A famewok fo the selection of entepise esouce planning (ERP) system based on fuzzy decision making methods Omid Golshan Tafti M.s student in Industial Management, Univesity of Yazd Omidgolshan87@yahoo.com Mohammad Amin Bodba M.s student in Industial Management, Univesity of Yazd mohammadaminbodba68@gmail.com Iman Noubakhsh M.s student in Industial Management, Univesity of Yazd noubakhshiman@yahoo.com Abstact ERP system implementation poject on the one hand equies consideable s financial investment. And on the othe the stuctue and infastuctue has a geat impact on oganizational pefomance, theefoe equies adequate pe-feasibility and peliminay studies. The expeiments show that one of the main easons fo failue in the implementation of entepise esouce planning system is inappopiate selection of ERP package. Consideing the numbe of ERP softwae packages povides, thee is consideable diffeences between featues and the way of suppoting of softwae. Theefoe the coect choice equies consideation diffeent kind of both quantitative and qualitative citeia. On the othe hand the uncetainty and eliability must be consideed in evaluating the decision-makes. To achieve this, the famewok consists of methods fo fuzzy multiple citeia decision making (MADM) and anking method of fuzzy appoach fo the evaluation and selection of Entepise Resouce Planning systems is pesented. Keywods: Entepise esouce planning (ERP), evaluation and selection fuzzy multiple citeia decision making (MADM), fuzzy anking Intoduction All scholas and expets in the past two decades emphasized the changes in envionmental conditions and foms of business oganizations. The fomation of global economy and globalization, changing wokfoce and the types of customes who ae able to impose thei demands on manufactues is tiggeed a stessful envionment with many challenges fo oganizations today [1]. Among these, oganizations ae successful using new management tools and technologies, could take advantage of the ceated oppotunities [2]. Feasibility befoe applying any changes will help to gain knowledge and awaeness. Feasibility educes the change isk and will save time and cost. Implementation of Entepise Resouce Planning systems (ERP), including pojects that because of its impotance, both fom a financial and investment aspect, stuctual and infastuctual aspects needs feasibility studies befoe it is implemented. While the extensive wok was done in the field of infomation systems implementation, but in the field of evaluation and selection them has not been done scientific and eseach wok [3]. In this pape, a bief intoduction of entepise esouce planning systems is intoduced and citical citeia fo evaluating and selecting of ERP softwae systems povides is investigated. Seveal citeia must be consideed in such a choice; On the othe hand mechanism should be adapted to coves uncetainty in identifying and assessing. To achieve these objectives, in the end of this pape a famewok fo selecting an appopiate ERP fo the oganization is povided. In this famewok, the combination of fuzzy multiple citeia decision making (MADM) and a fuzzy anking method fo the evaluation and selection of the best choice of Entepise Resouce Planning systems is used. What is Entepise esouce planning system (ERP)? 373
ERP is a thought, technology and management system fo high pefomance on a vaiety of souces in an oganization. This kind of management is done though integating of activities in ode to enhancing the efficiency and poductivity of the oganization and custome satisfaction impovement. ERP shows all opeational steps in a pocess in an oganization. Afte eceiving an ode is diected to design and poduction section. Then goes to waehouse section and finally shipping. The steps up to the billing and evenue calculations in connection with the ode will be ecoded in the ERP system in the company and made available to all elevant sectos. Theefoe, the ERP is called a Back - Office softwae. Because it only deals with communication and intenal units of oganization and not to the extenal communications (known as the font - Office). These functions ae now the esponsibility of the CRM system. Some ERP softwae packages poducing companies cuently offe CRM sevices with thei poduct. Status of ERP systems in oganization In geneal, in maco level, two goups of infomation systems ae classified to infomation systems management suppot and infomation systems opeations suppot. Some of the Opeations Suppot Systems include: 1 - Tansaction Pocessing System (TPS): These systems ae esponsible fo infomation pocessing of business pocesses. 2 - Pocess contol systems (PCS): These systems ae esponsible fo the task of contolling the poduction pocess. 