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IAIDQ Publications

A Comprehensive Approach to Data Quality Governance
June 2006
Thomas Redman

While most organizations will enthusiastically agree that data are key assets, they also acknowledge that
these assets are in poor shape. Too often the data needed for critical decisions and operations are
unavailable, poorly defined, out-of-date, incorrect, or otherwise unfit for use.

Further, traditional hierarchical organizational structures are ill-suited to managing data. Therefore in this
paper we propose a comprehensive approach to data quality governance. Our model features six
mutually-reinforcing components:

  • A Data Council for senior leadership,
  • A Data Quality Staff for managing meta-data processes and conducting certain staff functions,
  • Information Chain Management for data created inside the organization,
  • Data Supplier Management for data received from outside the organization,
  • Specific roles for the Information Technology department, and
  • Continuous improvement through chartered improvement teams.

Each component has proven its mettle in leading-edge organizations. Further, we believe that (in some
industries at least) the time is ripe for creation of a “Chief Data Officer” position. This person will head
the Data Quality Staff and drive implementation of other elements of governance.

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