When the Universities of Kent and Greenwich announced last week that they would merge to create the UK’s first “super-university,” effective from 2026/27, many saw a straightforward response to the higher education sector’s ongoing financial pressures. But this move reveals something deeper: universities are facing many of the same existential demands as startups. And just as startups must adapt or die, universities may increasingly need to think like startups to survive and fulfil their mission.
This month’s Innovate Together builds the case that universities and startups are more similar than the common narrative suggests – and that universities thinking in startup terms (agile, lean, customer-focused, product-market oriented) isn’t just possible, but necessary.
The convergence of pressures
Financial sustainability under strain
Clearly, the Universities of Kent and Greenwich are merging because they are being squeezed: rising costs of staffing, estates, regulation; declining income from international students; and tuition fees that are effectively frozen in real terms. These are not just institutional problems – they’re symptoms of a high education sector adjusting to shrinking margins and increasing expectations. What’s interesting is that the decision to merge reflects a logic that startups face every day: find efficiencies, streamline overheads, focus resources on core value-creation.
A startup with mounting operational costs and uncertain revenue must do similarly – cut what isn’t mission-critical, sharpen focus, adapt quickly. Universities increasingly find that traditional models (large campuses, dispersed services, cross-subsidy) are under stress. Merger becomes one path to emulate startup cost-leverage and scale economies.
Employability, skills mismatch and talent demand
Perhaps the bigger pressure is cultural, not financial. It is a widely rehearsed narrative across government and the press: many graduates who leave university are well versed in theory but under-prepared for the immediate demands of working life. Employers often report gaps in teamwork, communication skills, adaptability and real problem-solving skills.
Beyond this being merely discursive, recent UK data supports this vividly:
- The Employer Skills Survey (2024) of over 22,000 employers found frequent reports of difficulties recruiting for graduate-level roles due to lack of required qualifications or experience. Many employers also identify skills lacking in the existing workforce (not just in new hires).
- From the Survey of Adult Skills 2023 (OECD) for England: 37% of workers report being overqualified for their current jobs, compared with the OECD average of 23%. Also, 41% say their field of study does not match their job. Overqualified workers in England tend to earn 18% less than comparable matched peers.
- Other researchers (e.g. “Vertical and Horizontal Mismatch in the UK: Are Graduates’ Skills a Good Fit for Their Jobs”) estimate that roughly 30-34% of graduates are in roles where either their qualification is more than required, or their field of study doesn’t align.
What does this mismatch tell us? Unfortunately, at least if public discourse is to be believed, it’s that having a degree, or deep academic preparation, is necessary but no longer sufficient. There is a growing premium on employer-readiness – on skills, adaptability, situational judgement, cross-disciplinary thinking, and resilience.
How universities can learn from startup thinking
So, given that universities and startups are grappling with overlapping pressures – financial constraints, talent supply, the need to translate potential into performance – the question becomes: how should universities shift, by borrowing from startup practices? Here are threads that emerge from the data, and from observing what is already happening, including via recent mergers like Kent and Greenwich.
Lean operations and agile structures
Startups are born lean; they iterate fast and reorganise when something doesn’t work. Universities, by contrast, often carry heavy legacy overhead. The Kent and Greenwich merger’s approach – to merge back-office, leadership, research capacity, while preserving local identity – in some ways mirrors a startup’s strategy of retaining customer-facing brands while consolidating its support services.
Thinking like a startup therefore means being willing to streamline structures, reduce duplication, simplify decision making and maintain flexibility in resource allocation.
Market-orientation: focus on relevance and demand
Startups succeed when their product meets a market need. It’s that simple. Universities have historically been somewhat insulated from market feedback: notions of academic value, research citations and teaching excellence awards follow a different logic. But employability metrics, skills mismatch data and employer feedback are increasingly demanding that universities respond to labour market signals much more directly. For example:
- The demand for graduate-level qualification continues to rise: the Skills & Employment Survey 2024 shows 46% of workers say their current job requires graduate level education. Yet many of those same workers are in roles where their highest qualification may be more than strictly necessary.
- Also, skill-based hiring is increasing, especially in AI and green roles: a recent study of around 11 million UK job vacancy postings from 2018-2024 shows that for AI roles, demand for skills rose, while formal degree requirements declined by 15%. Skills in AI carry a wage premium (23%) over jobs requiring the degree alone.
Universities are now grappling with the knowledge that they all need to treat employer and market input not as a nice-to-have, but as central to how they design curriculum, qualifications and career pathways.
Embedding learning into real-world context
But, again, the startup mindset is incredibly valuable here. Startups test fast: prototypes, pilot projects, feedback from users. Meanwhile, universities often segment “learning” (classrooms, lectures) from “application” (placement, internships). But given the level of mismatch and over-qualification, the separation is proving increasingly costly.
Data and commentary show that many graduates would benefit if university learning included more project work, live briefs, authentic assessment of teamwork, leadership, and – of course – commercial viability.
In this case, thinking like a startup means bringing the market “inside” – projects co-taught with industry practitioners, labs and studios partnering with businesses, multidisciplinary innovation challenges as part of every programme.
Responsive feedback loops and iteration
Similarly, in startup worlds, when something fails or underperforms, rapid iteration follows. Universities sometimes lag in feedback mechanisms: curricula can remain static for years at a time, assessment formats remain traditional, change is slow.
Worse still, the aforementioned Employer Skills Survey and Skills & Employment Survey both indicate that training provision, employer skills gap data and local labour market intelligence are available but often under-utilised for shaping programmes in real time.
If universities were to think like startups, though, it would build in short feedback cycles: not just surveys from graduates, but regular employer panels, constant harnessing of local skills data, rapid testing of new modules, and revoking what doesn’t work.
Why this matters: stakes for universities, students and economy
The implications of failing to adapt are severe:
- For students: degrees alone may not secure meaningful work; the over-qualification data suggests many graduates will be underemployed relative to their training. Wage penalties and dissatisfaction likely follow.
- For universities: reputation, funding, enrolment all increasingly depend on outcomes. Universities unable to demonstrate graduate success, employer satisfaction and research translation will be under pressure from regulators, funding bodies and competition.
- For the economy: under-utilised talent is wasteful. Skills mismatch reduces productivity, weakens innovation and increases social costs. International competitiveness depends on alignment of education with growth sectors (AI, green tech, health, sustainability, etc.).
It’s obvious that the merging of Kent and Greenwich signals that universities are recognising these stakes. By aligning more closely with regional priorities (creative industries, health, sustainability), consolidating capacity and seeking to increase scale and impact, they are implicitly embracing startup-like thinking: responsiveness, relevance, lean design.
Conclusion
Startups and universities may often get cast as opposites – one agile, tight, market-driven; the other sprawling, slow, academic. But the lived reality is that their pressures are converging more than ever: financial strain, talent supply, relevance, translation, governance. The Kent and Greenwich merger is a landmark case study in that convergence.
If universities are to thrive once more, they must think like startups – not by mimicking them wholesale, but by adopting key startup mindsets: lean operations; market-oriented curriculum; embedded real-world learning; iterative feedback loops.
This isn’t abandoning the intellectual mission of universities. If anything, it’s enhancing it. It’s recognising that in the 21st century, knowledge without readiness is an incomplete offering. The most resilient universities will be those that combine seriousness of scholarship with responsiveness of startup: leaders, not laggards.
