Dr David Bozward

Tag: university strategy

  • Why Universities Are Measuring Employability Completely Wrong

    Employability has become one of the defining metrics of higher education. It sits at the centre of league tables, regulatory frameworks, and institutional strategy. Yet, despite the attention it receives, most universities are measuring it in ways that fundamentally misunderstand what employability actually is—and how it is created.

    This is not a minor technical issue. It is a structural flaw. And it is quietly shaping the behaviour of institutions, the design of curricula, and the experiences of students in ways that ultimately undermine the very outcomes universities claim to prioritise.

    The Problem: Measuring Outcomes, Ignoring Systems

    Most universities measure employability through a narrow set of outcome indicators:

    • Graduate employment rates (often within 6–15 months)
    • Salary levels
    • Progression into “highly skilled” roles
    • Further study rates

    These metrics are attractive because they are simple, comparable, and quantifiable. They allow regulators and rankings to create clean hierarchies. But they also create a dangerous illusion: that employability is an endpoint rather than a process.

    In reality, employability is not something that happens after graduation. It is something that is developed—often unevenly—over time.

    By focusing only on outcomes, universities overlook the underlying systems that produce those outcomes. This leads to three critical distortions:

    1. Short-termism – prioritising immediate employment over long-term career capability
    2. Attribution errors – assuming university input is the primary driver of outcomes
    3. Metric gaming – designing interventions to improve scores rather than substance

    The result is a measurement system that is precise, but not accurate.

    Employability Is Not Employment

    The first conceptual error is simple but profound: employability is not the same as employment.

    A graduate securing a job within six months tells us very little about their underlying capability. It tells us even less about their long-term trajectory.

    Employment outcomes are shaped by multiple external variables:

    • Local and national labour market conditions
    • Socio-economic background and networks
    • Prior work experience
    • Industry demand cycles
    • Geographic mobility

    A student with strong social capital and access to networks may secure employment quickly, even with relatively underdeveloped skills. Conversely, a highly capable student without those advantages may take longer to secure a role.

    If we measure employability purely through employment outcomes, we are effectively measuring advantage, not capability.

    This distinction matters. Because universities are not primarily responsible for labour markets—but they are responsible for capability development.

    The Missing Layer: Capability Development

    At its core, employability is about the development of capabilities that allow individuals to:

    • Enter the labour market
    • Navigate uncertainty
    • Create and capture value
    • Adapt over time

    These capabilities are multi-dimensional. They include:

    • Human capital (skills, knowledge, competencies)
    • Social capital (networks, relationships, signalling)
    • Cultural capital (confidence, norms, behaviours)
    • Experiential capital (practical application, real-world exposure)

    Most employability metrics fail to capture these dimensions in any meaningful way.

    Instead, they rely on proxy indicators—such as employment status—that sit several steps removed from the actual developmental process.

    This creates a measurement gap: universities are judged on outcomes they only partially control, while the capabilities they do influence remain largely invisible.

    The Pipeline Fallacy

    Universities often treat employability as a linear pipeline:

    Education → Graduation → Employment

    This model is intuitive—but wrong.

    In reality, employability is a complex, iterative process that begins long before university and continues long after graduation.

    Students do not enter university as blank slates. They bring with them:

    • Prior educational experiences
    • Family expectations
    • Networks and connections
    • Confidence (or lack of it)
    • Exposure to the world of work

    Similarly, graduation is not a fixed endpoint. Careers are no longer linear. They involve transitions, pivots, and periods of uncertainty.

    By imposing a linear model onto a non-linear reality, universities create systems that are poorly aligned with how careers actually develop.

    The Timing Problem: Measuring Too Late

    One of the most significant flaws in current employability metrics is timing.

    Most measurements occur after graduation—often 6 to 15 months later. By this point:

    • The student has left the institution
    • Multiple external factors have influenced outcomes
    • The opportunity for intervention has passed

    This is equivalent to evaluating a learning process only after the exam, without ever assessing progress during the course.

    If universities are serious about employability, measurement must shift upstream.

    We need to ask:

    • What capabilities are students developing during their studies?
    • How are these capabilities evolving over time?
    • Where are the gaps—and how can they be addressed early?

    Without this, employability becomes a retrospective exercise rather than a developmental one.

