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Thank 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 the importance of campus culture, why it matters, and how to leverage culture as a foundation for successful and sustainable data work. My guest today is Dr. Jason Simon. Dr. Simon has over 30 years of leadership experience working with enrollment management, finance and administration, academic affairs, alumni relations, and student services as a leader in higher education data analytics and research roles. His service to the IR and IE community at large includes current work. As a co-instructor for the AIR Leads Leadership Development Curriculum and as a contributing author on the 2019 statement on analytics, Analytics Can Save Higher Education Really, jointly produced by EDUCAUS, AIR, and Nakubo. Jason, it's great to see you again. So in
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Likewise, right back at you. I'll be here.
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Yeah, it it it is great, always great. In 2025, you announced that you were not retiring, but rather you were rewiring to become the co-founder of SCL Impact LLC. So, congratulations to you and to the campuses who are going to benefit from your knowledge. And today we're going to share from your 2026 AIR forum presentation, Analytics Without Culture, a recipe for stalled progress. And let me just start by saying I think this is something that is really underestimated on campuses. We focus a lot on technical abilities. we focus a lot on data cleanliness, and all of that is really important. But you're gonna talk to our listeners today about why culture matters. So let's stay set the stage with that, with you sharing why should they care? Why does culture matter?
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Well, I I I believe from my perspective, we throw a lot of time, energy, and resources, as you were saying, towards the technical elements of the challenges we're facing as data practitioners. But it it's ironic to me that even institutions with almost unlimited financial resources, large staffs, robust technology platforms, they still are struggling. And so that tells me that the answer is not just on the technical investment as well. And so the culture component is what is probably preventing a lot of practitioners from achieving the levels of success. And I would also say what their executive sponsors, presidents, trustees are hoping for as well. And so by taking a culture-oriented approach and creating an opportunity to layer that on top of the technical approach. I believe it gives leaders a much more robust opportunity to really analyze the situation that's going on in their ecosystem. And it also, I would say, honors the fact that every institution of higher education has a different culture. Just because something might have worked at one institution doesn't mean you can lift and shift it to another one and expect the same results. and lastly, I think, and I I know we're gonna probably dig a little deeper into this, but there's a name for all of this, and it's called Adaptive Challenges. And adaptive challenges really stem from the work of of a professor at Harvard, Heifritz, who wrote a series of leadership books on this topic. And the theory is is that the technology is not gonna be the root of the challenge. It's people. We are all social animals, we're all social beings, and we all contribute to a campus culture. And by By divorcing, if you will, the human element of our work, it's really setting us backwards, in my opinion.
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Right. Yes. I totally agree. Totally agree. And all all of that is familiar to me. I did my master's in organizational leadership. And so you are really speaking to to to what really resonates with me. So you included a collection of interesting quotations in your presentation. So here are two winners that popped out for me. So I I even assigned them categories, okay? So in
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Go for it.
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the most controversial category,
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Yeah.
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data is like garbage. You better know what you're going to do with it before you collect it from Mark Twain. And in our most uncomfortable truth category, data, data everywhere, but not a thought to think. From John Allen Paulos. So why did you choose to include these quotes? And are they connected to uncomfortable confrontation that happens when we try to address internal challenges?
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definitely. I mean, if we take the garbage quote for example, how many times in our roles have we been asked, Well, I just need the data? Or I want data that that we as data practitioners know doesn't exist. And so, sure, I can build you a relational table. Sure, I could build you a technical connection that allows you to have access to data you don't have right now. But the underlying question is for what purpose? And and from a from a pro-data culture perspective, we're trying to enhance data literacy, right? And and so a part of data literacy is understanding appropriate uses for data resources. And so it doesn't make sense to me to boil the ocean and create this massive data lake or data warehouse if the institution culturally isn't even prepared to deal with the data that we uncover. And so it is kind of like garbage because then we're just sort of farming it together without ever really understanding the higher purpose for it.
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Right.
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Right. And and so I believe that that is a cultural phenomenon because oftentimes Cultures will exist where people will just constantly ask for more and more data as a stalling tactic to not address making the difficult decision. And so it does
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Yes.
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pile up. It it becomes like piles of garbage. And in my presentation, I showed the opposite of that, which was from a garbage heap to sort of like a recycling company where there was piles of like minded data that were situated. And it was there was some thought behind which pile goes where and why. and so I believe that that is really a key purpose for that. And then the second quote, which I really like, is, you know, just because we're surrounded by data doesn't necessarily mean that people know how to understand it or use it. And so how many times have we heard in our practice the the end of one examples? Well, I know a student who said, or I met an advisor who thought, or
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Yes.
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as a faculty member in my class, and and in reality that doesn't also help support a pro-culture campus because we're allowing individual opinions then to drive larger decisions that from an ecosystem perspective aren't really appropriate.
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Right, right. So it it reminds me of some guidance that we received at my former institution when we were part of the recent cohort invited to do the Aspen Institute.
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Right.
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And the advice was that we needed to be able to demonstrate initiatives that had scaled up. It's exactly what you're saying, not just something that helped 30, 40, or 50 students, even though they acknowledged that was really important, especially on a small campus. But they wanted to see the things that impacted the majority, how we'd made widespread cultural shift. And then the other thing I was thinking about as you were talking about the the data is like garbage, is one of the firm rules I had all throughout my career, which took a little training for my coworkers, was they would use my email, request a data set, and I would email back, hi, what's your research question? What are you going to be doing with this? How are you going to be using the data? Who who are you going to share it with? What you know? And at first that was met with a little, well, what's it to you? attitude. But then afterwards, my colleagues began to discover that that initial conversation was really quite valuable and actually saved time. Because if I don't understand what you're going to do with the data, how do you know I'm not going to give you garbage?
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Wa well it also positions the IR function then As being an ally in the institutional research, not the IR research, but the faculty members research
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Yes.
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priorities. And and from my perspective, we did similar things. We would ask them for the research questions. We would also ask them for very specific details on the cohorts that they were interested in. We would ask them follow-up questions on our form. So we weren't going to do the back and forth 35, you know, ad hoc requests until we actually figured out what you want. And
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Right.
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and A culture perspective that also created real opportunities for us to partner with our Office of Sponsored Research. And then the Office of Sponsored Research, the vice president, would bring us in to do trainings for faculty researchers. And so it created not just a cultural implication of hey, you can't ask for data hypothetically, this never happens, the day before a grant is due.
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Yeah.
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likewise, it also created a situation where the for From a culture perspective, the IR office positioned itself then as being an ally with that faculty member. And
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Yes.
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that that blossomed into real opportunities, even beyond that one individual research project, because now we had a cohort of individuals who went to bat, if you will, for the
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Yes.
