Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD]

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1 International Journal of Advances in Engineering Science and Technology and ISSN: Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] SATBIR SINGH SAINI 1 [RIET,PHAGWARA] ER.HARWINDER LAL 2 [RIET,PHAGWARA] SUMEET NAGAR 3 [LPU,PHAGWARA] Department of Production engineering satbirsaini1985@gmail.com,lal.harvinder@gmail.com,sumeetnagar@rediffmail.com Abstract- This study explores the ranking of external supply chain performance of FMCG firms using multi criteria decision making technique of supply chain performance evaluation. By following this study, a firm can identify areas of opportunity for improvement in its external supply chain. For the firms manufacturing FMCG goods and having a large product range can calculate the length of supply chain from the data available at wholesaler, super marts and retailers. This data will be analyzed to compare the length of supply chains of different product, fast and slow moving products between wholesaler, super marts and retailers for the same product. The study explored various new results and conclusions. The focus of the study was on the effect of inventory, the ordering cycle mode of information flow on the length of supply chain at various levels. The ranking of different FMCG companies was done by using VIKOR TECHNIQUE and different weights of the selection criteria were calculated by pair-wise comparison using the AHP TECHNIQUE. Further, the framework can help to identify specific reasons behind the performance levels in the external supply chain and stimulate performance improvement. To illustrate the framework, it is applied to fast moving consumer goods ( FMCG) industry. Keywords: Fast moving consumables goods (FMCG), Multiple criteria decision making (MCDM), Ranking, Vikor, Analytical Hierarchy Process [AHP] 1. INTRODUCTION A firm can compare its performance with of its competitors and the industry aggregate in order to ascertain where it stands in terms of supply chain performance. Further a firm can also compare its own profile with that of its competitors in order to ascertain where it stands in terms of costs and length of time in the supply chain. Benchmarking is a useful tool for comparing the performance of competing firms so as to identify areas of improvement in supply chain performance. Supply chain performance of a company is compared with competitors by comparing there external chain length. FAST MOVING CONSUMER GOODS Fast moving consumer goods (FMCG) alternatively known as consumer packaged goods CPG are products that are sold quickly and generally consumed at a regular basis, as opposed to durable goods such as kitchen appliances that are replaced over a period of years. The FMCG industry primarily engages in the production, distribution and marketing operation of CPG. FMCG product categories comprise of food and dairy products, pharmaceutical, consumer electronics, packaged food products, household products, drinks and others. Meanwhile, some common FMCG include coffee, tea detergents, tobacco and cigarettes, soaps and other. The big names in this sector include Sara lee, Nestle, Reckitt Benckiser, Unilever, Procter & Gamble, Coca-Cola, Carlsberg, Kleenex, General mills, Pepsi, Mars SUPPLY CHAIN MANAGEMENT (SCM) The concept of supply chain management is based on the fact that practically every product that reached an end user represents the cumulative effort if multiple organizations. These organizations are referred to collectively as the supply chains. Though

