Prioritization of Data Governance Frameworks Using a Fuzzy MCDM Approach: A Case Study

Data is one of the most valuable assets of any organization and plays a key role in decision-making and performance improvement. As organizational data grows, the need for effective data governance to maximize value becomes increasingly important. Selecting an appropriate framework for implementing data governance requires careful attention to the criteria and priorities of each organization. Qualitative and intuitive approaches often do not yield desirable outcomes due to the diversity of organizations' needs. Consequently, adopting a quantitative approach to select the optimal framework based on various criteria becomes essential. This paper aims to present a quantitative approach based on fuzzy multi-criteria decision-making (FMCDM) to address this issue. We used the fuzzy analytical hierarchy process (FAHP) method to prioritize data governance frameworks for optimal implementation at Saman Bank. Four reputable frameworks-DGI, DAMA-DMBOK, COBIT, and Eckerson-were evaluated based on three key bank criteria including coverage, cost, and security. The results indicate that the DAMA-DMBOK framework, with a weight of 0.418, is the most suitable choice for implementation at Saman Bank.