    The Behavioural Consequences of Bad Metrics

    Metrics do not just measure behaviour—they shape it.

    When universities are judged primarily on graduate outcomes, they respond rationally:

    • Focusing resources on final-year students
    • Prioritising “quick wins” in employment outcomes
    • Targeting students who are easiest to place
    • Investing in reporting systems rather than developmental systems

    This creates a skewed distribution of support, where those who need the most help often receive the least.

    It also encourages surface-level interventions:

    • CV workshops without real experience
    • Mock interviews without industry context
    • Job boards without network development

    These activities are not inherently bad—but they are insufficient on their own. They treat employability as a set of discrete tasks rather than a deeply embedded process.

    The Employability Illusion

    Many universities can point to impressive employability statistics. High employment rates. Strong salary outcomes. Positive graduate surveys.

    But these metrics often mask underlying issues:

    • Students lacking confidence in real-world environments
    • Graduates struggling to progress beyond entry-level roles
    • Limited entrepreneurial capability
    • Weak industry integration within curricula

    This creates what might be called the employability illusion: the appearance of success without the underlying substance.

    The danger is that institutions begin to believe their own metrics—while students experience a very different reality.

    Reframing Employability: A Systems Perspective

    To fix this problem, we need to move from an outcome-based model to a systems-based model.

    Employability should be understood as the interaction of multiple systems:

    1. Curriculum systems – how learning is designed and delivered
    2. Experience systems – access to placements, projects, and real-world exposure
    3. Support systems – careers services, mentoring, coaching
    4. Network systems – employer engagement, alumni connections
    5. Student systems – motivation, agency, identity

    Measurement must reflect this complexity.

    Instead of asking, “Did the student get a job?” we should be asking:

    • What capabilities has the student developed?
    • What experiences have they accumulated?
    • What networks have they built?
    • How confident are they in navigating uncertainty?

    These are harder questions—but they are the right ones.

    A Better Model: Measuring Development, Not Just Outcomes

    A more effective employability measurement framework would include three layers:

    1. Input Measures (What Universities Provide)

    • Integration of employability into curriculum
    • Access to industry projects and placements
    • Quality of employer engagement
    • Availability of mentoring and coaching

    2. Process Measures (What Students Do)

    • Participation in work-based learning
    • Engagement with careers services
    • Development of portfolios and projects
    • Network-building activities

    3. Capability Measures (What Students Become)

    • Problem-solving ability
    • Communication and collaboration
    • Adaptability and resilience
    • Entrepreneurial thinking

    Outcome measures (employment, salary) should still exist—but as one part of a broader system.

    This shifts the focus from what happened to how it happened.

    Embedding Employability, Not Bolting It On

    One of the most persistent challenges is that employability is often treated as an add-on rather than a core function.

    Careers services operate in parallel to academic departments. Workshops are optional. Engagement is uneven.

    This model does not work.

    Employability must be embedded into the curriculum itself:

    • Assessment linked to real-world problems
    • Industry projects integrated into modules
    • Reflection on skills and development built into learning
    • Continuous exposure to professional contexts

    This requires a fundamental shift in how universities design education.

    It also requires academic staff to see employability not as an external requirement—but as part of their core role.

    The Role of Data: From Reporting to Insight

    Universities are not short of data. The problem is how it is used.

    Most employability data is designed for reporting—to regulators, rankings, and stakeholders. It is retrospective and static.

    What is needed is developmental data:

    • Real-time insights into student engagement
    • Tracking of capability development over time
    • Identification of at-risk students early
    • Feedback loops that inform intervention

    This is where systems such as integrated dashboards, longitudinal tracking, and learning analytics become critical.

    But the purpose must be clear: not to produce better reports, but to enable better decisions.

    The Equity Dimension

    Current employability metrics also obscure issues of equity.

    Students from disadvantaged backgrounds often face structural barriers:

    • Limited access to networks
    • Financial constraints limiting unpaid opportunities
    • Lower confidence in professional environments
    • Fewer role models

    If universities are judged purely on outcomes, there is little incentive to address these deeper issues.

    A capability-based model, by contrast, allows institutions to:

    • Identify gaps early
    • Target support where it is needed most
    • Measure progress in a more nuanced way

    This is not just a measurement issue—it is a question of fairness.