2 IJAEST, Volume 2, Number 2 SATBIR SINGH SAINI et al. supply chains have existed for a long time, most organizations have only paid attention to what as happening within their four walls. The result was disjointed and often ineffective supply chains. Supply chain management of the materials, information and fund across the entire supply chain(from suppliers to component producers t final assemblers to distribution and ultimately to the consumer) in order to maximize the customer value and achieve a sustainable competitive advantage. In fact, it often includes after sales and returns of recycling. Supply chain management is the management of eight key business processes: customer relationship management, customers service management, Procurement, demand, management, order fulfillment, manufacturing flow management,procurement, product developments and returns. These processes include much of logistics, purchasing marketing and operations management supply chain management is very important in controlling the operations of the supply chain to satisfy customer requirements as efficiently as possible. Parameters for measuring supply chain Total length of the chain:- The total length of the chain is arrived at by adding up the days of inventory for raw materials, work in progress and finished goods. The firm that has the minimum total length of the chain is said to have the best performance. LENGTH OF SUPPLY CHAIN The length of supply chain is arrived at be adding up the days of inventory of raw material, work in progress, transportation and days of finished goods to reach the end user. The length of supply chain is dependent on whether different coordination mechanisms are efficient or not. In case supply chains would with different coordination mechanisms are inefficient, the length of these supply chains would then show a significant negative relationship with the coordination mechanism, disintermediation of the supply chain would occur to bring the supply chain back towards efficiency. As companies move from internal manufacturing to outsourced manufacturing they are faced with a new set of supply chain constraints and trade-offs. As supply chains elongate, the physical movement of goods in the supply chain increased manifold. The companies which deliver the goods directly from the vendors to the customers increase their manifold. The companies which deliver the goods directly from vendors to the customers increase their profits margins where as the companies which are outsourcing the intermediate goods or components of the complete product results in increased supply chain length. The situation is worsened in a reverse supply chain scenario where the goods are returned from the customer and sent back to the right supplier, which could be located on a different continent External chain length increases due to transportation delay, inventory as distributor, inventory at whole seller and inventory at retail outlets. This affect the pricing of the product, it the inventory at whole seller level is less than it has less cost of caring inventory which ultimately at whole resulting in lowering the price of products which tend to increase the sale of the product. The profit margins are also high due to increase the sale of the product. The profits margins are also high due to increase sale less inventory cost. 2. METHODOLGY BASIC PRINCIPLE OF VIKOR ALGORITHM The VIKOR method is a multicriteria decision making (MCDM) or Multi-criteria decision analysis method. It was originally developed by Serafim Opricovic to solve decision problems with conflicting and noncommensurable (different units) criteria, assuming that compromise is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. VIKOR ranks alternatives and determines the solution named compromise that is the closest to the ideal. VIKOR is a helpful tool in MADM, particularly in a situation where the decision maker is not able, or does not know how to express preference at the beginning of system design. The obtained compromise solution could be accepted by the decision makers because it provides a maximum group utility (represented by E i-min. ) of the majority, and a minimum of individual regret (represented by F i-min. ) of the opponent (Opricovic and Tzeng, 2002, 2003, 2004, 2007). The compromise solution could be the basis of negotiations, involving the decision makers preference by attribute weights. The MCDM problem is stated as follows: Determine the best (compromise) solution in multicriteria sense from the set of J feasible alternatives A1, A2, AJ, evaluated according to the set of n criterion functions. The input data are the elements fij of the performance (decision) matrix, where fij is the value of the i-th criterion function for the alternative Aj.

3 198 Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] CALCULATION STEPS OF VIKOR ALGORITM The VIKOR procedure has the following steps: Step 1: The first step is to determine the objective, and to identify the pertinent evaluation attributes. Also determine the best, i.e., (m ij ) max. and the worst, i.e., (m ij ) min. values of all attributes. Step 2: Calculate the values of E i and F i : Ei = wj [(mij)max - (mij )] / [(mij)max - (mij)min] j=1 Fi = Maxm of {wj [(mij)max - (mij )] / [(mij)max - (mij)min] j = 1, 2,.., M} Step 3: Calculate the values of P i: Pi = v ((Ei - Ei-min) / (Ei-max - Ei-min)) + (1 - v) ((Fi - Fi-min) / (Fi-max - Fi-min)) Where, E i-max is the maximum value of E i, and E i-min. the minimum value of E i ; F i-max. is the maximum value of F i, and F i-min. is the minimum value of F i. V is introduced as weight of strategy of the majority of attributes. Usually, the value of V is taken as 0.5. However, V can take any value from 0-1. Step 4: Arrange the alternatives in the ascending order, according to the values of P i. Similarly, arrange the alternatives according to the values of E i and F i separately. Thus, ranking lists can be obtained. The compromise ranking list for a given V is obtained by ranking with P i measures. The best alternatives, ranked by P i, are the one with the minimum value of P i. Step 5: For given attribute weights, propose a compromise solution, alternative A k, which is the best ranked by the measure P, if the following two conditions are satisfied (Tzeng et al., 2005): Condition 1: Acceptable advantage P(A k )-P(A l ) (1/(N-1)). A l is the second-best alternative in the ranking by P. Condition 2: Acceptable stability in decision-making alternative A k must also be the best ranked by E and/or F. This compromise solution is stable within a decision-making processes which could be; voting by majority rule (when V>0.5 is needed) or by consensus (when V 0.5) or with veto (when V>0.5). If one of the conditions is not satisfied, then a set of compromise solution is proposed, which consists of: Alternatives A k and A l if only condition 2 is not satisfied. Alternatives A k, A l,, A p if condition 1 is not satisfied; A p is determined by the relation P(A p )-P(A l ) ( 1/(N-1)). VIKOR is a helpful tool in MADM, particularly in a situation where the decision maker is not able, or does not know how to express preference at the beginning of system design. The obtained compromise solution could be accepted by the decision makers because it provides a maximum group utility (represented by E i-min. ) of the majority, and a minimum of individual regret (represented by F i-min. ) of the opponent (Opricovic and Tzeng, 2002, 2003, 2004, 2007). The compromise solution could be the basis of negotiations, involving the decision makers preference by attribute weights. Analytical Hierarchy Process Analytical hierarchy process (AHP) comes under multi criteria decision making that was originally proposed by Thomas L. Saaty. It is a technique developed to deal with complex and complicated decisions. First of all the decision problem is decomposed into a hierarchy of more easily comprehended sub-problems, and each can be analyzed independently. The elements of hierarchy can relate to any aspect of the decision problem like tangible or intangible, roughly or carefully measured and estimated etc. Once the hierarchy is build the decision makers systematically evaluates its various elements by comparing them with one another two at a time. It is the essence of AHP that the human judo vent and not just the underlying information can be used in performing the evaluations.

