Data Governance: Current State, Objectives, and Challenges

Report Summary

Data Governance: Current State, Objectives, and Challenges

Eric Weisburg
Senior Principal

October 2019 - Data governance is emerging as a critical success factor for insurance organizations. Carriers rely on complete, accurate, and secure data to assess risks, predict losses, and understand their customers better. Increasing regulation and security concerns also dictate that carriers know where they store their sensitive information and that they secure access to comply with the regulatory environment.

This brief presents insights from a study of 61 carriers with various types of data organizations that Novarica conducted with the Insurance Data Management Association (IDMA).


  • Data Governance Objectives. Objectives vary across different types of data organizations.
  • Data Sources. Most carriers rely on internal data while fewer look to external sources.
  • Measuring Success. Some carriers rely on measurements to gauge success, while others do not track metrics at all.

Key Points and Findings

  • Carriers prioritize structured internal policy and claims data for governance. Other internal data sources receive less governance, as do big data and third-party data.
  • Weak executive sponsorship is the biggest challenge to data governance. Drivers of the data governance practice need executive support to operationalize governance effectively.
  • The majority of data organizations do not formally measure ROI. Measurements of success in data governance are immature across the board.

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