Disruption caused by Data Governance?

Instituting Data Governance is a major initiative providing a significant opportunity to leverage enterprise data assets more effectively. As such, there is sometimes concern about being seen as a roadblock or concerns about formulating new enterprise level organizations, such as a Data Governance board and Data Stewardship committees. To be sure, a proper balance between enforcing standards and retaining agility will be needed, and of course Data Governance organizations should not be assembled without careful thought in a phased approach. However, Data Governance is all about making strategic decisions about enterprise data assets – and of course people have to meet to discuss and make these decisions. Not just anyone should be making these decisions and so Data Governance organizations need to be formed.

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Forming Data Governance organizations should take place only after an assessment, strategy, and roadmap project. Part of this project should be identifying roles and executive stewards for these roles, after significant collaboration with the Executive Sponsor. The first organization to be formed should be the Data Governance Board, as other organizations need to be formed under the direction of the Data Governance Board. Enterprise standards should be enforced after careful deliberation, approval, and promotion by Data Governance.

Some take a more surreptitious approach to data governance, by trying to apply heroic effort to applying best practices such as developing an enterprise data model, setting up a metadata repository, of undertaking data quality initiatives. While these are worthwhile objectives, unless there are supporting Data Governance organizations to endorse, promote, and oversee these initiatives, these efforts tend to be difficult to sustain (due to lack of resources) and cause frustration and burnout. More importantly, there may not be enterprise alignment. For example, an Enterprise Conceptual Data Model not reviewed with and approved by the business, may just be the perspective of the data modeler.

Data Governance should be a disruptive agent for (good) change, and needs to be implemented after careful deliberation and executive sponsorship. Forming Data Governance organizations needs to take place in a phased approach.