Progress Over Perfection:
Adaptive Data Governance

00:38Thank you for joining me today for another episode of Data Stakes, where I have conversations with professionals who work directly in the institutional research or effectiveness field, or are data adjacent in their role in higher education. Today's conversation will focus on how you can create a plan of action that will lead to sustainable data governance strategies on your campus. And I'm excited to introduce my guest today. Dr. Webb is the Associate Vice President for and Chief Data Officer at Rhodes College in Memphis, Tennessee. Rhodes College, a private liberal arts and sciences institution, was founded in 1848 with approximately 1,800 students. Also, I'd like to mention that Tara has been a member of the Future of AIR committee, and as a board member, I'm really a beneficiary of the hard work from that committee this year. So, Tara, not only thanks for being on, thanks for speaking at a forum last year, which is where I met you, and also for your contributions to helping the board look into the future to have valid, meaningful conversations about not only our profession, but where the association is going. So data governance is a frequent topic of discussion in the IIIE community with well attended sessions at forum and other professional conferences. And as I just said, that's how I became acquainted with Tara through her conference presentation at the 2025 forum. And so I'm again, very grateful that you are willing to take your time out of your busy day to talk data governance. That presentation, adaptive data governance steps to success was filled with practical guidance for an attainable iterative just-in-time approach where you shared a structured framework and an implementation roadmap. So let's start out today's conversation with this question. What is exactly is data governance and why should we care about it?

02:46Thank you so much for having me today. I'm excited to join you to talk about data governance. And I'm actually glad that you started with that question as well, because it's a question that intimidates so many higher education professionals. What is data governance? We hear about it and we know that it's important, but it can feel so theoretical and so technical and just not in our wheelhouse. But I like to define it practically. So to me, data governance is a framework that is made up of people and knowledge and processes. And that enables us to have available, usable, reliable, and secure data on our campuses. And in higher education, data-informed decisions about enrollment and student success and the allocation of our resources. But if people can't access or trust our data, they won't use them. And if our data are not protected properly, that puts the institution at risk. So we should care about data governance because at its core, it really is about both maximizing value and minimizing risk.

04:06Okay, so an earlier conversation that we had, I shared with you that when I start to talk about data governance, before the eyes start rolling and everyone starts sighing, I try to communicate it as a way of empowerment. That not only are you now the owner, typically of a data module or a certain set of data, say you're the financial aid director and that is your data, but you're also empowered to make decisions about that data. It's not just a set of rules that are being enforced on Yale, but I see a knowledge management culture as one where the module managers or whatever you want to call them, champions, they are empowered to make good decisions that benefit the entire campus. So this might be the more important question for listeners who are working to convince their colleagues. What do our institutions lose when data governance isn't regarded as an important strategy by colleagues outside the data office?

05:13Well, effective data governance is a team effort. So institutions lose the ability to use their data as an asset when the data office is the only group that is interested in prioritizing that work. So the first thing that institutions may lose is trust in their data. People will provide different numbers, and then you'll start hearing questions like, well, why doesn't that number match mine? And meetings may then become discussions about definitions or data sources instead of conversations about strategy or decision-making. And that really can consume so much of the valuable time and energy because people want to make data informed decisions. We know that it is important to the work that we do. But over time, they may decide that it's safer to move forward without relying on the data at all. And so when that happens, data democratization suffers. And what I mean by that is just data democratization is when people have the right access to the data that they need to do their jobs. And I would say too, in this age of AI augmentation, where higher education institutions are using AI to augment their data activities, we can't do that responsibly if we don't have well-governed data. So ultimately, I would say the biggest loss to an institution is strategic value.

06:51Yes, I would agree. Without it, you can't really have the deeper conversations that really benefit the organization as a whole and the students that we serve. So what about the colleagues who are less than enthusiastic about data governance? How do you bring them on board?

07:08Well, that's a great question because what I always say is our data stewards already have full-time jobs. They have full-time responsibilities. So you don't want this to feel like extra unimportant work. So it's important to respect their time. And the way that I do that in our data governance efforts is to create focused working sessions. So some institutions plan data governance meetings where they talk about strategy and planning and all of that, but our data governance working sessions, one hour every two weeks, and we do the work together. So there's no homework for these already busy professionals. And I like to frame data governance as enabling, as you mentioned, instead of restricting. This is intended to empower them to do their jobs more effectively. And I like to make progress visible. So I share updates. How many definitions have we added? What workflows have been improved? What's changed? Visible wins matter in higher education change management. And what I found, I've even had some colleagues that were initially skeptical who have later said things like, wow, this has really increased transparency, or this has helped me think more strategically about our data. And that feels like a win.

