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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.
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1. Be Clear on Purpose
Build governance to guide and oversee your strategic direction and enterprise mission.
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2. Use Enterprise Thinking
Provide consistency and coordination for cross-functional initiatives. Maintain an enterprise perspective on data.
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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.
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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.
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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.
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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.
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Thanks and More
Special thanks, again, to Angie Pribor of First San Francisco Partners for the list. For more slideshows visit here.