Casey Green:

What are the priorities for doing better? Because some are more attainable in a short period of time, but with fewer or more resources than others. And how do we kind of do that? Triage? what are the specifics for doing better? What does doing better look like in terms of instruction, academic performance, administrative resources and services, a whole bunch of things. And, and how do we get consensus of that? You know, your experience, Joe, about doing better may be very different in terms of my list of doing better, but at least have, let’s have that public conversation. If, if we’ve got 20, let’s pick six where there’s consensus and prioritize those as opposed to arguing about 19. You know, 17, 18 and six.

Joe Gottlieb:

That’s Casey Green, an award-winning researcher, author, and consultant. His work draws on more than four decades of research, consulting, and experience in the higher education arena, focused on IT planning and strategy, institutional strategy, professional development, and labor markets. Launched in the 1990s, Green’s Campus Computing Project has been widely cited by both campus officials and corporate executives as a definitive source for data and information and insight about critical planning and policy issues affecting e-learning, online education and information technology in American higher education. We had a great, albeit lengthy conversation about myths, trends, and forward-looking best practices in higher ed. I hope you enjoy it.

Welcome to TRANSFORMED, a Higher Digital podcast focused on the new why’s, the new what’s and the new how’s in higher ed. In each episode, you will experience hosts and guests pulling for the resurgence of higher ed, while identifying and discussing the best practices needed to accomplish that resurgence. Culture, strategy and tactics, planning and execution, people, process and technology. It’s all on the menu because that’s what’s required to truly transform. Hello, welcome and thanks for joining us for another episode of TRANSFORMED. My name is Joe Gottlieb, President and CTO of Higher Digital, and today I’m joined by Casey Green, creator in 1990 of the Campus Computing Project and award-winning analyst in higher education. Casey, welcome to TRANSFORMED.

Casey Green:

Joe. Thank you for the invitation to participate in this conversation. I, I think it’s gonna be interesting, engaging, informative. That’s my hope.

Joe Gottlieb:

Excellent. Well, let’s dive right in. I hope that we can talk today about three topics. And I think this actually is gonna be become a three-part series, so we make it easier on our listeners. And so those three topics are past myths in higher ed, present trends in data happening in higher ed, and future practices required of higher ed. But first, tell me a bit about your personal journey and how it’s shaped your perspective on this industry, which we both find so fascinating.

Casey Green:

Yeah. Alright. Thank you for that opportunity. I think, like, a lot of folks who work in higher ed, I’m an accidental academic. You know, we get recruited, most of us don’t live in environments where we have role models as academics. You know, we get to campus and then somebody taps us on the shoulder and says, you can do this. And that’s certainly what happened to me in many ways. My undergraduate and later graduate career, I did my doctoral work at UCLA under Sandy Aston, but it was Alexander w Aston Aston and the Fresh Annual Freshman Survey, which is the largest continuing empirical study of in American higher education effectively, was doing big data before big data were big data, surveying hundreds of thousands of students annually, he and his colleagues, and then doing follow-up studies with those students to look at multivariate analysis, to look at institutional impact.

Casey Green:

I intentionally went to UCLA ’cause I wanted to apprentice myself into that program and with him to learn how to do that. After finishing my ate, I stayed on at UCLA at the Higher Ed Research Institute for another eight years as the operating officer. And about this time, this is the early, mid late 1980s, all of a sudden we have a new kind of technology coming in that didn’t require me to go sit in front of a CRT screen in the computer center, but allowed me to do some stuff on the desktop primitive by today’s standards, but advanced at the time. And I became quite interesting, enamored, kind of drawn into that kind of, that shifted some of my research focus in 1989. I left USC, went to UCLA, went to USC Center for Scholarly Technology, where we launched the campus computing project as a way to kind of do data feedback benchmarking for not just the IT community, but for the campus community.

Casey Green:

But a series of primarily initially academic and later broader IT issues because the boundaries that separated academic and administrative computing were quickly dissipating in the early nineties with the emergence of the internet campus environments and other kinds of stuff. So, launched the campus computing project in 1990. We did annual surveys of, of IT leadership, a lot of other work related to these issues that, that project ran for 30 years. I finally closed it down in 2019 and did a lot of other stuff along the way. Worked provosts working with presidents, working with campuses, working with technology providers to, to kind of foster a conversation between groups on campus or between the provider community and the campus team. But how do we do this better? Because in higher ed we can’t advertise our mistakes. We have to share information towards a common goal of how do we do better? You know, what have we done well? What do we, and what do we need to do better? And how do we do that? Let me stop there.

Joe Gottlieb:

Well, I love your background. You’re, you’re multiple things about it are just so fitting for a conversation like this because A, you’ve been watching this for a long time and you have a great grasp of the history of how higher ed has evolved to present day and, and therefore a great vantage on, on where it could be headed. But importantly, within that, from the very beginning, as you pointed out, you’ve been approaching this from through the lens of the best data available. And so to me, that speaks to the practicality and the reality of forcing oneself to look at data rather than opinion or, or rhetoric and the light, even if it sometimes requires some rhetoric to get that point across <laugh>.

Casey Green:

Of course.

Joe Gottlieb:

So I’m looking forward to this. Go ahead. Good.

Casey Green:

Where do you wanna begin?

Joe Gottlieb:

Well, let’s, let’s dive into our topic one of three, and that is past myths in higher ed. We’re gonna have some fun here, but what are some of your favorite myths that have existed in higher ed, particularly in the areas where perhaps technology’s been oversold?

Casey Green:

Alright, so the first might be academic productivity. That sounds like an oxymoron for many of us. You know, at least on the model of traditional economics, that historically some increment or investment technology should yield some productivity. We have a hard time proving that we can sort of do that with some operational stuff. Hard to do it in many by traditional metrics in terms of a return on investment with a lot of the academic enterprise. The second is about administrative systems, data analytics. You know, most recently the cloud will save us money. You know, we’re gonna get off, we’re gonna go off prem, we’re gonna save a lot of money migrating to the cloud. That’s not been well documented. It’s been proclaimed frequently, but not well documented. You know, the cloud shifts some of your expenses and provides some other benefits, but that’s not necessarily the case.

Casey Green:

I think that the other part of that is quite honestly, kind of the overpromise and underperformance of administrative systems in terms of data and analytics. When I began my career, the only thing you could get out of an administrative information system effectively was credit our matrices. They were flat this quarter, if you wanted to do a cohort, cohort flow, how many freshmen came in in one year and how many graduated four years later? You had to take the individual tapes, merge ’em together on a student, ID throw it over the wall to the IR office or a third party contractor to run those data. Today, the systems are so much better, but consistently over the course of the last 12, 15 years, as I’ve done surveys, presidents, CFOs, provost CIOs, only about a third say that they, their institution really does a good job of using data for campus planning and policy making. That’s been a pretty number over 15 years. That’s troubling. We continue to do too much of this stuff on the basis of opinion and epiphany and not on the basis of evidence data. And how do we connect the dots to move forward, to do as, as my mantra is, how do we do better? We have to do better, and we’ve always had to do better. The stakes are just even higher now, or they seem to be,

Joe Gottlieb:

Well, let’s, let’s double click on each of those in order. I think the first one, ac academic productivity, that’s what you called it, right? Academic productivity. Mm-Hmm.

Casey Green:

<Affirmative>. Yeah.

Joe Gottlieb:

I, I think it begs a little bit of context that I’d like to put on the table and see how you react. And that is this, we tend to see the whole, the, the sort of the state of academia and, and the, the relationship that academia has had with technology and for that matter, relationships with it. Mm-Hmm. As being something requiring gray scales to, to really understand as opposed to something that is black or white. We often hear about how academics are difficult to serve and difficult to include in change and, and, and get to adopt new things. On the other hand, they’ve been sold lots of bills of goods over time, and we haven’t particularly, we haven’t been particularly good at engaging them from it to academia with a service oriented model that can, can embrace some semblance of the latitude that they, they either expect or need or at least want to do their jobs. So, isn’t isn’t it true that, that, that both the perceptions of that difficulty and the overall complexity of that, of that synergy, of that relationship, it’s a bit more complicated than might meet the eye?

Casey Green:

No, it is gray. It is the elephant, and it’s the story of the blind touching the elephant. You know, what you understand depends what part you touch. Look, there, there is no question the technology tools that are today available, not just to faculty, but the students, and in many ways, students are, are often more likely to exploit them than faculty members. Faculty have made a tremendous change in terms of the academic enterprise and instruction. You know, as an, as an undergraduate, I had to wait for two days to, for the New York Times to get from New York to Sarasota, Florida. It shows up on my screen every day. If I were teaching, I could send, blow that out to my students and say, there’s something in the Times to the Washington Post, to the Wall Street Journal of some sort that’s relevant for what we do today.

