ClusterOS Diagnostic Profile
Liverpool City Region Digital Creative
Liverpool City Region Digital Creative draws £351m of UKRI lead-led funding across 358 grants, anchored by Liverpool (25%), with James Fisher Nuclear and Rockley Photonics on the industrial side.
The cluster shows medium-confidence "Forgiving instead of redesigning" and "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.
Intermediaries produce narrative about their facilitation role; narrative legitimises intermediary existence and funding; uncertainty about direct coupling absorbed by narrative rather than demonstration.
"If one public report (e.g., annual ecosystem review, Combined Authority performance report) separated extraction metrics (capital leaving region, talent exiting to non-regional employers, IP licensed to external entities) from retention metrics (capital reinvested locally, talent employed regionally, IP commercialised by regional actors) for 2 years, it might reduce the system's ability to absorb uncertainty about extraction through success narratives by making the difference visible."
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.