11th November 2025

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Governments are placing greater emphasis on technologies that support economic resilience, societal missions, and strategic autonomy. Spinouts emerging from universities are being positioned as an important vehicle for unlocking and delivering these breakthrough technologies. Yet legacy classification systems, such as Standard Industrial Classification (SIC) codes, fail to capture the technological depth, cross-sectoral relevance, and public value of university spinouts operating at the innovation frontier. These limitations obscure strategic insights, reduce the visibility of emerging capabilities, and constrain policy effectiveness.

In response, this paper introduces a multi-dimensional framework for classifying spinouts, based on five key dimensions:

• Technological domain: the core scientific or engineering field underpinning the spinout’s innovation (e.g. AI, quantum, biotechnology).
• Application area: the sector or domain in which the technology is deployed (e.g. healthcare, energy, defence).
• Strategic priority: alignment with national or regional policy priorities (e.g. technological sovereignty, clean energy, digital infrastructure).
• Societal impact: contributions to global challenges, captured through alignment with the UN Sustainable Development Goals (e.g. SDG 3, 7, 9, 13).
• Temporal readiness: stage of technological maturity and deployment readiness, enabling better-targeted policy support.

Drawing on strategy documents and critical technology lists from the UK, US, EU, China, Japan, and Australia, the paper illustrates how each dimension can be populated using real-world policy sources. This approach supports more meaningful classification for monitoring, benchmarking, and targeted support, complementing existing datasets and enabling more policy-aligned, impact-oriented innovation analysis.