All companies struggle with how to respond to recommendations that come out of Data Governance-led issue analysis efforts.
This type of funding is more problematic than the questions of how to fund the development of a program, ongoing governance, and ongoing Stewardship / Quality efforts. It’s tougher because it’s harder to predict. How much time/money/attention should we set aside to correct problems that we haven’t yet analyzed to determine their scope – much less the level of effort to address them?
How can we make accurate budgeting estimates when “we don’t know what we don’t know?”
Clearly, we can’t. And so, organizations usually take a different approach. They create “buckets” of time/money/attention that they can use to solve issues uncovered during governance-led issue analysis.
Still, this is not easy for anyone. Regardless of the focus of the Data Governance program and the frequency of issue analysis efforts, all organizations must answer the same types of questions:
- Once solutions are identified, how should they be prioritized, and by which part of the organization?
- While prioritizing them, how should they be ranked against other proposed efforts?
- How much should it matter that they were not identified early, during budgeting sessions?
- Now that they have been identified, how should they be paid for, and by whom?
In short, Data Governance-facilitated issue analysis forces organizations to answer a tough question: How do you budget for the unexpected?
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