سیستم پشتیبانی تصمیم گیری منطق فازی مبتنی بر AHP برای انتخاب سیستم ERP در صنعت نساجی با استفاده از کارت امتیازی متوازن

An enterprise resource planning system (ERP) is the information backbone of a company that integrates and automates all business operations. It is a critical issue to select the suitable ERP system which meets all the business strategies and the goals of the company. This study presents an approach to select a suitable ERP system for textile industry. Textile companies have some difficulties to implement ERP systems such as variant structure of products, production variety and unqualified human resources. At first, the vision and the strategies of the organization are checked by using balanced scorecard. According to the company’s vision, strategies and KPIs, we can prepare a request for proposal. Then ERP packages that do not meet the requirements of the company are eliminated. After strategic management phase, the proposed methodology gives advice before ERP selection. The criteria were determined and then compared according to their importance. The rest ERP system solutions were selected to evaluate. An external evaluation team consisting of ERP consultants was assigned to select one of these solutions according to the predetermined criteria. In this study, the fuzzy analytic hierarchy process, a fuzzy extension of the multi-criteria decision-making technique AHP, was used to compare these ERP system solutions. The methodology was applied for a textile manufacturing company.

ERP systems are becoming more necessary for almost every firm to improve the competitiveness. According to the success of the implementation of ERP system; companies can obtain a competitive advantage in the global market rapidly. Over the past decade, many ERP projects have resulted in substantial tangible and intangible improvements in a variety of areas for the organizations (Davenport, 2000, Umble et al., 2003 and Yusuf et al., 2004). However, there are a number of examples where organizations were not successful in reaping the potential benefits that motivated them to make large investments in ERP implementations (Davenport, 2000 and Umble et al., 2003). Implementations of ERP systems are one of the most difficult investment projects because of the complexity, high cost and adaptation risks. Companies have spent billions of dollars and used numerous amounts of man-hours for installing elaborate ERP software systems (Yusuf et al., 2004). A successful ERP project involves selecting an ERP software system and co-operative vendor, implementing this system, managing business processes change and examining the practicality of the system (Wei & Wang, 2004). Karsak and Özogul (2009) presented a novel decision framework for ERP software selection, employing quality function deployment, fuzzy linear regression and zero–one goal programming. Teltumbde (2000) proposed a methodology based on the nominal group technique and the AHP for evaluating ERP systems. Chang et al. (2008) proposed a neural network evaluation model for ERP performance from SCM perspective. The survey data was gathered from a transnational textile firm in Taiwan (Table 4). Determining the best ERP software that fits with the organizational necessity and criteria, is the first step of tedious implementation process. Hence, selecting a suitable ERP system is an extremely difficult and critical decision for managers. An unsuitable selection can significantly affect not only the success of the implementation but also performance of the company. However, many companies install their ERP systems hurriedly without fully understanding the implications for their business or the need for compatibility with overall organizational goals and strategies (Hicks & Stecke, 1995). The result of this hasty approach is failed projects or weak systems whose logic conflicts with organizational goals. This paper aims: • to manage the early stages of ERP selection according to the vision and strategies by using balanced scorecard and • to provide an analytical tool to select the most suitable ERP software for textile industry. Kumar, Maheshwari, and Kumar (2003) investigated the key considerations and successful strategies in ERP implementation projects. Byun (2001) explored the use of AHP for deciding on car purchase. Cebeci and Ruan (2007) investigated some quality consultants using fuzzy AHP. Wei, Chien, and Wang (2005) proposed a comprehensive framework for selecting a suitable ERP system based on an AHP-based decision analysis process. The AHP is one of the extensively used multi-criteria decision-making methods. One of the main advantages of this method is the relative ease with which it handles multiple criteria. In addition to this, AHP is easier to understand and it can effectively handle both qualitative and quantitative data. Perry, Sohal, and Rumpf (1999) described quick response supply chain alliances in the Australian textiles, clothing and footwear industry. Calisir, Kulak, and Dogan (2005) explored the influence of various factors on textile companies’ satisfaction with ISO 9000. Chand, Hachey, Hunton, Owhoso, and Vasudevan (2005) provided a balanced scorecard (BSC)-based framework for valuing the strategic contributions of an ERP system. This paper illustrates that an ERP system does indeed impacts the business objectives of the firm. Eilat, Golany, and Shtub (2008) presented a multi-criteria approach for evaluating R&D projects by using the balanced scorecard and data envelopment analysis (DEA). The organization of this paper is as follows. First textile and clothing industry and the case of Turkey are analyzed. Then the balanced scorecard method is explained and the proposed methodology is introduced. Fuzzy sets and fuzzy numbers are introduced because our comparison method, fuzzy AHP, includes fuzzy numbers and their fuzzy algebraic operations. Then, a comparison among ERP vendors is made by using fuzzy AHP for a textile firm as a real life case study.

ERP systems have a vital role in today’s organizations to realize their vision and strategies. However, they have also high costs and high implementation risks. This study presents an approach to select a suitable ERP system for textile industry. At first, the vision, the strategies and key performance indicators of the organization are checked by using balanced scorecard method. After strategic management phase, the proposed methodology gives advice before ERP selection. According to the company’s vision, strategies and KPIs, we can prepare a request for proposal. There is no study focusing request for proposals in the literature to select ERP systems. This study focuses RFPs by using balanced scorecard concept. Then ERP packages that do not meet the requirements of the company are eliminated. The criteria were determined and then compared according to their importance. The rest ERP system solutions were selected to evaluate. An external evaluation team was assigned to select one of these solutions according to the predetermined criteria. The proposed ERP selection methodology was applied successfully for a textile manufacturing company for young people as a real case study. The methodology also gives some suggestions about successful ERP implementation. The proposed methodology can be used for other sectors with some changes. Decisions are made today in increasingly complex environments. In more and more cases the use of experts in various fields is necessary, different value 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 difficulty. In general, many concepts, tool and techniques of artificial intelligence, in particular in the field of knowledge representation and reasoning, can be used to improve human consistency and implement ability of numerous models and tools in broadly perceived decision-making and operations research. The proposed decision support system integrated with strategic management by using BSC may be an alternative to some methods for ERP selection. In this paper, ERP packages and vendors for textile companies were compared using fuzzy AHP. The presented methodology is flexible and can be used for other sectors with some sector specific characteristics changes. Humans are often uncertain in assigning the evaluation scores in crisp AHP. Fuzzy AHP can capture this difficulty. However, Fuzzy AHP cannot support all phases of ERP selection and implementation. Hence, an intelligent decision support system or expert system can be added when gathering data for selection process. Also, the expert system can be used before and after the ERP system selected. The lessons from this textile firm case or other applications can be added into the knowledgebase of the expert system. The expert system can also help to prepare a more detailed request for proposal for a textile firm, because this stage needs experience about the selection process.