4 IJAEST, Volume 2, Number 2 SATBIR SINGH SAINI et al. The Al It' converts these evaluations into numerical values that can be processed and used for the entire range of problem. A numerical weight is derived for each element of hierarchy allowing diverse and often incommensurable elements to be compared to on an other a consistent manner. This capability distinguishes the A]-IP from other decision making techniques. Analytical hierarchy process (AHP) is most useful where teams are working on complex problems, especially those with high stakes, involving human perception and, judgment. It has a unique advantage when important elements of the decision are difficult to quantify and compare. AHP can be applied to the decisions related to choice, Ranking, Prioritization, Resource allocation, Benchmarking, and Quality management decisions. Other areas include Forecasting, service evaluation etc.ahp is a method requires pair-wise comparison. Suppose we do not have any weighting instrument, can we, somehow, try to estimate the relative weights of several different objects by hands? One way is to use the lightest one as a primary standard, assume it is weighted unit (1). On the basis of that, we can guess one other object's weight by lifting the lightest one and another one at the same time and compare them. Another way is to compare the objects in pairs: lift two objects. record the estimated difference between them; then lift another pair until we are done with all the possible pairs (i.e., if we have three objects A, B and C, then we need to judge three times: A and B, B and C, A and C.). Clearly, the second way named pair wise comparison utilizes more available information. Thomas L. Saaty develops a system called Al-IP that transforms the pair wise comparison scores into weights of different attributes and priorities of all alternatives on each attribute to obtain the overall ranking of alternatives.the procedure of AHP can be summarized as: 1) formulate the problem; 2) determine the relative weights of the comparison attributes; 3) compare the alternatives on each attribute; and 4) aggregate weights to produce final evaluation. In the present research various retail and wholesale outlets in and around Jalandhar(PUNJAB) were taken which are selling different type of FMCG goods of different brands. The methodology adopted for the present study is shown which gives the step by step procedure to carry out the study. The detail of each activity is explained consecutively. The flow diagram is as shown. Input from literature Identify the data to be collected Collection of data Analysis of data Vikor method Ranking ESTIMATION OF EXTERNAL CHAIN LENGTH On the basis of data collected from various retail outlets regarding packaging date, current stock of the product at the retail outlet, and average monthly sale of that product the chain length calculations are done as shown (Janat shah 2009)

5 200 Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] Manufacturing date Date of study Point of sale Time scale in months Let us suppose that two products X and Y have been chosen for the study and the study was carried out at the end of February Data (stocks. sales rate. manufacturing date on stocks on the shelf) and estimation of length of chain for the two products is as shown in the table below Item Data collected from retailer A=(Date of study)-(date Stock Sale Date of of (units) (unit/month manufacture manufacture) ms) (in months) B=(stock /sale) /2 Chain length (A+B) (in months) Product X Dec Product Y Nov COMPARATIVE ANALYSIS In a highly competitive environment, the relative performance of firm in sale, market share and its supply chain depends primirly on its strategic decision and financial aspects. Supply chain affectivity makes the firm profitable in one or many ways, either through efficient distribution network or through less cost transaction and well defined information flow. In this study we were trying to measure the Impact of length of external supply chain on the overall performance of the firm CHARACTERSTICS OF FIRM UNDER STUDY The chain length obtained by the data collected from different retail, and wholesale outlets from urban and rural areas was plotted and compared.

