From Strategy to Execution Bridging the Gap between Data Strategy and Data Governance

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Examensarbete för masterexamen
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Almost a decade ago, the term ‘big data’ emerged to describe a new and advanced stage of digitalization. Fast forward nearly ten years, and it is widely acknowledged that companies should seek to utilize data as a key mechanism for creating competitive advantage. Doing so is, however, easier said than done. Practical knowledge of data management remains limited, even as organizations generate, acquire, and process unprecedented amounts of data. While companies skilled at managing data outperform competitors by wider and wider margins, the legal landscape relating to data is growing increasingly complex by the minute. This makes data strategy, governance, and management vital for companies across all sectors - whether traditional industry giants or cutting-edge digital platforms. Through a comparative multiple case study, this thesis explores how the gap between data strategy and data governance can be bridged, ultimately facilitating the execution of a firm’s data strategy. The thesis examines three cases to uncover the governance mechanisms firms employ to manage their data assets, the varying levels of strategic maturity companies exhibit concerning their data assets, and how data governance supports the implementation of data strategies. The cases represent different levels based on identified strategic maturity, enabling a comparison of practices. Additionally, by adopting an interdisciplinary approach, the thesis explores how regulatory requirements can be integrated into strategy and governance structures to ensure compliant data management while facilitating data-driven digital innovation. The findings show that strategic data maturity can be categorized into four distinct levels underpinned by the foundational process of data classification. Reviewing each individual level from a governance perspective has shown key characteristics of the individual levels. From this, specific governance mechanisms crucial for implementing each level of strategic maturity emerged. The study also demonstrates that perceptions of regulation vary across the different strategic maturity levels. This highlights that strategically mature firms possess the expertise to incorporate com pliance into their strategy and governance structures, allowing them to maintain both compliance and innovation in managing their data assets.

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data assets, data governance, data strategy, big data, data management, compliance, artificial intelligence, digital innovation

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