3 - Office Automation Systems (OAS): These systems ae esponsible fo office automation tasks. Some management suppot systems include: 1 - Management Infomation Systems (MIS): these systems povide infomation to help management to suppot daily decisions (stuctued decisions) at vaious levels. 2 - Decision Suppot Systems (DSS): These systems povide infomation to help senio and middle level management decisions fo non-stuctued ones. 3 - Executive Infomation Systems (EIS): The system povides specific infomation fo senio and middle management to achieve oganizational stategic objectives. The Role of Entepise Resouce Planning system (ERP) in elation to management infomation systems in oganizations is shown in Figue 1(16). ESS MIS DSS KWS &OS ERP TPS Figue 1. Status of entepise esouce planning systems (ERP) in elation to othe infomation systems Selecting an appopiate ERP Even though most ERP systems and packages seem vey simila to each othe but ae significantly diffeent in stuctue. On the othe hand the implementation of entepise esouce planning system equies a significant investment both financially and in tems of time. Theefoe, the selection pocess of entepise esouce planning system of systems available on the maket, is vey difficult and toublesome and must be done caefully and patiently. Studies show that most companies in etun on investment in this aea ae deficient between 25 and 50 pecent, the losses ae because of ignoing one o moe phases of the pocess of selecting an 374
appopiate softwae package, in such a situation the selected system will not ovelap pefectly with the needs of the company. Today, moe than 300 companies ae woking as ERP Supplie woldwide, and each of them intoduces thei poduct as they can fulfill all the needs and demands of the oganization. In such a situation, the question aises that despite the wide ange of poduces and povides of poducts, how it will be acted to ovecome not only the isks but also achieve the intended benefits? What pofessionals and expets have poposed about this woldwide, is Moving in path fo not to encounteing isk duing this step by step citical path. Jacques Veville et al (2002) offeed a six-step model fo supply and puchase of ERP softwae. This pocess includes planning, infomation seeking, and initial selection, evaluation of altenatives, selection and negotiation [4]. CJ Stefanou Emphasize the impotance of selecting an appopiate ERP, poposed a conceptual famewok fo evaluating ERP softwae. He maintained that the ERP selection and evaluation should conside both stategic and opeational citeia [5]. Stategic Planning is in the fist place fo ERP implementation. A stategy should be in accodance with available esouces, conditions and goals. To achieve a specific stategy, pesent situation and path diected towad taget always should be consideed. Opeational citeia efe to the actions and activities that make stategies opeational and esulted in achieve to objectives. In othe eseach, Tunc & Bugoon listed the expectations of each of the diffeent pats of the ERP, in diffeent pat of oganizations, Fo example, in the human esouces depatment, infomation that should be in tems of pesonnel as a custome oiented standad has been poposed [6]. In geneal, in ode to establish a famewok fo the successful implementation and achieving maximum investment ate, nine steps in the pocess of selecting an appopiate ERP system is poposed as shown in Figue 2. ceating Futue vision and setting goals of oganization Pepae a list of equied functions and chaacteistics Pepae a list of candidates fo poviding softwae Selected thee finalists (the final supplies) RFP pepaation limited Candidates to 4 o 6 seious candidate Explain and demonstate each of the softwae by supplies Pick the winne (final supplie) Contact negotiation, expeimental implementation and justification of investments Figue 2: The pocess of selecting an appopiate ERP system Poposed famewok fo selecting ERP In eveyday life we ae faced with diffeent situations that need to decide to choose one of the available options. Application of fuzzy sets in decision making filed is done by changing the classical theoies to fuzzy ones. 375
While decision-making unde conditions of isk has been fomulated using pobability and game theoy, Fuzzy decision theoies ae used in ode to deal with ambiguity and non-essential featues of the pioity, constaints and objectives fomulation. Fuzzy logic includes a ange of theoies and techniques that essentially ae built based on fou concepts; Fuzzy sets, linguistic vaiables, pobability distibution (membeship function) and fuzzy if - then ules [7]. A fuzzy set is a set that its elements belong to the set with membeship degee of μ. In situations whee the equied infomation ae Quantitative they expessed numeically, Howeve, when conducting eseach is qualitative and its knowledge has uncetainty, the infomation can not be expessed as exact numbes. Most manages can not expessing thei idea with