Casey Green:

I can do statistical analysis on a PC that I used to have to walk over to the mainframe and wait for hours to churn. I can do inter, you know, graphics and scholarly communication and, and have this conversation with you on screen in real time that I could never do. So the, the environment and the richness and the content, no question, is improved dramatically in terms of the resources at our fingertips. On the other hand, if, if you take sort of the, the courses with most common metric of productivity, has this stuff contributed in terms of student retention and graduation rates in aggregate? Not much. You know, there have been some, there’s some stories and well-documented stories of campuses that have made investments in analytics have made investments in infrastructure, made in other kinds of investments that have dramatically moved the needle, moved the numbers in terms of student retention and graduation rates. But in aggregate across the system, we’ve not seen much great, you know, we’ve not seen significant change in terms of grad, you know, retention and completion rates at large. Again, there are ex, there are exceptions to be sure, but in aggregate we’ve not much. And unfortunately, that’s the metric that we’re most often held to. Yes. In terms of, you know,

Joe Gottlieb:

And when we look at those metrics, they are, they look back, they have to look back because they can only look back at reality. And, and so then my question, I think we’ve, we established before we, we started this effort that I sometimes come at these things with a bit more optimism and maybe naivete. And that’s why I’m, I’m really enjoying leveraging your perspective as a, as a, as an acid test for some of these ideas. But w will it be true, do you believe that as more of this technology becomes available, and, and in particular you mentioned the, the, the, the, the pathway of infection being consumer technologies or, you know, the things that everyone can use, right? And so some part of that is showing up in certain, certain individuals roles that are in academia and are in positions to be change agents within academia, whether they’re provosts or deans or professors or TAs or what have you, right? All the way down to the student co co-creating programs where we’re really getting innovative and, and open. But will we see more institutions at least leverage the, the model of a portion of the, of the community leading by example? So a certain subset of the faculty, for example, being more receptive to these new ideas. Maybe they’re younger, maybe they aren’t, but this is more sometimes about personality type and, and, and relationship that they have with technology. Will we see this picking up speed as triggered by both Covid and now ai?

Casey Green:

Maybe. Maybe. And I, you know, I’ve been described sometimes accused of being a cynic, you know, my 40 plus years working in higher ed. I, I would prefer to describe myself as a pragmatist. You know, what works in, in the quest to do better over this long period of time? And, and to, for those, those kinds of things to happen. Joe, one, recognize it’s not higher ed at large, it’s my part of the higher ed empire. I’m in a department, I’m in a community college, I’m in a state school, I’m in a, you know, residential college. My benchmark is not the universe at large. So, you know, while there’re exemplars to be sure Arizona State, Southern New Hampshire, what Georgia State did was student retention and completion rates. Just to cite three examples. Not everybody can do that, or those are not necessarily, you know, they’re, they are interesting and informative, but I’m not that place.

Casey Green:

I’m looking for stories about peer institutions, campuses like mine, students like mine, resources like mine that become far more useful. Role models. I used to tell my corporate clients, you know Ivy League schools, elite institutions, you know, the, the quest to say that their reference clients is, you know, continues. We’ve got our stuff at some place. You know, Harvard, MIT, Stanford, wherever, they’re not really great reference accounts because then there’s only 16 or 20 of those campuses. You’re better off having Mass Bay Community College or Maricopa Community College District because there’s a thousand community colleges in the country as opposed to 20 of the elites. And, and so as a president, as a provost, as a faculty member, I need reference points that are like me about what’s attainable. Can I visualize what we can do for places like me? The, the elites are interesting and informative, but they’re not necessarily instructive.

Joe Gottlieb:

I think it’s a fantastic point. I think it mirrors what we see in every industry, but we also see how industries vary in their adoption of technology forever. The finance industry has been aggressive in their adoption of technology because they’ve just been on a great role for decades in terms of achieving an ROI or, or having a necessity to accomplish the next thing that’s going on in those businesses, right? Higher ed, you could argue, is on the opposite side of the spectrum, where the mousetrap worked really, really well for centuries, if not a millennium ish, right? And, and now suddenly, if you’re like me, you see more disruption than average. And I won’t, I’ll just say that’s my personal opinion. There’s been plenty of disruptions that have led to some false promises and some difficulty in the broader community getting on board where only the elites could get on board ’cause they could afford that kind of investment. But wouldn’t you agree though that as more technology is more democratized through its evolution to become more facile, we will see more of higher ed participating in these trends?

Casey Green:

I don’t think there’s any question that we’ve had a rising lowest common denominator of technology experience, exposure ex use on the part of different pockets in higher ed. You know, the finance office, the admissions office, faculty members graduate, you know, the library, wherever it might be. But recognize that what differentiates finance on campus from individual faculty members is the finance office has a kind of command and control under the CFO. And that doesn’t occur in the same way in academic departments. You know, essentially it’s more and cajole, what incentives can I provide to you to make, to help you understand that this is ultimately in your benefit, the benefit of your program and the benefit of your students. And that’s decidedly different. And then the second part, just to backtrack a bit, you know, you mentioned a few moments ago, a lot of our expectations now are fostered about what happens off campus.

Casey Green:

We have these experiences and we see what corporations and what, what’s going on in the corporate and the consumer economy. And we say, well, why can’t we do that on campus? Or our board members who are many of whom are, you know, working corporations, we’re doing that over here at Acme Technologies should be a piece of cake to just kind of wave the digital wand for it to happen at Acme University. It ain’t that simple. There’s a whole infrastructure, you know, and, and other kinds of things. I mean, for example, the cost issues, whatever the cost is to do a technology from a particular provider, your price is not, my cost is the response from campus because, so I gotta think about the infrastructure necessary to do that, which may be hardware, may be software, may be training, may be goodwill on the part of the people who have to adopt this change in this technology, this resource.

Joe Gottlieb:

Yeah. No, it’s a great thing for you to point out. And I’d say you uncovered between finance department in a higher ed institution and the academic department, this dichotomy or, or difference in approach, there’s more command and control and finance. There’s more rules that the institution has, has adopted mostly out of, out of compliance, right? But Right. But they have them and, and on. And in the a academia we have, we have fewer rules and we have a tradition of fewer rules. And we’re, and and that’s been a part of what’s been special about it in ways it’s a microcosm of this, the differences between higher ed as an industry and what we just said about, for example, the finance industry, right? That has made big bets on technology time in and time out as a pattern. And so with higher ed, we have this complex beast that has some areas that have lots of rules and some areas that have not had lots of rules. And what’s interesting to contemplate, I think is, and I think we’re gonna get to this later in the podcast, is how might a few more rules help us advance on this along this continuum?

Casey Green:

Okay, let’s go there.

Joe Gottlieb:

But, but before we get there, I want to, I wanna, I unpack this whole cloud economics topic that we said was the second of these three subtopics within the three topics we’re tackling together. And I’ll just throw it out there for sure. There are ways to say that cloud could easily be positioned or hawked at you with a false hope around what it’ll cost. However, my thesis is if you explore the total cost of ownership and whether you can get certain things or not via, via cloud versus other avenues, right? That sets up a different context for evaluating the cost. And as one of my guests Milo, the CIO at Grand Valley State University shared when I said, oh, you moved a bunch of stuff to cloud, right? I remember reading that. And he goes, well, we removed. Yeah, some stuff, lots of stuff maybe. But we moved this stuff that we knew we were no longer in a position to add value to, per se, you know? Mm-Hmm. <Affirmative> personal productivity as an easy example. Whereas there were research applications that we needed to have more control over because they had more special requirements. And it still made sense for us to have a cadre of folks that could keep those systems running. So I’ll pause there. Reactions to those gray scales.

Casey Green:

Yeah. So first, let’s separate the silos in terms of the conversation of movement to the cloud. Go to the, the administrator and the operational as opposed to the academic and instructional. And, and by, by extension research, you know, on the administrative operational, the cloud is in one sense, the, the current iteration of decades of promises about infras operational infrastructure. You, you go back to EDI 40 years ago, electronic data exchange is gonna make it easy for data across different things to come together and we’ll be able to do analytics. Didn’t quite happen. Mm. You know, then we got into ERP, enterprise Resource and web services was the next version of that. And then the cloud’s, the current version of that, you know, we’ve kind migrated up there. The data’s all gonna join itself together, you know, rainbows and unicorns and, you know, high level analytics that are gonna just provide us all kinds of insight.

Casey Green:

And particularly when we, we sprinkle some of this AI pixie dust on it, that’s going to make it even more valuable and more powerful. Show me, I mean, there’s the question on that in terms of both the, the cost issues, you know, more often than not, movement to the cloud on the, on the operational administrative stuff is, is not so much reducing costs, but shifting costs, hopefully with better outcomes. And then the second part is, you know, where are those, and, you know, where gains in terms of using data for planning and policy when the data migrates to the cloud, and we can do better analytics, better insight with the data that we have in a more timely and more informed way. And will AI help that along? That’s certainly one of the promises that we’re, or expectations or aspirations that we’re hearing for ai.

