Creating the Vision for Data Governance – “Do You See What I See?”

By Anne Smith

At the highest level, data governance is concerned with the management of data – its availability, currency, usefulness, accuracy and relationships with other enterprise data. Governance of data is not an IT function, although many technical products and tools are used to administer governance. Data governance is a business responsibility, shared with IT but “owned” by the business entity and instituted across the enterprise. Like any other enterprise effort, successful data governance involves people, processes, tools, standards and activities that are managed at both strategic and operational levels. And, like any other successful enterprise initiative, data governance starts with a vision, which is communicated and sustained by the enterprise.

Webster defines “vision” as:a thought, concept, or object formed by the imagination; unusual discernment or foresight; the act or power of seeing. With this definition as a basis, we can say that a “vision” for data governance would include the articulation of what the organization thinks that concept should entail for them, what they “see” as the state to be achieved by the act of governing data. To achieve that end-state, it is imperative that the organization communicates a compelling vision for change, setting achievable targets and contributes sufficient enterprise resources to develop the vision / concept. To be successful, this vision must be commonly understood and supported by the senior management and business sponsors of the data governance initiatives.

Many organizations launch data governance efforts as part of a business-unit or division-level project, and do not acknowledge the need for an enterprise approach to managing the common asset, data. This project-oriented approach to overarching programs such as governance can cause the development of multiple initiatives, each with its own set of missions, standards, procedures, policies and activities, creating a “Tower of Babel” and not a unified view of data governance. When the organization finally recognizes the need for an enterprise view of data and the need for enterprise governance, all of these disparate governance efforts must be dismantled and replaced – causing confusion and conflict within the affected areas.

The first step in every successful governance effort is the establishment of a common vision and mission for data and its governance across the enterprise. The vision articulates the state the organization wishes to achieve with data, and how governance will foster reaching that state. Through the skills of a specialist in governance and using the techniques of facilitation, the senior business team develops the enterprise’s vision for data and its governance. All of the subsequent activities of any data governance effort should be formed by this vision.

Visioning offers the widest possible participation for developing a long-range plan, especially in enterprise-oriented areas such as governance. It is democratic in its search for disparate opinions from all stakeholders and directly involves a cross-section of constituents from the enterprise. Developing a vision helps avoid piecemeal and reactionary approaches to addressing problems. It accounts for the relationship between issues, and how one problem’s solution may generate other problems or have an impact on another area of the enterprise, and develops a holistic approach to setting goals that will enable the organization to realize the vision.

Creating a vision is a specific step in the planning process, and should not be overlooked or shortened. Scheduling the visioning step should incorporate sufficient time for framing issues, eliciting comments through surveys or meetings, recording statements from participants, and integrating them into draft and final documents. Preparation for visioning is crucial and touches on many complex issues. Advance work is essential to give time for staff to prepare the governance vision meeting purpose and agendas, questionnaires, and methods of presentation and follow-up. The visioning program should be carefully scheduled to maximize senior management input and response time and sufficient time for revisions to draft vision statements.

To ensure that all data governance efforts are shaped by the organization’s vision, communication of this vision is essential. Every person responsible for creating, managing or using any data must understand and support the governance vision. Data governance activities should be part of all projects, and measurement of a project’s success should include how well the project achieved the organization’s governance vision as well as whether the project’s timelines were met. Periodic refinement of the vision is an important step, so that the enterprise continues to follow the best governance path as conditions change and new situations develop.

In the final analysis, the best governance programs are those that begin with a clear and achievable vision for data governance, one that is uniformly communicated to the organization, refined as necessary and incorporated in the enterprise’s governance approach.

About the Author

Anne Marie Smith is a leading consultant in Information Management and is a frequent contributor to various IS publications. Anne Marie has over 20 years experience in information management for several corporate entities and has successfully led the development of data resource management departments within corporations and consulting organizations. Anne Marie is active in the local chapter of DAMA and serves on the board of directors of DAMA International, and is an advisor to the DM Forum. She has been an instructor of Management Information Systems (MIS) with Philadelphia, PA area colleges and universities. Anne Marie has taught topics such as: data stewardship and governance, data warehousing, business requirements gathering and analysis, metadata management and metadata strategy, information systems and data warehouse project management. Anne Marie’s areas of consulting expertise include metadata management including data stewardship and governance, information systems planning, systems analysis and design, project management, data warehouse systems assessment and development, information systems process improvement and information resource management/data resource management. Anne Marie holds the degrees Bachelor of Arts and a Master's of Business Administration in Management Information Systems from La Salle University; she has earned a PhD in MIS at Northcentral University. She is a certified logical data and process modeler and holds project management certification. Anne Marie can be reached at

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