This is part 1 of a 4 part series on Data Governance, taken from a paper written by Manager Partner Virginia Flores.
The implementation of a data governance program is of primary importance to most organizations today, and yet the majority of companies that try to implement even a simple infrastructure are doomed to fail. Without the ability to describe data in real financial terms, support at the management level is usually lacking. With no well-defined infrastructure, some data issues get resolved and some slip through the cracks and the data governance objectives are not reached.
Part of the problem is how people define data governance within an organization. They could be talking about organizational bodies, rules, decision rights, accountabilities, or monitoring, controls, and other enforcement methods. Lack of senior-level sponsorship, cultural barriers within an organization, incomplete data definitions and classifications, and the misconception that islands of information are more easily controlled then an integrated data framework all add to over 90% of data governance projects failing in their initial implementations.
Data Governance programs can differ significantly, depending on their focus (Compliance, Data Integration, Master Data Management). Regardless of the “flavor” of governance, however, every program will have essentially the same three-part mission: to make/collect/align rules, to resolve issues, and to monitor/enforce compliance while providing ongoing support to Data Stakeholders.
In the next post, we examine the effects of poor data on the decision making capability of an organization.