Casey Green:

And, and certainly we’re seeing some early parts of that as, as those stories come over from the consumer and the corporate side. Every technology vendor you provider, you and I have discussed this briefly, you know, before we went on screen it turned on the mics is making promises that we’re gonna either bake in, you know, bolt on or bake in AI to whatever we do, you know, could be 2%, could be 98%, but, but they’ve gotta do it. That’s just the current environment. The question is who’s actually gonna do it? And where do the best, where do the stories come from? Where do the case studies come from of it actually being done? And how was it done and who did it? And under what circumstances, how did they do it? Those are the stories we need on the academic side. This is, a lot of this is gonna really depend on, to some degree, the infrastructure providers, LMS providers, virtual learning providers, the content providers, but also the willingness of individual faculty members to go there.

Casey Green:

And the, the wild card in all of this is the students who will always be ahead of US campus committee. You know, there’s a lot of survey data over the last year. Campuses are forming committees to deal with an AI policy about instruction. Students are off doing it in some cases they’re doing, and individual faculty members are off doing it. In some cases. They’re doing really interesting stuff. Some cases they’re doing stuff that gets to be a little scary, particularly in the area of academic integrity. But it’s happening. So it’s, it’s not as if we can stu you know, the genie’s out of the bottle, right? ’cause With, with, with ai, this is accessible at any time to anyone, just like the early version of the internet. You know, you get a sign up for an ISP account, you can be online in 1995, go buy yourself an a AI, a OL starter account that comes with a modem, throw away the modem. You gotta throw away the a OL software, keep the modem so you can, you know, log in at home kind of stuff.

Joe Gottlieb:

So I’m, I’m hearing a couple things here just to, so we do a little inventory, and that is a there’s been a whole lot of false promises. This techno technologies have been oversold and the cloud phenomenon is, is not, you know, to be excluded from that characterization.

Casey Green:

Not yet. Not yet. Yeah.

Joe Gottlieb:

Not yet. But wouldn’t you agree that when you get down into the details, right, while lots of this stuff has been oversold, there are certain things that it makes real good sense to do in the cloud now. Like the, just the, the economics and the what functionality you can get a hold of. And you wouldn’t, you wouldn’t, for example, put system. I mean, you wouldn’t do personal productivity OnPrem, would you? And, and so that, so, or, or you wouldn’t have a, it wouldn’t be at least considering this pathway that will get you to certain things that are gonna render new benefits in that domain. You might still be on it, but I would think you’d have a path to get off it at some point here soon. That, that opens up the topic of, there’s a synergy point. We’re starting to reduce the, the hardware footprint in our campus on, in our shop, and the, and the personnel required to maintain it. And I’m talking hardware os and dare I say, even now, getting into application software that we’re patching

Casey Green:

And potentially even user support. Yeah. You know,

Joe Gottlieb:

And in which case I want to include private cloud in this, you know, private cloud is no, is you got, you’ve captured part of this problem and not all of it, right? But if as soon as we begin reducing that footprint, we ought to be hunting for as many chances as we can get, and figuring out what is the economics around the things I should not move right now. And, and redesigning around that in terms of our cost footprint while trying to capture the, then the benefits of having more things over in the cloud that have crossed that chasm, let’s say, of economic viability. Is that a way to think about this? Or you think more institutions are, are, are marshaling forward in that regard?

Casey Green:

I think institutions have under are, are, are by their nature and their leadership risk averse, so on their own. And then given the history of, you know, what we’ve had over the last 40, 50 years with technology so, you know, on a whiteboard, everything that you’ve said makes sense. There’s a logic to it, there’s a flow to it, there’s a messaging to it that is compelling. But I also recall my first day in a graduate course in public policy, some 50 years ago, the risk of showing my age where the faculty member walked in, slapped a bunch of textbooks down on the desk, and the first things he said were implementation is the movement of cup to lip. And the question is, how do we move cup to lip in this environment in terms of making the choices that you talked about in terms of on-prem, and, you know, how do we, how do we tactfully and thoughtfully, carefully set priorities, do triage, if you will, for, for what we move now and what we move later, what we wait and, and let some other folks go forward who are like us, and see what their experience has been and who they did that with, you know, in terms of trusted advisors and trusted providers.

Casey Green:

Yes. So it it’s always gonna be slower than we thought. You know, the cloud conversation in higher ed began 15 years ago with an ed cost publication and, and a bunch of other stuff. And again, you know, there’s, there’s the pressure from the outside. Let’s be very clear, both in terms of the, the broad, broad messaging, but also board members, quite honestly, who look at their own environments, who work in a corporate, many work in a corporate environment who are appointed to boards in part for their wisdom and expertise. And let’s also, you know, for their contributions to a campus and say, Hey, we’re doing this over here at Acme Technologies. We’re doing this over here at Omega manufacturing. The cloud has done all these things. Looks like you’ve got an analog set of circumstances here in higher ed. Why not? And maybe, you know, and, and sort of picking and doing the triage and the planning about how to do that thoughtfully and carefully, strategically and effectively is, is part of the challenge. You know, some we can do faster than others.

Joe Gottlieb:

Yeah. I know we’re gonna talk about that a bit more later, but I, I think that is, that’s the major point here, which is this is, it’s back to these gray scales, right? And gray scales require you to distinguish one thing from another to prioritize the triage, as you said. Let’s come back to, to that. Absolutely. I think it’s time. Let, let’s shift to our second topic. So for our second topic, I wanna use a recent publication as a starting point. Yeah. So the, but the, but the, the topic is present trends in data. And I’d like to call out a Harvard Business Review article recently published. It’s actually earlier this month here in January of 2024, they published the latest wave stone survey in this article written by Tom Davenport and Randy Bean of data leaders across all industries. And notably, higher education is not one of those industries represented in the survey.

Joe Gottlieb:

It’s classic, right? Higher ed’s left out of such things because there probably isn’t as much to member measure, let’s say. Or, you know, notably federal government is in there, but, but higher ed is not. So, yeah. So it’s a fact. But what I found interesting about the data is the resurgence of all five of their data and analytics initiative classifications and the articles inevitable observation that chat GT’s Big Splash in November of 22 helped trigger this resurgence. So, mm-hmm, <affirmative>. So first of all, these, these items are, they’re ranging from driving business innovation with data to competing on data and analytics, managing data as a business asset, created a data-driven organization. And last but not least, my favorite, established a data and and analytics culture. Those are the five initiatives they’ve been tracking for six years. Now, do you think this same resurgence, thanks to chat GPT awareness is happening, or could happen in ed, could be happening in higher ed?

Casey Green:

So I’m gonna qualify, I’m a pragmatist. I think it could happen. I think it needs to happen. The question is how will it happen? I’m, I’m looking at that chart as we talk. You know, it’s striking to me that three of the metrics went up more than 20 percentage points driving business innovation with data creating a data-driven organization and establishing a data and analytics culture. No question. Those are huge needs and great challenges in higher ed. And, you know, less so competing on data and analytics because, you know, ultimately campuses we don’t compete the same way, you know, that other cultures do and managing data as a business asset. We should be, but again, but a lot of this, again depends, you know, it, it’s highly contextual. It’s, it’s coming back to the story of the guys in the elephant, what part of the elephant you touch determines what you see.

Casey Green:

And again, the reference points are not gonna be across, you know, whatever thousands of degree granting institutions that are registered with the federal government. The reference point is going to be for campus leadership at a particular college to say, what’s happening at my peer institutions that I can relate to? Can I visualize us doing what someone like us has done? Because I can’t visualize us for the most part, doing what a SU has done or Southern New Hampshire has done. Or, or, you know, a couple of other places that are, are leaders on some of these or other kinds of issues. What’s accessible? What’s possible? Who are the partners? Who are the providers? I need to, you know, who’s, what help do I need? How do I enlist and motivate our personnel, faculty support personnel, technology personnel, our financial people? This, this is a team effort, you know, and it, it’s not a matter of, of a a, a proclamation coming out of the office of the president of the provost or the CIO, you know, these things have lots of moving parts, lots of moving organizations, lots of moving entities, and how do you get the buy-in across the campus to do this, to make these things kind of happen, to get the, to move to driving innovation with data, right?

