The rapid increase in data generated by humans and machines has made companies aware of data’s strategic potential. With this changing role of data, enterprises have to effectively implement a set of data governance mechanisms to meet strategic goals and increase organizational performance. However, existing research on data governance tends to emphasize operational aspects and is less applicable to the strategic roles that data plays today. Based on a multiple case study involving companies with substantial data governance experience, we identify three data governance archetypes: (1) Improve master data quality, (2) Enable enterprise-wide data management, and (3) Coordinate the network to enable data monetization. Our findings advance the field of IT governance in general and contribute to data governance research by detailing structural, procedural, and relational governance mechanisms for different strategic contexts. For practitioners, our research provides insights into the priorities of data governance initiatives and outlines pathways to manage data as a strategic asset.
Fadler, Martin; Lefebvre, Hippolyte; and Legner, Christine, "Data governance: from master data quality to data monetization" (2021). ECIS 2021 Research Papers. 155.
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