SELECTING THE SUITABLE ERP SYSTEM: A FUZZY AHP APPROACH Ufuk Cebeci Department of Industria Engineering, Istanbu Technica University, Macka, Istanbu, Turkey - ufuk_cebeci@yahoo.com Abstract An Enterprise Resource Panning System (ERP) is the information backbone of a company that integrates and automates a facets of business operations. It is a critica issue to seect the suitabe ERP system which meets a the business strategies and the goas of the company. This study presents an anaytica too for seecting the suitabe ERP system. This ERP seection method was appied in a textie manufacturing company. At first, the criteria were determined by the interna evauation team of the company and then compared according to their importance. Five ERP system soutions were seected to evauate by the same team. An externa evauation team consisting of three ERP consutants was assigned to seect one of these soutions according to the predetermined criteria. In this study, the fuzzy anaytic hierarchy process, a fuzzy extension of the muti-criteria decision making technique AHP, was used to compare these ERP system soutions. Keywords: ERP System, Fuzzy AHP, Decision making, textie. Introduction ERP systems are becoming more necessary for amost every firm to improve the competitiveness. According to the success of the impementation of ERP system; companies can obtain a competitive advantage in the goba market rapidy. Over the past decade, many ERP projects have resuted in substantia tangibe and intangibe improvements in a variety of areas for the organizations (Davenport, ; Umbe et a., and Yusuf et a., ). However, there are a number of exampes where organizations were not successfu in reaping the potentia benefits that motivated them to make arge investments in ERP impementations (Davenport, and Umbe et a., ). Impementations of ERP systems are one of the most difficut investment projects because of the compexity, high cost and adaptation risks. Companies have spent biions of doars and used numerous amounts of manhours for instaing eaborate ERP software systems (Yusuf et a., ). A successfu ERP project invoves seecting an ERP software system and co-operative vendor, impementing this system, managing business processes change and examining the practicaity of the system (Wei & Wang, ). Determining the best ERP software that fits with the organizationa necessity and criteria, is the first step of tedious impementation process. Hence, seecting a suitabe ERP system is an extremey difficut and critica decision for managers. An unsuitabe seection can significanty affect not ony the success of the impementation but aso performance of the company. However, many companies insta their ERP systems hurriedy without fuy understanding the impications for their business or the need for compatibiity with overa organizationa goas and strategies (Hicks & Stecke, ). The resut of this hasty approach is faied projects or weak systems whose ogic conficts with organizationa goas. This paper aims to provide an anaytica too to seect the most suitabe ERP software. Kumar et a., () investigated the key considerations and successfu strategies in ERP impementation projects. Byun () expored the use of AHP for deciding on car purchase. Wei et a., () proposed a comprehensive framework for seecting a suitabe ERP system based on an AHP-based decision anaysis process. Cebeci and Kahraman () compared some catering firms using four attributes and fuzzy AHP. The AHP is one of the extensivey used muti-criteria decision-making methods. One of the main advantages th Internationa Conference on Computers and Industria Engineering
of this method is the reative ease with which it handes mutipe criteria. In addition to this, AHP is easier to understand and it can effectivey hande both quaitative and quantitative data. The organization of this paper is as foows. First fuzzy sets and fuzzy numbers are introduced because our comparison method, fuzzy AHP, incudes fuzzy numbers and their fuzzy agebraic operations. Then, a comparison among five ERP vendors is made by using fuzzy AHP for a work wear firm.. Fuzzy sets and fuzzy numbers To dea with vagueness of human thought, Zadeh () first introduced the fuzzy set theory, which was oriented to the rationaity of uncertainty due to imprecision or vagueness. A major contribution of fuzzy set theory is its capabiity of representing vague data. The theory aso aows mathematica operators and programming to appy to the fuzzy domain. A fuzzy set is a cass of objects with a continuum of grades of membership. Such a set is characterized by a membership (characteristic) function, which assigns to each object a grade of membership ranging between zero and one. Zimmermann () gives the agebraic operations with Trianguar Fuzzy Numbers (TFNs). Many ranking methods for fuzzy numbers have been deveoped in the iterature. They do not necessariy give the same rank. The agebraic operations with fuzzy numbers can be found in Kahraman () and Kahraman et a. ().. Case Study In this study a Fuzzy AHP is deveoped to seect the appropriate ERP software for a medium-size Turkish work wear (textie) firm. The textie industry is one of the most important industries for export in Turkey. Nowadays, the companies have to decrease the costs to improve competitiveness. The firm Ismont is eader in work wear. It is very important to manage to manage their suppy chain, customer orders and costs. The firm