The Knowledge We Ignore: Activating Common Knowledge for Better Innovation Policy Outcomes

John Howard, 10 June 2025

This Innovation Insight explores how economic frameworks for innovation policy can be enriched by fully integrating common knowledge alongside proprietary knowledge systems.

Current approaches emphasise market mechanisms, measurable outputs, and intellectual property—all valuable elements—but innovation outcomes can also be significantly enhanced by embracing the tacit, shared, and socially embedded forms of knowledge that strengthen innovation ecosystems.

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The Insight examines how these complementary knowledge systems function together, offering pathways toward more comprehensive policy approaches that leverage traditional metrics and practice-based wisdom. By building on these complementary strengths, innovation systems can develop greater resilience and adaptability, supported by decision-making that values quantitative evidence and informed judgment, knowledge stewardship, and institutional capacity to cultivate diverse knowledge resources.

This perspective offers practical recommendations for designing more inclusive, durable, and intelligent innovation systems for policymakers, innovation leaders, and researchers committed to addressing complex challenges.

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Introduction

Innovation is a profoundly social and institutional process, not merely about technology or investment. While economic theories have contributed valuable frameworks for understanding innovation through market behaviour and private incentives, an opportunity exists to broaden this perspective. By expanding the view to include shared, distributed, and publicly accessible forms of knowledge that strengthen real-world innovation systems, more comprehensive and effective approaches can be developed.

This Insight focuses on how common knowledge—the wisdom held across communities, institutions, professions and supply chains—can be better integrated into innovation frameworks.

Common knowledge serves as the connective tissue of innovation: the tacit expertise, institutional practices and professional norms that enable systems to coordinate, adapt and learn. By recognising and nurturing these knowledge commons, new sources of value can be unlocked that complement existing innovation models.

While innovation discourse has evolved through various phases—knowledge management, entrepreneurial ecosystems, intangible capital—there now exists an opportunity to combine the strengths of each approach. By creating frameworks that value both individual initiative and collective capabilities, innovation systems can be built that are more inclusive, resilient and productive.

The following sections explore how current frameworks can be enhanced, understanding of knowledge assets enriched, and a more balanced and integrated approach to innovation policy constructed for the future..

Expanding Economic Frameworks for Innovation

Economic models have provided valuable tools for understanding innovation as a rational choice process: firms invest in research and development to maximise returns, with knowledge functioning as an input or output in production functions. Market-oriented approaches have successfully stimulated private sector engagement, entrepreneurship, and competitive innovation.

Building on these foundations, there is an opportunity to enhance these frameworks by incorporating a richer understanding of knowledge dynamics. While proprietary knowledge—codified, excludable and privately monetised—drives important aspects of innovation, common knowledge that is widely shared, collectively generated and socially embedded complements and amplifies these contributions.

The most advanced innovation systems worldwide successfully integrate both dimensions: they create strong incentives for private investment while cultivating the shared knowledge resources that enable system-wide learning and adaptation.

By recognising the complementary relationship between proprietary and common knowledge, more comprehensive policies can be designed that harness the full spectrum of innovation drivers.

Why Common Knowledge Matters: Building Innovation Capabilities

Common knowledge provides a powerful foundation that enables actors in a system to coordinate, collaborate and adapt. It encompasses multiple forms of knowledge assets:

• Tacit knowledge embedded in work practices, routines and craft skills;

• Institutional knowledge developed within professions, public agencies and technical systems;

• Community knowledge that thrives in networks, social norms and local traditions;

• Scientific and technical knowledge that is public, cumulative and generative.

This knowledge accumulates through practice, is shared through collaboration, and is transmitted through social mechanisms: mentoring relationships, professional communities, standards-setting, and collaborative problem-solving. While different from private knowledge in how it is developed and shared, common knowledge creates essential infrastructure for innovation.

