The Scale-Up Gap Is an Evidence Allocation Problem

The scale-up gap concerns more than capital or invention. It also concerns whether technical, commercial, governance and operating evidence reaches the right decision-maker at each transition. The OECD study of almost 200,000 innovative EU and US firms moves scale-up beyond a simple shortage of capital toward the evidence required at different stages. A patent establishes part of a technical asset but cannot independently prove customer adoption, unit economics, management capability or cross-border delivery. A company may be technically ready while institutionally unable to support late-stage reliance. This Signal treats the evidence-allocation problem beneath the start-up scale-up gap as a direction emerging across institutional actions, not as a joint programme announced by any one authority. Legal status, publication date and population remain source-specific. Cross-reading supports a directional judgement only; similar language must not be converted into a single obligation. To make the lead decision-ready, it answers five questions together: what has occurred, which first-party record supports it, through what mechanism the effect may travel, which outcome evidence is still missing, and what next observation could strengthen or overturn the judgement. Any causal relationship not stated by the source remains an editorial inference and is not converted into a factual claim through confident wording.

The OECD study covers nearly 200,000 innovative EU and US ventures founded from 2000 to 2025 and examines patents, finance, acquisitions, professionalization and spillovers. Early investors, growth capital, acquirers, banks, boards and overseas customers make different judgements. First patent, revenue growth, management professionalisation, appointment of a CFO and acquisition pathways are different signals. One composite score conceals which evidence matters to which scale-up decision. Convergence is not established by repeated vocabulary. It is established when independent institutions begin to require comparable capabilities around identity, origin, method, accountability, control and version. Every source retains its own authority and time reference so that comparison does not become a claim of institutional merger. Time and authority must also be separated. An announcement date is not an effective date; a pilot is not general adoption; a technical specification is not a legal obligation; and voluntary enterprise use is not regulatory approval. Putting these events on one timeline shows when an institutional development actually enters data, contract, investment or disclosure processes and which actor is authorised to make that transition.

European patenting ventures are not uniformly weaker inventors, yet the path from first patent to scale is about 1.49 years longer. Invention does not prove market adoption or institutional readiness. The main discontinuity occurs after invention. Research teams hold technical proof, customer and contract records remain unstructured in commercial teams, and finance and governance data were formed for internal purposes. When late-stage investment or cross-border partnership requires a whole-enterprise judgement, narrative substitutes for evidence and lengthens due diligence. When upstream evidence lacks stable identity, formation time, applicable boundary and version, a standardised output may still be impossible to reconstruct. The material risk is not one missing field. It is the silent conversion of the wrong entity, an expired method, an inferred relationship or an unapproved version into an apparent fact as information moves downstream. Concrete failure modes include incorrect entity matching, an incomplete data population, inconsistent boundaries, unversioned methods or factors, exceptions without rationale, approval occurring after publication, and downstream reuse outside the original purpose. Each failure can turn a reasonable individual record into a conclusion that cannot be defended after aggregation, comparison or machine-assisted interpretation.

Scaling requires commercial traction, financial performance, governance readiness, management capability and cross-jurisdiction evidence to become understandable, verifiable and reliable. Evidence allocation maps technical, intellectual-property, market-traction, unit-economics, governance, team, compliance and delivery evidence to decision stage, with source, period, review and permitted use. Evidence can be reused, but investment, acquisition and customer decisions require different combinations and strength. The implementable control unit is a governed evidence object. Each material claim links to its primary source, calculation or judgement method, organisational and temporal boundary, accountable owner, control state, exception, approval and version. When any component changes, the system preserves the difference and affected uses instead of overwriting the earlier basis. A minimum operating control set includes a claim register, evidence owner, source snapshot, method identity, valid period, control frequency, exception threshold, review, approval and permitted downstream use. High-judgement or high-financial-impact items receive a stronger review tier. Lower-risk records use automated completeness and consistency checks so that governance effort is concentrated where a wrong claim would change a decision.