Casey Green:

And some of that, and part of that is people act and organizations act outta their self-interest. Show me how this will benefit my students, my program, my work, my institution. So in one sense, you need the data to bring folks in. You need that analytic capability to say, here’s how this works. Here’s how others like us have done it. This is the path that we, we want to get concurrence in for us here at this, you know, at, at acne college, at acne State, at acne Community College, whatever it might be. And let’s move forward with reasonable expectations and reasonable timelines. I I love

Joe Gottlieb:

The reminder that this, it comes down to where you fit in terms of your peer group relative to other peer groups, and whether or not this is a disruption that you must triage to address. And that’s just a great mantra, I think, because it, it should always be true, right? At the end of the day, change involves work, change has risk. The question becomes, do I need to change to reduce my risk? Because if I don’t change, I have higher risk. And so that could be in anything from, even if it’s not competing as, as you pointed out in higher ed, there’s less of that classically, but making sure that I’ve got the right programs and the right courses and the right amount of faculty to deliver those courses relative to the demand for same. Right? Is an exercise in determining, are things changing? And if things, if things are changing, I need to, I need to readjust each time.

Joe Gottlieb:

We’ve gotten reasonably good at that, but we could always be better, right? So back to the peer group concept, I’ll really start feeling the pain if I’m no longer able to recruit students that ought to be coming to this school because it had been delivering a value prop. Maybe it’s regional, maybe it’s, maybe it’s not regional, but for for many it will be regional, right? Can I recruit students to this place to endeavor these fields of study that I’ve delivered education within? And if I can’t, to your point, the measurement, the metric, the data is going to indicate that now it’d be good to get some as much advanced warning on this as possible, right? And so if you get better at this, you, you, you, you embrace these things earlier. So I think that’s just what, whatever level you are in, this seems to be the common approach required. Is that, does that make sense?

Casey Green:

It does. I I’m, I’m gonna make a smart comment, please. An old joke about how many psychologists in California does it take to change a light bulb? And the answer is none. The light bulb has to wanna change. But the reality is that in any organization, you need a consensus for change on the part of different constituencies. You don’t need a hundred percent, but you need a critical mass on the part of influencers and leaders and, and people, different parts, you know, of the, of the enterprise of the organization. And that’s how it gets done. You, you can’t, you know, if you’re out there yelling, change, and there’s no consensus, right? Or there’s no agreement, or there’s no commitment of resources, and there’s no leadership, then so what? But if you, you, and, and, and part of that’s also then a communication process.

Joe Gottlieb:

Absolutely.

Casey Green:

Why are we doing this? How do we do this? How do we benefit? What do we do better? How does that benefit? Not just in an aggregate macro level, but you know, at a micro level as well.

Joe Gottlieb:

So if we’re trying to get that light bulb to believe <laugh>, right? The old way would’ve been maybe arming ourselves with psychologists that could influence or might have the power over that light bulb, right? Mm-Hmm. <affirmative> like to, to change. But we must embrace, I think, and I, I don’t, I don’t imagine you would disagree, but I’m, I’m curious to get your take that the old way of changing in higher ed, if I’m just to make it binary for a moment Yeah. Is about, is political. Who has the power at the institution to change or not change, right? And we’ve already said a lot of the structure has set up the academics who are in charge of product delivery that the reason to exist, right? They hold the keys to that power, which makes a lot of sense from a lot of angles. And, and, but with data, with data, we have an opportunity to make it more informed.

Joe Gottlieb:

So now, let’s say that the power structure of an organization might have gone one way, but good data would help us fi discover that we might go a different way. So two things to ponder, right? A how do you make, do you want that to happen? And, and maybe you’re, if you’re in control, maybe if you’re a beneficiary of the old model, you don’t want that to happen. But generally speaking, if you agree that that’s a good thing, how do you, you know, how do you make that happen? I think it comes back to this notion of you have to have the will, right? And data may be, may be able to help you get there faster in a more objective way. But that does fight against the political power centers of the old.

Casey Green:

Yeah. But I, I think let’s recognize that many of the academics who ultimately have power don’t necessarily think of themselves as empowered among, among faculty. And so that’s where part of the tension is, even though

Joe Gottlieb:

Interesting,

Casey Green:

They, they can slow some stuff down. Same thing in terms of administrative groups. It’s, it’s that inner 2-year-old, I don’t wanna, I, you know, I don’t, you guys go do this kind of stuff. And, and it’s, it’s more, Joe, it’s more than just data. It’s the narrative that adds value to data, you know, data, information, insight, narrative, and the narrative becomes compelling. So if for, so for example, if I can show you a technology intervention creates some clear benefit in a class, in a course, in a program, in administrative services, you know, and I’ve got real numbers to do that, then it’s hard to refute that as opposed to the epiphany and the, and and the opinion. And the question is, again, you know, we mentioned this earlier. You we’re, we’re kind of stuck at only 30% of c-suite campus leaders over time think that their campuses does a good job of using data for planning and policy making. That’s gotta change. That’s part of a culture that’s gotta change. That needs to change in order to do better. Or alternatively, in the wake of the, you know, to the covid, a crisis is a terrible thing to, to waste. And you have no choice. There was no, you know, you may not have wanted to do remote learning. You had no choice for two years, beginning in March, 2020 when everything shut down.

Joe Gottlieb:

I think there are two interesting things, by the way. I love your point. The finer point about it’s data is insufficient. It is the narrative. It is the, the discipline of taking data and putting it into context. So it can be useful for decision making, right? Amongst those that are assembled, hopefully in a structure that will make decisions. Now, now we’re starting to incorporate data in their decision making, et cetera. But it’s gotta, there’s the hard work is the context. The hard work is the narrative. We would be overwhelmed. We, we, we are overwhelmed by all the data that exists and the ease with which we can get to just data. Now, sometimes that’s withheld from us within organizational structures. But if we consider the internet our, our, our experience with the internet as consumers, right? There’s so much data out there, it’s easy to be overwhelmed. And now we have very interesting thing happening with, with either fake news or, you know, you know, choose your, your, your, your thematic trend. But trusting the internet, trusting chat. GPT, if you notice how chat PT has really backed off a lot of subjective mm-Hmm. <Affirmative> categories topics. Yeah. It’s, it’s been now, it’s now been told to stop sending people over the edge with it’s, it’s either cogent analytics about subjective topics, or it’s hallucinations. ’cause It’s hard to determine which is which, right? But anyway,

Casey Green:

It’s very hard.

Joe Gottlieb:

The context is key

Casey Green:

Context really matters. And that’s, that’s, that’s why, for example, institutional context matters. It’s, it’s maybe interesting to talk about something at large or a particular campus, but context matters in terms of how do I, how do I visualize that in terms of how it affects my campus, my program, my department, my students, my world, my small empire, right? And, and the other empires of the city, you know, effectively metaphorical city states on a campus Absolutely. That I have to interact with.

Joe Gottlieb:

Yeah. I I also love the point you made about, while academics might have theoretical control, they don’t feel that way. And I wanna throw out a, a hypothesis that comes to mind, and you tell me if you think it’s accurate. So that, I think is a result of the fact that, huh, there’s, there’s, there’s less command and control across academia by design, at least historically. And so while there’s collective relative power in an institutional organizational context, the, the fact is, is that the, all the different freedoms across all the different departments in, you know, all the programs right, are such that they’re not, they’re not organized to be a union, for example, necessarily, and, and foment influence in a, in a structured, organized way. Now that, that probably varies according to provost leadership and, and maybe dean leadership and some other factors. Is that the way you see it?

Casey Green:

Where do we find common interest? If I’m in the physics department and you’re in sociology, or you’re in engineering, you know, or you’re, you’re an English professor, where are our common interests in some of these issues about change?

Joe Gottlieb:

Yeah.

Casey Green:

What, what’s the tie that binds, you know, it may be 20%, it may be 40%, but that, that too is part of the narrative challenge. There’s a piece that I do with, with various groups about that, that actually I’m riffing off worker colleague did some years ago about guidelines from Machiavelli and change agents. And, you know, one of ’em is go have coffee, go talk with folks. Yeah. And, and you know, before you start making proclamations, you don’t hit the ground running. If you’re the new person or the newly appointed person, you, you hit the ground walking and you do a lot of walking and talking at the same time. Because otherwise you’re just gonna make the same mistakes that others have made. You know, you, you really need to understand the context and the environment and the microenvironments

Joe Gottlieb:

Interesting. One, one provost I had on, i i, he pointed out how he was looking to evolve programs Mm-Hmm. <Affirmative> and decided to fund a data analytics program Yeah. And encouraged all of his deans to come forward with. He, he, he said two things, you need to come in. He groups more than one, right? So buddy up, which will force collaboration, which will be good for our culture, and present a proposal for a program that’s going to utilize this data analytics capability that we’re gonna go recruit experts for. We’re gonna recruit faculty to serve, but now fit into your program in a way that’s thoughtful, but then create some synergy Cross program. And, and it was an interesting way to think about how to stimulate this kind of evolution. What, what you said was you put, you know, you’ve ed,

Casey Green:

Wait a second. Did it work? Were people willing to share the sandbox?