    Entrepreneurship: The Missing Piece

    Another major omission in employability measurement is entrepreneurship.

    Most frameworks assume that success means entering employment. But for many students, particularly in a changing economy, value creation may take different forms:

    • Starting a business
    • Freelancing or portfolio careers
    • Creating social enterprises
    • Innovating within organisations

    Entrepreneurial capability is increasingly central to employability. It includes:

    • Opportunity recognition
    • Resource mobilisation
    • Risk management
    • Value creation

    Yet it is rarely measured explicitly.

    This reflects a deeper issue: universities are still operating with an industrial-era model of employment, while the economy is moving towards a more fluid, entrepreneurial reality.

    Towards a More Honest System

    Fixing employability measurement does not require abandoning metrics. It requires making them more honest.

    An honest system would:

    • Acknowledge the limits of outcome data
    • Measure capability development explicitly
    • Track student engagement over time
    • Reflect the diversity of career pathways
    • Prioritise long-term outcomes over short-term wins

    It would also require regulators and rankings to evolve—moving beyond simplistic indicators towards more nuanced frameworks.

    Conclusion: From Metrics to Meaning

    The current approach to employability measurement is not failing because it lacks data. It is failing because it is measuring the wrong things.

    By focusing on outcomes rather than systems, employment rather than capability, and short-term metrics rather than long-term development, universities have created a model that is easy to report—but difficult to defend.

    If we are serious about preparing students for a complex, uncertain, and rapidly changing world, we need to rethink what employability means—and how it is measured.

    This is not just a technical adjustment. It is a strategic shift.

    Because in the end, employability is not about whether a graduate gets a job.

    It is about whether they can build a career, create value, and adapt over time.

    And that is something no single metric can capture—but a well-designed system can support.

  • Why Entrepreneurship Education Must Move Beyond Business Start-Up

    Why Entrepreneurship Education Must Move Beyond Business Start-Up

    For years in my view, entrepreneurship education has been framed too narrowly. In many institutions, it is still treated as a route into venture creation: write a business plan, build a pitch deck, test an idea, raise funding, launch. That matters, but it is no longer enough. If entrepreneurship education is defined only by the number of start-ups it produces, then it misses its wider purpose and undervalues its deepest contribution to students, institutions, employers and society.

    A broader understanding is now well established in the literature. The European Commission’s EntreComp framework defines entrepreneurship as acting on opportunities and ideas to create value for others, and that value may be financial, social or cultural. It also makes clear that entrepreneurial competence applies across education, work and civic life, not only in the creation of a new venture. That is a significant shift. It means entrepreneurship education should not be confined to teaching students how to start companies. It should help them learn how to recognise opportunities, mobilise resources, solve problems, collaborate, adapt and create value in many contexts.

    This matters because most students who encounter entrepreneurship education will not become founders immediately after graduation. Many will enter employment. A small number will work in large organisations, public institutions, charities, most will work in SMEs or family firms. Others will move between employment and self-employment across their lives. If entrepreneurship education is designed only for the minority who want to launch a venture now, it excludes the majority who still need entrepreneurial capability. A more effective model prepares students for intrapreneurship, innovation, leadership, employability and social impact, alongside venture creation.

    The case for change is also pedagogical. Entrepreneurship education is strongest when it develops mindset as well as method. The literature increasingly presents it not simply as content about business, but as a way of thinking and acting. Recent reviews emphasise its role in building attitudes, skills and personal qualities such as initiative, creativity, resilience, adaptability and reflective judgment. These are not secondary outcomes. They are central outcomes. In a labour market shaped by automation, uncertainty and rapid change, these capabilities are arguably more durable than technical start-up knowledge alone. (ScienceDirect)

    This is where many current programmes fall short. When entrepreneurship education becomes overly start-up centric, it often defaults to a familiar set of activities: business plans, venture finance, lean canvases and investor pitches. Those tools are useful, but they can reduce entrepreneurship to a commercial formula. They can also overemphasise venture mechanics at the expense of creativity, critical thinking, ethical reasoning and contextual awareness. Students may learn how to present a venture without fully understanding how entrepreneurial action works in communities, professions, public services or existing organisations.

