A Systematic Method for Prioritizing Stakeholders in Data Governance Steering Committees: An Organizational Data Ecosystem Approach
Subject Areas : Information and Knowledge Technology
Fahimeh Salimi Kouchi
1
,
abolghasem sarabadani
2
1 - Department of Information Technology Management, Faculty of Management and Economics, Tarbiat Modares University
2 - Department of Information Technology Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
Keywords: Data Governance, Data Governance Steering Committee, Data Ecosystem, Stakeholder Prioritization, Data Ecosystem Stakeholder Prioritization Algorithm (DESPA),
Abstract :
In today’s data-driven economy, data governance is not merely a technical and control requirement but a strategic capability for enhancing efficiency, ensuring compliance, and creating value from data assets. In this context, identifying key stakeholders and determining how they should participate in the data governance steering committee remain important yet insufficiently addressed issues. To address this gap, this study proposes the Data Ecosystem Stakeholder Prioritization Algorithm (DESPA), a systematic, data-driven method for identifying and prioritizing stakeholders within an organization’s data ecosystem. By considering the business importance of datasets, the frequency of data exchanges, and the direction of data flows, DESPA calculates stakeholders’ relative importance and classifies them according to their appropriate mode of participation in the steering committee. The study’s main contribution is to provide a quantitative, transparent, and reproducible basis for translating data-exchange relationships into specific recommendations regarding committee composition and stakeholder roles. The applicability of the method was examined through a realistic scenario involving a hypothetical petrochemical holding company. The results demonstrate that DESPA can distinguish between the number of data relationships and stakeholders’ substantive importance, classifying them into three categories: core, advisory, and regular stakeholders. Accordingly, the proposed method reduces reliance on subjective judgments, supports the determination of appropriate membership arrangements in data governance steering committees, and can serve as a decision-support tool for large, multi-stakeholder organizations.
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