Joe Gottlieb:

It enabled, it enabled the funding to occur at that point in time, which was the current point in, in time when I talked to this person, and now I’m gonna have to, I’m gonna have to find the reference ’cause I’m forgetting. I’ll add the reference to the notes in this podcast, but I’ll, I’ll go back and check how things are going. But it was at a point where they had gotten through their investment cycle, and they were in the process of, of moving forward with sufficient projects that had been identified. I don’t know Okay. How it worked yet.

Casey Green:

All right.

Joe Gottlieb:

But the, the, you’ve made the point though.

Casey Green:

But, but, but the key is that the, you know, the dean of the provost changed the incentives.

Joe Gottlieb:

Correct.

Casey Green:

Okay. So you’re gonna benefit, but you’re gonna have to share the resources in a way that the sum is gonna be more than the parts. That’s right. If you do that, there will be a clear benefit that goes just beyond your silo to other silos, right? On the sum will be more than the parts and communicated that, and that in that incentive, you know, financial, whatever it might be, and, and the possible outcomes from, from at least the front end of the story that, you know, becomes quite informative in terms of one way of moving forward.

Joe Gottlieb:

And in this case, it was merely some leadership offering an incentive to, to catalyze this behavior. But you put your finger on it from the beginning, whether you have an incentive or not. It, it, it starts with common interest. It starts with finding that common interest. And some, you know, sometimes coffee is the best way to proceed, right? Coffee,

Casey Green:

Pizza, a drink, whatever it might be.

Joe Gottlieb:

Right on, you

Casey Green:

Know, stop, you know, stop communicating an email and just sit down with one another for 30 minutes.

Joe Gottlieb:

So on this topic of data, and first of all, I, I, I believe, I think we both believe that this chat, CPT splash might itself create a short-lived peak that will then result in some realities of how hard it is to apply ai. Do you, do you agree with that?

Casey Green:

I, yes. Because the Gartner heart curve has proven to be true time and time again,

Joe Gottlieb:

The, the, whether it was the trough of disillusionment within the hype cycle that was actually mentioned by the article. It’s funny that you,

Casey Green:

Yeah. You know, I mean that there is, you know, over inflated expectations, the tr of disillusion and finally sort of the pragmatic implementation of real benefits, you know, it goes up, goes down, and then goes forward. We’ve time and time again, we’ve seen this in lots of different ways. And so, you know, ultimately time will tell and the stories will tell in the narratives. And again, let’s go back to context. It, it’s gonna be different in different context. It’s gonna be different in different sectors. It’s gonna be different in different applications. It’s gonna be different as each technology prevent provider knocks on the door of their campus clients and says, we are AI enabled. Okay, show me, tell me. As opposed to just proclaiming it to be, and then I wanna apply that, you know, how can I do that here in a way that you, that maybe you’ve done it someplace else, right? Because again, your price is not my cost in doing that.

Joe Gottlieb:

Everything. And, and so while we, we often make comment, we often remind ourselves that we aren’t quite real snowflakes in higher ed. Although sometimes higher ed has a tendency, each institution thinks of itself as a snowflake. There’s a, there’s a a broader of less fine-grained macro version of this that is true. Which is we are all a bit different in our context, and we have to understand how we could move forward and pace, let’s say with a peer group. So I think that’s the gray scale we have to hit there. I wanna actually indulge you in indulge your historical perspective now on this topic. I’ve pushed you forward a little bit, but I also do wanna look back. I, you wrote a great piece on the Georgia State case that the New York Times reported on back in May of 2018. Mm-Hmm. <Affirmative>.

Joe Gottlieb:

But the point that you made in your piece, which I really like, that I want to play around with a little bit here, talk about, is we were talking a moment ago about the context ne necessary for data to have useful impact, right? That is for a point in time for a decision. But real delivery takes more than that initial decision, let’s say, to commit on the basis of data. In good context, there’s actually a series of decisions, but ultimately there’s a series of operational behaviors and commitments and, and investments that one must make to actually make a decision to make a change, actually yield value impact. And I love the way you pointed out what was really going on at Georgia State was something that went way beyond just supplying data about retention and how to improve retention. So you talked about other investments made. You wanna elaborate on that?

Casey Green:

Sure. I mean, Georgia State has perhaps one of the most striking stories about retention and degree completion of any place in the country. And the, the public presentation of that story is, it’s often repeated by others, not necessarily Georgia State folks, is that they made a huge investment in analytics and, you know, sort of threw everything into the data gumbo and ultimately came up with some 600 plus independent variables that potentially could predict retention and degree completion. And, and the geor, what’s striking about the Georgia State story is the improvements were across almost every student demographic, low income students of color, students at different performance levels. Everybody went up and it went up dramatically. And it went up in academic Lightspeed in terms of just five years unparalleled to the best of my knowledge. Talk with the folks at Georgia State. You know, read the New York Times article.

Casey Green:

I did a podcast with them some years ago on this. And, and the story behind the story is not just the analytics, but in fact they built an infrastructure of student support. So that on Monday morning when that email was kicked out by the analytic engine and came into my email box as a first term or second term freshman, says, Casey, we’ve been tracking, you know, watching you carefully unobtrusively, and based on a lot of different metrics, you know, we’re in terms of whatever it might be, class, attendance, midterms, whatever it might be, you’re in trouble. And we, we don’t say this to scare you. We say this to essentially give you a way out of trouble. And here’s that pathway out. They hired, I believe it was almost 200 people to do the, that support service academic and other kinds of support services for students. So they built a support infrastructure that gave, that gave life, that gave possibility to what the analytics identified, here’s the problem, here’s the remedy. And the remedy was we need support services to make this work. And it turned out the support services make a difference. A SU has been lauded for its online programs early on. If you go back to the history of, of a SU online, they built a support infrastructure to make that work.

Joe Gottlieb:

Hmm.

Casey Green:

To, you know, for those students to, you know, make it sticky. Southern New Hampshire, the st lots of other places have done that as well. And it’s that I, you know, we’ll come back, we’ll come to this I think as we close, but the reality is that infrastructure fosters innovation and outcomes. It’s not the other way around. You know, at Georgia State, they had an analytics, you know, they had ana compelling analytics and they built an infrastructure to get to an outcome. They took it apart and they put the pieces back, the moving pieces back together. So that when I got that email on Monday morning, instead of saying, oh, crap panicking. ’cause They’ve, they’ve essentially, you know, stigmatized me, giving me a red flag, I’m in trouble. They’ve said, no, here’s how you do this. Take a deep breath. Go knock on some doors, set up some appointments. We’re gonna get you through this. Yeah. And they did for large numbers of, for a striking number of students, again, across all student demographics,

Joe Gottlieb:

It reminds me of the total quality management movement that Mm-Hmm. <Affirmative> helped evolve, maybe revolutionized manufacturing over several decades in, in, you know, in the recent history, recent past. Yeah. And, you know, it’s questions, beget questions, data begets, right. More questions. But ultimately with quality, it’s about, it’s about understanding root cause and deciding whether or not you want to improve or not, and prioritizing improvements based upon things that you now understand through your measurement. And you don’t hear of the quality movement talked about in terms of the data side of it, right? Like you needed data to drive quality. Right. But we focused on the qua, you know, the, you know, the, the, the activity of improvement or, or the measure. But you speak to how do we keep that line producing better cars, for example. Right. And I think you’ve made a point, which I love that compares the auto industry to higher ed. So help me with it. But it’s something on the order of, you know, in the auto industry, if you discover something bad about the car, you get it onto the line quickly, as quickly as you can, albeit within the context of your windows for change.

Casey Green:

Right.

Joe Gottlieb:

But in higher ed, that it doesn’t exactly work that way.

Casey Green:

The calendar works against us. Yeah. The structure works against us. You know, we’re kind of locked in, you know, whether it’s sort of administrative or instructional infrastructure. We can plan 10 months of the year. We get a window over the summer of two months to kind of do it or do much of it. And then, you know, pretty much we’re locked and loaded, unlike, you know, gee, we got a problem with, with something in, in the, in the brake line or something, in the, you know, an electronic ship. Stop the line, fix it, and go forward. Right there, there was a period 20 years ago where higher ed participated, I forget this, it was the Secretary of Commerce, you know the TQM awards, higher ed participants, that’s largely gone by the wayside. And and I, to the best of my knowledge, you know, it was kind of a flare up lot of focus, and at least on the higher ed side dissipated, although it hasn’t in other sectors and segments, because I, you know, I’m throwing away a soundbite here, but, you know, Peter Drucker told us a long time ago, and the conversation about change culture eats change for breakfast.

Casey Green:

And, and that that’s part, you know, make it give me a compelling reason to change and show me the benefit.

Joe Gottlieb:

Yeah.

Casey Green:

And show me the path.

Joe Gottlieb:

So let’s tackle our third topic. Okay. Future practices required.

Casey Green:

Yeah.

