Data governance is emerging as a top-of-mind concern as carriers seek gains in areas like digital process automation, analytics, and business intelligence. Emerging data privacy regulations also require carriers to be knowledgeable about their data and ensure regulatory compliance without hindering innovation initiatives.
Despite its broad value, data governance can be the most onerous aspect of a data and analytics effort. Value and results are not immediately visible making it difficult to gain organizational support and incentivize teams to contribute. Data can also be highly political: it is a shared resource, and ownership is often disputed. Ineffective leadership and a lack of commitment by team members may also compound challenges in data governance.
Successful data governance programs bring together roles and responsibilities and enable an organization to better understand its data, control access to its data, and ensure that the data is fit for purpose. They require establishing data ownership and developing a metadata repository for consistent data definitions. Overall monitoring of data governance program also makes sure that teams across the enterprise contribute to maintaining data quality.
Data governance is not a “once-and-done” initiative: it tends to involve significant changes, sustained effort, and opaque return on investment. Yet it is also paramount in enabling efficient use of data to understand performance, generate insights, and maintain regulatory compliance.
More information on best practices and navigating organizational challenges in data governance is available in Novarica’s recent report, Data Governance in Insurance: Overview and Best Practices.
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