Document Type : Original Article

Authors

• Babak Sohrabi ¹
• Iman Raeisi Vanani ²
• Mahdi Kiaei ³

¹ Professor of Information Technology Management, Faculty of Management, University of Tehran .

² Assistant Professor of Industrial Management, Allameh Tabataba’i University, Tehran, Iran.

³ Master of Information Technology Management, Faculty of Management, University of Tehran.

Abstract

One key factor in the formation of organizational ERP systems is the requirement of integration at the organization's internal and external levels to survive in competitive markets. These systems have gained a lot of popularity not only by increasing the pace and accuracy of registering the organizational information but also by providing a quick reporting infrastructure. Registration, storing, and recovery of integrated and reliable information throughout the organization is another feature that has affected the penetration of ERP systems in organizations. However, the argument about the high cost of purchasing and implementing such systems between financial and IT departments have always been a challenge in the way of ERP expansion; Therefore, in such a case, it seems necessary to provide evidence of the efficiency or inefficiency of them in the form of an analytical model with a predictive approach and through quantitative indicators to resolve these contradictions. It should be considered that if a clear vision, accurate and quantitative information based on the performance indicators of the organization is given to the decision-makers, the disagreement in such issues will be meaningless. Now, the question is that what tool can provide such valuable information? Predictive models depict the probable future, given the current terms and variables, so that they can solve the issue around using the ERP systems. The present study has extracted the raw, reliable, and not manipulated quantitative data from the ERP system's database and has designed a quantitative predictive analytic model by them to provide clear and accurate answers to existing questions based on quantitative performance indicators. An approach that has not been seen before.

Keywords

• Enterprise Resource Planning System
• Data mining
• Neural Network
• Organizational Performance Indicators
• Predictive Analytics
• Quantitative Indicators