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IJAET/Vol.III/ Issue I/January-March, 2012/275-279 Research Paper STANDARDISATION OF VENDOR PERFORMANCE INDEX USING ANALYTICAL HIERARCHY PROCESS Saravanan,B.A a., Jayabalan,V b., Moshe.J.Aaron c, Jesu Antony Xavier, P d. Address for Correspondence a Department of Mechanical Engineering, Easwari Engineering College, Chennai 600 089 b Professor, Department of Manufacturing Engineering, CEG Campus, Anna University, Chennai 600 025 c & d Alumni, Department of Mechanical Engineering, CEG Campus, Anna University, Chennai 600 025 ABSTRACT Increase in demanding customers, globalization, accelerated competition, technological advances in the communication of information are leading the firms toward adoption of supply chain management. As purchasing is being a starting point of five echelons in supply chain, more emphasize should be given on supplier evaluation and selection. Moreover purchased parts, components and supplies typically represent 40 to 60 percentages of the sales of its end products. Therefore analysis of the supplier selection process is getting more attention to enhance the SCM concepts. In practice, Vendor Performance Index (VPI), used in supplier evaluation is not found to be with strong technical background. In order to strengthen the technical evaluation, a survey has been carried out in automobile industries of South India, especially in Chennai hub. With this survey, the relative importance and weights of vendor selection criteria were found out using Analytic Hierarchy Process (AHP) and subsequently Vendor Performance Index is standardized. Software has been developed for the purchase managers to evaluate the vendors based on their requirements. KEYWORDS Supplier Selection, Vendor Performance Index(VMI), Analytical Hierarchy Process (AHP), Software tool. 1 INTRODUCTION Supply Chain Management (SCM) is a strategy that integrates operative functions such as marketing, planning, purchasing, production, and finance etc. Supply Chain Management is a set of approaches utilized to efficiently integrate Suppliers, Manufactures, Warehouses and Stores; so that merchandise is produced and distributed at the right time, in order to minimize system wise costs while satisfying service level requirements. SCM concepts require functional units such as purchasing, manufacturing, logistics and marketing as well as suppliers and transportation providers to co-operate in eliminating the duplication of tasks and competencies. Suppliers have always been an integral component of a company s management policy; however the relationship between company and its supplier has traditionally been a distant one. While the supplier selection decision needs to be made, the buyer establishes a set of evaluation criteria. Dickson had formed 23 criteria in the selection of suppliers (1). The four dimensions namely competitive pricing, product quality, product variety and delivery service will decide the frame of SCM concepts. Yahya and Kingsman (1999) used Saaty s Analytic Hierarchy Process (AHP) method to determine priority in selecting suppliers (2). The AHP has found widespread application in decision making problems, involving multiple criteria in systems of many levels. The strongest features of the AHP are that it generates numerical priorities from the subjective knowledge expressed in the estimates of paired comparison matrices. The method is surely useful in evaluating suppliers weights in marketing and in ranking order for instance. In this paper, the survey has been carried among the purchase manager in the Chennai hub Auto industries. Based on priorities of the factors obtained from purchase managers, the weights for the factors are found using AHP tool and used in the supplier selection. 2 LITERATURE REVIEW There are varieties of works that have been carried out in the supplier selection field. Lewis (1943) described that none was more important than the proper source (3). England and Leenders (1975) stated the same point, as Supplier selection is purchasing s most important responsibility (4). Due to the emergence of supply chain management, the location and importance of the supplier selection are clearly exposed (Lee et al., 2001) (5). Supplier selection is having two particular issues for discussion, one is which criteria should be considered and the other one relates to what methods should be used. The two issues have made the researchers and practitioners to give clear idea of the supplier selection problem. Weber et al (1991) had given the importance of the criteria in the supplier selection (6). Dickson (1966) has identified 23 criteria in the supplier selection process that had given a framework for the consideration of the factors. Further these criteria were expanded and some new criteria were added. Criteria were expanded into sub-criteria like the net price can be subdivided into discounts, the fixed cost, design cost, supplier cost, inventory holding cost fixed ordering cost, freight charges etc. There are many approaches attempted in the supplier selection. Weber et al. (1991) categorized the quantitative approach to three categories: Linear weighting models, Mathematical models and statistical/ probabilistic approaches (7). Monckza, 1998(8) and Porter, 1993(9) had observed the companies total cost based approach. Harding, Porter and Monckza(10) had carried