Joe Gottlieb:

What are the most important practices that higher ed institutions should be adopting looking forward?

Casey Green:

So there’s lots of talking heads that offer lots of, you know, sound bites about this. And I, I’m unfortunately gonna step into that as well. Given your invitation to, to me, the, the questions that I, I think we should ask in a very pragmatic way, it’s, is what have we done well and what must we do better? Because intuitively, we know, quite honestly, we know our institutions, we know our programs, we know our personnel. And, and those are the private conversations we have in closed, you know, ENC closed offices. You know, we, we know who teaches well, we know which programs we’re doing well, we know, and we, we need to go a little more public about that, but not in a stigmatizing way. What have we done well? What do we do better? What are the priorities for doing better? Because some are more attainable in a short period of time, but with fewer or more resources than others.

Casey Green:

And how do we kind of do that triage what are the specifics for doing better? What does doing better look like in terms of instruction, academic performance, administrative resources and services, A whole bunch of things. And, and how do we get consensus of that? You know, your experience, Joe, about doing better may be very different in terms of my list of doing better, but at least have, let’s have that public conversation. If, if we’ve got 20, let’s pick six where there’s consensus and prioritize those as opposed to arguing about 19, you know, 17, 18 and six in terms of that conversation. Again, think about the post-it note exercise that, you know, many of us have been through. You fill the wall with different colored post-it notes, pardon me. And then what do you do with ’em? Well, you’ve gotta prioritize, you gotta do triage, what you know, what are the highest priorities, and then put a temporal dimension on those, you know, given resources, calendar, other things.

Casey Green:

What can we do by fall, the next fall? In this case we’re talking about fall 2024. What do we kind of, it’s gonna take more time or more resources or more planning for fall 2025 and fall 2026. And then it’s an iterative process. You continue to do it. There’s a te there’s obviously, you gotta anticipate the temporal dimension to it. You gotta still have conversations and communication about this. How do you, how do you connect the dots on doing this kind of thing? And communication, you know, sort of public transparency, communication is critical as well into a lot of that

Joe Gottlieb:

Transparency. You, you, you finished with that? So I wanna pick on that one first. Mm-Hmm. <affirmative>, how much transparency do you see in the higher ed universe that we’ve been talking about? How does it vary? What are the nuances of transparency? Because I believe, I agree with you, transparency is essential, but it also gets back to this notion of transparency goes really well when there’s data and a context for interpreting data and maybe a structure of the way we’re using it and maybe investing based upon it. But let’s talk about transparency for a moment.

Casey Green:

Okay. So over the course of my o ouch, four decades plus career in higher ed, it goes back 1980s, right? You know, at a macro level, we’ve had great gains in transparency gains in terms of the pardon gains. Gains, gains in terms of the availability of institutional, you know, through I high he just higher education, general information survey, which is now iPads and a number of other metrics. So what, you know, we can see retention rates, we can see degree completion rates. We, you know, if, if I, I wanna do academic planning and I wanna launch a new program in widgets, I can go to the iPads and I can look at peer institutions and geographic neighbors to see who’s offering that program as a, that’s public data. That, that’s a kind of transparency. You know, the, the, the larger questions become, you know, the transparency at the institutional and programmatic level, and how do we go public with that, you know, completion rates in different, in courses and in programs.

Casey Green:

Let’s put this in a medical context because it’s easier to talk about others. And then kind of, you know, infer you think about hospitals and the kind of the data the feds collect about people who go in for certain kinds of treatment and what the success rate is on the part of hospitals or programs or physicians. We don’t do that publicly. Hmm. And yet, intuitively, you know, if you and I and five others, Joe, were teaching the same freshman widgets class, it had, you know, over a course of two semesters or three quarters. You get some of my students in the second semester and I get some of yours. And, you know, there’s some mix of some others as well. You know, over time, because you and I and others have done this, you know, more often than not, we’re gonna have a pretty good in, you know, sense of who came out of whose course and who’s better prepared.

Casey Green:

And yet we don’t talk about that publicly. And we need to do that, not in a way that data becomes a weapon, but data becomes a resource. How do we do better? Because too often data’s been used as a weapon against us individually and collectively in higher ed. The good retention rates, you know, and, and percentage of students who going to community colleges who complet a degree, you know, that becomes a weapon. Well, in fact, large times of students who go into community colleges don’t want a degree. They’re there for a couple of courses because that fills the immediate need to get into the job market. And then they come back. And particularly in the new economy, you know, we see a lot of this kind of churn here where I live in southern California, for example, 30 years ago, we lost a couple hundred thousand jobs during the recession of the 1990s.

Casey Green:

And those jobs were geographically concentrated south of the L airport in DOD defense contractors, aerospace contractors. A lot of those folks already had one, two, and three degrees. They didn’t need another degree, but they needed a couple of courses to kind of refresh and refill and expand, particularly as the internet was coming in. You know, I’ll go to community college, I’ll learn how to use Lotus 1, 2, 3 in the 1990s or something like that. Or I’m gonna learn about the web, I’m gonna learn about SEO, or I’m now gonna learn about AI. Or, you know, community colleges backfill that in a way that others, you know, other, you know, other institutions don’t because of their structures. So yeah, you know different parts of that are all different levels of transparency. But we need the, the underlying way to approach transparency is if we’re gonna make those data public, we need to do it as a resource, not as a weapon. We’re not gonna punish you for that. We’re gonna show you the way outta the rabbit hole, you know, how to do better the same way we want those, those students at Georgia State, we’re shown a way out and a way forward

Joe Gottlieb:

On this point, is competency-based education a a more data-driven way forward.

Casey Green:

Maybe, you know, maybe, you know, again, it, it depends on, you know, how what we measure and how we measure it

Joe Gottlieb:

Requires a lot of change.

Casey Green:

Requires a lot of change. But, you know, what we knew is the current system doesn’t work. Grade inflation is rampant in high schools and in colleges. So those metrics are not as useful, you know, are not as useful as they once were. I mean, it’s a striking, it’s a striking moment for me, given the current conversation about the SAT that’s been going on just in the last month, for example, that for much of my career, the SAT was appropriately discarded because of, you know, kind of cultural bias, documented cultural bias of bias, call it whatever you want. And now because of great inflation, you know, we’re seeing some new data that says, oh, wait a minute. The SAT in fact may be a far better predictor than high school grades. Where in the past there was a lot of evidence to say grades were a better predictor than the SAT for, for, you know, different populations and different demographics of students. That’s a huge swing in the pendulum. Yeah. But it’s, it’s a swing prompted by data, by evidence.

Joe Gottlieb:

Absolutely.

Casey Green:

And that has consequences for policy.

Joe Gottlieb:

Right? And so right now I’ve, I’ve maybe been listening to the same podcast you have on the topic, but it’s fascinating that we would, we would now discover how hard it is to make choices based upon grades given the inflation.

Casey Green:

Yeah.

Joe Gottlieb:

And without this tool that we used to have, which yes, we could, it was imperfect, like anything’s imperfect, right. But there was data suggest it was a better predictor of across all categories.

Casey Green:

Yeah.

Joe Gottlieb:

Fascinating. Okay. Let’s talk about how practices might evolve. I love the list of practices you gave, but let’s now look at this through the lens of different roles. Mm-Hmm. <Affirmative> and the roles that come to mind. You and I did this beforehand, CIO provost, CFO, president Board, lots of different touch points in, in in the structure. But let’s, let’s have some fun thinking about what’s needed. Where would you like to start?

Casey Green:

Let’s start with the board, because that, I like it in some ways, you know, kind, kind of an, I don’t wanna say it’s an easier target <laugh>, but it, it, it’s a, it’s a, let me rephrase that. It’s a clear opportunity. You know, boards are engaged and at the same time they’re remote, you know, many boards, you know, I I, I heard long ago, early in my career, you know, that you’d get selected for a board on the basis of the three Ws, wealth, wisdom, and work. You contribute two of the three, you know, some of that still applies to some other factors and you know on campus boards that still apply to some of that. And particularly, you know, as we’ve seen the technology, the ascendants of the technology industry on the, the wisdom and wealth at many institutions in terms of being, you know, encouraged to join advisory boards through departments, and later, you know, essentially board of trustees or board of advisors or whatever it might be at, at the higher level.

Casey Green:

You know, the, the board folks bring their experience, their expertise and their perspective to these things. And particularly if they were alumni, you know, of, of an experience of, at a particularly zeitgeist, whenever that might have been when they were a student at, at, at, at a particular institution. And that goes into the gumbo with their professional and and personal experience in the industries and, and their professional work. And, and again, I think this is where the, the consumer and corporate economy kind of lead or raise expectations for campus to say, well, wait a second. You know, we just moved all our, as an example, all our HR to the cloud,

Joe Gottlieb:

Right?

