ClusterOS Diagnostic Profile
DevonTorbay Digital
Devon and Torbay Digital draws £311m of UKRI lead-led funding across 263 grants, anchored by Exeter (35%), with Plessey Semiconductors and Met Office on the industrial side. 11 Companies House-traced spin-outs translate to £28m UKRI per spin-out.
The cluster shows low-confidence "Re-proving instead of narrowing" behaviour — research narrative is reinforced by recurring programme launches rather than narrowing toward commercial scaling, with academic capacity reabsorbing the cluster's signal.
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Same data examined through five diagnostic lenses — Pipeline, Leverage, Triple Helix, Throughput, Collaboration. The interactive diagnostic is currently in private preview.
Sources: UKRI Gateway to Research (grants, outcomes); OpenAlex (publications); Companies House (spin-out lifecycle); DSIT (cluster mapping); Public investment data. Snapshot May 2026.
Stabilisation stacks · Why single interventions fail
Value extraction events generate narrative about ecosystem success; narrative legitimises continued extraction by framing it as ecosystem contribution; uncertainty about whether extraction is harmful absorbed by the success narrative.
"If UKRI or devolution deal reporting separated "ecosystem success" metrics (spin-offs created, patents filed, equity raised) from "local retention" metrics (spin-offs HQ'd in Devon/Torbay, patents held by regional entities, equity investors located regionally), it might reduce the system's ability to absorb success signals through narrative that conflates extraction with contribution."
Leverage hypotheses are testable perturbations, not prescriptions. Where demand-side behaviour is weakly visible, the correct move is observation — improving visibility before attempting change.
Structural resemblances · Clusters with similar stall configurations
A full ClusterOS diagnostic adds actor questionnaire data, working sessions, and anchor interviews — producing higher-confidence stall identification, board-ready stack analysis, and leverage hypotheses calibrated to your specific context.