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data function at the institution. And that's the kind of things we're talking about here today. Is is it's it's those soft skills that IR needs to embrace. Know we're all trained from a practitioner-based model. The person who trained you is probably trained by their boss and IR. There's no master's degree solely focused on institutional research. Maybe there's a course here or there. And so it really is institutional culture. And so I feel like one of my hopes and dreams, if you will, for our field is that I wish we had more opportunities to dig into conversations like you and I are having today, because it's the differentiator, I think, and it really can boost an individual's performance. Performance, make an impact on our students, but also set them up for a future career that they're viewed as an expert. And that's what we all want.
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Right, exactly. So I know you want to circle back to the importance of adaptive leadership for data professionals. and I really loved this statement from your presentation. Almost every adaptive challenge is directly linked to campus culture. So let's talk about what an adaptive challenge is as opposed to a technical challenge and why you think adaptive leadership skills are the key to changing culture.
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Well, obviously, you know, technical is typically focused on a problem, right? What's the problem we're trying to fix? Adaptive challenges typically work best when we're trying to understand what we need to learn. So that's your first your first clue, if you will. Is it a learning issue? Second, technical problems oftentimes don't require people to lose something. Whereas an adaptive challenge requires individuals to have a loss. Now, that might be in in autonomy, that might be in individual decision-making ability. That that might just be in having to come to terms that they're wrong, right? About something. And so that that is really a big differentiator. And typically, adaptive challenges are also ones that are not as easily to see on the surface. They're usually the things that are inextricably linked as as you just said to culture, which is norms, symbols, values,
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Right.
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beliefs, how the campus allows data to either be utilized for good or weaponized, right? As a punishing tactic.
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Yes.
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That that is all part of adaptive challenges and culture. Also, adaptive challenges in my mind are the reason why you can have the best strategic roadmap for a data maturity process or a new data warehouse, etc. But but it's the adaptive challenge. So, what is the relationship like between IR and IT? What is the relationship between the folks that are doing data quality work and data cleansing work and the folks that are just building out table structure? So your data modeling team. Though those are all adaptive, they're not technical. because it comes down to competing priorities, timelines, purposes. And so what I'm urging is institutional researchers, if they really want to be an effective data culture leader, they've got to begin to embrace the really hard parts of our job, which are the relationships and the people. And
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Yes. Yes.
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and not also just work with people that you feel like you like and they like you.
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Yes. I was thinking about that. Yes. No.
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It it right, right? That's the hard part, right? The hard part is building those allyships across your institution.
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Yes.
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With folks who may have been your harshest critic, who you
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Yes.
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just maybe need to take out to lunch or coffee and say, Hey, you behaved or said this in a meeting. And I I wanted to unpack that with you so I could better understand where you are coming from. But notice how I did that. That wasn't, hey, I felt offended from you and
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Right.
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I felt I'm angry at you. No, I want to learn. And that's the adaptive piece. adaptive leaders want to continually learn, and they want to learn more than just the facts. They want to learn
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Yes.
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the people, the beliefs, the feelings. So
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Yes.
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hopefully that sort of unpacks that a little bit. And and and I would encourage your listeners to really read up on adaptive leadership because I think they'll find that it offers real opportunities, especially from a reflective leadership perspective. I believe very heavily in reflective praxis where you look backwards and then think about how it informs the future. And as I dug into adaptive leadership, the I I s things became clear. You know, why someone might have behaved one way or why a certain leader did something one way or maybe why something fell off the rails and we had to put it back on the track. and so I think it's a valuable exercise to to think beyond just the technical toolbox.
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Yes. So what this means is we have to, as data professionals, embrace a side of ourselves that maybe even makes us uncomfortable because this takes a certain amount of emotional intelligence. And and
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Mm-hmm.
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let's face it, we have a lot of colleagues who, when they signed on to a data role, it was not necessarily one where your door was open. You know, you
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Mm-hmm.
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you got to stay in your safe space, and you really didn't have to, you know, deal With a lot of colleagues, and but I think we're seeing more and more of that as campuses shift to having institutional effectiveness roles, which indicate this expectation that you're sharing. You know, one of the things that are really underestimated at the beginning of my career was how much fear plays a part in strategic planning. So strategic planning has always been in my role because it's supported by data. Great piece of advice I got during my first strategic plan was from a president who said, I noticed you have only invited people that you already get along with. I want you to invite and he he named two people who would have been like, get out the cross in the garlic. I was like, I I don't want to, I don't want to. And he his his response was, No, this will stretch you. You will grow, you'll learn to to to to know them better. And if you're successful at this. They might be new allies. And you know, those beginning meetings were very uncomfortable because we were working to revise the mission statement.
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Yep. Yep.
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And but it was so worth it. It was so worth it. And I had another situation where I was an interim for another administrator for a little while and had to work with faculty on outcomes assessment. And I literally sat and listened to a faculty member yell at me for 10
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Yeah. Yeah.
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or 15 minutes. And when it was done, just like you said, I I didn't tell him how it worried me or a upset me, it was to to say, I understand. I'm sorry. Because he taught career and technical education. And he had it had been objectives and then it was outcomes and then it was something else and now it was outcomes again and he was tired. He was tired. And it was right. Yes. But that's part of
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Yeah. And and you weren't the target, you were just the outlet for his frustration. And and that
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culture.
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it is a part of culture. And and my example would be, you know, when we first because when I first joined my previous employer, we were still using a PDF paper fact book. No joke, three hundred and sixty-four pages. And by the time I left, we had a full machine learning data science capability. And we went from paper to dashboards. And when we were first introducing the program, I we didn't just drop a new tool onto the institution. I went around and talked with all of our deans. And one dean in particular said, It doesn't matter what you bring. I can't, I don't have the mental space right now to learn yet another system at the institution. There's so much on my plate, I can't take it. And and that was an important lesson for us because We we at least had the value of having those conversations before we even announced what the tool was. So we knew by the time I left, that was the one dean who would have taken the hill with me if the system had had had to go away, because she now saw the value. in that investment and she felt heard right and she felt like that that she was was a participant in the creation of that tool and from a culture perspective one of the things we did very intentionally and I recognize that people are gonna listen to me say this now and go I don't have time for that but we very specifically introduced sort of like concierge training to a select group of individuals who I knew had the ability to talk to their peers And create positive messaging for me. And it's a force multiplier. And that's the other piece. Excuse me. A lot of our IR shops are one-person shops that and they're expected to do so much. By building these kinds of allyships and relationships, you create an opportunity then for your message to be expanded more broadly because it's not just you out there preaching. And that's the other piece, too, I think, from a culture perspective. Yeah.
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Yeah. So important. So you listed six key takeaways that lead to what you call a culture in action. So can you speak more about three of them? And here they are: making
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Okay.
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sense of your institutional culture, deciphering leaders' words and actions, and responding
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Mm-hmm.
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to change.
