With Master Data Management (MDM) coming to the forefront of both the operational and business intelligence space, it is essential to be aware of the benefits and risks involved in this discipline. Having to agree upon a standardized view of information across multiple business areas and on the accompanying processes and procedures for the utilization of that information can appear to be an overwhelming task. Without an active management strategy in place, this could be an insurmountable undertaking. To help meet these demands, more and more companies understand the importance of implementing Data Governance as a key element of their MDM initiative. Many companies credit a strong Data Governance program for the success of their MDM implementations.
A Data Governance implementation requires a holistic view involving people, processes, and technology. It requires an organization-wide cultural change toward understanding data as a strategic asset; every person must recognize that they have some sort of data accountability. As such, it is critical that organizational change management (OCM) tools and techniques be employed to mitigate risk to your organization’s ROI.
In order to have a successful Data Governance program, employees at different levels of the organization must work together. This is accomplished by designation and assignment into the Executive, Strategic, Tactical, and Operational levels.
The Executive level includes the sponsor(s) of the initiative and executive representatives from other lines of business. This group removes organizational roadblocks to the Data Governance effort.
The Strategic level houses the Data Governance Steering Committee, which encompasses representatives from different areas of the business who are responsible and accountable for data related decisions that concern more than one area of the business. Among the strategic decisions the Steering Committee has to make are the approval of data policies, methodology, priorities, tool, and technology evaluation.
At the Tactical level, individuals should come from a business unit, functional area, or information technology (IT). Although they represent a specific area of the organization within the enterprise, as members of an integrated program, they look at issues from other business perspectives. The responsibilities of this group include resolving issues pertaining to data in their domain, classifying data, and securing business rules.
The Operational group is function-specific and has the responsibility of day-to-day data operation. They support the entire data lifecycle, which includes data definition, measuring and ensuring data quality, and monitoring data utilization, among other things.