OECD findings show divergence after invention, with late-stage capital, acquisition pathways and professionalization signals such as an external CFO associated with scaling dynamics. The OECD research supports sample, EU-US comparison, scale-up timing and management-professionalisation observations. It cannot establish that any one item causally guarantees success. SNN's interpretation as an evidence-allocation problem is institutional analysis, not investment advice or a start-up scoring model. Evidence is assessed through source comparison rather than a simple source count. Documents that repeat one underlying dataset remain one evidential path. Similar requirements from independent institutions can strengthen a directional signal, but they do not prove implementation results, legal equivalence or equal market maturity. Every material sentence should enter a claim ledger and be classified as official fact, direct measurement, estimate, corporate commitment, delivered outcome or SNN editorial inference. The ledger records the precise scope that each source supports. Conflicting evidence is retained with the resolution rationale; absent evidence is marked pending rather than filled with a convenient analogue from another entity, period or jurisdiction.

More consequential capital decisions require broader evidence. A venture can be technically ready before it is institutionally ready for investor, board and cross-border reliance. The signal suggests that ecosystem policy should not increase only early-stage firm formation. It should help companies convert technology into evidence usable by later capital and cross-border markets. Professional management, standardised finance, governance and transaction records reduce decision friction and create transferable ecosystem capability after acquisition or talent movement. The purpose of this information density is not length for its own sake. It is to shorten the verification distance between claim and decision. Boards, investors, regulators and operational teams should be able to distinguish fact, estimate, commitment, progress and outcome, then update the judgement when conditions change without reconstructing the case from scattered files and oral explanation. Accountability therefore attaches to decision rights. The data owner maintains the source, the method owner controls calculation, the business function defines the use case, internal control or assurance tests reproducibility, and the approver accepts responsibility for final use. An exception without an expiry date, remediation owner and impact scope stops being temporary treatment and becomes persistent evidence debt.

SNN editorial analysis: European and global scale-up research suggests that Taiwan AI, semiconductor, biotech and sustainability startups need more than early capital. They must convert demonstrations into growth evidence for international customers, investors and partners, with traction, unit economics, IP, governance, compliance and cross-border delivery matched to each decision stage. Taiwan AI, semiconductor, biotech and sustainability start-ups often have strong technology and grant records, while overseas investors and customers need adoption, IP rights, compliance, governance and delivery evidence. Verified customer milestones, unit economics, board decisions and chains of title should be preserved early instead of reconstructed in a pitch deck during fundraising. For Taiwan, relevance should be traced through an actual transmission path. An international rule or customer requirement first enters finance, procurement, contract, supplier-data and assurance processes, then changes local systems and controls. It does not automatically become Taiwan law. Companies need to identify the applicable scenario, preserve bilingual mappings and make the evidence chain reviewable under controlled access. Taiwan companies can perform the transmission test on concrete objects: the company and legal entity, facility, product, batch, supplier, contract, financing instrument and disclosure field. Chinese and English names, internal and external classifications and different reporting frameworks should resolve to the same claim identity. Traceability must still preserve commercial confidentiality, personal data and access boundaries; it does not require unrestricted publication.

Future evidence should show how individual success becomes transferable talent, supplier capability, investor knowledge and commercialization infrastructure across an ecosystem. Future evidence should examine how late-stage capital, acquisition and professional management affect scaling in Taiwan and other markets. A low-regret action is an evidence-readiness matrix for the next material decision, identifying decision-maker, required claim, supporting evidence, gap and owner and testing it from an external perspective before due diligence. Future monitoring should separate final text, technical guidance, adoption scope, operating controls, supervision and observable outcomes. A low-regret step is to select one high-risk claim for an end-to-end reconstruction test and record missing identity, source, method, accountability and version. That is governance preparation, not a compliance guarantee or forecast of results. Monitoring should be event-triggered as well as calendar-based. A final rule, amended technical guidance, expanded scope, supervisory action, adoption data or observed outcome creates a new version and a reassessment of the earlier judgement. The prior conclusion is not erased. It retains its original basis, identifies the new evidence that changed it and states which decisions or downstream uses now require review.