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Sure. I would say, and maybe I'll just lump them all together under one general rubric, which is we we no longer can afford to be the fish in the fish tank not seeing the water. And we've got to start to look more critically in the ecosystems and where we work. And one of the ways that that I would say practitioners can do that is by even if it's just a half hour a month. Taking some time, being reflective, and asking yourself, and maybe even having it as a team discussion, if you have a team, what is happening within our campus right now from a data perspective that we need to be paying attention to? And from my perspective, we have to first to thine own selves be true, right? We first have to understand what our perspective is. Then we have to begin to look at the campus community and start asking bigger questions. Some of those really important questions to me are why do new initiatives fail? and that's a really fascinating project to look into or unpack. another really good question that I like to ask is what is being said versus what is being intended? Because sometimes we know that that what is said is not exactly what the intent is. I Always encouraged my team to either go or to join if it was being web hosted into the State of the Union address from our president because I needed for my team to also hear what I was hearing about the institutional perspectives and priorities. And then I would come back and we would have a facilitated conversation about reading between the lines, what was said, and then what how is that going to now impact us as a team and impact our data ecosystem? and then the last point that I would make is you know. Part of the practice in my mind is, and it kind of builds on our last conversation, having those uncomfortable conversations with folks on campus who maybe could offer you a different perspective on the work that you do. And that I I get the inherent risk. I get the inherent that doesn't feel comfortable. I I get the inherent I'm putting myself in a dangerous position because I've heard this in my feet in my career. Well, if we ask the question and they tell us the answer, that means we're gonna more work to do. And and in my mind, I would rather have those difficult conversations and understand what the expectations are than be judged or my office be judged or my function be judged against a litmus that I don't even understand.
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Right.
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And so it it to me, all of those taken together, it it creates this need for IR practitioners to run a different race as opposed to the horse racing where the blinders are on and we're only looking one direction ahead. But really think about if every to your point, every strategic plan initiative is tied back to data and we're the data team, then
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Yes.
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we are inextricably involved in the success of the institution, even if our leaders don't recognize that to the level they should, we don't, we do. And so from my perspective, it's just adding tools to an already technical toolbox that are more here we go, full circle, adaptive in nature that allows you to recognize the need not just for technical subject matter expertise, but functional subject matter expertise that includes human relationships.
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Yeah, so totally agree. So I know you weren't expecting this, but let's let's flash back to to a regular survey that AIR does. And that is when we would fill out information about the function and our role on our campus. Okay. So
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Sure. Love that survey.
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let's you know, and I in in my early career I did not report to the president. but at my first institution a president came in that's that expressed exactly what you've said. We involve data in everything. Why isn't Debbie on the administrative council? Why isn't art you know? And so if Listeners, you do not sit in a place where you feel you can effectively move culture because of your role. Maybe it's time to talk to your dean, your provost, your president about how to make your role more effective. Because you can only function within the within the fence around your field. Does that make sense? If your pasture isn't very big, here comes the Cansan in me. If your pasture isn't very big, you really can't wander into other areas because people will people would say to me, Well, you work in student services. Why
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Mm-hmm.
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why are you making suggestions to us in academic affairs? But then I got lucky and I was moved to academic affairs and worked for a dean who it helped me expand. my role. She legitimized data on our campus. And that's what led to eventually becoming an administrator with even greater reach and ability to affect culture.
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Yeah, you know, and this is one of those challenging ones where I would always build in and it drove it drove my my drove my team a little crazy. So I will admit this may not be a best practice for everybody. But I would build in 15 minutes before and after any meetings that we had in the main administrative building. I was housed in the main administrative building for many years and then we were moved to part of an IT collaboration. Let's get everyone to do an open office, speaking of no walls. But I would build in that extra time and I would literally just pop in. If I saw someone was in their office and I had, but but I built a relationship over time. I didn't just do that on my Very first day. But
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Right.
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but I wanted to be out there and those conversations in the hallway, those conversations that were just bumping into people. it might look like it was unintentional, but no, there was actual strategy around that because I wanted to have that touch point with those individuals who were in the conversations that I was not, and would allow them to then begin to help me. Spread my case for why the data function is important.
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Right, right. And all of that impacts culture and and building elections. Okay.
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Okay.
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So you ended your presentation at forum by challenging attendees to embrace one of the nine data forward behaviors you recommended as catalyst to culture change. So let's end our conversation today by sharing our favorites from your list. And I'll go first. so these all were so critical. But for me, I liked this one. Behave with confidence, make data a non- Negotiable in decision making. That has been a drumbeat, a drumbeat throughout my 20 years in higher education. It's even the impetus for the name of this podcast, data stakes. Data deserves a seat at the table. I firmly believe that. And that IRIE professionals should not be viewed just as the person who does all the external reporting. Well, what does Debbie do? Well, she does iPads. That's always how it starts out. Isn't it? But instead, as an important administrative asset who helps to guide meaningful changes on every campus. Because without data, where does the conversation even begin? It's it's like you said, is it built on anecdote? That's not enough. I think between data and context. And to learn context, you have to have allies. You have to have conversations.
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Well, yeah. And in my mind, I mean, let's face it, if we can be honest here for a second, higher ed is i isn't exactly in a well perceived public state right now. And
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Yes.
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and that's I think that's being a little generous. And one of the criticisms of I think our field, writ large. Is that disconnect between outcomes driven behaviors and practices and what makes sense? You know, how many times have we heard we'll just be more like a business? We're not a business, we're higher ed, right?
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Yeah. Right.
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Now we have certain elements of what we do that that mirror those corporate ecosystems. But no, if we go back to the founding of higher education, all the way back to, you know, pick pick one, either sub-Saharan African institutions that have started in the in the in the early zeros, all the way up to England and you know, German institutions in the thousands, right? So th this is not new, but my perspective on this is that we as practitioners need to be comfortable calling use a bad word, I'm from New Jersey, but calling out things that aren't true when we sitting in meetings, when we're part of discussions, when when we are hearing things unfold and we are in the room and not taking the moral high ground to say, well, what does the data tell us about this? And and I by the time I I rewired and left my last institution, one of the things that that I felt most proud about was several VPs came up to me at At the going away congratulations event. And they said, you know, the one thing that we always could rely on you is to tell us the truth, the facts.
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The truth.
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the facts and and to not to not use hyperbole and to not sugarcoat and to not we we just knew where we stood in terms of the data with you. And and I took that as the ultimate compliment because that that was part of my toolbox, right? You you can't
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Absolutely.
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you can't misuse data if you're afraid to even tell people what it is. It does take courage. It does.
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Yes. Yes. It takes courage. It it it takes courage to work in data. It's it's yeah, it's not for everyone, but
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But no, it's not. But but you when I but when I'm working with IR teams and consulting and coming in for doing staff retreats and those kinds of things, these topics always come up. And part of my sh my goal at this phase in my career is to still give back to higher ed, but I want to do it by educating practitioners. to be the force multipliers at their own institutions. I I wanna just not contribute anymore at one institution. I wanna help the entire field. Because as a first generation student myself who broke literally four cycles of poverty, four generations of poverty, Higher ed was a differentiator for me. I mean, I'm on a completely life, different life trajectory now because of the role that higher ed played for me. And so for me, it's a it's a it's a social and ethical calling. And so why wouldn't we want people to use information resources to make better decisions when it has profound outcomes on people? You know, we're we're so quick to talk in our field about graduation rates, retention rates, enrollment counts, D FWI grade distributions that we oftentimes think I think we forget the individual impact on the student's life. And you know, and so from my perspective, it that's something that I think we as a field of practitioners could do a better job is really understanding and and and sharing and I mean sometimes yes, taking a hill and planting a flag and saying we are gonna talk about the uncomfortable data that this situation encounters. So
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Right, right.