08:33Yes. Yes, yes, that definitely is. When I was first hired at Cowley College, as I went around campus, talked to staff who had direct access to the computer system, were responsible for entering information, and also had access to reports, what I found was they weren't lacking in technical skills. But what they lacked was confidence. Confidence that they understood what was being extracted out of the system, confidence that they would know how to use it to make a good decision. And that was actually something that we tackled right away to determine what was leading to that. And a lot of it was simply data governance. It was the definitions, it was the common understanding and the common language that we had to create. So now that we've kind of established why we should have data governance and why everyone else should love to be in that room with us, can you share more about your iterative approach and who should be involved with each stage?

09:39Of course, one of the things that I found when I was entering the data governance space is that peers were telling me that some of the biggest reasons that their governance effort stalled or failed is because they were trying to do it perfectly upfront. And so it started too big and it was overwhelming and it delayed progress. So my approach has been starting small, but strategically. So I recommend that you choose something that will produce meaningful institutional impact that will be visible, that will be valuable, and begin there. I really think that it is better to build something sustainable than something that is impressive in this process. So I like to start, as I mentioned, I think about this in terms of people, knowledge, and process. And so I designed this implementation around that. So I like to start with people first. And in that, I mean, you start by defining and implementing clear roles and responsibilities. Who's accountable, who's involved in decisions, and that creates a structure. So one of the things that I found is really important is starting with an executive sponsor who is going to champion this effort on your college campus. That is key to success. So

10:57Yes.

11:01Here it's my provost. And the next set of roles that you really want to look at are those data trustee roles. Those are usually vice presidents. They usually have high level accountability over functional areas. And they can help identify the data stewards for their areas. And those data stewards are largely responsible for the next steps. So building the knowledge and the processes. So they're going to help with laying the foundation where we establish common language or build a glossary or document key data sources. And then they also help with building processes. So developing those management standards, access procedures, how we make data requests on a campus, how data are shared. And then they're also involved in that training and sustaining step which comes next. But I like to think of this all as an iterative cycle. You will revisit each phase as your campus evolves and more individuals engage in the work.

12:07Do you have anything that you can share with our listeners about the other stages?

12:12Yes, wonderful. So in laying the foundation, one of the practical strategies that we have taken is to define IPEDS definitions. And that is very valuable for an institution. And so you can document all of IPEDS definitions, but the data stewards can then look at each definition and determine whether that aligns with our own institutional definition or how we would define that institutionally. And along with that process, they can document the reporting fields and sources as well. So as they create this IPEDS definition document, you... It enables the campus to report to IPEDS accurately and consistently every time, which we know is very important for data professionals, especially at this point in time.

13:13Yes, yes, as a survivor of the new IPEDS axe, yes, you know exactly what you're talking about. You know, earlier you mentioned what happens when different datasets are brought into the same room and then it's almost a competition for what is truth. I was really very fortunate because when I was hired at Cowley College, the creation of a knowledge management culture was actually a pillar in their current strategic plan. And so, yes, when you talk about your provost being your champion, my champion was my supervisor, the college's president. And this was a very high priority for him. He had spent time working for the Kansas Board of Regents and he understood that data is really a strategic asset, you know, an asset, as you mentioned earlier. And so one of the first conversations that we had was should we have a data set that is a consistent source of truth for important tasks, especially when we're in the public facing setting. So for example, what data set should we be talking about when we're at our public board meetings or that I should publish in my by the numbers reports that went on the website? And so we talked about that and as a group, my knowledge management team, you know, selected one. It turned out not to be IPEDS, but it did. It was a very robust collection from the Kansas Board of Regents from which I built almost all of my IPEDS reporting from. And I found that once we did that, there was no more questioning of whether we knew what we were doing with data on campus because it was aligned with the other public sources that our community was turning to, our trustees were turning to. And I felt like you said we really could then begin to have the more important conversations instead of this little bit of struggling on who has the truth and what is right. So Let's talk about the roadmap and the matter of time. So are we ever done with data governance? And if our listeners are just starting this journey, what type of timeline are they facing?

15:36Well, data governance is never done.

15:39There folks, there's the bad news. Yes, it is.

16:10And honestly, that's healthy because our institutions are changing. People change roles. Our systems change. Our enterprise reporting platforms change. Our ancillary systems change. Regulations change. Reporting requirements change. And even institutional priorities shift over time. So this will be an ongoing process and not one project with an end date. But Institutions can make meaningful progress in a short amount of time if they start small with meaningful projects that will have high level impact. And so I've seen meaningful progress made within one year. So in a year, you could move through an implementation roadmap where you clarify rules and determine what your next step for building a foundation of knowledge might be. So maybe you build a glossary. You can also establish data classification categories as part of the process documentation, looking at those processes. And data classification categories can be a very important part of that project because it matters whether your data should be restricted or they're just confidential or they're just internal or they should be public. So that can be a big win in a short amount of time as well. And formalizing those requests workflows can be an early part of that first year process. So all of that can be done in one year's time.