a pecise numbe, And theefoe the vebal assessments was used athe than specific numeical values [8]. Theefoe, the fuzzy sets theoies is vey impotant because of consideing uncetainty and uncetainty in decision making, Especially in cases whee decision making is about human esouces and complex systems. In this pape we use a combination of fuzzy multi-citeia decision making and fuzzy anking methods fo selecting appopiate ERP softwae. Multi-citeia decision-making techniques ae divided into multi-objective decision making models and (MODM) and multi-attibute decision making models (MADM). Multi-objective models ae used to design and the multi- attibute models ae used to select the best choice [9]. Multiple attibute techniques and goup decision-making ae used extensively in the liteatue, and povide the ability of evaluating the options fo manages and decision-makes [10]. The following easons can be mentioned fo using the fuzzy MADM techniques in the poposed famewok [11] (in this pape is called the fuzzy multiple citeia decision making): 1 The method that is used by decision makes in the case of quality citeia is eithe liteal o vebal. 2 - The cedibility of fuzzy MADM methods, due to the possibility of enteing pesonal and inaccuate comments of decision makes, is high. 3 - Fuzzy MADM methods can be used easily fo simultaneous evaluation of qualitative and quantitative citeia fo each unit and scale. 4 - In cases whee the weight of the citeia is not clea, the use of fuzzy MADM is ecommended instead of classic MADM methods. 5 - Fuzzy MADM poblems solving method that used vebal vaiables, is one of the best ways to deal with the issues that have lage dimensions. 6 In this method thee is the possibility of applying the goup decision make s opinion diectly in the model. 7 - The use of fuzzy technique cause not wasting any ight of decision makes. Multi-attibute decision-making methods In eality, decisions ae often multi- attibute and the appopiate o inappopiate citeia of decisions is usually moe than one? To undestand the poposed famewok, fist multiple attibute decision making techniques should be intoduced. In This method pimay data ae collected based on decision-makes opinions and in the fom of Decision making matix and it will be the base fo final decision. MADM methods will detemine the best choice based on mathematical easoning and pioitizing [12]. In Multi Citeia Decision Making methods to pioitize and select the best choice we use n altenative and m citeia. Let X={x 1, x 2, x n } and C= { c 1, c 2, c m } be, a set of altenatives and a set of citeia chaacteizing a decision situations, espectively. The basic infomation involved in multi citeia decision making can be expessed by the matix: 11 1n m1 mn Columns ae attibutes and Rows of matix ae altenatives, that ae X={ x 1, x 2, x m } and C= { c 1, c 2, c m } espectively. Assumes fist that all enties of this matix ae eal numbe in [0, 1], and each enty expess the degee to witch citeion c i is satisfied by altenative x j (i N m, j N n ). Then R may be viewed as a matix epesentation of a fuzzy elation on C X. 376
It may happen that, instead of matix R with enties in [0, 1], an altenative matix conveted to the desied matix R by the fomula: / max jn min n n / / min / jn jn Fo all i N m and j N n. The most common appoach to multi citeia decision poblem is to convet them to single- citeion decision poblems. This is done by finding a global citeion, j =h( 1j, 2j,, mj ), that fo each x j X is an adequate aggegate of values 1j, 2j,, mj to witch the individual citeia c 1, c 2,, c m ae satisfied. A fequently employed aggegating opeato is the weighted aveage: j m i1 m i1 w i w i n (j N n ) Whee w 1, w 2, w m ae weights that indicate the elative impotance of citeia c 1, c 2, c m. A class of possible weighted aggegations is given by the fomula: w1 w2 w h(,,..., m ) j 1j 2j mj Whee h is an aggegation opeato and w 1, w 2, w m ae weights. Conside now a moe geneal situation in witch the enties of matix R ae fuzzy numbe on R +, and weight ae specified in tems of fuzzy numbes multiplication, we can calculate the weighted aveage w i on [0,1]. Then, using the opeations of fuzzy addition and fuzzy j i i1 j by the fomula; Since fuzzy numbes ae not linealy odeed, a anking method is needed to ode the esulting fuzzy numbe 1, 2,..., n. Fo this pupose we use the one of the simple fuzzy anking methods hee. m w Fuzzy anking method This method is based on α-cuts. In fact, a numbe of vaiations of this method have been suggested in the liteatue. A simple vaiation of this method poceeds as follows. Given fuzzy numbes A and B to be compaed, we select a paticula value of α [0,1] and detemine the α-cuts A [ a1, a2] and B [ b1, b2], then we define A B if a 2 b 2 This definition is, of couse, dependent on the chosen value of. It is usually equied that α > 0.5. Multi peson decision making method A social choice function must then be found which, given the individual pefeence odeing, poduces the most acceptable oveall goup pefeence odeing. Basically, this model allows fo the individual decision makes to possess diffeent aims and values while still assuming that the oveall pupose is to each a common, acceptable 377
