Which colleges best set up its graduates for careers in finance? Or data science? Or law? It turns out that different schools really help students pursue careers in different fields. And other schools, not so much. Our guest, Matt Sigelman, from the Burning Glass Institute, helps breakdown the latest research that they published with the Wall Street Journal on the topic and helps you know what it all means—plus other insights on the connections between education and careers.

For those who have been in the worlds of education and workforce, you probably know Matt and the great analytical work he has led to help build the field of labor market analytics. This conversation is the first in a semi-regular set that Matt and I plan on having each year to help share insights from the latest in research that the Burning Glass Institute does and help share why it matters.

As always, subscribers can listen to the conversation above, watch it below, or read the transcript.

Horn: Welcome to the show where we are dedicated to building a world in which all individuals can build their passions, fulfill their potential, and live a life of purpose. And to help us think through that today, our guest is Matt Sigelman. He's the president of the Burning Glass Institute, a nonprofit that mines for data-driven insights around the future of work and pathways into the job market, and then works with educators and employers and policy makers to help build those better pathways to advance opportunity for more people. That's my language. I'll let Matt give a crack at it in a moment in his. But before the Burning Glass Institute, he was the CEO of Emsi Burning Glass for nearly two decades, which is now known a Lightcast, where he's still the chair of that board. And he really helped pioneer this notion of data-driven labor market insights. So Matt, welcome to The Future of Education. It's great to see you. We've been threatening to do this for a while. I'm glad we're finally getting to do it.

Sigelman: Well, very much likewise, Michael. Thanks so much for having me.

Morning Warmup

Horn: Yeah, you bet. So four parts to the show. We're going to start with our morning warmup, go into a work time of specials and closing time. And in our morning warmup, sort of our lightning round, if you will, I want folks to get to know you and your work better because you and I anticipate doing this on a more regular basis. So first, just give us a little bit more about the fundamental work that the Burning Glass Institute does and your raison d'etre. Why do you exist?

Sigelman: So the Burning Glass Institute is a fully independent nonprofit that advances data driven research and experimentation at the intersection of the future of work and the future of learning. As you mentioned a few minutes again, I spent most of my career building what's today Lightcast, terribly proud of its breakthrough innovation of bringing really robust and granular and timely data to understanding the supply and demand of skills in the market today. The Burning Glass Institute builds on novel data sources like Lightcast and a number of others to be able to answer the question of: How do we take these kinds of data sets and drive fundamental transformation? We know that the world of work that we live in is one that still is rife with inefficiencies, with inequities, and the question is: How do we bridge those gaps?

So we've been doing a ton of work recently, for example, looking at worker mobility this past fall together with the support of the Schultz Family Foundation and in partnership with Joe Fuller at Harvard Business School, we released what we called our American Opportunity Index, which is our first foray into saying, "Hey, look. How we do evaluate worker outcomes in a truly quantitative way?" And specifically, what the was doing was measuring the Fortune 250 based upon the level of opportunity that they create for workers. At a broader level though, what we were doing was creating a methodology for evaluating mobility. And it's something that we've more recently been applying to understanding the trajectories of learners after the complete programs of study.

As you know, there's a lot of work that's out there. They're trying to figure out: How do we make sure everyone complete a degree? But how do we make sure that degree actually bears out over time? And so some of those same metrics that we used in the opportunity index to study worker mobility are proving to be terribly relevant in measuring learner mobility as well.

Horn: Yeah. I mean, it's just fascinating the amount of work that you're doing in these areas. And focusing on the real question, which is the ultimate value, not just: Did we print a card that says, "You graduated," which is the easy part, I like to think? You did a bunch of reports recently that I think ranked schools in an incredibly novel way, at least as far as I can tell. You basically looked at the careers themselves and asked, "Which undergrad institutions were the best at not just placing students in those careers, but helping them earn high salaries in those careers?" I think the areas were data science, consulting, law, finance. I'd love to know more about the research and the methodology behind that.

