By Jim Orr, Director, Enterprise Data Strategy, Harte-Hanks Trillium Software
I’ve been traveling a lot lately and have had a number of really interesting and engaging conversations about data governance. And you know what? I’m not convinced that we all are even talking the same language yet. That is to say, organizations continue to have vastly different perspectives on what data governance is, and equally diverse ways on how to approach it. My notion is supported by the types of data governance RFPs that are being written.
Like anything else, it’s always good to carve things up into smaller, manageable pieces (read Jon Asprey’s blog). With this in mind I propose that you think of data governance in terms of 3 distinctly different yet fundamental categories:1) Administrative data governance
2) Technical data governance
3) Business data governance
Administrative data governance focuses on things like direction, prioritization, scope, structure, organizational alignment, business case, and funding. It also includes other administrative issues like policy, procedure, roles and accountability. This parcel of data governance requires executive and business leader support and participation. It also requires a distinct set of business leadership skills to formulate and implement.
Technical data governance relates to activities around technologies and systems that facilitate data management such as data models, metadata management, workflow management, data quality tools, CRM, and BI. As you might expect, this segment of data governance should be IT-led
Business data governance pertains to business centric activities that influence data outcomes such as business process, business rules, data standards, stewardship, reporting, metrics, and other associated activities. All of which should be business led.
Now, am I advocating 3 separate data governance programs? Absolutely not! In fact one is dependent on the other with administrative governance serving as the overarching authority over the entire program. What I am saying is that by dividing these things up, organizations can better clarify their business requirements, develop better strategies and plans to solving their challenges, and ensure that the right skills, people, and groups are involved in the right activities at the right time and for the right reasons.
Does this ring true with you and your experiences? Tell us how you’re dividing and conquering data governance.