    A broader conception of entrepreneurship education would start from value creation rather than firm creation. That distinction is important. Value creation invites students to ask different questions. What problem is worth solving? For whom? In what context? What resources are available? What constraints matter? What does responsible action look like? These questions apply equally to a start-up founder, a nurse redesigning a patient pathway, a lecturer creating a new learning model, a graduate leading change inside a company, or a community organiser responding to a local challenge. EntreComp is helpful precisely because it frames entrepreneurship as a competence for life, not only for enterprise formation.

    There is also a strong social argument for moving beyond start-up. Research published in Scientific Reports argues that well-designed entrepreneurial education contributes to sustainable communities by developing socially conscious entrepreneurs, strengthening communities and supporting longer-term job prospects. In that work, partnerships, curriculum design, alumni networks and sustainability-oriented structures are treated as key drivers. This pushes entrepreneurship education beyond private gain and towards public value. It aligns entrepreneurship with social innovation, sustainability and civic responsibility. That is especially important in higher education, where the purpose of learning should include contribution as well as commercialisation.

    The field itself is also moving in this direction. A recent (Springer) state-of-the-art review argues that entrepreneurship education needs reshaping because the literature has often been fragmented and overly limited in scope. At the same time, pedagogical reviews show that experiential, interdisciplinary and reflective approaches are becoming more prominent. In other words, the debate is no longer whether entrepreneurship education should do more than produce founders. The debate is how quickly institutions can redesign provision to reflect that reality.

    What should this look like in practice? First, entrepreneurship education should be embedded across ALL disciplines, not isolated in business schools. Engineers, artists, health professionals, educators and social scientists all need the capacity to identify opportunities and turn ideas into action. Second, the curriculum should include value based entrepreneurship (think social entrepreneurship but more impact-focused), intrapreneurship, innovation in employment settings, ethical decision-making and community problem-solving. Third, pedagogy should remain experiential, but with wider forms of application: live projects, challenge-based learning, design thinking, interdisciplinary teamwork, reflective journals and community partnerships. These approaches retain action and experimentation while expanding the meaning of entrepreneurial success.

    Assessment must change too. If institutions only reward venture outputs, they will continue to teach to that narrow outcome. Students should also be assessed on opportunity recognition, problem framing, collaboration, resilience, ethical reasoning, stakeholder engagement and the ability to generate value in context. These are the capabilities employers increasingly need and societies increasingly depend upon.

    Ultimately, entrepreneurship education should not be reduced to a pipeline for company formation. Start-ups remain one legitimate outcome, but they are not the only one, nor always the most important one. The real promise of entrepreneurship education is that it helps people become more capable of acting in uncertainty, creating value, initiating change and responding intelligently to complex problems. That makes it relevant not just to founders, but to graduates, employees, citizens and leaders. If universities want entrepreneurship education to remain credible, inclusive and future-facing, it must move decisively beyond business start-up.

    References

    European Commission, Joint Research Centre. (n.d.). EntreComp: The entrepreneurship competence framework. European Commission. (Joint Research Centre)

    Passarelli, M., & Bongiorno, G. (2025). Is it the time to reshape entrepreneurship education? State-of-the-art and further perspectives. International Entrepreneurship and Management Journal, 21, Article 61. (Springer)

    Rodrigues, A. L. (2023). Entrepreneurship education pedagogical approaches in higher education. Education Sciences, 13(9), 940. (MDPI)

    Suguna, M., Sreenivasan, A., Ravi, L., Devarajan, M., Suresh, M., Almazyad, A. S., Xiong, G., Ali, I., & Mohamed, A. W. (2024). Entrepreneurial education and its role in fostering sustainable communities. Scientific Reports, 14, Article 7588. (Nature)

    Weber, S., Packard, M. D., & Bylund, P. L. (2022). Entrepreneurship education but not as we know it: Reflections on the relationship between critical pedagogy and entrepreneurship education. The International Journal of Management Education, 20(3), 100726. (ScienceDirect)

  • Entrepreneurship Is Not Start-Up: A New Framework for Value Creation, Education, and Economic Growth

    Entrepreneurship Is Not Start-Up: A New Framework for Value Creation, Education, and Economic Growth

    Entrepreneurship has been reduced to a narrow and ultimately unhelpful idea: starting a business.

    Across universities, policy frameworks, and media narratives, entrepreneurship is framed through start-up activity—pitch decks, venture capital, and the pursuit of rapid scale. This interpretation is not simply incomplete; it is distorting how we educate students, design economic policy, and evaluate success.

