Measuring What Matters:

From Principles To Measurement: Closing The Policy Gap

Over the last years, the adoption of the Council Recommendation on Guiding Principles for Knowledge Valorisation and the related Codes of Practice developed by the European Commission has provided both a normative vision and a structural understanding of how knowledge flows across systems in Europe. Yet one critical piece has taken longer to mature: the ability to systematically measure the performance and impact of knowledge valorisation activities.

While the need for measurement was acknowledged early on, its development required time. As the broader valorisation agenda evolved, it took a period of alignment for the concept itself to fully take root across the European research and innovation landscape. The emergence of a concrete measurement framework therefore marks not only a technical step forward, but also the consolidation of a policy vision now ready to be operationalised across the European Research Area.

Today, knowledge valorisation is no longer a peripheral concept. It is a core element of Europe's innovation strategy, embedded as a structural priority within the ERA Policy Agenda and increasingly reflected in initiatives such as the EU Startup and Scaleup Strategy and the next Horizon Europe framework programme.

The expert study addresses a long-standing gap directly. It reframes knowledge valorisation channels as interdependent components of a broader system and, crucially, makes them measurable across different national contexts. In doing so, it bridges policy ambition and operational reality while remaining adaptable to actors working inside innovation ecosystems.

Why Measuring Knowledge Valorisation Matters

The new framework represents a significant step forward because it enables more consistent monitoring, comparison and learning across Member States and associated countries. It supports coordinated policy development, while also offering tools that organisations and ecosystems can use to better understand their own performance.

Importantly, it moves beyond fragmented metrics and isolated success stories. Traditional indicators such as patents, licences or spin-offs capture only a narrow part of the picture. They often overlook crucial drivers of impact such as informal knowledge exchange, societal engagement and long-term value creation.

The proposed approach instead works with a portfolio of indicators across channels, reflecting the systemic and interconnected nature of knowledge valorisation. This matters because knowledge does not move linearly from research to market. It circulates through networks of actors, feedback loops and collaborative environments. By capturing these dynamics, the framework aligns closely with the reality of innovation ecosystems and with Future8's own experience of collaborative research and innovation as a driver of impact.

At the same time, measurement is not framed as a tool for control, but for learning. As highlighted during the related European Commission online session, what gets measured gets done. Equally important, what gets measured must be meaningful. The framework therefore emphasises continuous learning and helps policymakers and practitioners understand what works, under which conditions, and how strategies can be refined over time.

From Data To Insight: Building An Evidence Base On Impact

A key strength of the study lies in its practical grounding. Through detailed metric factsheets, it identifies indicator definitions, concrete data sources, levels of application and implementation limitations. But beyond listing sources, the real breakthrough lies in the way these are combined to capture the many layers of knowledge valorisation activities.

Several established data infrastructures are central to this effort, including:

• CORDIS and Horizon project databases for structured information on funded projects, participants and collaboration patterns
• Scopus and Web of Science for scientific publications, co-authorship and citation impact
• PATSTAT for tracking technological outputs and diffusion
• Eurostat and OECD STI databases for harmonised indicators on R&D investment, human resources and innovation performance
• researcher mobility data such as ORCID, national registries and Marie Skłodowska-Curie Actions datasets
• the ERA Monitoring Framework for alignment with broader EU-level monitoring efforts

The study's added value lies in the way these sources are translated into a coherent and operational system of indicators. For each channel, it proposes a structured indicator architecture that captures different stages of the valorisation process: from inputs and activities to outputs, outcomes and, where possible, longer-term impacts.

This makes it possible to move beyond static measurement towards a more dynamic understanding of how knowledge flows and creates value over time. The study treats collaboration, commercialisation, mobility, engagement, dissemination and uptake as complementary lenses on the same process. Taken together, these dimensions allow for a more robust reading of how knowledge moves, evolves and ultimately generates value across the system.

The study also underlines the need to combine indicators into portfolios that reflect the diversity of valorisation pathways. For example, the impact of collaborative research cannot be understood solely through co-publications. It needs to be linked to mobility patterns, follow-up innovation activities and downstream societal uptake.

Together, these sources and indicators form a more robust and comparable evidence base across the European Research Area while also enabling more granular insights at organisational and ecosystem level. This marks a shift from data abundance to data intelligence on the societal and economic impact of European research.

Opportunities, Challenges And The Road Ahead

While the framework is primarily designed to support monitoring and policy coordination at national level, its relevance extends directly to actors operating within innovation ecosystems.

For Future8, it offers a shared language to understand how knowledge flows, where bottlenecks exist and which forms of collaboration are most effective. This can strengthen collective intelligence, support more strategic partnerships and improve the ability to demonstrate impact in an increasingly results-driven environment.

At the same time, important challenges remain. Many dimensions of knowledge valorisation such as trust-building, informal exchanges or cultural change are inherently difficult to quantify. Data availability and comparability still vary across countries and institutions, and interdisciplinary approaches add further complexity.

As practitioners across Europe have highlighted, measuring knowledge valorisation also requires addressing coordination challenges across faculties, disciplines and data systems, while agreeing on common definitions before meaningful comparison becomes possible.

Emerging practices across Europe already point in a useful direction. Public research funders are developing impact frameworks grounded in theories of change, universities are combining quantitative indicators with qualitative assessment, and networks increasingly recognise that mindset change remains just as important as measurement itself.

Looking ahead, the study outlines several next steps to ensure the framework can deliver on its potential. These include piloting and validating the proposed indicators in real-world contexts, further harmonising data collection practices across Member States and strengthening coordination between national and European monitoring efforts. Equally important is the need for capacity building so that institutions and ecosystem actors can collect, interpret and use data effectively.

Ultimately, what gets measured will shape what gets done. The real question is no longer whether we can measure knowledge valorisation, but whether we are ready to use these measurements to drive real change. For anyone seeking to shape the future of knowledge valorisation in Europe, engaging directly with this study is not just useful, but necessary.

Image: Photo by Deng Xiang on Unsplash