Evaluating Business Intelligence of Enterprise Systems with Fuzzy MultiCriteria Approach Advisor: Dr. Ghazanfari Co- Advisor: Dr. Jafari Internal Committee Member: Dr.Fathian , Dr. Noori External Committee Member: Dr. Taghavi Fard, Dr. Akhavan Abstract: Most organizations still experience a lack of Business Intelligence (BI) in their decision-making processes when implementing enterprise systems, such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM). Consequently, a model and techniques to evaluate and assess the intelligence-level of enterprise systems can improve decision support. This research discusses BI evaluation criteria, fundamental structure and factors used in the evaluation model. Factors and the proposed model can evaluate the intelligence of enterprise systems to achieve enhanced decision support in organizations. The research combines a comprehensive review of the recent literature, survey methodology and statistical methods such as hypothesis testing, factor analysis and regression. The statistical analysis identified six factors of the evaluation model: “Analytical and Intelligent Decision-support”, “Providing Related Experimentation and Integration with Environmental Information”, “Optimization and Recommended Model”, “Reasoning”, “Enhanced Decision-making Tools”, and finally, “Stakeholders’ Satisfaction”.This research also proposes an expert tool to evaluate the BI competencies of enterprise systems Utilizing the extracted loads of each unique criterion, the intelligence of the work systems can be measured and depicted on the six dashboards based on the corresponding factors, actualizing an expert tool that can diagnose the intelligence level of enterprise systems. To evaluate and rank enterprise systems this research proposed a fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of enterprise systems. As applicable approach, multi-criteria decision-making procedure and a multi-objective 0-1 programming model is designed to evaluate and make final decisions about the selection of enterprise systems that also include the requirements of business intelligence in addition to their other goals and requirements. In order to validate the model with a real application, all phases of the approach were applied in the evaluation of the enterprise systems of a company in the case study. Enterprises can use this approach to evaluate, select, and buy software and systems that provide better decision support for their organizational environment, enabling them to achieve competitive advantage.
Keywords: Business Intelligence; Decision Support; Enterprise Systems; Evaluation Model
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