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Complexity is often quoted as the main reason for avoiding data governance. It needs a collaborative effort from IT as well as the Business Team. There is always more focus on data quality issues, while data governance takes a back seat. The combination of technology, people and processes can often prove too much due to the changes in responsibility, thinking and culture that are required.

Most data governance initiatives are funded through IT; very few are directly funded by individual business units. While half of companies understand that data management is an ongoing process, not a project, half don’t, citing de-duplication or data cleansing as a one-time data management effort.

A strong data governance programme should be enterprise wide. It will not only identify who owns the data and who can use it, but also provide KPIs for measuring data quality and the effectiveness of the data governance program.

Data governance needs to define what is important to the business, from metrics to business rules; for this reason it often is able to provide sign posts for what’s really important to the business as well as decision rights and who’s accountable for data. This is valuable information, and surprisingly hard to pin down in a world where business divisions see data as an IT problem.

A mature data governance programme can save organisations money, through established best practices and standardisation on methods and tools for data management. The realized operational excellence that comes with providing downstream processes with better data, the agility that comes with continuous improvement of core business processes and the risk avoidance that comes with understanding how data governance processes are performed provide the real, but often hidden value.