Casey Green:

Over here at Acme Widgets or Acme Technologies, or Acme manufacturing non higher

Joe Gottlieb:

Ed industry that that board member is working in, right?

Casey Green:

Yeah. Yeah. So, you know, we, we just, you know, we, we’ve looked at a lot of, HR was really easy, you know, because it was fairly straightforward, linear, and we had defined categories and everything else. Higher ed doesn’t look like that. Part of higher ed looks like that, but other parts of it don’t in terms of, you know, kind of customizing in terms of how do you deal with the faculty side of HR as opposed to the folks who have, you know, operational, administrative, clerical and other kinds of things. And, and who are the technology providers who have skill in that and understand the culture without go owing overboard on customization. Bingo. So there, there’s a, and then campus culture as well. So, so part of the challenge in terms of this conversation is a board conversation or a board education about some of these issues.

Casey Green:

Yes, we wanna tap your expertise, but understand it, it’s not, you know, we’re, we’re different for good reasons. Yeah. Not always the best reasons. And we wanna find that best fit. That’s one. Presidents I, I think are highly contextual depending on the campus and what the role of the president is. You know, there are many large institutions that the president is public facing and also, you know, spent huge amounts of his or her time engaged with, you know, donors. And if you, in a public institution dealing with legislature, governing, engaging of government, state government and other kinds of things but still is, is a key part of that management core at the c-suite with the provost, the CFO and the CIO and some other titles. But those are the, the ones we selected for this conversation. And a lot of this is, is longer ago in graduate student, I, I learned about, there’s a kind of a five tier process of when does a president at, at, at the executive level, when government get involved, it’s a personal, highly involved issue.

Casey Green:

President throws his or her support behind the issue, but is not the operational manager president is in, you know, there’s, there’s some steps in this thing. Mm-Hmm. And, and those are the choices presidents have to make as well. You know, go back to the, the turn of the and the Y 2K experience, you know, every campus was doing, almost every campus was doing a ACME College and Y 2K Acme College, 21st century, lots of things about how technology is gonna transform. Acne college was a couple of boil and play paragraphs that didn’t vary much from campus to campus in terms of operations and instruction, but there was no nothing underneath it about connecting the dots and building the infrastructure. So, you know, a president can be the person who steps in and steps up on that and says, okay, show me the beef, show me the plan.

Casey Green:

And, and you know, with that, the role of the provost is the chief academic officer, particularly, you know, instruction and scholarship and other kinds of things. How do we do this? And the collab, you know, essentially a collaborative working team at ika with the CFO and the CIO on these issues. So the sum is more than the parts, as opposed to separate administrative silos. These folks have to talk, they have to have coffee, and they, you know, again, this is what’s the vision? What’s the mission? How do we get there and do we, do we share that or have enough commonality and agreement between us to move this forward, that we communicate that consistently to all parts of the organ, the empire, the organization, the academic enterprise, the operational parts.

Joe Gottlieb:

We’ve talked about the potential benefits of adding a bit more process Mm-Hmm. <Affirmative>, or as you like to say, dicta to the higher ed management apparatus. Yeah. And I think that, as you pointed out, it’s first about culture Mm-Hmm. <Affirmative>. And so my question to you is, do you see it as, is the president ultimately responsible for accomplishing that cultural shift, knowing full well that it is a, a village across these roles? We’ve gotta, we’ve gotta come together. But is that the, is that up to the president?

Casey Green:

Certainly the president is the most public face of that, you know, regardless of the institution. Sometimes they are, you know, more directly involved just given the culture of the organization or the requirement of the job. You know, sometimes they are less involved and they delegate because they’ve got other, other operational responsibilities as it relates to fundraising. Donors, agent government agencies, particularly for public institution, you know, public institutions community college presidents dealing with local boards, local communities. And, and again, the role of the, the provost is the chief operating officer in some way, or, you know, the CFO often the chief administrative officer, defacto. But this is a team. And, and so, you know, kind of consistency and collaboration, communication become essential for that. And, and with presidents in particular, more than just I, and, and provost to some degree, I think more than just kind of a, a suit, a surface knowledge of what’s going on, particularly with the technology side, whether it’s operational or it’s instructional. I wrote a piece from my blog some years ago suggesting that presidents need to get, and by extension, some provost need to get themselves to technology to it. And, and the reason for that was, is I talked with presidents and provost often, you know, they could kind of talk in, in, in kind of bullet point form about interesting things at their campus, but their eyes would light up when they started talking about their children or more often their grandchildren.

Casey Green:

And yet, you know, we know from the corporate experience let’s go back to Microsoft in 1995, like this may be more history than, than some of your folks wanna know, but Microsoft was a young organization, the leadership guys that, you know, gates and Balmer and others were in their thirties. And yet it was the flow of recent college graduates coming off campus with the internet, already had a, not just a toho, but a foothold, you know, a just a, a huge hand on things. And it, it was already creating change that ultimately led gates to issue a, you know, isolate himself, write a long internal paper that went public, called the internet tidal wave about how the internet’s gonna change everything. And Microsoft has to do this at IBM when the first non non IBM president went in, in 1990, after that huge turmoil, he got himself a technology tutor.

Casey Green:

Gates got technology tutors, you know, one student once a week for an hour or two. One me show you let, you should touch for a lot of the talking heads, you know, who talk about learning management systems or chat, you know, AI and other kinds of, how many have actually touched and used in more than just the most superficial way. See it, do it under, you know, where the shoes sit in front of the keyboard, you know, have a more direct experience with some of this stuff, I think would also help in a lot of ways. Doesn’t take a lot of time. It takes some focus time with a guide. Yeah. You know, it’s a tremend it’s a tremendous opportunity. It it for that whoever that student or graduate student might be, and also for them, the president or provost, to get a kind of up close personal kind of guide for that.

Joe Gottlieb:

I love the, the recommendation to get a tutor. It, it’s so universal, right? Mm-Hmm. <Affirmative>, when you, especially when you’re in leadership, leadership by definition is, is should be a step away from specialization. Right? And so to cover all the bases with your personal past experience is impossible by definition as you go up in leadership, particularly if we’re gonna start acting more as a team. So some teams are just a team of specialists, right? And they have limited understanding, appreciation or interest in other domains. But if they had that they can function more effectively as a team. They can become more holistic, or can stay more holistic, easier, or get there faster at any given, in any given situation. And so that reminds me, when I was hunting for the responsibility for this culture of evolving towards a somewhat more controlled, somewhat more coordinated approach to driving strategic change, I thought of the president just by virtue of that person’s, you know, that role’s responsibility, knowing full well that in some organizations they might have a provost that is going to be a great change agent for culture.

Joe Gottlieb:

And they can all rally behind that because that the person’s, the chief academic officer, in some cases it’s a pre president with very good facilitation skills. I’ve had some great conversations with presidents about the rising, a rising occurrence. It certainly is different from the historical trend of non-pro descending to president or coming out of mm-Hmm. <Affirmative> industry even, right. Where there’s, there’s a little more, there’s more acumen, perhaps more experience in facilitating change, leading change. The point you made about Gerner and IBM, right? That was what happened there. Mm-Hmm. Gerner was able to come in as a non-incumbent and bring some different perspectives. So,

Casey Green:

But, but I wanna come back to something there. Culture matters and attending to culture matters. There’s a great story about Dwight Eisenhower and I, you know, so, you know, in the course of this conversation, you’ve begun to realize, I tell stories. Yeah. So Eisenhower in the interim between, you know, leading allied forces in Europe during the second World War and running for president in 1951 and 52, and, you know, ascending to the presidency in 1953, had a short period and period as president of Columbia University. Not many folks know this. And there’s a story about Isen, you know, so after the appointment is made, Eisenhower’s spending some time on campus, and Rick, I Eisenhower lived in command and grew up in command and control environments. He went to military academy. He lived his entire life in the military. And after the war, you know, he was the ex, you know, he, he was the supreme leader of NATO in the early years, you know, during the Berlin blockade, Eisenhower’s walking across the campus, supposedly talking with the provost.

Casey Green:

And the provost was talking about a couple of, of issues on at the university where there’s some contention between the administration and the faculty. Eisenhower product of command and control lived this life in the military. He says, well, why does it, the university tell the faculty what to do? And the provost, supposedly without missing a beach general, you have to understand the faculty are the university. So these cultural issues run deep. And, and we have, you know, you can’t ignore them. They vary dramatically from campus to campus in terms of history and personalities and everything else, but they’re as much a part, you know, they, they’re much a part of the landscape as anything else and must be attended to

Joe Gottlieb:

What happened next. He was there much longer.

Casey Green:

Yeah. What happened next is he had a short run at Columbia, and then he ran for president, right. And he won and had an upset win. And, and ironically given the calendar, he had an upset winner from New Hampshire, primary Republican primary

Joe Gottlieb:

<Laugh>.

