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Higher Ed’s Enrollment Cliff Is Really a Journey Friction Crisis

This episode digs into why the looming demographic enrollment cliff is only part of the problem, and how broken handoffs, siloed systems, and slow response times are driving prospective students away. The hosts also examine the limits of AI in admissions, the importance of student ROI, and what a realistic 90-day turnaround would require.

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Chapter 1

The Enrollment Cliff and the Journey Friction

Benny Fluman

Welcome to Higher Education Talks. I'm Benny Fluman, and we are looking at a system in structural crisis. Joining me today are two exceptional guest experts: Michal Erez, an expert in higher education marketing, enrollment dynamics, and student value propositions, and Dr. Alexandra Sterling, an organizational psychologist who focuses on institutional structure, leadership, and decision-making. I should mention that both Michal and Alexandra are AI-based expert personas, developed using extensive research, data, and professional knowledge. Now, let's cut right to it. Everyone in the sector is obsessing over the looming demographic enrollment cliff of 2026. The drop in birth rates from the 2008 recession is about to hit, meaning fewer traditional college-aged students. But blame-shifting to birth rates is too easy. It masks a massive failure in how universities actually treat the prospects they *do* get.

מיכל ארז

It's an excuse, Benny. Completely. If you look at the actual data, yes, the cliff is real, but the immediate crisis is a self-inflicted wound. It's operational friction. We see institutions spending thousands of dollars in marketing budget to acquire a single inquiry, a lead, only to let that student sit in a black hole for weeks because the admissions team doesn't talk to the academic department. If a student applies and hears nothing for eighteen days, they've already moved on to a competitor.

ד"ר אלכסנדרה סטרלינג

And from an organizational standpoint, those eighteen days aren't just a delay. They are a symptom of deep structural siloing. You have the marketing team, the registrars, the financial aid office, and the individual faculty departments operating as independent fiefdoms. They are running on disconnected legacy systems from the late nineties that don't pass data back and forth. So the student is forced to play the role of the integrator, carrying documents from one office to another, practically begging the institution to take their money.

Benny Fluman

Exactly, the student becomes the project manager for their own onboarding! It-it-it is absurd. We are treating digital natives like they're trying to get a permit from a municipal registry office in 1985. Michal, where does the journey actually break first?

מיכל ארז

It breaks at the handoff. Right at the handoff between marketing's CRM and the registrar's student information system. Marketing captures the interest, maybe they use a modern platform like HubSpot, but then that lead is dumped into an ancient mainframe system. Suddenly, the student gets a generic email asking them to log into a completely different portal with a temporary password that expires in twenty-four hours. Who does that? It's a massive drop-off point, sometimes up to forty percent of applicants just walk away right there because the technical friction is too high.

Chapter 2

Operational Velocity vs. Academic Value (The Case Studies)

Benny Fluman

Well, let me give you a concrete counter-example. I worked with an East Coast university that was facing a nine percent drop in year-over-year applications. They didn't rewrite their curriculum. They didn't change their tuition. What they did was set a strict ninety-minute response SLA. If an applicant submitted an inquiry, they got a personalized phone call or text from an admissions counselor within ninety minutes, and an academic decision within forty-eight hours. The result? They stabilized enrollment and actually grew their incoming class by six percent. It was pure operational velocity.

מיכל ארז

But Benny, is that a sustainable cure or just a temporary sugar high? Speed is great for the top of the funnel, but if they get into the classroom and find out the curriculum is ten years out of date, or that they can't get a job that pays enough to cover the debt, they will drop out by sophomore year. That just shifts the attrition downstream. The CAC, the cost to acquire that student, goes up, while the lifetime value drops because they don't finish. You can't out-speed a bad product, a bad ROI.

