A Systematic Method for Prioritizing Stakeholders in Data Governance Steering Committees: An Organizational Data Ecosystem Approach
Fahimeh Salimi Kouchi
1
(
Department of Information Technology Management, Faculty of Management and Economics, Tarbiat Modares University
)
abolghasem sarabadani
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 no longer merely a technical or compliance requirement; it represents a strategic organizational capability that enhances operational efficiency, ensures regulatory compliance, and fosters sustainable competitive advantage. Effective data governance frameworks rely on three pillars: people, processes, and technologies. Among these, the people dimension—particularly the design of decision-making structures and organizational mechanisms—plays a decisive role in the success of governance initiatives. In complex data-intensive organizations, such as ministries and large holding entities, much of the data value emerges through inter-organizational interactions and external stakeholders, including data providers, business partners, strategic customers, and governmental bodies. Excluding these stakeholders from governance design, especially in determining the composition of the data governance steering committee, can disrupt the data value chain and reduce governance effectiveness. To address this gap, this study proposes a systematic, transparent, and data-driven algorithm, the Data Ecosystem Stakeholder Prioritization Algorithm (DESPA), for identifying and prioritizing key stakeholders in the steering committee. The algorithm models the organizational data ecosystem as a directed graph of stakeholders and data exchanges, with edges weighted by the strategic importance of datasets and the frequency of exchanges over a defined period. By integrating network analysis, direction-sensitive weighting with emphasis on inbound data flows, and quantitative thresholding, DESPA provides a well-justified, repeatable, and defensible method for determining the steering committee composition.
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