Paper Number
2436
Paper Type
Complete Research Paper
Abstract
Data governance is a prerequisite for organizations wanting to harness the strategic potential of data. Although the conceptual foundations of data governance have reached a sound level of clarity, research still does not explain how data governance unfolds in large and complex organizations. To address this gap, we introduce the Viable System Model as theoretical lens and examine data governance at five multinational companies with varied organizational structures. We find that data governance orchestrates data practices on multiple, interconnected levels, through sub-systems. The interplay between these sub-systems facilitates the establishment of a dynamic balance, enabling (1) the delineation of responsibilities, distinguishing between global and local data governance that orchestrates data practices, and (2) the implementation of data practices at the operational level that simultaneously emphasize control and foster innovation. Our research contributes to rethinking data governance and addresses previous calls for research that accounts for its dynamic nature in practice.
Recommended Citation
Lefebvre, Hippolyte and Legner, Christine, "Rethinking Data Governance: A Viable System Model" (2024). ECIS 2024 Proceedings. 11.
https://aisel.aisnet.org/ecis2024/track07_busanalytics/track07_busanalytics/11
Rethinking Data Governance: A Viable System Model
Data governance is a prerequisite for organizations wanting to harness the strategic potential of data. Although the conceptual foundations of data governance have reached a sound level of clarity, research still does not explain how data governance unfolds in large and complex organizations. To address this gap, we introduce the Viable System Model as theoretical lens and examine data governance at five multinational companies with varied organizational structures. We find that data governance orchestrates data practices on multiple, interconnected levels, through sub-systems. The interplay between these sub-systems facilitates the establishment of a dynamic balance, enabling (1) the delineation of responsibilities, distinguishing between global and local data governance that orchestrates data practices, and (2) the implementation of data practices at the operational level that simultaneously emphasize control and foster innovation. Our research contributes to rethinking data governance and addresses previous calls for research that accounts for its dynamic nature in practice.
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