The Application of Fuzzy-Neuro Approach for ERP System Selection: Case Study on an Agro-industrial Enterprise

Abstract

Enterprise Resource Planning (ERP) adoption emphasizes business transformation that leads to change business processes in an effort to maximize profits and competitive advantage of the enterprise. Many companies were unsuccessful in implementing ERP system. Selection failure affected implementation failure. ERP system selection that misfit and ineffectively caused a major failure of ERP system adoption which is a critical investment, risky and expensive. ERP selection is a complex decision-making process and must be conducted carefully because of the important impacts. Many researchers have studied related to the approach used, but still little was associated with complex and standardized criteria. Most studies were to simplify the complex criteria, which often will eliminate the meaning of the standardized criteria. This study discusses the hybrid approach of Fuzzy - Neural Network (Fuzzy-Neuro) for the ERP selection with numerous and complex criteria. The criterions used were the characteristics and subcharacteristics that compatible with ISO25010, vendors and consultants, fit strategy, change management and cost. A case study was simulated in the agro industrial company that has some special characteristics. The results confirm the Fuzzy-Neuro approach can be used optimally even for ERP selection with many, complex and tiered standardized criteria.