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These two sets of activities – “little g governance” on the one hand, “Big G Governance” on the other – require very different skill sets, organizational knowledge and levels of authority. That’s because data governance roles and responsibilities are also very different: The people involved in "Big G" efforts set governance policies and translate them into objectives and rules of engagement for "little g" teams to follow as they build, manage and monitor individual data controls.
"Big G" participants must have excellent analytical and communication skills. They must have the organizational power to negotiate on behalf of the departments or business units they represent. They must have the respect, support and trust of their constituents – the users in those operations.
Not all contributors to a "Big G" initiative need to be data experts, but they do have to be able to understand the root causes of data errors and issues. They also need to know – or be able to learn – basic concepts about how data flows through systems and business processes. And they must be able to express the data governance needs, requirements, priorities and constraints of their stakeholder units.
If decisions or recommendations made by a data governance council or other type of “Big G” group will have a significant impact on operations within an organization, the data governance program also requires resources who can work with affected business managers to explain governance policies and their rationale, set expectations for compliance, detail the process for escalating and resolving issues, and monitor the status of data controls based on the policies.
Different options on key data governance roles and responsibilities
Sometimes those activities are performed by the members of a data governance council, data roundtable or data stewardship committee. In other cases, the outreach duties will be a function of a formal data governance office staffed by workers responsible for implementing an aligned approach to governance logistics, administration and communications.
Often, however, other groups that can be leveraged for such "soft skills" work already exist. For example, perhaps an organizational change management group can help with the internal changes that come with a data governance program. In addition, many CIOs have created a communications arm within IT that can be invoked to support the data governance office.
The work that goes into "little g governance" tends to be more routine, and more hands-on. It depends on specific skills for designing, analyzing, maintaining and monitoring the data controls that have been inserted into systems, applications, data stores and data flows. Those duties might be labeled data stewardship instead of data governance; either way, they involve executing everyday activities in a way that enforces data-related policies.
But what happens when data governance issues bubble up through the layers of operations? Who documents, addresses or escalates them? In some organizations, that is a function of the management structure: Issues and concerns flow up the corporate hierarchy until they reach the appropriate level to be addressed or are handed off to a data governance council or equivalent group.
However, other companies find that approach to be ineffective or inefficient. Instead, they create layers of data stewards – workers who have other jobs but also defined data stewardship responsibilities. Typically, they’re organized into groups, teams or hierarchies focused on specific information issues. The rationale for this approach is that the potential for bureaucratic overhead is far outweighed by the advantages of focused attention, clear paths of communication and the deepening knowledge of participants.
Such data stewardship hierarchies can include high-level roles with titles such as "lead steward" or "enterprise steward." The people filling those roles might also serve on data governance councils or other "Big G" groups, effectively tying together all of the various strands of data governance and data stewardship. But those are complex models that you might not want to implement.
Setting data governance roles and responsibilities: question and answer time
So, what kind of resources will you need for your data governance program? And what skills and knowledge will they need to make the program successful? The answers, of course, depend on the data governance model you adopt and the type of data governance framework you implement.
The decision about which model is right for you depends on what your organization wants to achieve through data governance and how much it's willing to put into reaching those objectives. Indeed, that question needs to be asked before a data governance program is designed or staffed, and every time a new governance project, task or challenge is taken on.
The ability to ask the question, get an answer from senior management and validate it with business stakeholders is probably the most important skill that a data governance manager can have. Next is the ability to recognize political danger in the answers (or non-answers) you receive. The ability to learn how to respond to such dangers is also critical to the long-term survival of a data governance program
As a result, choosing the right data governance manager or managers is potentially the most important decision that can be made when a governance program is being designed. The temptation is to pick someone who is deeply knowledgeable about information management practices and can work well with the organization's operational layer.
However, "Big G Governance" programs require leaders who can manage out and up as well as down. Your data governance management team must be skilled in activities such as securing access to required resources and bringing participants to the point where organizational alignment on data governance policies and procedures is possible. They must be trusted diplomats with the confidence, communication skills and organizational power to do what needs to be done to make your data governance program a success.
About the author: Gwen Thomas is the president and founder of the Data Governance Institute, which offers consulting and training services in the areas of data governance and data stewardship as well as a variety of information resources on those topics. As a consultant, Thomas has helped companies such as American Express, Sallie Mae, Wachovia Bank and Disney to build or upgrade their data governance and stewardship programs. She also is a frequent speaker at industry events, a regular contributor to IT and business publications, and the author of the book Alpha Males and Data Disasters: The Case for Data Governance.