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yeah.
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So which one of those nine was your pick?
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That was hard. That's like asking a parent to pick their favorite child. well, because I tr when I wrote these, I tried to create them in such a way that I felt like they they hit on different aspects of culture, right? Probably
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huh.
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the one for me. all right, I'll I'll say behave as a champion, promote data literacy across all roles. That that to me is is huge because when I say day l data literacy, I'm talking about helping people understand the sources of data. The way data is gathered, collected, and utilized, the use cases for that data. And lastly, in the piece that think we often miss in the field, the return and investment of leveraging that data. What was the good that happened? How do we measure that good?
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Right.
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And data literacy, from my perspective, meets the individual data consumer at the institution where they are. It doesn't assume anything. And so when we put our program in place at my last institution, we had entry courses, we had secondary courses we had we had a virtual online training that people could take through the HR training platform that was a short video presentation and and one of our goals for that was to help people ask better questions of the data And and
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Yes.
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it was remarkable to watch how the ad hocs changed. And my my team both loved it and hated it. And they cursed my name and sometimes they didn't. But the reason why was we found that the questions, the the super simple questions were no longer coming in because people we were training people to use our dashboards, we were training people to use our data products. The questions that were coming in were the really thorny, sticky ones. And that's how we knew we were being successful because now people were asking us questions at a level that told us they were no longer data agnostic. They were really data literate. And and that is that should be our goal, right? I mean, we
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Yes. Yes.
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wouldn't it be great to not have a a a frontline entry level analyst handle the same requests every single day. From a professional development perspective, that's how we burn our staffs out. That's why they leave.
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Right.
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So so giving people the ability, it it Raises all boats. And so if you behave as a data champion, in every sense of the word, a champion, it it profoundly changes the discussions that you're part of. It profoundly changes the campus culture. And it hopefully it should profoundly change the student outcomes. Now that might be pie in the sky. I'm Pollyanna, I get it. But I feel like as professionals, if not us, then who? And that's something I say all the time to my team: if not us,
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Right. Yeah. Yeah.
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then who? And so So that's where I would land on that one.
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You know, you're what you're also talking about though is a shifting of ownership so that the ownership of data is not just in the IR office.
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No.
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It's it's moving when I went to Cali, one of the first things that I shared was that one of my mottos was moving it from me to we. And at first that's rather intimidating for you know your colleagues who who don't work in data. however, with patience and the right types of relationships that you talked about, they you begin to see shifting and changing. And you know, just
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Yeah, yeah.
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like your example, I had a faculty member call me. We'd we'd had the tableau dashboards, we'd been doing academic program review in them for I think two or three, three-year cycles, and she called one day and said, I've been thinking, our program is different from all of the others. Could we add this? And before I could ask her, she said, and here's why. And she explained it to me. I was so proud. That was a huge
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Mm-hmm.
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moment for me.
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Yeah, because it acknowledges the fact that you have built competency in someone who is not that's not their main line of work.
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Right. Well, and not only that, but she felt comfortable. She didn't She probably worried about am I gonna sound stupid? But she still called me, she still asked. And it was a terrific addition that I hadn't thought of because I don't teach her subject. So yeah, culture, culture,
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Correct, correct. Yeah.
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culture. The data can be perfect, it can be clean, you can win a prize for it. But if you want sustainability, if you want to be able to shift at the organizational level, if you want to impact students at scale, you have to have that culture.
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Well and and I want people to be upset, offended, and angry if something you built provides value and is now no longer there.
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Yes.
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See, that's the hallmark of success, right? apathy doesn't help us. We we need people engaged. You know, and and and if I if you if you permit me, I would say that that my close second tie, because it just ties directly into what you just said, was to behave as a connector and to break down data silos. Because that's another area that I think we have to look in the mirror as a field and acknowledge we're missing the boat on some things. Specifically HR data for staff. We do a lot with faculty, but hardly anything with staff. Finance data, real finance data, general ledger, commitment control, right? Cost margins, net, you know, price
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Right.
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impact. And and really unpacking, I think, the research data. Because if you're gonna create a data culture focused institution of higher education, the IR role has specifically been historically pigeonholed within academic affairs. And we need to open up those blinders. If we're gonna be advocating for data on our campus, then we have to be in conversations in areas that are not comfortable to us. And and it raises all boats. Even if IR doesn't ultimately end up doing the work of financial analysis, but you partner with the people that do, you're creating that culture where there's a shared vision for how data can elevate the institutional outcomes. And the last thing I'll say, and I'll leave on this, is you know, eight. Does an annual survey of presidents every year. And I often would laugh out loud when the one question that they would ask presidents is how important is data to you and data informed decision making in your campus? And they would always say, very important. But then the next question was: where are you putting your financial priorities and your spending? Data and technology fell to the bottom. So
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Yes.
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we have a fundamental opportunity, I believe, as IR practitioners, to help influence some of of those decisions and and show our value in new ways beyond just the I need the ad hoc 19-C every first Monday of the week. You know it we've got to change our practice and we've got to open it up to include a culture view and a and a view of adaptive leadership that that really elevates the role from just being technical to being technical and functional.
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So I agree with everything. Yeah.
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Yeah.
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So thanks again for being a guest. I've attended your AIR forum sessions in the past, and I think that our listeners will agree. You can see so clearly your dedication to the creation of meaningful data work grounded in integrity and focused on student success. So thanks again. it was so great. You know what's gonna happen 2027. You're gonna get another email from.
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That's okay. Anytime Danny. Anytime. Anytime.
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me. I'm gonna say what what are you talking about now? What
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Because I mean this is the and thank you for that. Because and thank you for this opportunity to talk with your viewers because it is something I'm passionate about. And it's something I want to help more people unpack their skills in. I I've just seen it firsthand that when you add these components into your toolbox. you're not pigeonholed in the same job for your entire career. It opens up opportunities. It allows you to advance professionally. It allows you to to do more with with your office. It allows you to do more with your role. And who wouldn't want to be a part of those kinds of conversations? And so thanks
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Agreed.
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for the opportunity to elevate this.
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Agreed. So listeners, thanks for joining us for another episode of Data Stakes. Data Stakes is sponsored by the Data Analytics Alliance for Higher Education. You can visit our website to learn more about our upcoming quarterly meetings. And you can also join us. We're several hundred strong. We meet four times a year, and in a few weeks we'll be having more meetings focused on AI. If have any questions about today's conversation, don't hesitate to reach out to me at dephelps at datatelligent.ai. See you next time.
