Data governance has a kitchen sink problem. Common definitions for data governance include security, integrity, retention, metrics definition, quality, and standards. It requires you to manage multiple councils. The leadership of these efforts requires the diplomatic skills of Eleanor Roosevelt and the patience of Job.
If that’s not enough you have to have a reasonably deep technical skill set to understand the issues with the systems and a solid grasp on the data so you can analyze it for policy making and implementation.
It’s no wonder so many organizations struggle to get these monolithic efforts off the ground. And the ones that do get them rolling struggle to deliver tangible value because they’re really busy writing policies or organizing workgroups to create a single definition of words that will always mean multiple things to multiple people.
We are all really comfortable blaming the data, it’s not good quality, we don’t define it the same, we don’t have enough of it, and it’s too slow. But rarely do organizations build the one thing that can alleviate the pain, a clearly defined and manageable data governance effort.
Where Do We Start with Data Governance?
The term governance implies that one must create governing bodies, policies, and in many cases bureaucracy to ensure that the data is good enough to use. But I have yet to have a client ask me to build them more barriers to the data. But they will ask me to help them with their governance because they need better and faster access to data.
Data governance is finally evolving to account for the different governing functions that are needed in modern organizations. The reason we have a kitchen sink problem is because we need every aspect of governance to be functioning on all cylinders. We need to have good quality and integrity of the data; we need to secure it and follow regulatory rules. But we also must act fast when analyzing data because the pace of business requires it.
Separating out the “church and state” of data governance will help organizations focus on better and faster access to data while also doing the important work of policy and procedure creation that is demanded for regulatory and compliance. The governance body must include your compliance, privacy, security, and data departments. Don’t put it all on the back of a data governance lead that you bury in a department. Make each of these departments equally accountable for their role in the expanding requirements of data governance.
With a vision of increasing usage of the data in your organization this governing body will be responsible for the creation of policies, procedures and operationalizing those requirements into the technology platforms to allow your analysts to do their job. They literally must manage the data like an asset. Versus other data governance councils that help create definitions and identify data quality standards. Separating out these two functions, a church and state if you will, allows for focus and clarity.
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