Effective data governance starts with a vision, and that vision must be at the enterprise level and commonly understood and communicated.
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 data 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 data governance, all of these disparate data governance efforts must be dismantled and replaced – causing confusion and conflict within the affected areas.
The first step in every successful data 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 data governance will foster reaching that state. Through the skills of a specialist in data management and data governance and using the techniques of facilitation, the senior business team develops the enterprise’s vision for data and its governance. All 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 data 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. Developing a vision at the enterprise level allows the organization to create a holistic approach to setting goals that will enable the it 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 data 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 data governance path as conditions change and new situations develop.
Conclusion
In the final analysis, the best data 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 data governance approach.