Sigelman: Yeah, for sure. This is something that we undertook together with The Wall Street Journal. I'd first just point out, I don't believe that the world necessarily needs more college rankings. But I do believe that learners deserve transparency into how, again, the kind of outcomes they can expect. Not every student going into school knows what she wants to do on the other side. I certainly didn't. But for those who do have an ambition, and I think that's increasingly important, given the very high cost of college and the debt that students find themselves saddled with. How do you know which schools are going to place you furthest toward that ambition?

So here's what we did and why this looks pretty different from things like the College Scorecard or the like. College Scorecard says, "Okay, in a given major," for those not familiar with it, this is the US Department of Education's effort to, and I think a very important effort, to say, "Okay, what are the earnings of graduates in the first few years after graduation?" It's limited to a few years. And it's really about looking at majors and just saying, "Okay. Where do people wind up?" And so you wind up with a lot of this sort of calculus of: Okay, well, if somebody goes on to become a social worker, not earning terribly much, but very well fulfilled, is that a poor outcome? Right?

Instead, we looked at this from the other direction. We said, "Okay, if you want to become ultimately a software engineer, if you want to become a data scientist, you want to become a management consultant, if you want to go into marketing, what are the schools that have been most successful at placing people into top paying roles within that career?" And so we're looking both at the share of graduates from a given institution who go into that field. And then specific to the ranking itself, of those at the school who go into the field, what percentage of them are in top paying roles? And some of the kind of results are pretty surprising.

So if you looked at the software engineering rankings, and again, you see this in The Wall Street Journal, I think they've got ... They're putting it all together. They launched it list by list, but-

Horn: It's quite clever, the PR rollout.

Sigelman: Next week, I think they're then going to kind of take the second bite of the apple and launch a print feature, I think. But so stay tuned, I'll do my job and do a little bit of advertising here. But one of the things you will find if you look at the software engineering ranking, look, there's a bunch of schools in there that ... Look, there's no surprise that MIT and Cal Tech and Stanford are top at sending, or some of the top schools, I don't remember the exact order, at sending kids on to software careers that pay well over a span of 10 years. But we found a number of small liberal arts schools, even ones that don't have engineering programs, I'm pretty sure don't have computer science departments, Schools like Mount Holyoke, which do very well.

And I think it speaks both to the nature of software development and how it's changing and probably will change even more in an era of generative AI. But it also speaks to: What's the broader set of tools that somebody needs in order to be successful in a career?

Work Cycle

Horn: Super interesting because I think what you're starting to show is, I know you've done a lot of research on the importance of major and where it helps and so forth. We'll get to that actually maybe toward the end a little bit. But I will note that major's not always predictive of what you want to do. And so I think you're starting to point to the nature of this set of skills that go beyond the narrow technical skill, but also, the social capital that accrues in a lot of these places and giving guidance. I suspect as we move into the work time, everyone's going to want to know a few of the top performers with these rankings. So can you just tease a little bit in different disciplines? Because what's interesting again, just to say this, you did law, for example. But this isn't the top law schools, it's the top colleges.

Sigelman: It's the top undergrads that send students on.

Horn: It's so interesting.

Sigelman: So first of all, by the way, one thing I should point out is how much it matters. And again, I don't have the rankings in front of me right now, but if I'm remembering correctly, the top earning ... Of the schools that had the most students graduate and ultimately go on to top paying law careers, their students were making about $50,000 a year more than graduates of median performing schools who went into law. So put that across a 30-year career, that's a one and a half million dollar difference in pay. One of the things that was really interesting in law as an example is that there was ...

So again, no surprise that going to Harvard is a great choice. I think we found was that first of all, there's very often a geographic effect in fields like the law, certainly in marketing. Some of the best paying jobs today are in tech or at least were until recent layoffs. And tech is sort of this black hole that's swallowing a lot of talent, lot of graduates. And so being in California, for example, a big leg up if you're going into finance, being around New York has a lot of the same kind of ecosystem effect. Baruch, for example, one of the CUNY schools, which is part of the City University system of New York. It's not one of the most selective schools out there, and yet, was far better performing in terms of what we call the school effect, the wage effect of associated with going to school, than many other schools that are considered far more elite. And I think it reflects the fact that, okay, well, if you're at Baruch, you're going to wind up doing an internship in the finance industry in New York on Wall Street, and you're going to be very well positioned.