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Thank 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 the importance of campus culture, why it matters, and how to leverage culture as a foundation for successful and sustainable data work. My guest today is Dr. Jason Simon. Dr. Simon has over 30 years of leadership experience working with enrollment management, finance and administration, academic affairs, alumni relations, and student services as a leader in higher education data analytics and research roles. His service to the IR and IE community at large includes current work. As a co-instructor for the AIR Leads Leadership Development Curriculum and as a contributing author on the 2019 statement on analytics, Analytics Can Save Higher Education Really, jointly produced by EDUCAUS, AIR, and Nakubo. Jason, it's great to see you again. So in
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Likewise, right back at you. I'll be here.
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Yeah, it it it is great, always great. In 2025, you announced that you were not retiring, but rather you were rewiring to become the co-founder of SCL Impact LLC. So, congratulations to you and to the campuses who are going to benefit from your knowledge. And today we're going to share from your 2026 AIR forum presentation, Analytics Without Culture, a recipe for stalled progress. And let me just start by saying I think this is something that is really underestimated on campuses. We focus a lot on technical abilities. we focus a lot on data cleanliness, and all of that is really important. But you're gonna talk to our listeners today about why culture matters. So let's stay set the stage with that, with you sharing why should they care? Why does culture matter?
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Well, I I I believe from my perspective, we throw a lot of time, energy, and resources, as you were saying, towards the technical elements of the challenges we're facing as data practitioners. But it it's ironic to me that even institutions with almost unlimited financial resources, large staffs, robust technology platforms, they still are struggling. And so that tells me that the answer is not just on the technical investment as well. And so the culture component is what is probably preventing a lot of practitioners from achieving the levels of success. And I would also say what their executive sponsors, presidents, trustees are hoping for as well. And so by taking a culture-oriented approach and creating an opportunity to layer that on top of the technical approach. I believe it gives leaders a much more robust opportunity to really analyze the situation that's going on in their ecosystem. And it also, I would say, honors the fact that every institution of higher education has a different culture. Just because something might have worked at one institution doesn't mean you can lift and shift it to another one and expect the same results. and lastly, I think, and I I know we're gonna probably dig a little deeper into this, but there's a name for all of this, and it's called Adaptive Challenges. And adaptive challenges really stem from the work of of a professor at Harvard, Heifritz, who wrote a series of leadership books on this topic. And the theory is is that the technology is not gonna be the root of the challenge. It's people. We are all social animals, we're all social beings, and we all contribute to a campus culture. And by By divorcing, if you will, the human element of our work, it's really setting us backwards, in my opinion.
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Right. Yes. I totally agree. Totally agree. And all all of that is familiar to me. I did my master's in organizational leadership. And so you are really speaking to to to what really resonates with me. So you included a collection of interesting quotations in your presentation. So here are two winners that popped out for me. So I I even assigned them categories, okay? So in
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Go for it.
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the most controversial category,
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Yeah.
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data is like garbage. You better know what you're going to do with it before you collect it from Mark Twain. And in our most uncomfortable truth category, data, data everywhere, but not a thought to think. From John Allen Paulos. So why did you choose to include these quotes? And are they connected to uncomfortable confrontation that happens when we try to address internal challenges?
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definitely. I mean, if we take the garbage quote for example, how many times in our roles have we been asked, Well, I just need the data? Or I want data that that we as data practitioners know doesn't exist. And so, sure, I can build you a relational table. Sure, I could build you a technical connection that allows you to have access to data you don't have right now. But the underlying question is for what purpose? And and from a from a pro-data culture perspective, we're trying to enhance data literacy, right? And and so a part of data literacy is understanding appropriate uses for data resources. And so it doesn't make sense to me to boil the ocean and create this massive data lake or data warehouse if the institution culturally isn't even prepared to deal with the data that we uncover. And so it is kind of like garbage because then we're just sort of farming it together without ever really understanding the higher purpose for it.
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Right.
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Right. And and so I believe that that is a cultural phenomenon because oftentimes Cultures will exist where people will just constantly ask for more and more data as a stalling tactic to not address making the difficult decision. And so it does
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Yes.
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pile up. It it becomes like piles of garbage. And in my presentation, I showed the opposite of that, which was from a garbage heap to sort of like a recycling company where there was piles of like minded data that were situated. And it was there was some thought behind which pile goes where and why. and so I believe that that is really a key purpose for that. And then the second quote, which I really like, is, you know, just because we're surrounded by data doesn't necessarily mean that people know how to understand it or use it. And so how many times have we heard in our practice the the end of one examples? Well, I know a student who said, or I met an advisor who thought, or
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Yes.
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as a faculty member in my class, and and in reality that doesn't also help support a pro-culture campus because we're allowing individual opinions then to drive larger decisions that from an ecosystem perspective aren't really appropriate.
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Right, right. So it it reminds me of some guidance that we received at my former institution when we were part of the recent cohort invited to do the Aspen Institute.
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Right.
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And the advice was that we needed to be able to demonstrate initiatives that had scaled up. It's exactly what you're saying, not just something that helped 30, 40, or 50 students, even though they acknowledged that was really important, especially on a small campus. But they wanted to see the things that impacted the majority, how we'd made widespread cultural shift. And then the other thing I was thinking about as you were talking about the the data is like garbage, is one of the firm rules I had all throughout my career, which took a little training for my coworkers, was they would use my email, request a data set, and I would email back, hi, what's your research question? What are you going to be doing with this? How are you going to be using the data? Who who are you going to share it with? What you know? And at first that was met with a little, well, what's it to you? attitude. But then afterwards, my colleagues began to discover that that initial conversation was really quite valuable and actually saved time. Because if I don't understand what you're going to do with the data, how do you know I'm not going to give you garbage?
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Wa well it also positions the IR function then As being an ally in the institutional research, not the IR research, but the faculty members research
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Yes.
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priorities. And and from my perspective, we did similar things. We would ask them for the research questions. We would also ask them for very specific details on the cohorts that they were interested in. We would ask them follow-up questions on our form. So we weren't going to do the back and forth 35, you know, ad hoc requests until we actually figured out what you want. And
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Right.
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and A culture perspective that also created real opportunities for us to partner with our Office of Sponsored Research. And then the Office of Sponsored Research, the vice president, would bring us in to do trainings for faculty researchers. And so it created not just a cultural implication of hey, you can't ask for data hypothetically, this never happens, the day before a grant is due.
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Yeah.
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likewise, it also created a situation where the for From a culture perspective, the IR office positioned itself then as being an ally with that faculty member. And
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Yes.
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that that blossomed into real opportunities, even beyond that one individual research project, because now we had a cohort of individuals who went to bat, if you will, for the
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Yes.
