Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines like master data management, big data, metadata, data management, data quality, and data governance.
And it’s that last one (data governance) we invoke as the name of the program that stabilizes the world spinning around data. But just the like Copernican Revolution reversed the belief that the Sun revolved around the Earth, we have to realize that data is not the center of the universe.
As Gartner’s Andrew White lamented, the success of data governance programs are too often “focused on intermediate metrics and analytics that don’t relate directly to business outcomes and their improvement.” In other words, data governance, perhaps at least in part due to its name, is often focused on how well is data is governed. Whereas the real point of data governance, White argued, “is the improvement in business outcomes. You should always and in every case, focus on business outcomes first. That prioritization drives the resulting narrow focus on what data needs to be governed.”
“The future of data governance,” Jelani Harper blogged, “is one in which governance practices, roles, and responsibilities are organized around attaining business objectives. It is a future in which the various aspects of governance (stewardship, governance councils, metadata) are mastered and benefits are determined by business value.” This is especially important, Harper argued, since “contemporary and future governance programs will have to come to terms with a substantial increase in the sources and types of data.”
This substantial increase in the volume and variety of data has created a massive center of gravity pulling more of our focus toward data. But just as the Moon orbits the Earth as the Earth orbits the Sun, our focus on data has to always be considered within a wider focus on the business objectives that data can help us achieve.
Data needs a Copernican Revolution so that data governance, as well as all of our other data disciplines, is properly understood as revolving around business objectives and business outcomes, not data.
1 Comment
Nice analogy Jim. This point that you and Andrew White have made is self-evident to a degree where there should be no need to make it. However, it seems to me that even with the increasing all pervasiveness of data, most organizations treat it as an IT issue. This means that the people working tend to be technical people who are more concerned about metrics and analytics rather than business objectives.
The only way to tackle this problem is to get a greater buy-in from business leaders, not just in terms of green lighting data governance projects, but also getting involved in the project themselves.