One other thing which I found striking is this, and this was disappointing. We found that for the most part when we looked at sort of the best, the 20 performers overall in each field, very few of them were public, so much so that when we turned the list over to The Wall Street Journal, we said, "Hey, look, we're giving you both as sort of a ... We're actually going to split this into a private list and a public list because otherwise, you actually don't wind up seeing more than Berkeley or one or two others in most lists." And I think that speaks to both some of the continued equity challenges that we have in our higher education system. It also speaks to the problems of getting lost in scale.

If you're at a ... And you were talking about the methodology, I'm hoping I'm not getting too far into the weeds here, but if you're in a really big school, they may be delivering lots of people into great careers, but there's only so many jobs at Goldman-Sachs if you go into finance. There's only so many jobs at Cravath if you're going into law. And so there's just a lot of graduates from the University of Michigan or wherever it may be, so part of what we saw there was also kind of where you have the best change of getting seen.

Horn: That's super interesting because in essence, you're saying if Mount Holyoke, small class, sends X number into computer science, software engineering jobs, whatever it might be, they're all doing pretty ... Well, maybe. Right? 100% of them are hitting it out of the park. Michigan may send a bunch of kids to those jobs that do even better, but they're also sending a bunch who are maybe going into that career pathway and not doing as well, so the law of averages sort of hurts them in these sorts of rankings.

Sigelman: I think there's also a social capital question here as well. So again, if you're in just that great big melting pot, harder to get the signals, harder to get the help, and to get the concentrated attention. I think there's also what accountants would call positive selection effect. So most Mount Holyoke grads don't go into software engineering. The ones who do want us to imagine really are special people and who are really determined to be successful in that field. And so that may also explain some of the difference.

Horn: That's really interesting. So The Wall Street Journal obviously when it came out, they publicized who got on top of the rankings. Those were the headlines for the private and public institutions. But I'm sort of curious about the flip side of it, the institutions that maybe failed to make the grade, if you will. And maybe the way to ask this is more like: What insights could I harvest from this if I'm a prospective student to avoid making a mistake if I'm set on a particular career path?

Sigelman: So look, in terms of this body of research, we didn't do tons to mine the bottom of the list, I think, and that's partly practical because there's a lot of schools that-

Horn: Right. You could go down forever, yeah.

Sigelman: I think this is a ... And this is something which Jeff Selingo and I recently looked at, you'd mentioned that paper and I think probably worth bringing to bear here. The success of graduates is defined at a three-way intersection between the program of study, your major, the school you go to, and the skills you acquire. So there is a big difference in any program of study between whether you're at a highly selective institution or a non-selective institution. There's also a big difference between what program of study you're in. Look, let's call out what I think we all intuitively know, but which was I think a really remarkable finding just to see nonetheless, when we looked at that sort of intersection of programs of study and institutional selectivity, you would rather be a tech or engineering major at a totally non-selective institution at a regional public, or four year community college, or what have you, than be pretty much any other major at the most selective institutions.

And so I think that sort of speaks to some of the decision landscape that people have to make. We tend to focus on rankings at the institutional level. And we focus not enough at the program of study level. And again, some of that's natural because people don't necessarily know what they want to do. And there's this idle that we have of college is this kind of wonderful sorting hat, if you will, where we kind of come out knowing what we want to do. It's a very expensive sorting hat, and the stakes are very high. And so if you don't know where you want to go, what you want to do, you can wind up making some serious mistakes. Now it's interesting because this often gets cast as a debate between the STEM fields and the humanities. And indeed, there's been a significant flight out of humanities over the years.

Horn: The numbers have declined dramatically.