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data function at the institution. And that's the kind of things we're talking about here today. Is is it's it's those soft skills that IR needs to embrace. Know we're all trained from a practitioner-based model. The person who trained you is probably trained by their boss and IR. There's no master's degree solely focused on institutional research. Maybe there's a course here or there. And so it really is institutional culture. And so I feel like one of my hopes and dreams, if you will, for our field is that I wish we had more opportunities to dig into conversations like you and I are having today, because it's the differentiator, I think, and it really can boost an individual's performance. Performance, make an impact on our students, but also set them up for a future career that they're viewed as an expert. And that's what we all want.
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Right, exactly. So I know you want to circle back to the importance of adaptive leadership for data professionals. and I really loved this statement from your presentation. Almost every adaptive challenge is directly linked to campus culture. So let's talk about what an adaptive challenge is as opposed to a technical challenge and why you think adaptive leadership skills are the key to changing culture.
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Well, obviously, you know, technical is typically focused on a problem, right? What's the problem we're trying to fix? Adaptive challenges typically work best when we're trying to understand what we need to learn. So that's your first your first clue, if you will. Is it a learning issue? Second, technical problems oftentimes don't require people to lose something. Whereas an adaptive challenge requires individuals to have a loss. Now, that might be in in autonomy, that might be in individual decision-making ability. That that might just be in having to come to terms that they're wrong, right? About something. And so that that is really a big differentiator. And typically, adaptive challenges are also ones that are not as easily to see on the surface. They're usually the things that are inextricably linked as as you just said to culture, which is norms, symbols, values,
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Right.
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beliefs, how the campus allows data to either be utilized for good or weaponized, right? As a punishing tactic.
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Yes.
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That that is all part of adaptive challenges and culture. Also, adaptive challenges in my mind are the reason why you can have the best strategic roadmap for a data maturity process or a new data warehouse, etc. But but it's the adaptive challenge. So, what is the relationship like between IR and IT? What is the relationship between the folks that are doing data quality work and data cleansing work and the folks that are just building out table structure? So your data modeling team. Though those are all adaptive, they're not technical. because it comes down to competing priorities, timelines, purposes. And so what I'm urging is institutional researchers, if they really want to be an effective data culture leader, they've got to begin to embrace the really hard parts of our job, which are the relationships and the people. And
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Yes. Yes.
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and not also just work with people that you feel like you like and they like you.
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Yes. I was thinking about that. Yes. No.
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It it right, right? That's the hard part, right? The hard part is building those allyships across your institution.
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Yes.
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With folks who may have been your harshest critic, who you
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Yes.
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just maybe need to take out to lunch or coffee and say, Hey, you behaved or said this in a meeting. And I I wanted to unpack that with you so I could better understand where you are coming from. But notice how I did that. That wasn't, hey, I felt offended from you and
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Right.
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I felt I'm angry at you. No, I want to learn. And that's the adaptive piece. adaptive leaders want to continually learn, and they want to learn more than just the facts. They want to learn
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Yes.
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the people, the beliefs, the feelings. So
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Yes.
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hopefully that sort of unpacks that a little bit. And and and I would encourage your listeners to really read up on adaptive leadership because I think they'll find that it offers real opportunities, especially from a reflective leadership perspective. I believe very heavily in reflective praxis where you look backwards and then think about how it informs the future. And as I dug into adaptive leadership, the I I s things became clear. You know, why someone might have behaved one way or why a certain leader did something one way or maybe why something fell off the rails and we had to put it back on the track. and so I think it's a valuable exercise to to think beyond just the technical toolbox.
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Yes. So what this means is we have to, as data professionals, embrace a side of ourselves that maybe even makes us uncomfortable because this takes a certain amount of emotional intelligence. And and
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Mm-hmm.
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let's face it, we have a lot of colleagues who, when they signed on to a data role, it was not necessarily one where your door was open. You know, you
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Mm-hmm.
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you got to stay in your safe space, and you really didn't have to, you know, deal With a lot of colleagues, and but I think we're seeing more and more of that as campuses shift to having institutional effectiveness roles, which indicate this expectation that you're sharing. You know, one of the things that are really underestimated at the beginning of my career was how much fear plays a part in strategic planning. So strategic planning has always been in my role because it's supported by data. Great piece of advice I got during my first strategic plan was from a president who said, I noticed you have only invited people that you already get along with. I want you to invite and he he named two people who would have been like, get out the cross in the garlic. I was like, I I don't want to, I don't want to. And he his his response was, No, this will stretch you. You will grow, you'll learn to to to to know them better. And if you're successful at this. They might be new allies. And you know, those beginning meetings were very uncomfortable because we were working to revise the mission statement.
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Yep. Yep.
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And but it was so worth it. It was so worth it. And I had another situation where I was an interim for another administrator for a little while and had to work with faculty on outcomes assessment. And I literally sat and listened to a faculty member yell at me for 10
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Yeah. Yeah.
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or 15 minutes. And when it was done, just like you said, I I didn't tell him how it worried me or a upset me, it was to to say, I understand. I'm sorry. Because he taught career and technical education. And he had it had been objectives and then it was outcomes and then it was something else and now it was outcomes again and he was tired. He was tired. And it was right. Yes. But that's part of
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Yeah. And and you weren't the target, you were just the outlet for his frustration. And and that
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culture.
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it is a part of culture. And and my example would be, you know, when we first because when I first joined my previous employer, we were still using a PDF paper fact book. No joke, three hundred and sixty-four pages. And by the time I left, we had a full machine learning data science capability. And we went from paper to dashboards. And when we were first introducing the program, I we didn't just drop a new tool onto the institution. I went around and talked with all of our deans. And one dean in particular said, It doesn't matter what you bring. I can't, I don't have the mental space right now to learn yet another system at the institution. There's so much on my plate, I can't take it. And and that was an important lesson for us because We we at least had the value of having those conversations before we even announced what the tool was. So we knew by the time I left, that was the one dean who would have taken the hill with me if the system had had had to go away, because she now saw the value. in that investment and she felt heard right and she felt like that that she was was a participant in the creation of that tool and from a culture perspective one of the things we did very intentionally and I recognize that people are gonna listen to me say this now and go I don't have time for that but we very specifically introduced sort of like concierge training to a select group of individuals who I knew had the ability to talk to their peers And create positive messaging for me. And it's a force multiplier. And that's the other piece. Excuse me. A lot of our IR shops are one-person shops that and they're expected to do so much. By building these kinds of allyships and relationships, you create an opportunity then for your message to be expanded more broadly because it's not just you out there preaching. And that's the other piece, too, I think, from a culture perspective. Yeah.
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Yeah. So important. So you listed six key takeaways that lead to what you call a culture in action. So can you speak more about three of them? And here they are: making
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Okay.
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sense of your institutional culture, deciphering leaders' words and actions, and responding
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Mm-hmm.
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to change.