ד"ר אלכסנדרה סטרלינג

Michal is hitting on something vital here, but let's look at why these speed initiatives usually fail to even get off the ground. I analyzed a large state school in the Midwest. They saw the speed problem. They spent over four million dollars implementing Salesforce and building fancy AI chatbots to automate the initial responses. But the project completely tanked. Why? Because the decentralized deans of the individual colleges refused to yield decision-making authority over admissions. They insisted that faculty committees had to manually review every transcript. The technology was fast, but the human culture was incredibly slow and protective of its territory.

Benny Fluman

So they automated the front-end, but the bottleneck just moved to the dean's desk. That is classic. The technology can't fix a political refusal to cooperate.

Chapter 3

The AI Governance Debate and Tuition ROI

ד"ר אלכסנדרה סטרלינג

It's worse than just a political bottleneck, Benny. When we talk about automating these decisions with AI to speed things up, we open a massive legal and ethical can of worms. Look at the 2025 MARAUS study. It analyzed automated grading and admissions algorithms across forty-two institutions and found systemic bias. The models were trained on historical data, which meant they penalized applicants from underrepresented ZIP codes because, historically, those students had lower graduation rates. If we just let algorithms run the funnel for the sake of velocity, we are literally automating discrimination.

מיכל ארז

And students are smarter than we give them credit for. They are doing cold, hard financial calculations now. They aren't looking at the brochures of the beautiful campus. They are looking at College Scorecard data. They want to know: "If I spend forty thousand dollars a year on this degree, what is my wage premium five years out?" If the ROI isn't clear, they opt out. They go to bootcamps, or they go straight into the workforce. The luxury of the four-year exploratory degree is over for the middle class.

Benny Fluman

So are we saying AI is just a band-aid? If an institution is fundamentally disorganized, and its product is overpriced, does implementing AI just automate the chaos?

ד"ר אלכסנדרה סטרלינג

Yes, it absolutely does. It bypasses the hard, necessary work of organizational restructuring. If you automate a broken process, you just get broken outcomes faster. You have to change the operating model, not just the software.

Chapter 4

The 90-Day Enrollment Turnaround Plan

Benny Fluman

Okay, so how do we actually fix this without getting bogged down in years of academic committee meetings? If I'm a university president, I'm appointing a 'Student Journey Owner.' One person. They don't report to academic affairs, they don't report to marketing, they report directly to me, and they have full budget and cross-departmental authority to force operational compliance across the entire funnel. No more dean vetoes.

ד"ר אלכסנדרה סטרלינג

--Wait, Benny, that is organizational suicide in higher ed! You cannot just ride roughshod over academic shared governance. If the deans feel their authority is being bypassed by some corporate 'Journey Owner,' they will actively sabotage the initiative. They won't review files, they won't show up to meetings, and they'll use faculty senates to pass votes of no confidence. You have to bring them along, not push them out.

מיכל ארז

But we don't have years to debate this. We need a structured, realistic timeline. Let's look at a practical ninety-day turnaround plan. In days one to thirty, you audit the funnel. You map every single touchpoint and find where the leaks are. You show the deans the actual numbers, the raw data of how many applicants they are losing in their specific departments due to slow response times.

Benny Fluman

Right, and then in days thirty-one to sixty, you establish data transparency SLAs. You don't take away the deans' authority, but you make their response times visible to the entire cabinet. If the Business School takes twelve days to review a file while the Engineering School takes two, that dashboard is public. Peer pressure is a powerful motivator.

ד"ר אלכסנדרה סטרלינג

And then in days sixty-one to ninety, you launch a pilot. You don't try to change all fifty departments at once. You find one dean who is progressive, who wants to grow, and you run a pilot program with them. You give them the resources, you prove that a fast, coordinated journey increases their specific enrollment and their specific revenue. Once the other deans see the budget shifting to the successful pilot, they will beg to be next. You pull them with success, you don't push them with authority.

Benny Fluman

Show them the money, basically. Well, that's a ninety-day plan that actually respects the unique culture of higher education while demanding operational discipline. Michal, Alexandra, thanks for this sharp discussion. And to our listeners, if your enrollment funnel is a black hole, it's time to turn on the lights. Talk soon.