Sigelman: It's been a huge decline. But actually, where we see the biggest levels of under-performance are for the most part, less the humanities, though certainly most STEM fields outperform most liberal arts fields, not always, by the way. If you're going to be a life science major and not go on to graduate school, that's a mistake. But what kind of job do you get as a bio major who doesn't go get a nursing degree, or medical degree, or a PhD, or something like that? But most of the worst offenders are the kinds of programs that sound nominally practical, but which actually have either low demand or very little of the demand is for jobs that demand a degree. And it seems intuitively obvious to most of the people who are listening to us I'm sure, that mamas, don't let your babies go become parks and rec majors, or become transportation material moving majors, or law enforcement majors, or the like. If you're a first gen college goer-

Horn: You do not know.

Sigelman: There's nobody to tell you that.

Horn: Yeah.

Sigelman: And so we've actually seen a huge growth in those majors. If you look at enrollments and rather conferrals over the last 50 years, where are people getting degrees? STEM's been relatively constant. There's been a huge flight out of liberal arts. What's grown in the gap is those nominally practical majors that very often underperform.

Specials

Horn: It's interesting because you anticipated where I wanted to go, which as we move into the special section, is enlarging this with that research you did with Jeff. And you've just sort of alluded to it, that there's these bachelor's degree pathways that don't actually pay off in the same way that the bachelor's degree does on average. And I guess what was interesting to me was first, the first part of what you just said, is that these technical sounding, very vocation clear pathways that don't pay off, should avoid those if you're paying a lot I guess on the sticker price is the lesson.

But then you also found that there's certain pathways that are non degreed in nature that actually pay off better than some of those bachelor degree pathways you just mentioned. So what were some of those non-degree pathways that maybe people ought to be thinking about or considering?

Sigelman: So I will break this down into two parts. One is the non-degree pathways, but part of it is also: How do we create a more hybridized version of that? I mentioned there's a sort of three-way intersection here between programs of study and institutions. But the third leg of that stool is skills you acquire. And what we found was that in any given program of study, there are sets of skills that you can learn that significantly differentiate students that significantly change your prospects of success.

A public administration major who is able to learn public investment skills is making almost a quarter more than the public administration majors. Remember I was telling you about how there's a lot of life science majors who underperform, certainly other STEM majors, and in many cases, many humanities or social science majors. Well, a life science major who develops clinical research experience is making 60% more than other life science majors. So it's really about not necessarily the baby with the bath water, it's also for learners, it's not about oops, I made this terrible mistake and now I'm doomed. But it's: How do we make sure that learners have the information they need to know what they can do to make sure that they are maxing out their chances of success?

Horn: So that goes where I want to go, which is sort of the implications for this body of work, and I'm going to call it that because it's obviously lots of little strands that are significant each unto their own, but then together start to paint a very interesting picture about the landscape of pathways into the work and so forth. And so I'm just sort of curious at a macro level. What are things that we ought to be doing in your judgment to help empower learners to make investments and choices, and I'm going to phrase it this way, in line with the progress that they're seeking? And what are we learning about how to help them discern what is and isn't a good investment along that path that they've chosen?

Sigelman: So there's a couple of things that we've been working on here. First, I think it's just providing the insight about how different skills work. And different skills work in different ways. Right? So some skills are important because they're core to a discipline. Some skills are foundational. They aren't actually the skills of that job, but you kind of need to know them. And we often forget those. For example, if you want to be a graphic designer, graphic designers are doing project based work, and so they often need project management skills. They often need budget skills. But no one teaches you that as a graphic designer and graphic design school. But at the same time, there are sets of skills that are foundation, that are transformational to a role, that are fast-growing within it that drive significant premiums. And how do we identify those as well? So that's the first thing I'd say there.

We recently worked with Coursera to develop a framework to help both companies and learners make better optimized decisions about what skills to learn. Optimize is a funny, kind of wonky sounding word. You would just think how to make better decisions. But I think the optimization thing implies a set of choices around different priorities is really important to it because we looked at three dimensions, which sound really easy, and by the way, like huge loss of blood and whatever associated with producing them. One is: How much of an earnings boost does a skill give you? How much value does it give you in the market? A second is: How long does it take to learn? And the third is: How long does it last? How durable is that skill?