out their analysis on supplier selection based on the Unit Total cost and they found that the cost of the product is less significant than the other costs. Ellram, Carr, Cavinto, Porter and Bhutta included the many other purchase related costs (11). Tyndall, Morris and Kaplan used ABC costing approach to categorize costs in to ABC categories and then making a selection based on the criteria selected (12). To get the cost of the product for the whole life, Jacson, Ostrom, Handfield and Pannesi had made an attempt by Life Cycle Costing Approach (13). For the Just-in-management scenarios, Weber and Ellram used Multi objective Programming (14). Weber Nitszch had planned for the purchase professionals to handle multiple conflicting attributes in the supplier selection and framed the Multi Attributes Utility Theory (MAUT) (15). Masella and

IJAET/Vol.III/ Issue I/January-March, 2012/264-267 Rangore used Dynamic programming in the supplier selection by setting Input variables as Control and Environmental variables, state variables as the internal workings of the organization, and the output variables as the performance achieved by the organization based on the selection of suppliers made (16). Weber, Klein Souza, Clarke and Kent used Data Envelopment Analysis (DEA), an optimisation method, used to generalize single-input/single-output technical efficiency measure to the multipleinput/multiple-output case by constructing a relative efficiency score as the ratio of a single virtual output to a single virtual input (17). Moore and Fearson (1973) (18), Anthony and Buffa (1977)(19), Kingsman (1986) and Pan (1989) (20) had made the Linear programming approaches (21). Gaballa (1974)(22), Bender et al., (1986) (23), Narasimhan and Stoynoff (1986) (24) and Turner (1988) (25) had given Integer programming Approaches in the supplier selection by including goals Quality, Price and delivery. Buffa and Jackson (1983) used Goal programming in the supplier selection (26). Sharma et al (1989) had analysed the strategic issues in vendor selection (27). Saaty, Belton, Dyer, Bard, Bhutta and Nydick Hill had provided a frame work to cope with multiple criteria situations involving intuitive, rational, qualitative and quantitative aspects for prioritizing alternatives by AHP (27). AHP is a powerful tool in making decisions in multi-attribute decision making situations. This has been already utilized in the supplier selection in different ways. Mostly it was carried out for a specific company. In this paper, the purchase managers idea and relative importance on the factors are taken into account while selecting the supplier. AHP is used to find out the prioritization of the supplier selection attributes for standardization of Vendor Performance Index (Appendix A). 3. RESEARCH METHODOLOGY Chennai hub serves major segment of automobiles to South Asia because of the presence of major Automobile legends viz. Ford, Hyundai and Hindustan Motors (HM). Because of their establishments, Tier 1, Tier 2 and Tier 3 suppliers of auto components flourished in South India. Supplier selection has undergone many researches worldwide to refine the process. Having made a survey in automobile allied companies, it has been observed that vendor performance weights for Quality, Cost, delivery was not emphasized with statistical background. Purchase managers fix weights by their perspective, which leads to subjective evaluation. In this research work, weights of the factors have been determined using AHP to have objective supplier selection. In this paper, an empirical study was designed to make a study of purchase managers expectation on the selection of suppliers for their requirement. Questionnaire was formed so as to extract the expectations on the suppliers. First the unstructured questionnaire was formed on the basis of multiplechoice questions. It was surveyed with industrial experts and professors from academic institutions to form the structured questionnaire. Questionnaire was planned with an objective of finding pair wise comparison among the attribute so that this will be suitable for using the Analytic Hierarchy Process (AHP). The sample group consisted of manufacturing companies specifically automobile and allied companies in the Chennai hub. Survey has been carried out among 250 companies. Reasonable feedbacks were received from 56 raw material purchase managers and were analysed by AHP. The Analytical Hierarchy Process tool was first developed by Saaty (1971). The tool has been used for many more applications in the various fields such as planning, selecting the best alternative resource allocations, resolving conflicts, etc. This tool has more flexibility to integrate with linear programming, Quality Function Deployment, Fuzzy Logic etc. In this paper, AHP tool was used to prioritize the factors. Basic AHP methodology Some key and basic steps involved in this AHP methodology are 1. Definition of the problem. 2. Objective of problem to be broadened by considering all factors, objectives and its outcomes. 3. Criteria that influence the behavior to be identified. 4. Problem to be structured with hierarchy of different levels constituting goal, criteria, sub-criteria and alternatives. 5. Each element has to be compared at corresponding level and calibrated on numeric scale. It is required to make n(n-1)/2 comparisons, where n is the number of elements with the considerations that diagonal elements are equal or `1`and the other elements would simply be the reciprocals of the earlier comparisons. 