The most vibrant innovation systems cultivate both breakthrough discoveries and knowledge commons—the shared understanding that reduces transaction costs, enables interoperability, and supports cumulative innovation. By recognising and nurturing these complementary knowledge resources, more integrated, resilient and productive innovation ecosystems can be built

A more extensive discussion of Why Common Knowledge Matters is provided in an Addendum to this Insight

The Evolution of Common Knowledge in Innovation Studies

The concept of common knowledge has evolved within innovation studies, emerging from multiple disciplinary traditions.

Initially recognised in the post-war period through the work of economists like Friedrich Hayek and Michael Polanyi, common knowledge was framed as tacit, experiential and context-specific—attributes that resisted codification. In the 1980s and 1990s, innovation theorists including Christopher Freeman, Bengt-Åke Lundvall and Richard Nelson further advanced the idea within national systems of innovation, highlighting the importance of shared norms, institutional memory and interactive learning across firms and public institutions.

This trajectory was reinforced by organisational theorists including Ikujiro Nonaka and Etienne Wenger, who introduced constructs like “the knowledge-creating company” and “communities of practice.” These models emphasised that innovation was less about discrete inventions and more about collective sense-making and problem-solving within institutional contexts. During the 1990s, the popularity of knowledge management brought common knowledge into managerial discourse, albeit often stripped of its social depth.

In recent years, however, economic frameworks have narrowed their focus to proprietary, data-driven and market-based forms of knowledge. Despite rhetorical nods to openness and collaboration, much policy continues to privilege the privatisable and the measurable. Innovation studies has responded by reaffirming the importance of knowledge commons, professional practice and systems-level learning.

This historical evolution reminds us that common knowledge is not residual or secondary; it’s central to how innovation takes root, scales and endures.

Opportunities for Integration in Innovation Policy

Despite the clear value of common knowledge, economic models and policy instruments haven’t yet fully incorporated these assets. This presents a significant opportunity to enhance innovation frameworks through thoughtful integration.

As we well know, contemporary economic models excel at measuring transactional and proprietary outputs—patents, publications, investment flows. These can now be complemented with approaches that capture the value of common knowledge, which circulates through relationships, institutions and professional practice. Developing new metrics and evaluation frameworks can provide more comprehensive insights into innovation performance.

Current policy instruments, designed primarily to stimulate competition and reward private initiative, can be enhanced with tools that support shared infrastructures—such as standards bodies, collaborative platforms and public-interest research—that sustain knowledge commons. A balanced portfolio of instruments would stimulate both individual entrepreneurship and collective capability building.

The integration challenge is also cultural. While celebrating the heroic entrepreneur and breakthrough technology, it is equally important to recognise the essential contributions of knowledge stewards, system integrators, and capability builders. A more comprehensive understanding of how innovation works can be enhanced by developing richer narratives that acknowledge individual achievement and collective learning.

This integration opportunity extends to data-driven policymaking. Quantitative metrics provide essential insights, but their value multiplies when combined with deliberative judgement, narrative context and practitioner wisdom. This more integrated “judgement and evidence” decision-making model creates space for both empirical analysis and experiential learning.

Overwhelmingly, there is tremendous potential to strengthen the professional knowledge embedded in institutions. The erosion of capability caused by constant restructuring and the hollowing out of public agencies can be reversed by valuing institutional memory and creating mechanisms to preserve and share organisational learning.

These integration approaches do not represent an either/or choice, but together an opportunity. By combining the strengths of current frameworks with an appreciation for common knowledge, innovation systems that are more adaptive, inclusive and effective can be built.

Enhancing Innovation System Performance

By integrating common knowledge more effectively into innovation frameworks, several challenges can be addressed and new opportunities for system-wide performance improvement unlocked.

A promising development has been the emergence of balanced approaches to innovation infrastructure. While high-profile, commercially oriented initiatives such as start-up hubs and accelerators drive important aspects of innovation, there is renewed interest in complementary foundational infrastructure—vocational education networks, standards-setting bodies and industry-extension services. Countries and regions that effectively combine both types of infrastructure are achieving superior results through knowledge diffusion, skill formation and sector-wide capability development.