And I remember first sharing it with some folks and they're saying, "Okay, great. What are those skills?" What do you mean, what skills? The skills that are really quick to learn, that last a long time, and give you this huge lift in your career. Guys, there's no free lunch. There's precisely zero skills that match all of those criteria. But how do you decide which ones are worth the slog, which ones give you the quick hit? Those are decision spaces that you want to help people sort of make. And so part of it is this, how do we then, and I think this is where you're getting to, it's a question of: How do we create the structures and the transparency, structures of how people can acquire these skills on the fly? Because the ones from… as I know you agree, no longer works.

We did some work last year together with the Boston Consulting Group. We found that the average US job has seen 37% of its skills replaced in the last five years, which is an astounding pace of change. Right?

Horn: Wow, yeah.

Sigelman: Think of it as: Has the average curriculum changed 37% in the last five years? Well, of course not. Accreditors won't allow it. Right? So in that kind of context, everyone needs to acquire new skills. How do we construct a mechanism for people to be able to do that? Similarly, how do we enable people to stair-step their way toward economic mobility? Most people don't leap tall buildings in a single bound and go. There's wonderful programs out there.

Horn: Yeah. Do one thing and then build.

Sigelman: Exactly. Right? So I think we need to rethink our community college system because it is the natural infrastructure for people to be able to learn new skills on the fly. But right now, it's very oriented toward degree transfer, which so often doesn't work. Something like 80% of enrollments in community colleges are around people expecting to get a four-year degree. And according to the National Student Clearinghouse, only about 13% ever do. But this is also about: How do we give people transparency? And Michael, this is why I'm so proud of the work that we're just kicking off together around short-term credential transparency. You want to have a skill driven ecosystem, one where people, that life science major couldn't acquire that additional skill and clinical research experience and earn 60% more.

We have to have a way of representing skills that has real currency as a marketplace. And so you hear a lot of voices talking about hey, we need more short-term credentials. Actually, that's exactly not the problem. It's exactly the opposite problem from what we have. The US Chamber of Commerce's credential engine project tracks something like 1.2 million credentials. I always point out that there are 114,000 words in the Oxford Dictionary, so it's literally 10 times more credentials than there are words in English.

Horn: Than there are words to describe them.

Sigelman: Yeah. So we don't need more of them, we need more clarity about which ones actually deliver outcomes. And so we're [inaudible 00:28:38] to recently announced partnership together with Jobs of the Future to build on the work of the EQOS, the Education Quality Outcome Standards framework. People say, "How can we do this at scale?" How could we provide an evaluation of which credentials are actually bearing out for learners so that learners know which ones to invest in, so that employers know which ones to value and which ones represent the skills that they need?

Horn: Yeah. I think that's a perfect place to leave this conversation. I'll just add my appreciation, not just for the work that we're about to do with EQOS and JFF and Burning Glass Institute coming together in that, but more importantly, also the nuance that you just used to describe even those skills. Because what they stack on top of the experience, the program, the degree that you have makes a pretty big difference to answer: How valuable is it in the labor market?

And that level of nuance I think is important, just learning Python is going to have vastly different impacts on your career depending on what background you bring into it at that point. And so your answer to the person that says, "Well, where's the short-term durable magical skill?" It depends on context and that level of nuance I think that you all continue to craft, and this is incredibly important. So we're going to come back to you as you keep releasing these reports and breaking these insights because my hope is that it'll give people a clearer and clearer picture over time of this future of work and the different pathways, the winding pathways if you will, into it.

Sigelman: Well, always welcome these conversations, and I think we need to do so much better than we're doing right now. And there's a moment of opportunity when we see the kind of transformations that are taking place in the market, 37% of skills replaced in five years, we see the advent of generative AI, I think it's going to create an impetus for change at a policy level. It's going to create a demand from change both from learners and from employers at the other end, and that makes this an exciting moment.

Horn: No doubt. So we'll keep tracking it with you. Thanks for joining us on The Future of Education, all of you tuning in. Keep track of Matt, Burning Glass Institute, and all the insights that they're publishing. And we'll be back next time.

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