6. Calculations carried out to find the maximum Eigen value, consistency index CI, consistency ratio CR, and normalized values for each criterion alternative. 7. If the maximum Eigen value, CI, and CR are satisfactory, then decision is taken based on the normalized values; else the procedure is repeated till these values lie in a desired range. AHP in Supplier selection When following the above steps, 1. Our prime objective is to find out the weight of the attributes, which are affecting supplier selection to standardize the vendor performance index. 2. While selecting the supplier selection factors, all factors including Dickson s 23 factors were considered and brainstorming was conducted with the purchase managers, industrial experts and Professors from academic institutions to sort out. 3. Based on the literature survey and expert opinion, the top criteria Quality, Cost, Delivery, Technical Capability and production facility were considered. Based on the discussion with purchase managers, repair service and geographical location are included. Besides, recent advancements and requirements made to focus on the Just in

Time (JIT) and Vendor Managed Inventory (VMI). 4. Structure of the problem was plotted as shown in figure 1 by considering the selected factors for this research work. 5. Questionnaire was developed in such a way that each element is compared with each other i.e. pair wise comparison with 1 to 9 scales (Table 1). Prepared questionnaires were passed to the purchase managers of Chennai hub automobile industries for the survey. Every individual s feedback values were entered in the pair wise comparison matrix (A) and average of Eigen value is calculated. 6. The relative value of one attribute with respect to the other is filled in respective cells (Table 2). Table 1 Saaty s Nine Point Comparison Scale Here Ci represents the relative importance given to attribute in cell i. 6.2 By calculating Maximum Eigen value (priority matrix C), the prioritisation and weights of the factors can be found. Consistency index (CI), Consistency Ratio (CR), and normalized values for each criterion/ alternative is checked. Weights found from the Eigen vector is applied in the vendor performance index for the evaluation, as it was obtained from overall scenario. 7. Validation of AHP The consistency ratio is checked and the data verified with this following steps 7.1 Pair wise comparison matrix (A) is multiplied with priority matrix(c), the resultant matrix is called AC Table 2 Entries in Pairwise comparison matrix The parameter λ max is computed in the following form 7.2 The consistency index (CI) is computed by using the following formula. 6.1 Calculation of Normalized Matrix Each entry in column j of matrix A is divided by the sum of entries in column j. This yields a new matrix A w in which sum of entries in each column will be 1. A w is also called as Normalised matrix To find the approximation to W max which will be used as the estimate of W, estimate Wi as the average of all the entries in row I of Anormalized IJAET/Vol.III/ Issue I/January-March, 2012/264-267 7.3 CI is Compared with random index (RI) for the appropriate value of m to determine whether the degree of consistency is satisfactory or not. If CI/RI < 0.1, the degree of consistency is satisfactory, If CI/RI > 0.1, there are inconsistencies and hence, the AHP may not yield meaningful results. The reference values of RI for different numbers of m are given in the table 3. Table 3 Values of Random Index 2 3 4 5 6 7 8 9 10 RI 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.51 The consistency ratio (CR) is an approximate mathematical indicator of the consistency of pair wise comparisons. It is a function of what is called as the Maximum Eigen Value that is compared against the similar values if the pair wise comparisons had been merely random. (called as Random Index RI ). Software is developed based on the aforesaid steps to find out the original. 5 DATA PREPARATION AND RESULTS Analysis in this work is half way travel in AHP, because at the point of finding the Eigen vector to find out the weights for the attribute in the supplier selection. As the weights in evaluating and selecting

IJAET/Vol.III/ Issue I/January-March, 2012/264-267 the supplier in the industries is not having any strong back ground, these weights established from the Eigen vector can be used for the supplier evaluation purpose. Since the weights from the Eigen vector is based on the survey taken on the overall industry, this weights will reflect the actual priority of the purchase manager. 