Australia has gone a long way in developing this foundational infrastructure with the National Industry Extension Service (NIES), which was set up in 1986, and the Rural Extension Services, which are supported by State Agriculture Departments. NIES and many of the rural extension services fell victim to the New Public Management in the 1990s, on the grounds that the private sector would provide these services.   

There are renewed opportunities now being explored to strengthen coordinated sectoral approaches in areas such as advanced manufacturing and other knowledge-intensive industries. Several international cases illustrate how this integration drives performance. For example:

• Germany’s Fraunhofer Institutes combine proprietary innovation with shared knowledge infrastructure, contributing to that country’s manufacturing strength.

• Research by Breznitz and Murphree (2011) demonstrates how Taiwan’s ITRI (Industrial Technology Research Institute) created common technological platforms that enabled local firms to scale rapidly in semiconductors.

• Denmark’s agricultural extension services have facilitated knowledge transfer between universities, equipment manufacturers, and farmers, supporting that nation’s leadership in agri-technology exports (Christensen et al., 2017).

These examples suggest that improved productivity and scaling opportunities emerge when proprietary innovation is supported by shared knowledge infrastructure.

The university sector also represents a very significant integration opportunity. Top performing institutions worldwide now complement commercialisation activities (patenting, licensing and spin-outs) with equally valued contributions to open science, translational collaborations and regional capacity-building.

By recognising both forms of contribution, universities can fulfil their civic functions while driving economic impact, rebuilding trust with industry partners and communities. Several Australian universities are investing in building these capabilities, knowing that they support the teaching and research missions.

There is also significant potential to enhance institutional learning across government, industry and research organisations by creating mechanisms to capture, share and build upon accumulated knowledge and experience that can be converted into improved performance. Innovation becomes more than reactive novelty—it becomes a process of cumulative learning and capability building.

The problem of policy integration can be addressed by developing frameworks grounded in shared knowledge and cross-sector understanding. When departments coordinating R&D investments, regions developing strategic priorities, and sectors pursuing transformation agendas are linked through knowledge-sharing mechanisms, implementation improves and outcomes strengthen. For example, better alignment between federal innovation programs and state-based infrastructure planning could accelerate Australia’s renewable energy transition.

These integration strategies are not merely technical adjustments—they represent a fundamental enhancement in how value in innovation is conceptualised and measured, and how institutions can work together to build shared knowledge resources over time.

Building a Commons-Based Innovation Policy: Some Practical Steps

To realise the full potential of both proprietary and common knowledge, several pathways towards integration can be pursued:

• Investing more in Knowledge Infrastructure through sustained support for institutions that develop and share common knowledge—standards-setting organisations, applied research centres, vocational education systems and translational intermediaries that help codify tacit knowledge and build trust-based partnerships.

• Developing Comprehensive Performance Metrics that complement traditional bibliometrics and IP filings with measures capturing knowledge sharing, capability development, community engagement and cross-sector collaboration quality.

• Promoting Institutional Knowledge Stewardship by recognising universities, TAFEs and public research bodies as both producers of innovation and custodians of knowledge commons, designing funding instruments and evaluation systems that value continuity and knowledge transfer.

• Build Collaborative Platforms that enable collective learning through innovation precincts, challenge labs, cooperative data initiatives and communities of practice with inclusive governance models.

Enriching Innovation Capability

As complex challenges emerge across social, economic and environmental domains, innovation offers powerful tools for developing solutions. This Insight has highlighted an exciting opportunity to enhance innovation systems by integrating the full spectrum of knowledge resources—both proprietary and common, individual and collective—into more comprehensive frameworks.