    The consequence is a system that rewards activity over impact, formation over function, and visibility over value.

    If we are serious about improving productivity, employability, and long-term economic resilience, we need to move beyond the start-up myth and return to a more fundamental question:

    What is entrepreneurship actually for?

    The Problem: We Are Measuring the Wrong Thing

    Entrepreneurship policy and education are dominated by simplistic metrics:

    • Number of start-ups created
    • Amount of funding raised
    • Survival rates over three to five years

    These measures are easy to quantify, but they are poor proxies for what really matters: value creation.

    A business can be launched, funded, and sustained without creating meaningful economic or social value. Equally, significant value can be created within existing organisations, communities, or informal economies without ever appearing in start-up statistics.

    This misalignment has three critical consequences.

    First, it leads to policy inefficiency. Governments invest heavily in start-up ecosystems without understanding whether those ventures contribute to productivity, innovation, or regional development.

    Second, it creates educational distortion. Universities design entrepreneurship programmes around venture creation rather than capability development, leaving graduates underprepared for complex, non-linear careers.

    Third, it results in entrepreneurial failure. Founders are encouraged to pursue ideas without understanding the resources, processes, and conditions required to create sustainable value.

    In short, we are optimising for the wrong outcome.

    Reframing Entrepreneurship: From Activity to Value

    To correct this, entrepreneurship must be redefined.

    Entrepreneurship is not the act of starting a business. It is:

    The process of creating, capturing, and sustaining value through the effective orchestration of resources over time.

    This definition shifts the focus in three important ways.

    First, it places value at the centre, not activity. The purpose of entrepreneurship is not formation but transformation.

    Second, it emphasises process, recognising that entrepreneurship unfolds over time rather than occurring at a single moment of creation.

    Third, it highlights resource orchestration, acknowledging that entrepreneurs do not simply use resources—they combine, adapt, and transform them.

    This reframing aligns more closely with established economic theory. Joseph Schumpeter, for example, positioned the entrepreneur as an agent of “creative destruction,” reshaping markets through innovation rather than merely creating firms (Schumpeter, 1934). Similarly, Peter Drucker emphasised entrepreneurship as a systematic practice of innovation and value creation (Drucker, 1985).

    Yet despite this intellectual foundation, contemporary systems have drifted toward a far narrower interpretation.

    The Missing Mechanism: Understanding Entrepreneurial Capital

    If entrepreneurship is about value creation, the next question is straightforward:

    How is value actually created?

    The answer lies in capital—not just financial capital, but a broader set of resources that entrepreneurs draw upon and combine.

    The Eight Capitals Model provides a more complete view:

    • Financial Capital (money and funding)
    • Human/Experiential Capital (skills, knowledge, experience)
    • Social Capital (networks and relationships)
    • Intellectual Capital (ideas, IP, systems)
    • Cultural Capital (norms, behaviours, identity)
    • Natural Capital (environmental and physical resources)
    • Manufactured Capital (infrastructure, tools, technology)
    • Spiritual Capital (purpose, values, motivation)

    Traditional approaches overemphasise financial capital, yet evidence consistently shows that access to networks, knowledge, and institutional support often matters more in determining entrepreneurial outcomes (Acs et al., 2014).

    Entrepreneurs do not simply deploy these capitals independently. They orchestrate them—combining different forms of capital to create new forms of value.

    A founder launching a digital platform, for example, may rely heavily on intellectual and social capital in early stages, while scaling requires increasing levels of financial and manufactured capital.

    Understanding this dynamic is critical. Without it, both education and policy remain fundamentally incomplete.

    The Process Layer: The 9 Stages of Enterprise Development

    While capital explains what resources are used, it does not explain how entrepreneurship unfolds.

    Entrepreneurship is not a single act but a staged process. The 9 Stages of Enterprise Development provide a structured way to understand this progression:

    1. Discovery
    2. Modeling
    3. Startup
    4. Existence
    5. Survival
    6. Success
    7. Adaptation
    8. Independence
    9. Exit

    Each stage represents a different configuration of challenges, decisions, and resource requirements.

    Crucially, value is created differently at each stage.

