In our introduction to data governance, we almost always assert that “data governance is not about control.” When we say that data governance is not about control, we don’t mean that you don’t have controls around data capture, storage, access, usage, etc. What we mean is that you don’t institute data governance practices and protocols in order to “protect” your data from misuse; you govern data in order to make better use of it.
Wait, you might say, the reason we’re interested in data governance is compliance! We must report data, or our data policies, or demonstrate security, etc., to a growing number of external agencies, and failure to meet these obligations could be costly. At IData we wouldn’t dispute that, but we encourage you to look at these compliance regimes and requirements as opportunities. There’s nothing that says compliance isn’t a better use of data. And even if abiding by compliance requirements is your entryway to data governance, stopping there would be nearly criminal! (Not really. Unconscionable, maybe, but not criminal.)
Let’s return to our earlier point about data being a key organizational asset. Your policy about financial assets isn’t “don’t spend money,” it’s more like, “spend money wisely.” The same is true with your offices, classrooms, dormitories, etc.—you don’t want them empty, you want them filled; but you want them filled with people performing activities that are appropriate and productive. To use these assets best, you steward them actively.
Likewise, your data assets benefit from stewardship. While the specific tasks and responsibilities of data stewards are outside the scope of this post, it is worth emphasizing that data stewardship is not only a key concept, but in fact a foundational requirement, for data governance.
Stewards primarily bring to data governance a knowledge of data: where it came from, why we collected it, what it means, how it should be used, whether it’s accurate and complete, and so on. Other people provide different valuable inputs: analysts provide different ways to think about data; custodians can confirm the safety and reliability of data systems; curators present data to us in useful formats to improve our understanding and expand our options; and so on. The sum of this knowledge is powerful, but without a data governance framework our access to and use of this knowledge is fragmented and scattershot.
In our webinars, we describe data governance as “practices designed to help people access, understand, connect, protect, and effectively use your organization’s data across all systems.” So, yes, protecting data is one facet of data governance, but it’s not the only one, and we don’t believe it should be the primary one. Individuals at higher education institutions need to know what data exists and where it is housed, what data means in which contexts, how to access and utilize data, how and when some data can be combined with other data, whether and why it changes over time or as it moves from one system to another; and of course they should know the limits to each of these uses.
Regardless, the key component in our definition is not the list of uses and protocols—it’s the part about helping people. Data is critical in the modern educational institution, and nearly every employee will require it in the course of doing their work. Don’t we want to help them do that work more effectively? Of course. So how does data governance enable people to make better (wiser, safer, faster, etc.) use of organizational data?
In our experience, data works better when access to it is democratized, when responsibility for it is publicly assigned, and when it is managed transparently. Data governance provides a set of guiding principles, building blocks, and tools to assure access, accountability, and visibility.
Our recommendations for principles and goals include the following:
To recap: data is a critical organizational asset. Like all assets, it should be handled carefully and utilized appropriately. Locking down access to it, or instituting an environment of suspicion and control, is not wise or appropriate use (and in fact is likely to give rise to several less secure, essentially unmanaged practices. Data governance isn’t and shouldn’t strive to be a lock-box; rather, it’s more like instructions, or a set of tools, or a roster of practices to assist staff as they seek to improve their institution’s data use.
IData is expert in data governance, data intelligence and integration. Feel free to
(image credit StockSnap_NY963ZH6T2_DGHelping_BP #1027)