A Performance Assessment Model for Business Intelligence by using Fuzzy Analysis
Subject Areas : Knowledge Management
MohammadHosein
Ronaghi
1
Kamran
Feyzi
2
(Allameh Tabataba’I University)
Keywords: Business Intelligence, Performance Assessment, Fuzzy AHP, Nominal Group Technique, Process Management,
Abstract :
Business intelligence (BI) is the tool used by enterprises to collect, manage and analyze structural and non-structural data and also information by taking advantage of modern information technology. It utilizes a substantial amount of collected data during the daily operational processes, and transforms the data into information and knowledge to avoid the supposition and ignorance of the enterprises. In the last decade, Business intelligence has evolved as one of the critical applications in organizations to provide useful insight, support decision-making, and drive organizational performance. However, to avoid the ineffective experiences during the deployment, it is important to clarify the impact factors of a BI system and find out a Suitable assessment method to evaluate the performance of BI systems. Evaluating the effectiveness of business intelligence systems is vital to our understanding of the value and efficacy of management actions and investments. This research is a descriptive survey. We construct an Assessment model to assess the performance of business intelligence systems based on the outcomes of previous researches. Furthermore, an expert questionnaire using fuzzy analytic hierarchy process (AHP) was used to filter out useful performance indicators. The analytic hierarchy process is a structured technique for organizing and analyzing complex decisions. Finally, we analyze a real case by using the constructed assessment model for Business Intelligence systems. We choose an automotive parts manufacturer as a case. The survey sample population consisted of 66 randomly taken employees and managers of the case. The results indicate that the performance of Business Intelligence system in our case was suitable.