6 IJAEST, Volume 2, Number 2 SATBIR SINGH SAINI et al. FMCG Firm Chain length (months) Soap Hair Oil Shampoo Edible Salt HUL DABUR ITC MARICO FMGC FIRM Soap Hair Oil Shampoo Edible Salt Analysis of stock and chain length at retailer The weighted mean chain length of different products was compared with the stock of the respective product for different FMCG firms. Following data were collected from different retail outlets as shown Soap Hair oil Shampoo Edible Salt Chain length(months) Stock(units) Chain length(months)2 stock(units)2 Chain length(months)3 Stock(units)3 Chain length(months)4 Stock(units)4 FMCG Firms HUL DABUR ITC MARICO

7 202 Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] Products Chain length (months) Stock (units) Chain length (months) Stock (units) Chain length (months) Stock (units) Chain length (months) Stock (units) Soap Hair oil Shampoo Edible Salt ANALYSIS USING Vikor Method The study was conducted on the basis of data collected from various retail outlets of FMCG products including personal care, hair care, body care, edible and juices. The data collected was tabulated by vikor method on the basis of least chain length at any retail outlet, mean chain length of all retail outlets, and maximum chain length at any retail outlet for a particular product. This data is used to select the FMCG firm having least product chain length and for ranking the four firms in the study in ascending order on the basis of chain length from the data the product is packed. WEIGHTS USING AHP Step 1: From the literature review about various FMCG companies and from the sector wise sale of different products the following products found most selling and common in the four major FMCG companies 1. Soap 2. Shampoo 3. Hair oil 4. Edible products(juices, tea, refined oil) 5. Common salt Step 2: To find the relative importance of each criteria (product) from customer point of view the weights of different criteria were found by a pair wise comparison matrix as shown, prepared from the arithmetic mean of various scores given by about 50 respondents to each criteria. Step 3: Weights of each selection criteria were calculated as shown in the figure Step 4: The consistency ratio was calculated for the matrix value of each criteria and its value came out to be which is within the permissible limit of 0.1.The values obtained from step 2 are shown in table CRITERIA C1 C2 C3 C4 C5 Geometric mean

8 IJAEST, Volume 2, Number 2 SATBIR SINGH SAINI et al. C /5 C /5 C /5 C /5 C /5 Geometric mean Weights / /5 / = 0.05 [SOAP] / /5 /6.3308=0.14 [HAIR OIL] / /5 /6.3308=0.23 [SHAMPOO] / /5 /6.3308=0.45 [EDIBLE] / /5 /6.3308=0.13 [COMMON SALT] SUM= AHP Pair-wise comparison matrix C1: SOAP C2: HAIR OIL C3: SHAMPOO C4: EDIBLE C5: COMMON SALT Weights for selection criteria using AHP CRITERIA WEIGHTS SOAP 0.05 HAIR OIL 0.14 SHAMPOO 0.23 EDIBLE 0.45 COMMON SALT 0.13 SELECTION OF FMCG FIRM HAVING LEAST CHAIN LENGTH USING Vikor Method:

9 204 Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] FMCG Chain (months) Firm length Soap Hair Shampoo Edible Salt Oil HUL DABUR ITC MARICO Ei = wj [(mij)max - (mij )] / [(mij)max - (mij)min] j= / = / / = / = =0 E / =0 E / =0.71 E / =1 E / = = / = / = / = / = / = / = / = / = / = / = / =0.11 SUM E E E E Ei(min) = 0.21 Ei(max) = Fi = Maxm of {wj [(mij)max - (mij )] / [(mij)max - (mij)min] j = 1, 2,.., M} F(M1)=1 F(M2)=1 F(M3)=1 F(M4)=1 F(M5)=1 F(I max)=1 F(I min)=1 P(i) = v (Ei-Ei min)/(ei max-eimin) + (1-v) (Fi-Fi min)/(fi max-fi min) P(1)0.5 ( )/( ) + (1-0.5) (1-1)/(1-1) = 0 p(2) = 0.5 ( )/( ) + (1-0.5) (0) = p(3) = 0.5 ( )/( ) + (1-0.5) (0) = 0.5 p(4) = 0.5 ( )/( ) + (0) = 0.128

