Online Education Drives Financial Impact, Key to Higher Ed Growth

There was a time when academia was associated with calm thinking, intellectual patience, and the slow but steady pursuit of knowledge. Research was meant to be reflective. Teaching was meant to be transformative. Scholarship was meant to mature over time. Today, however, academia often seems to be in a hurry. The pressure to publish more, apply faster, respond immediately, show impact instantly, and document everything continuously has gradually shifted the academic culture from thoughtful inquiry to constant performance. The emphasis is no longer only on asking meaningful questions, but on how quickly outputs can be produced and counted. Institutional rankings, accreditation requirements, performance metrics, funding deadlines, citation targets, and administrative audits have collectively created an environment where speed is quietly replacing depth. Academics are increasingly navigating dashboards instead of ideas, timelines instead of theories, and reporting formats instead of reflection. This growing urgency has also changed the nature of teaching and mentoring. Faculty members are expected to multitask between research, administration, student engagement, industry collaboration, documentation, and digital presence—often simultaneously. In such a system, the time required for reading, thinking, and developing original perspectives becomes a luxury rather than a necessity. Ironically, knowledge creation—by its very nature—demands incubation. Breakthrough ideas rarely emerge from urgency; they evolve through contemplation, debate, failure, and revision. When academia begins to operate on corporate-style timelines, there is a real risk of valuing productivity over purpose. Perhaps the question we need to ask is not how to make academics work faster, but how to create academic ecosystems that allow them to think better. Because when academia is always in a hurry, it may produce more work—but not necessarily more wisdom. #HigherEducation #AcademicLife #ResearchCulture #FacultyLife #KnowledgeCreation #QualityInEducation #AcademicLeadership #IndianAcademia #EducationMatters #ImpactOverOutput

🎓 Higher education procurement is no longer just about cutting costs it’s becoming a catalyst for resilience, value, and impact. With tightening budgets, policy uncertainty, and rising expectations around transparency and sustainability, procurement leaders are being pulled into the center of institutional strategy. Our latest blog explores how higher ed procurement is evolving from cost containment to value creation helping universities support research, student success, and mission-driven goals, even in times of disruption. 🔍 Key themes covered: 🔹Moving from savings to strategic value 🔹Using AI and data to drive resilience and visibility 🔹Centralising spend for stronger control and compliance 🔹Embedding sustainability and DEI into sourcing decisions 🔹Empowering procurement teams to focus on higher-value work The institutions that embrace digital transformation, automation, and stronger supplier collaboration won’t just survive uncertainty they’ll thrive. 👉 Read the full blog: From Cost to Catalyst: https://okt.to/463tAg #HigherEducation #Procurement #DigitalTransformation #AI #Sustainability #SourceToPay #EducationLeadership #JAGGAER

Delighted to see Policy Evidence Unit for University Commercialisation & Innovation (UCI)'s Expert Insights Series on university knowledge exchange (KE) for regional growth is now live. Papers in the Series describe the current evidence base and what needs to be done to unlock our ability to develop better data and metrics to inform the development of more targeted and impactful KE funding programmes and strategies for regional growth. This work was commissioned in partnership with Research England as part of a programme to develop next generation KE data and metrics.

Beyond Rankings: Measuring What Really Matters The return of investment (ROI) Universities are increasingly being called to prove their worth not just through research papers and league tables, but through something far more tangible: territorial impact. Rethinking how higher education institutions measure success. Here's what that looks like: Map the real challenges facing your region, depopulation, digital transformation of local commerce, sustainability gaps. These become your anchors. Create cross-faculty task forces dedicated to each challenge. Break down silos. Put your collective expertise to work where it matters most. Measure differently. Yes, academic publications still count. But so do startups launched, public policies influenced, and community problems actually solved. The university of the future isn't the one with the prettiest campus—it's the one recognized as an indispensable partner in its region's development. Research stops being an end in itself and becomes a lever for real change. Through initiatives like Liveseeding, EU DUT ECLETIC, RHYTHM, and AGRIFLEX, we're proving that impact isn't just measurable—it's essential. Because when you invest in higher education, you're not just funding research. You're funding futures What does territorial impact look like in your region? #HigherEducation #TerritorialImpact #CommunityEngagement #Innovation #RegionalDevelopment

