the component of supply chain procurement, production, distribution and marketing worked independent. All the components are working for company's common objectives with their individual objectives e.g. Sale personnel have more emphasis on high level on inventory to achieve high customer service and hence satisfaction level as well as high sales volume on the other hand the objective of production and distribution is entirely different.
Globalization is forcing the supply chain management to address the challenge of cost pressures. It becomes further significant in the context of global sourcing. Though there is a perceived belief that global sourcing facilitates in cost reduction, but there are logistical challenges. Thus, it is crucial to develop capabilities and solve the challenges associated with global delivery, especially in the areas of inventory management, scheduling and timely delivery. The present competition in the global market is no longer competition between the two companies but the competition between their supply chains. A well designed and implemented supply chain management system is an important tool to increase competitive advantage in today uncertainty. The coordination among the organizations in supply chain has become more and more significant to achieve the short term and long term objectives of the supply chain management. In today's world of high competition, it has become highly difficult to produce high quality products at low costs having higher values.
In today's competitive and global markets, companies make every effort for any advantage they can get over the competitors. A superior supply chain includes, on time delivery, lower cost products and manufacturing flexibility as compare to their competitor. The Supply chain is the reality which has a long and the important history. Exchange of goods is a simple and easy example of supply chain. According to Juttner et al. (2003), despite the increasing awareness among practitioners; the concepts of supply chain vulnerability and its managerial counterpart supply chain risk management are still in their infancy. The enterprises that rely on their supply chains now are looking into more innovative ways to manage risk into the supply chain with the insurance of its smooth operations. Womack et al (2003) confers that the operational excellence of an enterprise has been demanded with the increased responsibilities of supply chain and more complex process are required for supply chain risk analysis than ever before. This includes lean manufacturing principles, process control theory, process mapping and modelling to the entire supply chain. This phenomenon is also applicable to the concept of risk management in throughout the supply chain risk analysis.
Supply Chain Management includes the planning and management of all activities involved in sourcing and procurement, conversion, demand creation and fulfilment, and all Logistics Management activities. Thus, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers. In essence; supply chain management integrates supply and demand management within and across companies Mentzer et al. (2008). Hofman et al. (2008) explains that how, where and when reliable value throughout the entire supply chain including flows of material, intellectual property and money in a global context can be created.
The automotive supply chain is mainly tied to forecasts. The automobile manufacturers must match supplies with demands from the raw material suppliers to the last end customer. The variation or uncertainty of demand due to forecasting is produced bullwhip effect at various stages of SC. The new direction for automotive supply chain is still based in part, on the forecast and, in part, on the capable and responsive supply chain with a greater strategic emphasis, and subsequently, on the logistics operations [Suthikarnnarunai, 2008]. An automobile manufacturing organization has to combine and coordinate the activities started from purchase of raw materials, sub assembly, infrastructural equipment/facilities. The automotive supply chain integrates four groups of players: original equipment manufacturers (OEMs), first-tier suppliers, sub-tier suppliers, and infrastructure suppliers. Traditionally, different types of technologies were used to establish the links between these groups. [Cassivi, 2000]
Vendor Managed Inventory Policy
Inventory includes all the physical entity which an organization need to keep till it is needed, consumes or incorporates into a product, sells, or otherwise disposes of. The inventory is temporary by nature. The objectives of maintaining the inventory are economies of scale (discount on bulk purchase), cushion between the supply and demand, protection from uncertainties and buffer. Due to the ongoing nature of the enterprise's operation, aggregate or total inventory is continually being replenished and restocked. The continuous replenishment forced the firm to have a "permanent investment" in inventory. Inventory accounts to a greater part of total cost of a product or service and by efficient and effective Inventory Management, this cost can be reduced to a greater extent and customer satisfaction can be enhanced. There is a high correlation between the inventory levels and service efficiency. Inventory turnover and fill rate are the examples of indicators for measuring an organization's performance in inventory management. Inventory turnover is calculated by dividing the annual sales by the average on hand inventory. Fill rate is the percentage of units available when requested by the customer.