decision. In ode to deal with the multiplicity of opinion evidenced in the goup, the social pefeences S may be defined as a fuzzy binay elation with membeship gade function S: X X [0, 1] Which assigns the membeship gade S (x i, x j ), indicating the degee of goup pefeence of altenative x i ove x j. The expession of this goup pefeence equies some appopiate means of aggegating the individual pefeences. One simple method computes the elative populaity of altenative x i ove x j by dividing the numbe of peson pefeing x i to x j, denoted by N (x i, x j ), by total numbe of decision makes, n. this scheme coesponds to the simple majoity vote. Thus, N( xi, x j) S( xi, x j). n Once the fuzzy elationship S has been defined, the final non fuzzy goup pefeence can be detemined by conveting S into its esolution fom. [15]. S [0,1] S The poposed decision famewok is pesented in Figue 3 [15]. 378
Detemine Membes fo decision making Fuzzy Multi Peson Decision Making Detemine the numbe of altenatives X={x 1, x 2,, x n} Detemine the numbe of attibutes C={ c 1, c 2,, c m } among the list of them Fuzzy Multi Citeia Decision Making Computing j Using a fuzzy anking method fo anking altenatives fo each membe Fuzzy Ranking Making Giving the pefeence odeing P k Fo each membe Computing S (Final Result) Figue 3: Poposed Famewok Conclusion Mistakes and inaccuacies in impotant decisions, leads to pay fo eos. Whateve The manages powe is highe, the cost fo the wong decision is highe [13]. The expeiments demonstate that one of the main easons fo failue in the implementation of entepise esouce planning is inappopiate selection of ERP package. Because thee is uncetainty in complex decision-making, this pape pesents a famewok in which a fuzzy multi-citeia decision-making method is used to select the appopiate softwae [14]. In the pesented 379
famewok a fuzzy multi-citeia decision method, and a fuzzy anking method is used to select the ight softwae fo the oganization. The poposed famewok coveing both quantitative and qualitative citeia involved in the evaluation and selection of Entepise Resouce Planning systems, and mentioned uncetainty in pocess of decision making. Refeences 1. Saafzadeh, A., "Infomation Technology in Oganizations", Tehan, Mi Publishes, 1386. 2. Zanjida, M. and Cohen, A. and Sultan Zade, A, "managing, measuing and epoting of intellectual capital ", Jounal of Commece, No. 18, 1387. 3. Nikju, M, "RUP methodology developed to analyze infomation systems", Poceedings of the Thid Intenational Confeence on Industial Engineeing, Tehan, Mach 1384. 4. Veville, Jacques & Halingten, Alannah, "A six stage model of the buying pocess fo ERP softwae", Industial Maketing Management 32, pp. 585-594, 2002. 5. Stefanou, CJ, "A famewok fo the ex-ante evaluation of ERP softwae", Euopean Jounal of Infomation Systems 10, pp. 204 215, 2001. 6. Tunc, Ena A. & Bugoon, Ronald L., "ERP Softwae Selection Pocess at a Mid-size Manufactuing Company", Asian Jounal of Infomation Technology 4 (12), pp. 1222-1226, 2005. 7. Yen, J., Langai, R., "Fuzzy Logic Intelligence, Contol, and Infomation", Pentice Hall Publishing Company, 1999. 8. Kacpzyk, J, "Goup decision making with a fuzzy linguistic majoity", Fuzzy Sets, 1986. 9. Asghapou, H and Mahmoud Zadeh, M, "Suvey about the diect and indiect tax evenue eceipts," Jounal of Economic, Ministy of Economic Affais and Finance, 1383. 10. Chu, Mei-Tai & Shyu, Joseph & Tzeng, Gwo-Hshiung & Khosla, Rajiv, "Compaison among thee analytical methods fo knowledge communities goup-decision analysis", Expet Systems with Applications 33, pp. 1011 1024, 2007. 11. Razmi, J, Haleh, H, and Meshkinfam, S., "Designing a new model to suppot decision making fo evaluating and selecting contactos (in Ian)", Jounal of Faculty of Engineeing, Volume 41, Issue 7, pp. 909-897, 1386. 12. Ghazi noui, S and Tabatabaeeian, H, "Sensitivity analysis of multi-citeia poblems of decision making with espect to the methodology used ", Tehan Univesity, Vol 15, No. 36, pp. 38-25, 1385. 13. Ghodsi Pou, H., "data analytic hieachy pocess (AHP) ", Tehan, Amikabi Univesity of Technology, Publishing Cente, 1381. 14. Hwang, ching & sun, Yoon Kwang, "Multiple Attibute Decision Making", Belin, Spinge valag, 1981. 15. Geoge. J., Yuan. K., Yuan. B., Fuzzy sets and Fuzzy logic: theoy and applications, 2003. 16. Hosseini, R., compehensive appoach to entepise esouce planning (ERP), Gostaesh Infomatics publishe, 1382. 380