17:26Right.

17:27I would say that the key here really is forward motion and progress over perfection.

17:33Yes. Yes, yes. I remember, you know, some concern early meetings on when I was first hired from my data stewards. Comments like, we've never done this before. What if we do it wrong? And I think we do always, we're kind of perfection centered when you're working with data. But you're right. It's always iterative. It's always evolving. And you know, my reassurance to them was, then we can change it. Yes, we can do that. We can change a rule. Like you said, we can have a very abrupt announcement of a new federal reporting requirement. And all of the sudden, student privacy is now an even more elevated topic on your campus. And so yes, you have to be open, flexible, willing to pivot, and understand that that's not a sign of a failure. You know, it's actually a sign of that data maturity growth. That's part of the journey is being willing to evolve over time. So let's talk about possible resources that our listeners might benefit from. What do you recommend to them?

18:26Yes. Well, I started by just searching online to see what was out there. And I found there are some books. One book is the Data Management Body of Knowledge. And that is highly recommended. But some of the online resources that I found helpful are available through the Association for Institutional Research and EDUCAUSE. But I always tell people as they look at these resources to not get stuck comparing models, focus on the common themes that you find there, clear roles, shared knowledge, repeatable processes, and then adapt those to fit your own institutional culture and needs. But also one of my biggest resources really is the AIR forum because

19:25Yes.

19:33You get to talk to your peers about what this is like on their campuses, how this is playing out in practice. And so you learn tips and tricks from other professionals, and that has been the most helpful for me. So I look forward to connecting and learning with my peers and colleagues there every year.

19:36Great. Yeah. That is nothing like forum. So for me, each year I used multiple assessments and those didn't exactly tell me they weren't prescriptive per se, but they did tell us whether we were moving toward our goal. And so I used an institutional transformation framework that addressed some of the higher level things and then the basics like the stewards and the glossary and all of that and if listeners were interested in that you could just email me I'd be more than happy to share it with you and also I think I'd be remiss if we didn't talk a few minutes about the AIR playbook which was created with Educause and Nakubo so listeners if you're not familiar with that you can go to the association's webpage it's AIRweb.org and under resources or learning, you'll find the playbook and there are multiple plays and you can begin to address not only data governance, but other foundational data activities on your campus that also support data governance and data literacy. So finally, how do you assess the effectiveness of your data governance strategy? Because I'm sure there are times you've been asked so what so what why are we so what

21:18Yeah, so I like to look at outcomes, which is no surprise for an institutional research and effectiveness professional. But I think of these outcomes both in operational and cultural terms. instead of looking just at activity when assessing, I'm looking at are our data requests routed and tracked appropriately? Are data availability, usability, integrity, and security actually improving as a result? Culturally, I would say I've looked for signs that it's becoming embedded in our work. And so are people following the processes that we've established or trying to go around them? Are people aware of who our data stewards are? and what they're responsible for. So I also like to pay close attention to whether our data stewards feel empowered in their roles because government or governance is most sustainable when they feel like they're empowered as the primary authority for the data in their areas. And that helps to make sure that the work that they're doing is sustainable and effective. And so that really is how I look at our data governance strategy and whether it's effective or not, whether it's working.

22:45One thing that I noticed during my time at Cowley was the longer I was there, the more I realized that when we were in a setting, any kind of committee, where a decision needed to be made, people stopped turning toward me, but instead had already. you know, we're already familiar with the data that they should be using to make the decision. And it was just the feeling that they weren't so dependent. anymore that I you know, it's kind of like a mother watching the child walk out the door to school, you know, you kind of miss their dependency, but you're so proud of what they've accomplished because that's really what it is. It's it's promoting a level of growth to our colleagues outside the data office, who at one point might have looked at you or I and said, I'm not a data person. And all of sudden, one

23:24It.

23:40Day because of the activities that you've involved them with, they wake up and they realize, hey, I really am a data person now. So thanks, and that's the end of our time for today. This has been very insightful conversation, one that I'm sure our listeners will benefit greatly from. And Tara, thank you again for being such a wonderful guest on Data Stakes today. Listeners, if you'd like to know more about data governance, I highly recommend that you follow Dr. Tara Webb on LinkedIn and take the time to visit two online resources. Again, first, the Association for Institutional Research's website to learn more about the leading change with analytics workshop series and the change with analytics playbook. And to our listeners, what do you want to talk about? You could be my next guest just by reaching out to me at dfelps at Datatelligent.ai. Thanks.