    • In Discovery, value lies in identifying opportunities
    • In Startup, it lies in mobilising resources
    • In Survival, it lies in achieving cash flow stability
    • In Adaptation, it lies in responding to environmental change

    This staged perspective aligns with broader economic development theories, such as Walt Rostow’s model of economic growth, which highlights the importance of sequential development phases (Rostow, 1960). However, unlike linear economic models, entrepreneurship is iterative and adaptive.

    The key insight is this:

    Entrepreneurship is the dynamic interaction between capital and stages, producing value over time.

    An Integrated Framework for Entrepreneurship

    To move beyond fragmented thinking, these elements must be brought together into a single model.

    Integrated Entrepreneurship Framework

    This framework is deliberately simple but conceptually powerful.

    • Capital represents the resources available
    • Stages represent the process through which entrepreneurship unfolds
    • Value represents the outcome
    • Context shapes and constrains the system

    Most existing approaches focus on only one of these elements. Effective entrepreneurship requires understanding all four—and, critically, how they interact.

    Implications for Universities: From Knowledge to Capability

    This framework exposes a fundamental weakness in higher education.

    Universities largely focus on knowledge transfer, while entrepreneurship requires capability development.

    Students are taught:

    • Business planning
    • Marketing theory
    • Financial modelling

    But they are rarely taught:

    • How to mobilise different forms of capital
    • How to navigate different stages of development
    • How to create and measure value in real contexts

    As a result, graduates leave with theoretical understanding but limited practical capability.

    To address this, universities must:

    1. Embed capital awareness into curricula
      Students should understand the different forms of capital and how to access them.
    2. Align learning with stages
      Programmes should simulate the progression from discovery to growth, not just start-up.
    3. Measure value creation capability
      Assessment should focus on outcomes, not outputs.

    This is not a marginal adjustment. It is a structural shift in how education is designed.

    Implications for Policy: From Start-Ups to Systems

    The same issue applies at the policy level.

    Entrepreneurship policy has become overly focused on:

    • Start-up grants
    • Incubators and accelerators
    • Venture capital ecosystems

    While these have value, they represent only a small part of the system.

    A more effective approach would focus on capital ecosystems:

    • Strengthening networks (social capital)
    • Investing in skills and education (human capital)
    • Supporting infrastructure (manufactured capital)
    • Enabling knowledge transfer (intellectual capital)

    This is particularly important in regional and rural contexts, where traditional start-up models often fail to translate.

    You cannot build entrepreneurial economies by funding businesses alone. You must build the systems that enable value creation.

    Implications for Entrepreneurs: Better Decisions, Better Outcomes

    For practitioners, this framework provides a more realistic lens.

    Instead of asking:

    • “Is this a good idea?”

    Entrepreneurs should ask:

    • “What value am I creating?”
    • “What capital do I need—and what am I missing?”
    • “What stage am I in—and what does that require?”

    This shift leads to better decision-making.

    It reduces overconfidence in early stages, improves resource allocation, and increases the likelihood of sustainable growth.

    Conclusion: A Necessary Shift

    Entrepreneurship matters—not because it creates businesses, but because it creates value.

    If we continue to define entrepreneurship as start-up activity, we will continue to miseducate students, misallocate resources, and misunderstand economic growth.

    The alternative is clear.

    We must move toward a model that recognises:

    • The role of capital
    • The importance of process
    • The centrality of value
    • The influence of context

    This is not simply an academic exercise. It is a practical necessity.

    The future of entrepreneurship lies not in more businesses—but in better value creation.

    References (APA Style)

    Acs, Z. J., Autio, E., & Szerb, L. (2014). National systems of entrepreneurship: Measurement issues and policy implications. Research Policy, 43(3), 476–494.

    Drucker, P. F. (1985). Innovation and entrepreneurship: Practice and principles. Harper & Row.

    Schumpeter, J. A. (1934). The theory of economic development. Harvard University Press.

    Rostow, W. W. (1960). The stages of economic growth: A non-communist manifesto. Cambridge University Press.

    Neck, H. M., Greene, P. G., & Brush, C. G. (2014). Teaching entrepreneurship: A practice-based approach. Edward Elgar.

    World Bank. (2020). Doing business 2020: Comparing business regulation in 190 economies. World Bank Publications.

    OECD. (2021). Entrepreneurship at a glance 2021. OECD Publishing.