6 INTERPRETATIONS OF RESULTS The results obtained from the AHP are depicted in the graph (Figure 2). The weights are drawn out from the Eigen vector of the AHP. It is supposed to be the mid process result, since remaining AHP process is used for the selection of suppliers. From the weights found from the Eigen vector, it is obvious that purchase managers have given primarily more priority on the quality, because irrespective of the company, Quality of raw material is a predominant factor in deciding the complete quality of the out coming product. The second priority is given on the delivery of product as it makes the adoption of the timely delivery of the final product as the automobile industries have pressure on Delivery from OEM (Original Equipment Manufacturers), Tier 1, Tier 2 and Tier 3 companies, competition leads in the market. With this study, it is significant to note that delivery attribute is given more importance than the costs of procurable. The third priority is given on the cost of the product, as purchase managers consider worthiness for the application because components and supplies typically represent major percentage of the sales of its products. Also requirement of the technical capability holds the fourth important position to adapt the new technical innovations and technology. Similarly, expectation of Purchase Managers on supplier is to equip for sudden changes in the markets up and down change in requirements. Next priorities are given to the technical capability and production facility of the supplier as those decide the adaptability & flexibility of the technology and performance consistency & reactions at critical demand situations respectively as these factors indirectly influence Quality, Delivery and Cost. In recent days, the cost and space for the inventory are considered to be of minimum importance. Deliveries of the raw material are expected at the scheduled delivery neither early nor later. These requirements can be enhanced by JIT that is why the sixth priority is given i.e. next to the top five criteria on the adaptability of JIT. The seventh priority is given to the repair service because it includes guarantee and warranty of the raw material. From the delivery point of view, purchase managers started thinking on time delivery to adapt the JIT policy to avoid the unnecessary inventory and the consecutive commitment with the suppliers. Requirement of the inventory and commitments for a period of time can also be tried with the suppliers i.e. Vendor Managed Inventory (VMI). Eighth priority is given to VMI, because companies are expecting more helping hand from the suppliers for their requirement in such a way that vendors can also manage the inventory of supplying goods. Ninth priority is given to the geographical location. Companies are ready to move for getting resources and quality of the product. Example: Hyundai, Ford, (BMW is also starting a new plant near Chennai) established their markets in India for the best resources. The importance of the geographical location is considered very much for the purchase managers for making Follow-ups, Change of Design and its remedial works. Besides, this attribute also influences the landing cost of product. 7 CONCLUSION This survey and analysis have sought to bring to light the existing scenario of the expectation of the purchase managers on the supplier while making decision in the selection process. It is revealed that the quality attribute is more important than the other attributes. So, it is evident that the loss of quality will give adverse affect on the profit. Purchase managers are focusing more on the delivery than on the cost of the raw materials. It can be said that purchase managers are ready to bear the amount to get the materials in right time, because delivery of the materials is straight away influencing the delivery of the product and goodwill of customers. Other factors, technical capability and production facility are given in the next priority level. This survey is reflection of the expectation of the purchase mangers on suppliers and their relative prioritisation on the attributes. The relative importance on attributes was found from the AHP. The same can be used as overall weights that are to be given on the attributes in the Vendor Rating Index. The weights that were found from the same level of automobile companies would reflect the exact scenario in the South Asian Auto Industries. So, the vendor performance index can be refined by the weights and can be considered as the requirement of the industries on supplier. Finally a software application package has been developed to rank and select the vendor using the AHP(Appendix A). In future, making a survey on the large samples can refine the vendor-rating index. The importance of the sub attributes can be used to find out the clear weights on the attributes. A comparative study can also be made on the perceived importance and actual importance on the supplier selection. REFERENCES 1. Dickson G.W. (1966), An analysis of vendor selection systems and decisions, Journal of Purchasing, Vol. 2, pp. 5-17. 2. Anthony T.F. and Buffa F.P. (1977), Strategic purchase scheduling, Journal of Purchasing and Materials Management, pp. 27-31. 3. Bender P.S., Brown R.W., Isacc M.H. and Shapiro J.F. (1985), Improving purchasing productivity at IBM with a normative decision support system, Interfaces, Vol. 15, No. 3, pp. 106-115. 4. Buffa F.P., Jackson W.M. (1983), A Goal-programming model for purchase planning, Journal of Purchasing and Materials Management, Vol. 19 No. 3, pp. 27-34. 5. Ellram L.M. (1990), The supplier selection decision in strategic partnerships, Journal of Purchasing and Materials Management, Vol. 26, No. 4, pp. 8-14. 6. England W.B. and Leenders M.R. (1975), Purchasing and Materials Management, Homewood: Richard Erwin. 7. Gaballa A.A. (1974), Min cost allocation of Tenders, Operations Research Quarterly, Vol. 25, No. 3, pp. 389-398. 8. Harding M.L. (1998), How to calculate total purchase cost, Hospital Management Quarterly.