10 IJAEST, Volume 2, Number 2 SATBIR SINGH SAINI et al. Where E i-max and E i-min are the maximum and minimum values of Ei, respectively, and F i-max and F i-min are the maximum and minimum values of Fi, respectively. v is introduced as weight of the strategy of the majority of attributes (or the maximum group utility ). Normally, the value of v is taken as 0.5. The compromise ranking list for a given v can be obtained by ranking with the Pi measure. The best alternative is the one having the minimum Pi value. VALUES OF P(I) RANKING P1 0 1 P P P VALUES OF P(i)WITH RANK VIKOR RANKING OF COMPANIES HUL MARICO DABUR ITC 5.CONCLUSIONS In this present study, feasibility of MCDM approach VIKOR method has been highlighted to solve impact of external supply chain length on the competitivess of the FMCG companies. The present study makes significant contribution towards finding the performance of the supply chain. The models were developed to target the internal benchmarking of the companies and the external chain length was not given that importance. The present study is the exploratory study on the base of a new model proposed by the janat shah (2009) to evaluate the performance of different FMCG companies. The given model can be clubbed with the previous existing models to get the models to get the complete benchmarking of internal and external supply chains. A framework for benchmarking using these performance measures was presented and applied to the FMCG companies. By following this framework, firms can identify areas of opportunity for improvement in their external supply chain. Such an exercise encourages firms to look outward and gain an external perspective on performance improvement opportunities. Further, the framework can help to identify specific reasons behind the performance levels in the external supply chain and stimulate performance improvement. The study demonstrates the effectiveness of the said MCDM technique in RANKING the best FMCG company in the specific region REFERENCES [1] Janat Shah and Nitin Singh, Benchmarking Internal Supply Chain Performance : Development of Frame Work, International Journal of Supply Chain Management, [2] Janat Shah, (2009). Supply chain management Text and Cases. Pearson Education [3] Liu, P. and Wang, M. (2011), An extended VIKOR method for multiple attribute group decision making based on generalized interval-valued trapezoidal fuzzy numbers, Scientific Research and Essays, Vol. 6 No. 4, pp [4] B.S. Sahay, VasantCarale. Ramneesh Mohan (2003), The Indian supply chain architecture, Supply Chain Management: An International Journal Volume 13 Issue :3 [5] Kumar, S., Parashar, N. and Haleem, A. (2009), Analytical hierarchy process applied to vendor selection problem: small scale, medium scale and large scale industries, Business Intelligence Journal, Vol. 2 No. 2, pp [6] Guo, J. and Zhang, W. (2008), Selection of suppliers based on rough set theory and VIKOR algorithm, Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops, pp [7] Gunasekaran, A., Patel, C.,Tirtiroglu, E., Performance measures and metrics in a supply chain environment. International Journal of Operations & Production [8] Kaplan, R., Norton, D., Linking the balanced scorecard to strategy. California Management Review, Vol.39 (1) [9] Lamouri, S., Thomas, A., The low level master production schedule and planning bills in a just in time context. International Journal of Production Economics, Vol 64, [10] Chakraborty, T., Ghosh, T. and Dan, P.K. (2011), Application of analytical hierarchy process and heuristic algorithm in solving vendor selection problem, Business Intelligence Journal, Vol. 4 No. 1, pp [11] Cakir, E., Tozan, H. and Vayvay, O. (2009), A method for selecting third party logistic party logistic provider using fuzzy AHP, Journal of Naval Science and Engineering, Vol. 5 No. 3, pp [12] De Boer, L., Gaytan, J. and Arroyo, P. (2006), A satisficing model of outsourcing, Supply Chain Management: An International Journal, Vol. 11 No. 5, pp [13] Pang, B. (2009), A fuzzy ANP approach to supplier selection based on fuzzy preference programming, International Conference on Management and Service Science, pp. 1-4.

11 206 Comparative Study Of External Supply Chain Performance Of FMCG Firms Using Multi Criteria Decision Technique [VIKOR METHOD] [14] Percin, S. (2010), Evaluation of third-party logistics (3PL) providers by using a two-phase AHP and TOPSIS methodology, Benchmarking: An International Journal, Vol. 16 No. 5, pp [15] Shemshadi, A., Shiraji, H., Toreihi, M. and Tarokh, M.J. (2011), A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting, Expert Systems with Applications, Vol. 38 No. 10, pp [16] Zeleny, M. (1982), Multiple Criteria Decision Making, McGraw-Hill, New York, NY