8 Data Governance Design Principles
Before you get deep into the specifics of master data management (MDM), it’s important to have an overarching approach to data governance. Among the logical steps: These eight data governance design principles, shared by Angie Pribor of First San Francisco Partners during our MDM & Data Governance Summit in San Francisco last week.
1. Be Clear on Purpose
Build governance to guide and oversee your strategic direction and enterprise mission.
2. Use Enterprise Thinking
Provide consistency and coordination for cross-functional initiatives. Maintain an enterprise perspective on data.
3. Be Flexible
If you make data governance too difficult then people will circumvent it. If you make it customizable (within guidelines), and people will get a sense of ownership.
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4. Simplicity and Usability Are the Keys to Acceptance
Adopt a simple governance model people can use. A complicated and inefficient governance structure will result in the business circumventing the structure.
5. Be Deliberate On Participation and Process
Select Sponsors and Participants. Do not apply data governance bureaucracy solely to build consensus or to satisfy monetary political interest.
6. Align Enterprise-Wide Goals
Maintain alignment with enterprise-level needs and local business needs. Prioritize and align your initiatives to overall enterprise goals along the way.
7. Establish Policies with Proper Mandate and Ensure Compliance
Clearly define and publicize policies, processes and standards. Ensure compliance through tracking and auditing.
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8. Communicate, Communicate, Communicate
Frequent, directed communication will provide a mechanism for gauging when to “course correct,” managed stakeholders and effectiveness of the programs.
Thanks and More
Special thanks, again, to Angie Pribor of First San Francisco Partners for the list. For more slideshows visit here.