By broadening the understanding of innovation beyond market transactions and proprietary outputs to include the shared, tacit and socially embedded knowledge that enables systems to learn and adapt, innovation ecosystems with greater capacity to address complex challenges can be built. This isn’t about replacing existing frameworks, but enriching them through integration and expansion.

Building this more comprehensive approach will require thoughtful adjustment of practices and institutions. But the rewards are substantial. Innovation systems that recognise, nurture and build upon both proprietary and common knowledge are more inclusive, resilient and adaptive. They’re better equipped to navigate uncertainty, more deeply connected to their social contexts, and more capable of collectively addressing the complex challenges.

Most importantly, this integrated perspective connects innovation directly to public value creation. It reminds stakeholders that innovation is not only about economic competition or technological novelty but also collective capabilities: the shared ability to learn, adapt and flourish over time. By valuing both proprietary and common knowledge, innovation systems can be built that generate both private returns and public benefits, creating lasting prosperity through shared learning and capability development.

References

Arrow, K. J. (1962). Economic welfare and the allocation of resources for invention. In The Rate and Direction of Inventive Activity (pp. 609-626). Princeton University Press.

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152.

Haskel, J., & Westlake, S. (2018). Capitalism Without Capital: The Rise of the Intangible Economy. Princeton University Press.

Lazonick, W., & Mazzucato, M. (2013). The risk-reward nexus in the innovation-inequality relationship. Industrial and Corporate Change, 22(4), 1093-1128.

Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company. Oxford University Press.

Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge University Press.

Polanyi, M. (1966). The Tacit Dimension. University of Chicago Press.

Slaughter, S., & Rhoades, G. (2004). Academic Capitalism and the New Economy. Johns Hopkins University Press.

Wenger, E. (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge University Press

Addendum: Why Common Knowledge Matters: Building Innovation Capabilities Through Knowledge Assets

Common knowledge provides a powerful foundation that enables actors in an innovation system to coordinate, collaborate and adapt. It encompasses multiple forms of knowledge assets. Four categories can be identified:

1. Tacit Knowledge—Embedded in Work Practices, Routines, and Craft Skills. The expertise that can’t be easily documented or transferred through written instructions alone. It’s the “know-how” that skilled practitioners develop through experience and embody in their actions. Examples include:

• Craft Traditions: The intuitive understanding a master carpenter develops about working with different woods, knowing by touch when a material will split or how it will respond to various techniques

• Clinical Judgment: How experienced medical practitioners develop pattern recognition abilities that help them diagnose conditions based on subtle cues that wouldn’t be apparent to less experienced clinicians

• Engineering Feel: The intuitive sense engineers develop for design tolerances and material behaviour that guides their decisions beyond what standard calculations would suggest

• Operational Adaptability: How manufacturing teams develop unwritten routines to handle variations in materials or equipment that formal processes don’t account for

• Productive Interactions: The tacit choreography that develops among high-performing teams, enabling them to anticipate each other’s needs and coordinate without explicit instruction

This tacit dimension underpins most forms of skilled practice but tends to be undervalued because it’s difficult to measure, codify or transfer through formal education alone. It typically develops through apprenticeship, mentoring relationships, and communities of practice where novices learn by working alongside more experienced practitioners.

2. Institutional Knowledge—Developed Within Professions, Public Agencies, and Technical Systems. Encompasses the accumulated understanding embedded in organisations about how to accomplish their missions effectively in specific contexts. It includes both formal and informal elements that enable coordinated action. Examples:

• Public Service Memory: How government departments develop contextual understanding of policy implementation challenges, and what approaches have succeeded or failed in the past

• Regulatory Insight: The accumulated experience within regulatory bodies about how industries respond to different regulatory approaches and what oversight mechanisms work best for different contexts

• Professional Standards: How professions like accounting, architecture or medicine develop shared frameworks of practice that incorporate both technical knowledge and ethical norms

• Procedural Knowledge: The detailed understanding within organisations about how processes actually work (often differing from formal documentation) and how to navigate institutional structures effectively

• Crisis Response Capabilities: How emergency services develop institutional protocols and adaptive capacities based on lessons from past events

This form of knowledge is particularly vulnerable to disruption through restructuring, outsourcing, and staff turnover. When organisations fail to value this knowledge as an asset, they often undergo costly cycles of rediscovering what was once known through painful trial and error.