A company has to make number of decisions for inventory management such as decisions related to controlling inventory costs, determining order quantity and reorder point, and selecting techniques in forecasting or handling the inventory. Representative inventory costs include holding costs, setup costs, ordering costs, and shortage costs. Within inventory management, these decisions affect inventory performance. This work has focused on inventory performance as measured by level of inventory within the type in relation with raw material purchasing, production, and shipment. Vendor managed inventory process can be defined as a mechanism where the supplier creates the purchase orders based on the demand information exchanged by the retailer/ customer. In simple terms, VMI is a backward replenishment model where the supplier does the demand creation and demand fulfilment. In this, instead of the customer managing his inventory and deciding how much to fulfil and when, the supplier does. A continuous replenishment program uses the exchange of information between the retailer and the supplier to allow the supplier to manage and replenish goods at the store or warehouse level. In this program, the retailer supplies the vendor with the information necessary to maintain just enough stock to meet customer. The VMI concept provides improved visibility across the supply-chain pipeline that helps manufacturers, suppliers and retailers improve production planning, reduce inventory, improve inventory turnover and improve stock availability. With information available at a more detailed level, it allows the manufacturer to be more customer- specific in it is planning. Instead of putting more pressure on suppliers performance by requiring faster and more accurate deliveries, VMI gives the supplier both responsibility and authority to manage the entire replenishment process. The manufacturer/retailer provides the supplier access to inventory and demand information and sets the targets for availability. Thereafter, the supplier decides when and how much to deliver. The measure for the supplier's performance is availability and inventory turnover. This fundamental change affects the operational mode both at the customer and at the supplier company. For the average item, the more frequent review in the VMI approach reduces the ordering delay in the information flow.
Vendor Managed Inventory (VMI) is also known as continuous replenishment or supplier managed inventory. It is one of the most widely discussed partnering initiatives for encouraging collaboration and information sharing among various constituents of supply chain. VMI has been originated in the early 1980s with mass retailers demanding vendors to take up the responsibility for inventory replenishment based on sales data made available by the retailers. Wal-Mart and Procter & Gamble has initiated popularization of VMI then after it was subsequently implemented by many other leading companies from different industries, such as GlaxoSmithKline, Electrolux Italia, Nestle and Tesco, Boeing and Alcoa etc.
The customer provides the vendor with access to its real-time inventory level. In this partnership program, the customer may set certain service-level and requirements, which are then taken into consideration by the vendor. VMI presents a competitive advantage because it results in higher product availability and service level as well as lower inventory monitoring and ordering cost as well as for vendors; it results in reduced bullwhip effect and better utilization of manufacturing capacity, as well as better synchronization of replenishment planning.
VMI provides freedom to the supplier to plan its production and decide upon the replenishment schedule as long as the agreed customer service levels are met. This facilitates suppliers to stabilize its production and to optimize the transportation costs on the other hand, buyer's administration and inventory costs can be decreased. This Enhanced collaboration between both supply chain partners reduces lead times and minimize the risk of demand amplification in the supply chain.
In vendor Managed Inventory supplier fulfils the customer's requirement as per demand information. The inventory is reviewed more frequently than purchase orders were placed before which reduces the delay in the information flow. VMI demand high confidence and trust between the customers and supplier as customer need to share the information with the supplier.
Achabal (2000) has described the market forecasting and inventory management components of a Vendor Managed Inventory (VMI) decision support system and how this system was implemented by a major apparel manufacturer and over 30 of its retail partners. Dong (2002) presented that VMI has reduced total costs of the channel system, but under certain cost conditions between buyer and supplier, it could decrease the purchasing price and supplier's profit. Disney (2002) has proposed a decision support system using causal loop diagrams and difference equations to determine the optimum design parameters in the vendor managed inventory, automatic pipeline, inventory and order based production control system (VMI-APIOBPCS) by relating it to the gain on demand when setting safety stocks at the distributor.
Disney (2003) proposed three different models: a traditional supply chain, an internal consolidation scenario (with batching in the order rule) and the VMI supply chain to investigates the impact of a vendor managed inventory (VMI) strategy upon transportation operations in a supply chain. He found that the VMI supply chain enabled a smoother dynamic response than that associated with the traditional supply chain, enabling a reduction in manufacturing on-costs. Towill (2003) has compared the expected performance of a vendor managed inventory (VMI) supply chain with a traditional ''serially linked'' supply chain. He compared the bullwhip performance of a number of VMI supply chains with two-level supply chains and in all cases there is substantial reduction in bullwhip effect. VMI is shown to be significantly better at responding to volatile changes in demand such as those due to discounted ordering or price variations.
