As systems mature and data volumes explode, the ability to control the flow and integrity of data becomes costly and cumbersome to manage. Developing a data governance program may be the most effective way to address these issues and ensure data quality across the enterprise. The most common definitions of data governance focus on achieving data quality through a combination of transparent data stewardship processes, a cross-functional hierarchy of committees, corporate policies and enterprise technology. This is all relatively straightforward, but challenges surface when trying to find the appropriate balance of data scope, executive leadership, cross-functional representation, business process reengineering and key initiatives. A method to reach that balance can be achieved by following a set of comprehensive steps in developing your data governance program.
1. Start with a working group. As with any major initiative, you need to determine your strategy and goals while building a business case to obtain funding. Establish a small working group that represents multiple business perspectives, and outline the key operational and cost benefits of the program. This group will vary in size depending on your initial goals, and it should not exceed more than a few individuals, with one person tasked in leading the program. Assume that less is more in this situation.
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