ClusterOS Diagnostic Profile
Greater Glasgow Digital Creative
Greater Glasgow Digital Creative draws £1.12bn of UKRI lead-led funding across 4,344 grants, anchored by Glasgow (37%), Strathclyde (27%), with Centre For Data Science And Ai on the industrial side. 34 Companies House-traced spin-outs translate to £33m UKRI per spin-out.
The cluster shows medium-confidence "Stabilising around incumbents" and "Extracting without reinvesting" behaviour — exit events recur while intermediation bodies absorb the signal rather than redesigning retention mechanisms. Pipeline 1 evidence: multiple established games companies, BBC Pacific Quay operations and large infrastructure investments to existing institutions evidence incumbent continuity, alongside 5 acquisitions by international buyers 2015-2021 and concentrated £5m+ private investments mediated through MGC and Scottish Enterprise.
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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 annual ecosystem reports (e.g., by Scottish Enterprise or Glasgow City Innovation District) separated extraction metrics (graduate hiring by non-local corporates, IP licensing to external entities) from retention metrics (local startup formation, local reinvestment), it might reduce the system's ability to absorb success signals through narrative without making the difference between value creation and value capture 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.