Tyan (2003) presented that VMI not only has the ability to reduce costs, but also to improve service levels and create business opportunities for both parties in the supply chain. The recommended VMI implementation approach provides an effective guideline to shorten the process and to maximize the VMI's benefits. Xiaoyuan (2005) have proposed optimization policy of the purchase price and the profit under vendor managed inventory (VMI) and established a supply chain mode of VMI for a saleable product based on deterministic demand, having initial stock and having stock-out cost. Xie (2006) presented a model for supply chain system, which is composed of m vendors and n identical retailers and study the conflicts between vendors and retailers. Zhang (2007) proposed procedure for an integrated VMI model based on the assumption that the buyer's cycle times may be different and the vendor's production cycle is an integer multiple of each buyer's replenishment cycle to determine the optimal investment and replenishment decisions. Yao (2007) developed an analytical to provide a better understanding of how important supply chain parameters, namely ordering costs and carrying charges, affect the inventory cost savings to be realized from VMI and the distribution of these savings between buyers and suppliers. Results from the analytical model and numerical examples show that benefits may be generated from VMI as long as the ratio of the order costs of the supplier to the buyer and the ratio of the carrying charges of the supplier to the buyer are favourable.
Al-Ameri (2008) designed two types of mathematical models to represent the VMI system; detailed and aggregate models. The detailed model represents the VMI system dynamically while the aggregate model focuses on steady-state overall decisions. The VMI system has been modeled as a mixed-integer linear program (MILP) using the resource-task network (RTN) formulation. He find that In this system, the entire supply chain performance is optimized in terms of production planning at vendor's site, distribution strategy, and inventory management at manufacturer's site. He also fined that by letting the vendor take over material replenishment in the manufacturer's site, the manufacturer will concentrate on other core processes. In return, end customers will receive better service quality while costs are minimized for both manufacturers and vendors. Wong (2009) proposed a model for a two-echelon supply chain with a single supplier serving multiple retailers in vendor-managed inventory (VMI) partnership. The proposed model demonstrates that the supplier gains more profit with competing retailers than without as competition among the retailers lowers the prices and thus stimulates demand.
Kwak (2009) proposed an adaptive VMI (Vendor Managed Inventory) model that controls replenishment quantity adaptively depending on a change in customer demand at each replenishment period in a two-echelon supply chain with unstable customer demands. The proposed adaptive inventory control model, supported by the situation reactive approach with the retrospective analysis, successfully relaxed an assumption of a stationary distribution for customer demands. Lin (2010) developed a fuzzy system dynamic to simulate vendor managed inventory, automatic pipeline, inventory and order based production control system (VMI-APIOBPCS) model based on fuzzy difference equations, and these operators of difference equations adopt the weakest t-norm () operators using genetic algorithms. Kim (2010) has developed a model, in which the retailer and the vendor should coordinate their decisions in order to maximize their individual profit or the total profit combining the two participants together. He suggest that the vendor should take into account the demand pattern throughout the product life cycle (PLC) when it decides its capacity commitment, which will affect its inventory management cost during the PLC, while the retailer should vary the retail price over the PLC so as to maximize the revenues and minimize the inventory cost at the same time.
Lee (2011) presented and analyzed a simple periodic-review stochastic inventory model to examine the benefits of VMI from economies of scale in production/delivery in a global environment characterized by exchange rate uncertainty and large fixed costs of delivery. He suggest that, despite of all the inventory costs transferred from the retailer, the supplier can be better off when his fixed cost of production/delivery is larger than the retailer's fixed ordering cost. Kristianto (2012) proposed an adaptive fuzzy control application to support a vendor managed inventory to generate an adaptive smoothing constant in the forecast method, production and delivery plan to eliminate, the rationing and gaming or the Houlihan effect and the order batching effect or the Burbidge effects and finally the Bullwhip effect. The results show that the adaptive fuzzy VMI control surpasses fuzzy VMI control and traditional VMI in terms of mitigating the Bullwhip effect and lower delivery overshoots and backorders. The simulation results show that adaptive fuzzy VMI control model reduces the Bullwhip effect by eliminating the Houlihan effect and the Burbidge effect.
Cárdenas-Barrón (2012) has presented an alternative heuristic algorithm to solve the vendor management inventory system with multi-product and multi-constraint based on EOQ with backorders considering two classical backorders costs: linear and fixed. He demonstrates that the proposed heuristic algorithm is better based on three aspects: the total cost, the number of evaluations of the total cost function and computational time.
Figure 2 vendor managed inventory Policy