3. Community Knowledge—That Thrives in Networks, Social Norms, and Local Traditions. Emerges from shared experiences and interactions within geographically or culturally connected groups. It reflects collective understanding about local conditions, relational dynamics, and effective approaches to common challenges. Examples:

• Place-Based Knowledge: How communities develop detailed understandings of local environmental conditions, resource availability, and sustainable practices adapted to specific regions

• Industry Clusters: The shared knowledge that develops in regional industry concentrations (like winemaking regions, manufacturing hubs, or technology precincts), where information flows through both formal and informal networks

• Cultural Practices: Traditional techniques and approaches that communities have refined over generations for activities ranging from food production to building methods suited to local conditions

• Social Capital: The networks of trust and reciprocity that enable coordination and collective action, particularly visible in how communities respond to challenges or opportunities

• Regional and Local Innovation Systems: How regions develop distinctive approaches to innovation based on their particular institutional configurations, industry specialisations, and historical development paths

Community knowledge often functions as the social infrastructure that enables other forms of innovation. When innovation policies focus exclusively on individual firms or formal R&D, they miss the critical role of these community knowledge assets in supporting sustainable development.

4. Scientific and Technical Knowledge—That Is Public, Cumulative, and Generative. This category encompasses the publicly accessible knowledge base that enables widespread innovation and provides a platform for further creation of knowledge. Unlike proprietary knowledge, it’s designed to be built upon and extended by others. Examples:

• Open Science: Research findings published in accessible formats with supporting data that enables validation, replication, and extension by other researchers

• Technical Standards: Publicly documented protocols and specifications that enable interoperability across systems and organisations, creating platforms for further innovation

• General Purpose Technologies: Foundational technologies like programming languages, algorithms, or scientific instrumentation designed to be applied across multiple domains

• Research Methodologies: Standardised approaches to investigation that allow distributed research communities to build upon each other’s work with greater efficiency

• Knowledge Infrastructures: Digital platforms, data repositories, and collaborative tools that support distributed knowledge creation and sharing across institutional boundaries

This form of knowledge is often produced through public funding but faces increasing pressure toward privatisation and enclosure. Strong innovation systems maintain robust commons of scientific and technical knowledge while still providing appropriate incentives for private investment in applications.

The Interconnection of Knowledge Assets. These knowledge assets don’t exist in isolation—they form an interconnected ecosystem where each strengthens the others. For example:

• Tacit knowledge helps interpret and apply scientific knowledge in specific contexts

• Institutional knowledge provides frameworks for organising both tacit and explicit knowledge

• Community knowledge creates the social fabric that enables knowledge exchange and collaboration

• Scientific and technical knowledge provides platforms that local communities and institutions can build upon

The most effective innovation systems recognise and support this entire knowledge ecosystem rather than focusing exclusively on any single element. A more resilient, inclusive, and productive innovation environment can be created by designing policies that nurture the full spectrum of knowledge assets.

This Insight was prepared by Dr John H. Howard, a policy analyst, economist, and innovation strategist with over three decades of experience advising governments, universities, and industry. As Founder of the Acton Institute for Policy Research and Innovation and Visiting Professor at UTS, John brings an integrative perspective to complex policy challenges. His work bridges academic insight and practical application, offering clear, evidence-based analysis grounded in deep professional and personal experience. His Innovation Insights are informed by a lifetime of thinking, doing, and questioning orthodoxies.

John can be contacted at john@actoninstitute.au

© Acton Institute for Policy Research and Innovation 2025