Are we misunderstanding value in universities? It is not a funding problem. It is a definition problem. I sit in meetings every week where “value” is described as: – delivering a new system – launching a new process – implementing a new platform – being flat out busy That is not value. That is activity. If we are serious about value, then we need to answer one simple question: What is different six months after we do this? Not what did we build. Not how hard did we work. Not how many milestones did we tick off. What actually changed? Did we: • Save money in a measurable way? • Reduce institutional risk? • Increase revenue or protect it? • Improve capability in a way that compounds? • Speed up delivery elsewhere? • Strengthen reputation in a way that matters? If none of those shifted, then we did not create value. We created motion. And motion is seductive. It feels like progress. It fills slides. It keeps teams busy. But it does not necessarily move the institution forward. For me, value is the answer to “so what?” “So what we implemented the new system?” “So what we redesigned the workflow?” “So what we migrated to the new platform?” If we cannot clearly articulate the outcome at the very beginning, then prioritisation is already broken. The essential step that is often missing is forcing the uncomfortable sentence: In six months’ time, this will have changed because… If that sentence is vague, the initiative probably is too. Delivery is important. I run delivery teams. I care deeply about execution. But delivery without a defined shift in cost, risk, revenue, capability or speed is just well organised busyness. And universities are exceptionally good at busyness. How is “value” defined and measured in your institution?

Europe’s technical universities play a decisive role in competitiveness, innovation and strategic autonomy. Check the new Science|Business report from the EIT Higher Education Initiative that highlights what needs to change — and fast. As I see it, the key takeaways from the report for technical universities like DTU, where I am working: 🔹 Stop copying — collaborate through complementary strengths. Rankings have pushed universities to look alike. Real impact comes when institutions collaborate based on distinct profiles in research, education and application. 🔹 From institutions to platforms. Universities should act as platforms for collaboration — connecting students, researchers, industry and society — and measure success by impact and relationships, not only publications or degrees. I think that DTU is doing quite good in this area. 🔹 Start small, move fast. Agile formats (challenge-based projects, joint courses, micro-credentials, short industry collaborations) often outperform large, rigid partnerships — also between universities. 🔹 Engineering excellence meets real-world problems. Strong theory must be paired with applied, interdisciplinary learning and closer engagement with SMEs and innovation ecosystems. 🔹 Entrepreneurial mindset is not optional. The report points out that technical skills alone are not enough. Risk-taking, systems thinking and collaboration across disciplines must be embedded early — especially at PhD and postdoc level. Well, what's my takeaway then: As I see it, the future is not one “best” university model. It is networks of strong, diverse technical universities, collaborating around shared missions while scaling their unique strengths. That’s where Europe can prevail in this very uncertain world. 🇪🇺⚙️ 📎 I've attached the report: “Reimagining research, innovation and education” #DTU #TechnicalUniversities #EngineeringEducation #UniversityCollaboration #ResearchAndInnovation #EIT #ImpactDriven

At a recent commercialization pilot project working with universities, I noted something interesting.  University-born ventures are often validated academically, not commercially. They are built to pass peer review, secure grant funding, and meet research standards. But the market plays by different rules. Customers don’t fund ideas because they are technically sound. They pay because the solution solves a problem they deeply care about. In several cases, we found brilliant innovations solving technically interesting problems but with limited real demand behind them. That meant going back to basics: Who is the customer? What are they willing to pay for? What needs to change before this can compete in the market? Commercialisation is not just about moving research out of the lab. it should translate into something customers understand, value, and buy. The lesson? Academic excellence and market readiness are not the same thing and both matter if innovation is to move from research to revenue. #SMEGrowth #AcademicResearch #ResearchCommercialization

