Organizational Considerations For Data Governance

While the People facet of our Data Governance Framework focuses on skills and responsibilities, the Organizational Alignment facet focuses on the working relationships between dependent roles.  Many organizations begin their data governance journey putting decision-making responsibility, resourcing and stewardship within existing organizational structures – and early business value and momentum can certainly be delivered this way.  But to truly scale data governance as a holistic, cross-enterprise effort benefiting multiple parts of the business, the current state of your organizational structure will have to adapt.

Data Governance 

In looking to define an optimal organizational structure to support your data governance goals, questions that should be addressed include:

  • Who will be the executive sponsor?  As discussed in my “…By The People, For The People” post, the optimal executive sponsor will be very senior CxO-level executive(s) whose responsibilities span functional, line of business, application and geographic silos.
  • Will there be an executive steering committee? For any organization larger than a few thousand employees or $1 billion in revenue, it’s very common – and a best practice – to form an executive steering committee or council to help support and drive the cross-functional decision-making, prioritization, resourcing and change management.  The steering committee will of course include the executive sponsor(s), dependent business and IT leadership, as well as the data governance program manager who will help to define the actionable agenda items for this forum – often held monthly, bi-monthly or quarterly.
  • Who are the business data owners? Every line of business, functional group and geographic area has different priorities for which business processes, decisions and interactions are more critical to supporting their key performance indicators (KPIs), and the business leaders goaled on delivering those KPIs must accept accountability for their role in ensuring the supporting data can meet their needs.
  • What are the escalation paths for policy and data conflicts?  Who are the stakeholders involved in mitigating an exception to your data quality or security policies, rules and standards?   For example, if you define a policy for customer data capture that requires a full name, address and phone number or email for a customer contact, what happens when you acquire a company and try to integrate its customer database that’s missing a significant amount of this information? Who decides what to do? What’s the process?
  • Are the data steward’s full-time or part-time roles?  Finding the right data steward is a challenge facing most organizations.  The best data stewards are your top subject matter experts across business and IT, but if they’ve achieved such a great reputation there is likely significant demand for their time and their bandwidth is stretched thin.  So do you beg for a small percentage of their time to be a part-time steward, or do you recruit full-time stewards with less expertise that can dedicate more time and ramp their knowledge?  There is no right answer here, but a combination of these approaches might be a good strategy to consider.
  • Do the stewards hold solid- or dotted-line reporting relationships to the executive sponsors? It’s unlikely the data steward is going to report directly to your executive sponsor, but will they even fall within the same organization?  Unless you plan to centralize your data stewardship activities, it’s likely that many of your subject matter expert contributors will remain reporting to the existing line of business, business function or area within the organization where they hold their expertise and will hold a dotted-line/virtual employee relationship to the executive sponsor and/or data governance driver.

I highly recommend that data governance drivers leverage a responsibility assignment matrix like RACI or DACI to help align and set expectations with the various stakeholders involved in all aspects of the data governance effort.  (RACI defines roles of Responsible, Accountable, Consulted, and Informed. DACI offers a similar framework and defines roles of Driver, Approver, Contributors, and Informed).