9. Jackson D.W. and Ostrom L.L. (1980), Life cycle costing in industrial purchasing, Journal of Purchasing and Materials Management, Vol. 16, No. 4, pp. 8-12. 10. Kingsman B.G. (1985), Raw material purchasing, an operation research approach, Perfamon Press, Oxford. 11. Lee E.K., Ha S. and Kim S.K. (2001), Supplier selection and management system considering relationships in supply chain management, IEEE Transactions on Engineering Management, Vol. 48, No. 3, pp. 307-318. 12. Lewis H. (1943), Industrial purchasing principles and practices, Chicago: Richard Erwin. 13. Masella C. and Rangone A. (2000), A contingent approach to the design of vendor selection systems for different types of co-operative customer/supplier relationship, International Journal of Operations and Production Management, Vol. 20 No. 1, pp. 70-84. 14. Monczka R., Trent R. and Handfield R. (2002), Purchasing and Supply Chain Management, Thomson Publication. 15. Moore D.L. and Fearson H.E. (1973), Computer assisted decision making in purchasing, Journal of Purchasing, Vol. 9, No. 4, pp. 5-25. 16. Narasimhan R. and Stoynoff L.K. (1986), Optimizing aggregate procurement allocation decision, Journal of Purchasing and Materials Management, pp. 23-30. 17. Pan A.C. (1989), Allocation of order quantities among suppliers, Journal of Purchasing and Materials Management, Vol. 25, No. 2, pp. 36-39. 18. Porter M.E. (1980), Competitive strategy: techniques for analyzing industries and competitors, New York: The Free Press. 19. Porter M.E. (1985), Technology and competitive advantage, The Journal of Business Strategy, Vol. 5, No. 3, pp. 60-78. 20. Saaty T.L. (1998), How to make decision: the analytic hierarchy process, European Journal of Operation Research, Vol. 48, pp. 9-26. 21. Sharma D., Benton W.C. and Srivastava R. (1989), Competitive strategy and purchasing decisions, Proceedings of the Annual National Conference of the Decision Sciences Institute, pp. 1088-1090. 22. Sunil Chopra and Peter Meindl (2001), Supply chain management, strategy, planning, and operation, Pearson Publication. 23. Turner L. (1998), An independent system for the evaluation of contrast tenders, Journal of Operations Research Society, Vol. 39, No. 6, pp. 551-561. 24. Tyndall G.R. (1988), Analysing the costs and value of product distribution chain, Cost Management, pp. 45-51. 25. Verma R. and Pullman M.E. (1998), An analysis of the supplier selection process, Omega, International Journal of Management Science, Vol. 26, No. 6, pp. 739-750. 26. Weber C.A. (1996), A data envelopment analysis approach to measuring vendor performance, Proceedings of the Annual National Conference of Decision Sciences Institute, pp. 1099-90. 27. Weber C.A. and Current J.R. (1993), A multi objective approach to vendor selection, European Journal of Operation Research, Vol. 68, pp. 173-184. 28. Weber C.A. and Ellram L.M. (1993), Supplier selection using multi-objective programming: a decision support system approach, International Journal of Physical Distribution and Logistics Management, Vol. 23, No. 2, pp. 3-14. 29. Weber C.A. Current J.R. and Benton W.C. (1991), Vendor selection criteria and methods, European Journal of Operation Research, Vol. 50, pp. 2-18. APPENDIX A Vendor Performance Index (VPI) There are various ways in which a supplier can be evaluated. Three of these, namely the categorical method, the weighted point method and the cost ratio method are the most popular. Among the three methods the weighted point is used with the background of important data. The weighted point method There can be any number of attributes and each can be given a weighted rating in accordance with their relative importance as determined by the buyer. However, the total of all these points should be 100, and grading similar to the categorical plan i.e., by experience can be prescribed. These can be given as points, as Vendor Performance Index(VPI) = Quality weighted value of Quality + Delivery weighted value of Delivery +.+ (for all attributes consider for the supplier selection) Normally the weighted value is assigned by the experience of the buyer /purchase manager. These values can be arrived/ assigned by the priority values found from the AHP method. Since the VPI is standardized. IJAET/Vol.III/ Issue I/January-March, 2012/264-267