Public universities are increasingly criticised for behaving like mini-fiefdoms. The critique is often cultural. I think the problem is economic. Over the last decade, public funding has continued to flow into hierarchical permanence — managerial layers, branding units, extraction-oriented commercialisation structures — while the transition from education to livelihood has been quietly outsourced to graduates. The labour market changed. Knowledge distribution changed. AI changed production economics. Funding logic didn’t. In today’s Substack, I outline a different allocation model: Not enrol → credential → hope But enrol → learn → incubate → launch → exit This isn’t about “defunding universities.” It’s about defunding hierarchy and funding transition. Digital fashion offers a live example. By 2026, digital fashion operates across platform economies, AI-assisted design pipelines, and hybrid physical-virtual studios. Yet institutional responses often prioritise internal upskilling and event programming over practitioner-led incubation and graduate launch infrastructure. The issue isn’t technology adoption. It’s where funding flows. Key shifts: – Post-graduation incubation windows – Microenterprise launch funds – Shared IP and governance clinics – Paid transition instead of unpaid employability theatre – Traceable authorship and accountability infrastructure Public money should fund public transition — not internal permanence. The next 5–10 years will determine whether universities function as prestige engines or as infrastructure for launch. Full argument here: https://lnkd.in/gABU683N #HigherEducation #PublicFunding #UniversityReform #Governance #ResearchPolicy #AIandInstitutions #DigitalFashion

Australia’s future productivity, health and innovation depend on a research system that actually works. The evidence is unequivocal. Independent reviews have confirmed what The Group of Eight has long said: Australia’s research funding system is financially unsustainable and is holding the nation back. As we approach the 2026-27 Federal Budget, the Government faces a clear test of its commitment to long‑term economic growth. Here are 3 practical priorities: • Begin the transition to funding the full economic cost of research • Lift the $650m MRFF cap and unlock up to $1 billion a year for medical research • Secure Australia’s associate membership of Horizon Europe, the world’s largest research and innovation program These are not discretionary expenses. They are nation‑building investments - in innovation, health, global collaboration and Australia’s economic resilience. https://lnkd.in/gfviTXGQ

Every university is being pitched a new “student success” platform. Early alert systems. Retention analytics. AI advising tools. Engagement dashboards. The pitch is always the same: “This will increase retention.” But here’s what actually happens on campus: • IT worries about integration. • Academic Affairs worries about faculty load. • Student Affairs pushes urgency. • Finance questions cost. • Leadership approves under pressure. A year later? No one can clearly answer: Did it work? Here’s what that same decision looks like inside CDR. Step 1: Submission A third-party tool proposal is submitted with: – Retention problem clearly defined – Baseline student outcome metrics – Projected impact – Total cost of ownership – Integration scope – Risk indicators Not a vendor slide deck. A structured decision container. Step 2: Routing The proposal routes automatically for structured input: IT / CIO Office – Integration feasibility – Data security review – Infrastructure requirements – Timeline realism Provost Office / Academic Affairs – Academic alignment – Faculty workload impact – Policy implications Institutional Research / Data Team – Validation of baseline metrics – Measurement methodology – Forecast accuracy Student Affairs – Advising workflow impact – Student adoption risk – Support capacity Engineering / Systems Team – Implementation lift – Resource allocation requirements – Technical dependency risks Finance / CFO Office – Budget impact – Cost modeling validation – Opportunity cost analysis Each unit provides documented input. No invisible objections. No side-channel approvals. Everyone sees where it is. How long it’s been there. What’s blocking it. Step 3: Final Decision Executive leadership reviews: – Cross-functional input – Financial impact – Risk profile – Strategic alignment Decision: Approve / Revise / Reject With documented rationale. Step 4: Aftercare (Implementation Engine) If approved, execution is structured through: – Defined sprints – Capacity tracking – System repair logging – Diagnostic checkpoints – Ownership assignments – Timeline visibility Now it’s not: “We bought a platform.” It’s actively implemented. Step 5: Health Check (ROI Measurement) 60–90 days later, leadership evaluates: • Are outcomes aligning with the original retention intent? • Would we make this decision again? • What actual financial impact has materialized? • Are results sustainable across terms? • What barriers surfaced? That’s the difference between: “We adopted a tool.” And: “We measured whether the decision strengthened the institution.” Higher education doesn’t need more vendors. It needs structured decision accountability. That’s what CDR provides. Try it today: https://zurl.co/FBhq6 #HigherEducation #UniversityLeadership #StudentSuccess #EnrollmentManagement #DecisionDesign #CDR