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Sure. I would say, and maybe I'll just lump them all together under one general rubric, which is we we no longer can afford to be the fish in the fish tank not seeing the water. And we've got to start to look more critically in the ecosystems and where we work. And one of the ways that that I would say practitioners can do that is by even if it's just a half hour a month. Taking some time, being reflective, and asking yourself, and maybe even having it as a team discussion, if you have a team, what is happening within our campus right now from a data perspective that we need to be paying attention to? And from my perspective, we have to first to thine own selves be true, right? We first have to understand what our perspective is. Then we have to begin to look at the campus community and start asking bigger questions. Some of those really important questions to me are why do new initiatives fail? and that's a really fascinating project to look into or unpack. another really good question that I like to ask is what is being said versus what is being intended? Because sometimes we know that that what is said is not exactly what the intent is. I Always encouraged my team to either go or to join if it was being web hosted into the State of the Union address from our president because I needed for my team to also hear what I was hearing about the institutional perspectives and priorities. And then I would come back and we would have a facilitated conversation about reading between the lines, what was said, and then what how is that going to now impact us as a team and impact our data ecosystem? and then the last point that I would make is you know. Part of the practice in my mind is, and it kind of builds on our last conversation, having those uncomfortable conversations with folks on campus who maybe could offer you a different perspective on the work that you do. And that I I get the inherent risk. I get the inherent that doesn't feel comfortable. I I get the inherent I'm putting myself in a dangerous position because I've heard this in my feet in my career. Well, if we ask the question and they tell us the answer, that means we're gonna more work to do. And and in my mind, I would rather have those difficult conversations and understand what the expectations are than be judged or my office be judged or my function be judged against a litmus that I don't even understand.
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Right.
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And so it it to me, all of those taken together, it it creates this need for IR practitioners to run a different race as opposed to the horse racing where the blinders are on and we're only looking one direction ahead. But really think about if every to your point, every strategic plan initiative is tied back to data and we're the data team, then
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Yes.
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we are inextricably involved in the success of the institution, even if our leaders don't recognize that to the level they should, we don't, we do. And so from my perspective, it's just adding tools to an already technical toolbox that are more here we go, full circle, adaptive in nature that allows you to recognize the need not just for technical subject matter expertise, but functional subject matter expertise that includes human relationships.
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Yeah, so totally agree. So I know you weren't expecting this, but let's let's flash back to to a regular survey that AIR does. And that is when we would fill out information about the function and our role on our campus. Okay. So
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Sure. Love that survey.
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let's you know, and I in in my early career I did not report to the president. but at my first institution a president came in that's that expressed exactly what you've said. We involve data in everything. Why isn't Debbie on the administrative council? Why isn't art you know? And so if Listeners, you do not sit in a place where you feel you can effectively move culture because of your role. Maybe it's time to talk to your dean, your provost, your president about how to make your role more effective. Because you can only function within the within the fence around your field. Does that make sense? If your pasture isn't very big, here comes the Cansan in me. If your pasture isn't very big, you really can't wander into other areas because people will people would say to me, Well, you work in student services. Why
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Mm-hmm.
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why are you making suggestions to us in academic affairs? But then I got lucky and I was moved to academic affairs and worked for a dean who it helped me expand. my role. She legitimized data on our campus. And that's what led to eventually becoming an administrator with even greater reach and ability to affect culture.
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Yeah, you know, and this is one of those challenging ones where I would always build in and it drove it drove my my drove my team a little crazy. So I will admit this may not be a best practice for everybody. But I would build in 15 minutes before and after any meetings that we had in the main administrative building. I was housed in the main administrative building for many years and then we were moved to part of an IT collaboration. Let's get everyone to do an open office, speaking of no walls. But I would build in that extra time and I would literally just pop in. If I saw someone was in their office and I had, but but I built a relationship over time. I didn't just do that on my Very first day. But
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Right.
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but I wanted to be out there and those conversations in the hallway, those conversations that were just bumping into people. it might look like it was unintentional, but no, there was actual strategy around that because I wanted to have that touch point with those individuals who were in the conversations that I was not, and would allow them to then begin to help me. Spread my case for why the data function is important.
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Right, right. And all of that impacts culture and and building elections. Okay.
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Okay.
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So you ended your presentation at forum by challenging attendees to embrace one of the nine data forward behaviors you recommended as catalyst to culture change. So let's end our conversation today by sharing our favorites from your list. And I'll go first. so these all were so critical. But for me, I liked this one. Behave with confidence, make data a non- Negotiable in decision making. That has been a drumbeat, a drumbeat throughout my 20 years in higher education. It's even the impetus for the name of this podcast, data stakes. Data deserves a seat at the table. I firmly believe that. And that IRIE professionals should not be viewed just as the person who does all the external reporting. Well, what does Debbie do? Well, she does iPads. That's always how it starts out. Isn't it? But instead, as an important administrative asset who helps to guide meaningful changes on every campus. Because without data, where does the conversation even begin? It's it's like you said, is it built on anecdote? That's not enough. I think between data and context. And to learn context, you have to have allies. You have to have conversations.
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Well, yeah. And in my mind, I mean, let's face it, if we can be honest here for a second, higher ed is i isn't exactly in a well perceived public state right now. And
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Yes.
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and that's I think that's being a little generous. And one of the criticisms of I think our field, writ large. Is that disconnect between outcomes driven behaviors and practices and what makes sense? You know, how many times have we heard we'll just be more like a business? We're not a business, we're higher ed, right?
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Yeah. Right.
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Now we have certain elements of what we do that that mirror those corporate ecosystems. But no, if we go back to the founding of higher education, all the way back to, you know, pick pick one, either sub-Saharan African institutions that have started in the in the in the early zeros, all the way up to England and you know, German institutions in the thousands, right? So th this is not new, but my perspective on this is that we as practitioners need to be comfortable calling use a bad word, I'm from New Jersey, but calling out things that aren't true when we sitting in meetings, when we're part of discussions, when when we are hearing things unfold and we are in the room and not taking the moral high ground to say, well, what does the data tell us about this? And and I by the time I I rewired and left my last institution, one of the things that that I felt most proud about was several VPs came up to me at At the going away congratulations event. And they said, you know, the one thing that we always could rely on you is to tell us the truth, the facts.
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The truth.
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the facts and and to not to not use hyperbole and to not sugarcoat and to not we we just knew where we stood in terms of the data with you. And and I took that as the ultimate compliment because that that was part of my toolbox, right? You you can't
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Absolutely.
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you can't misuse data if you're afraid to even tell people what it is. It does take courage. It does.
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Yes. Yes. It takes courage. It it it takes courage to work in data. It's it's yeah, it's not for everyone, but
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But no, it's not. But but you when I but when I'm working with IR teams and consulting and coming in for doing staff retreats and those kinds of things, these topics always come up. And part of my sh my goal at this phase in my career is to still give back to higher ed, but I want to do it by educating practitioners. to be the force multipliers at their own institutions. I I wanna just not contribute anymore at one institution. I wanna help the entire field. Because as a first generation student myself who broke literally four cycles of poverty, four generations of poverty, Higher ed was a differentiator for me. I mean, I'm on a completely life, different life trajectory now because of the role that higher ed played for me. And so for me, it's a it's a it's a social and ethical calling. And so why wouldn't we want people to use information resources to make better decisions when it has profound outcomes on people? You know, we're we're so quick to talk in our field about graduation rates, retention rates, enrollment counts, D FWI grade distributions that we oftentimes think I think we forget the individual impact on the student's life. And you know, and so from my perspective, it that's something that I think we as a field of practitioners could do a better job is really understanding and and and sharing and I mean sometimes yes, taking a hill and planting a flag and saying we are gonna talk about the uncomfortable data that this situation encounters. So
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Right, right.