shoud seect an appropriate ERP package fast, because the present information system cannot support their needs. The AHP mode provides priority weights for the ERP packages, based on the ERP project team s preferences on mutipe criteria. The aternative with the highest priority weight is then seected for the firm (Figure ). The Suitabe ERP A B C D E F G H I J K L M N O P W X N Y Z Figure. The AHP mode The attributes were determined according to the managers opinions, organizationa goas and iterature: I. Ease in customizing the system J. Cross modue integration K. User friendiness L. Compatibiity with other systems M. cost N. Better fit with company s business processes O. Impementation time P. Decision Support System Opportunity Q. Functionaity R. Adaptation to CRM and SCM systems S. Fexibiity T. Web based appications support U. Upgrade abiity V. After saes service W. Systems reiabiity X. Vendor reputation th Internationa Conference on Computers and Industria Engineering
Some questionnaires aiming at determining the degrees of preference by the hep of the pair wise comparisons among the attributes are prepared. The questionnaires faciitate the answering of pair wise comparison questions. The ERP project team consists of a director, two IT experts and a consutant, compared the five ERP software and vendors with respect to each attributes. The meanings of the attributes were expained in detai to every one in project team so that every one woud understand the same thing when they read the questionnaire. The matrix of paired comparisons for attributes is given in Tabe. After assigning the weights to each attribute, the project team compared a ERP aternatives; W, X, N, Y and Z. The matrix of paired comparisons for aternatives is given in Tabe. Summary of priority weights abe as attribute weights is given in Tabe and after appying the methodoogy, MBS NAVISION with Pebbestone (N) is seected. Tabe. The matrix of paired comparisons for attributes A B C D E F G H I J K L M N O P A,,,,,,,,,,,,,,,, B,,,,,,,,,,,,,,,, C,,,,,,,,,,,,,,,, D,,,,,,,,,,,,,,,, E,,,,,,,,,,,,,,,, F,,,,,,,,,,,,,,,, G,,,,,,,,,,,,,,,, H,,,,,,,,,,,,,,,, I,,,,,,,,,,,,,,,, J,,,,,,,,,,,,,,,, K,,,,,,,,,,,,,,,, L,,,,,,,,,,,,,,,, M,,,,,,,,,,,,,,,, N,,,,,,,,,,,,,,,, O,,,,,,,,,,,,,,,, P,,,,,,,,,,,,,,,, Tabe. The matrix of paired comparisons for aternatives cost W,,,, X,,,, N,,,, Y,,,, Z,,,,,,,, Functionaity,,,,,, W,,,, X,,,, N,,,, Y,,,, Z,,,,,,,, Upgrade abiity,,,,,,,,,,,,,,,,,, Impementation time, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,, Fexibiity,,,,,,, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Systems reiabiity,,,,,,,,,,,,,,,,,,,,,,,, th Internationa Conference on Computers and Industria Engineering
W,,,, X,,,, N,,,, Y,,,, Z,,,,,,,, User friendiness,,,,,,,, W,,,,, X,,,,, N,,,,, Y,,,,, Z,,,,,,,, Cross modue integration W,,, X,,, N,,, Y,,, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Ease in customizing the system, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Compatibiity with other systems, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Better fit with company s business processes W,,,,,, X,,,,,, N,,,,,, Y,,,,,, Z,,,,,,,,,,,, Adaptation to CRM and SRM systems Decision Support System Opportunity, W,,,,,,, X,,,,,,, N,,,,,,, Y,,,,,,, Z,,,,,,,,,,,,, Web based appications support W,,,,,,,,,,,, W,, X,,,,,,,,,,,, X,, N,,,,,,,,,,,, N,, Y,,,,,,,,,,,, Y,, Z,,,,,,,,,,,, Z,,,,,,,,,,,,,,,,,,,,,, th Internationa Conference on Computers and Industria Engineering
After saes service W,,, X,,, N,,, Y,,, Z,,,,,,,,,,,,,,,,,,,,,,,, Vendor reputation, W, X, N, Y, Z,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Tabe. Summary of priority weights abe as attribute weights Aternatives A B C D E F G H I J K L M N O P W,,,,,,,,,,,,,,,,, X,,,,,,,,,,,,,,,,, N,,,,,,,,,,,,,,,,, Y,,,,,,,,,,,,,,,,, Z,,,,,,,,,,,,,,,,,. Concusion ERP systems have a vita roe in today s organizations. However, they have aso high costs and high impementation risks. Decisions are made today in increasingy compex environments. In more and more cases the use of experts in various fieds is necessary, different vaue systems are to be taken into account, etc. In many of such decision-making settings the theory of fuzzy decision-making can be of use. Fuzzy group decision-making can overcome this difficuty. In genera, many concepts, too and techniques of artificia inteigence, in particuar in the fied of knowedge representation and reasoning, can be used to improve human consistency and impementabiity of numerous modes and toos in broady perceived decision-making and operations research. In this paper, ERP packages and vendors were compared using fuzzy AHP. Humans are often uncertain in assigning the evauation scores in crisp AHP. Fuzzy AHP can capture this difficuty. However, Fuzzy AHP cannot support a phases of ERP seection and impementation. Hence, a decision support system or expert system can be added when gathering data for seection process. Aso, the expert system can be used before and after the ERP system seected. The essons from this textie firm case or other appications can be added into the knowedgebase of the expert system. The expert system can hep to prepare A Request for Proposa for a textie firm. Because this stage needs experience about the seection process. th Internationa Conference on Computers and Industria Engineering
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