Casey Green:

And the rest is history.

Joe Gottlieb:

Great story. Great story. Let’s, let’s zero back in on the CIO I’ll, I’ll run another hypothesis by you. Yeah. Love to get your take. I believe that much like we’ve just been talking about how the president might be ultimately responsible for this culture of maybe, mm-Hmm. <Affirmative> maybe slightly improved process and command and control, but they may not always be the one that can deliver it. So they have to make, they have to facilitate. Its, its, it’s its growth. The CIO is a is in a role that must deal with the aggregate implications of all the different needs of an institution, right? In the digital era, that becomes virtually everything comes to roost with the CIO.

Casey Green:

Yeah.

Joe Gottlieb:

And when I think very optimistically on very sunny days here in California, where I’m also a resident excuse me, I, I think about, I’ve seen it and I think about more of this happening whereby the CIO is in a position to help teach the organization how to evolve strategically because they’re the ones that have the most to gain by rationale occurring in the set of choices that are put upon and the requests that are put upon it. And so it says, okay, rather than trying to please everyone politically let us all, you know, prioritize what you want from our finite resources here in it. So I’d love to talk about your, your, your views on that whole dynamic, because some CIOs are not prepared to do that. Some CIOs tend towards just being visionary and hauling towards a direction. Some are content to just put out the plumbing and survive. But there’s a, a wide variance here, and it varies by institutional you know, the, the different levels that we’ve been talking

Casey Green:

About, right? Yeah. So again, context matters dramatically in terms of the permission or the latitude that may be extended to the CIO to define his or her role. You know, the, the ones that I find most interesting are those who are pragmatic communic advocates and communicators. And the communication is a lar is a clear part of their job. Not just to advocate the possibilities, but to, but to articulate the pragmatic, what this is how we’re gonna do it, this is how we’re gonna make things better. And, and also do it candidly about it’s gonna take time. These are the steps along the way, but we’re gonna get there. It’s, it’s too angry for everybody to be angry at the computer center. The LMS goes down, user support’s not available. You know, there’s a hiccup in my software, which has nothing to do with the technology resource on campus, but you know, that’s the easy place to blame.

Casey Green:

And you, you know, you wanna get past that tier one crap, right? And you essentially become a an effective and articulate advocate for a better future that is not driven by technology, but is enabled by technology. Right? On. You know, I, I, you know, this is, this is not a matter of high tech versus high touch, which many academics think is, is where the choice is for, I, I have long advocated. The, the issue becomes how do we do tech enabled high touch? I love that. How do we make the, and, and, you know, we’re getting better at it in terms of, you know, the fact virtual learning, some of the other resources available to us in other different ways. We still have a way to go, but we’ve gotta provide an infrastructure where faculty believe it works for them, not against them.

Casey Green:

We have to provide an, an infrastructure, which also includes recognition and reward on the part of the campus, which is beyond the CIO to say, you can do this where I can visualize that I, I can do this, and it’s possible for me to do this. Right. You know, too often when, when we made these investments early on, we, you know going back to diffusion theory, we, we invested in the early innovators, which seemed like a good idea. They’ll be role models and you know, they, we, the hope was that they would infect too often they intimidated because I’m not like you, Joe. You get it. And I don’t, and for me, it’s risky and intimidating or, you know, the pul aggression that occurs in, we used to occur in classrooms where kids used to kind of chortle as faculty members are having problems with the technology in class, or, you know, could potentially embarrass a faculty member who’s, you know, working through some stuff and says, Hey, professor Green or Dr. Green, that slide’s interesting, but I’m on the website here and your data are five years out of date. You know, in terms of, ’cause they’re, they’re now enabled. Yeah. You know, how do we create an infrastructure that is safe and reliable not to protect and defend, but to support and enable, you know, in, in terms of those resources that those, those challenges and what faculty would like to be able to do.

Joe Gottlieb:

Right. Yeah. Great point. I think of another story where it was actually when I was working through, as you might imagine, podcasts over the last few years. So I launched this podcast, I’d have to say, yeah, right in the middle of the covid, you know, pandemic. And so invariably a lot of the conversations, less and less so, but a lot of them were about, okay, let’s talk about what you did during Covid, right? And right. And one of the stories that I heard and I’ll, I’ll find the reference in the notes, but as a way to provide a little bit of history on what they were able to accomplish during covid because of what had preceded covid, what they had done even prior to Covid, right? Sure. So as an example of, hey, we were doing some pretty interesting things. It helped us to do even more necessary things during Covid more quickly, but in this case it was faculty.

Joe Gottlieb:

Some, some faculty members had gone to a conference and seen the power of interactive classrooms and in particular whiteboard space and classrooms that could be configured for small groups. And the, the, the breakthrough that they loved was that students in smaller groups were more likely to engage and take risks and participate than they would if they had to go up to the front of a larger classroom and be the one called upon to, to try their, their hand at the chalkboard, right? So, so these, these, these, these faculty came back to the president and say, can we, can we invest in this? And, and it was a thrilling opportunity for the president because it was like, absolutely, it was an opportunity, right? For, for that president to say, mm-hmm, <affirmative>, you bet. Love your conviction about this new idea. Let’s pilot it. Let’s try it out, prove it in and let’s, yeah, let’s blow it out. And so they had done a pilot and they had some great results, and they were literally had already been reconfiguring classrooms for probably going on 10 years based upon this thing that the faculty brought. But I just love the story because it’s an example where, to your, to your point, if we can support innovation that comes from the place where innovation is needed, that becomes a pattern that we wanna stimulate.

Casey Green:

Yeah. It’s, I mean, it it sounds like a throwaway line. It’s innovation that it, it’s infrastructure that fosters innovation, not the other way around. You know? It, it’s, you are creating an environment that allows me to do these things that will support me, that will protect me, that is reliable. I mean, yeah, look at the whole ev conversation to go off campus for a moment. One of the biggest problems with migration to EV is range anxiety. And the fact, fact is EV chargers often don’t work. There’s too few of them. And the ones that are out there in small clusters are down. And I say that as somebody who has an ev, you know, wall Street Journals has been on this for the last couple of days and it’s gonna take a long time to get a reliable, sustainable, significant EV charger infrastructure except for Tesla. ’cause They built the infrastructure that fostered that innovation.

Joe Gottlieb:

Yeah, no, it’s a good parallel. Okay. So I would love to, let’s bring this to a close.

Casey Green:

Okay, let’s,

Joe Gottlieb:

What are three takeaways we should offer our listeners on these best practices looking forward?

Casey Green:

Okay, well, we’ve touched on some of these already, so I’m gonna try to recap briefly. You know, we, we spent the last couple minutes talking about infra, you know, in infrastructure fosters innovation. So no reason to, you know, not the other way around. We don’t do enough for recognition and reward for the people who are critical to our organizations. You know, whether it’s faculty or instructional support personnel or elsewhere, you know, and, and they are part of the infrastructure. It’s not just hardware and software and mortars and bricks and services. And we have to, and we can do better. You know, we’re, we’re seeing this now in terms of some of the challenges of, of hiring and retaining IT personnel. But it’s gonna be even, you know, other areas, particularly as folks can work remotely. And, and finally, again, we talked about this earlier.

Casey Green:

The whole issue of data and analytics we’re kind of stuck at, you know, roughly a third over time, multiple surveys of multiple c-suite personnel saying, you know, only about only about third say we do a good job with data and analytics that just can’t stand it. It shouldn’t have stood in the old environment and it can’t stand in the new environment. You know, maybe AI will be the catalyst. It’ll be a, the great leap forward because AI will help faster, better insight and narrative that helps connect the dots. And, and then people will, you know, grab it, hold onto it, advocate for it, make, and, and, and add a top level narrative in terms of how we do that.

Joe Gottlieb:

Casey, that’s a great summary. Thank you so much for joining me today.

Casey Green:

And, and Joe, my thanks to you for the opportunity and the invitation. You have been a generous, gracious and appropriately assertive, you know, host in terms of, you know, sort of pushing me to help clarify some of these things. So I thank you for that. Hopefully it worked well for your audience

Joe Gottlieb:

And thanks to our guests for joining us as well. Have a great day and we’ll look forward to hosting you again on the next episode of TRANSFORMED. Yo, stop the music. Hey, listeners have transformed. I hope you enjoyed that episode. And whether you did or not, I hope that it made you stop and think about the role that you are playing in your organization’s ability to change in the digital era. And if it made you stop and think, perhaps you would be willing to share your thoughts, suggestions, alternative perspectives, or even criticisms related to this or any other episode, I would love to hear from you. So send me an email at Info@Higher.Digital or Joe@Higher.Digital. And if you have friends or colleagues that you think might enjoy it, please share our podcast with them as you and they can easily find TRANSFORMED is available wherever you get your podcasts.