Enterprise resource planning (ERP) systems have gained major prominence by enabling companies to streamline their operations, leverage and integrate business data process. In order to implement an ERP project successfully, it is necessary to select an ERP system which can be aligned with the needs of the company. Thus, a robust decision making approach for ERP software selection requires both company needs and characteristics of the ERP system and their interactions to be taken into account. This paper develops a novel decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zero–one goal programming. The proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but also the interactions between ERP system characteristics through adopting the QFD principles. The presented methodology appears as a sound investment decision making tool for ERP systems as well as other information systems. The potential use of the proposed decision framework is illustrated through an application.
The unprecedented growth of information and communication technologies has influenced all facets of computing applications across organizations. At the same time, the business environment is becoming increasingly complex with functional units requiring more and more inter-functional data flow for decision making, timely and efficient procurement of product parts, management of inventory, accounting, human resources, and distribution of goods and services. To deal with these challenges, new software systems known in the industry as enterprise resource planning (ERP) systems have surfaced in the market targeting mainly large complex business organizations.
ERP comprises of a commercial software package that promises the seamless integration of all the information flowing through the company – financial, accounting, human resources, supply chain and customer information (Davenport, 1998). ERP systems are configurable information systems packages that integrate information and information-based processes within and across functional areas in an organization (Kumar & Van Hillsgersberg, 2000).
ERP software market has been and continues to be one of the fastest growing segments of the information technology (IT) industry. In recent years, globalization and competitive business environment compel companies to invest considerable resources in the implementation of ERP systems. Organizations choose and deploy ERP systems for many tangible and intangible benefits and strategic reasons (Kremzar & Wallace, 2001). Although implementing an ERP system may be costly and time-consuming, its benefits are worthwhile. However, there are a number of examples where organizations have not been successful in reaping the potential benefits that motivated them to make large investments in ERP implementations (Davenport, 1998).
Motwani, Mirchandani, Madan, and Gunasekaran (2002) emphasized that ERP adoption involves initiating appropriate business process changes as well as information technology changes to significantly enhance performance, quality, costs, flexibility, and responsiveness. There is a growing consensus among ERP system implementers that selecting an inappropriate system is a major reason for ERP implementation failure. Due to the complexity of the business environment and the diversity of ERP alternatives, ERP system selection is a tedious and lengthy task. Given the considerable financial investment and potential risks and benefits, the importance of selecting a suitable ERP system cannot be overemphasized since it is a decision on how to shape the organizational business (Teltumbde, 2000).
A suitable ERP system can radically improve the future competitiveness and the market performance of a firm. The complexity of ERP systems and the diversity of alternatives render this critical selection process complicated. This paper presents a novel decision framework for ERP software selection, employing QFD, fuzzy linear regression and ZOGP. The developed framework integrates ERP characteristics obtained from vendors in the market and the list of customer requirements by taking into account the company profile and strategic selection criteria. Essentially, using QFD provides the means for incorporating not only the relationships between user demands and software characteristics but also the relationships between software characteristics disregarding the unrealistic preferential independence assumption frequently encountered in earlier IS selection studies using MCDM techniques. The target values for ERP characteristics and the maximum achievable values for customer requirements (i.e., company needs) are obtained using fuzzy linear regression which can incorporate both the fuzziness inherent in the relationships between customer requirements and ERP characteristics, and the dependencies among ERP characteristics represented using expert judgment into the decision making process without requiring the rigid assumptions of statistical regression. Finally, the ZOGP model is employed to determine the ERP system alternative that minimizes the weighted sum of deviations from the maximum achievable values for company needs.
In brief, considering its capacity to account for both user demands and ERP system characteristics, the relationships between them, and interdependencies among ERP system characteristics, the proposed integrated decision framework appears as a robust alternative to methods presented in earlier studies addressing ERP system selection. It is also worth noting that the decision making approach presented herein is not restricted to ERP system selection. Future research will focus on real-world applications of the proposed framework for executive information or business information system selection.