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yeah.
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So which one of those nine was your pick?
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That was hard. That's like asking a parent to pick their favorite child. well, because I tr when I wrote these, I tried to create them in such a way that I felt like they they hit on different aspects of culture, right? Probably
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huh.
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the one for me. all right, I'll I'll say behave as a champion, promote data literacy across all roles. That that to me is is huge because when I say day l data literacy, I'm talking about helping people understand the sources of data. The way data is gathered, collected, and utilized, the use cases for that data. And lastly, in the piece that think we often miss in the field, the return and investment of leveraging that data. What was the good that happened? How do we measure that good?
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Right.
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And data literacy, from my perspective, meets the individual data consumer at the institution where they are. It doesn't assume anything. And so when we put our program in place at my last institution, we had entry courses, we had secondary courses we had we had a virtual online training that people could take through the HR training platform that was a short video presentation and and one of our goals for that was to help people ask better questions of the data And and
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Yes.
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it was remarkable to watch how the ad hocs changed. And my my team both loved it and hated it. And they cursed my name and sometimes they didn't. But the reason why was we found that the questions, the the super simple questions were no longer coming in because people we were training people to use our dashboards, we were training people to use our data products. The questions that were coming in were the really thorny, sticky ones. And that's how we knew we were being successful because now people were asking us questions at a level that told us they were no longer data agnostic. They were really data literate. And and that is that should be our goal, right? I mean, we
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Yes. Yes.
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wouldn't it be great to not have a a a frontline entry level analyst handle the same requests every single day. From a professional development perspective, that's how we burn our staffs out. That's why they leave.
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Right.
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So so giving people the ability, it it Raises all boats. And so if you behave as a data champion, in every sense of the word, a champion, it it profoundly changes the discussions that you're part of. It profoundly changes the campus culture. And it hopefully it should profoundly change the student outcomes. Now that might be pie in the sky. I'm Pollyanna, I get it. But I feel like as professionals, if not us, then who? And that's something I say all the time to my team: if not us,
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Right. Yeah. Yeah.
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then who? And so So that's where I would land on that one.
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You know, you're what you're also talking about though is a shifting of ownership so that the ownership of data is not just in the IR office.
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No.
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It's it's moving when I went to Cali, one of the first things that I shared was that one of my mottos was moving it from me to we. And at first that's rather intimidating for you know your colleagues who who don't work in data. however, with patience and the right types of relationships that you talked about, they you begin to see shifting and changing. And you know, just
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Yeah, yeah.
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like your example, I had a faculty member call me. We'd we'd had the tableau dashboards, we'd been doing academic program review in them for I think two or three, three-year cycles, and she called one day and said, I've been thinking, our program is different from all of the others. Could we add this? And before I could ask her, she said, and here's why. And she explained it to me. I was so proud. That was a huge
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Mm-hmm.
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moment for me.
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Yeah, because it acknowledges the fact that you have built competency in someone who is not that's not their main line of work.
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Right. Well, and not only that, but she felt comfortable. She didn't She probably worried about am I gonna sound stupid? But she still called me, she still asked. And it was a terrific addition that I hadn't thought of because I don't teach her subject. So yeah, culture, culture,
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Correct, correct. Yeah.
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culture. The data can be perfect, it can be clean, you can win a prize for it. But if you want sustainability, if you want to be able to shift at the organizational level, if you want to impact students at scale, you have to have that culture.
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Well and and I want people to be upset, offended, and angry if something you built provides value and is now no longer there.
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Yes.
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See, that's the hallmark of success, right? apathy doesn't help us. We we need people engaged. You know, and and and if I if you if you permit me, I would say that that my close second tie, because it just ties directly into what you just said, was to behave as a connector and to break down data silos. Because that's another area that I think we have to look in the mirror as a field and acknowledge we're missing the boat on some things. Specifically HR data for staff. We do a lot with faculty, but hardly anything with staff. Finance data, real finance data, general ledger, commitment control, right? Cost margins, net, you know, price
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Right.
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impact. And and really unpacking, I think, the research data. Because if you're gonna create a data culture focused institution of higher education, the IR role has specifically been historically pigeonholed within academic affairs. And we need to open up those blinders. If we're gonna be advocating for data on our campus, then we have to be in conversations in areas that are not comfortable to us. And and it raises all boats. Even if IR doesn't ultimately end up doing the work of financial analysis, but you partner with the people that do, you're creating that culture where there's a shared vision for how data can elevate the institutional outcomes. And the last thing I'll say, and I'll leave on this, is you know, eight. Does an annual survey of presidents every year. And I often would laugh out loud when the one question that they would ask presidents is how important is data to you and data informed decision making in your campus? And they would always say, very important. But then the next question was: where are you putting your financial priorities and your spending? Data and technology fell to the bottom. So
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Yes.
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we have a fundamental opportunity, I believe, as IR practitioners, to help influence some of of those decisions and and show our value in new ways beyond just the I need the ad hoc 19-C every first Monday of the week. You know it we've got to change our practice and we've got to open it up to include a culture view and a and a view of adaptive leadership that that really elevates the role from just being technical to being technical and functional.
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So I agree with everything. Yeah.
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Yeah.
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So thanks again for being a guest. I've attended your AIR forum sessions in the past, and I think that our listeners will agree. You can see so clearly your dedication to the creation of meaningful data work grounded in integrity and focused on student success. So thanks again. it was so great. You know what's gonna happen 2027. You're gonna get another email from.
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That's okay. Anytime Danny. Anytime. Anytime.
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me. I'm gonna say what what are you talking about now? What
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Because I mean this is the and thank you for that. Because and thank you for this opportunity to talk with your viewers because it is something I'm passionate about. And it's something I want to help more people unpack their skills in. I I've just seen it firsthand that when you add these components into your toolbox. you're not pigeonholed in the same job for your entire career. It opens up opportunities. It allows you to advance professionally. It allows you to to do more with with your office. It allows you to do more with your role. And who wouldn't want to be a part of those kinds of conversations? And so thanks
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Agreed.
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for the opportunity to elevate this.
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Agreed. So listeners, thanks for joining us for another episode of Data Stakes. Data Stakes is sponsored by the Data Analytics Alliance for Higher Education. You can visit our website to learn more about our upcoming quarterly meetings. And you can also join us. We're several hundred strong. We meet four times a year, and in a few weeks we'll be having more meetings focused on AI. If have any questions about today's conversation, don't hesitate to reach out to me at dephelps at datatelligent.ai. See you next time.
