Institutional
Research standards
The single standard governing evidence, forecasting, benchmarks, independence, data governance and corrections across Global Fashion Intelligence & Research at Global Fashion Group™.
Evidence, provenance and research design
Every published figure carries, where applicable, a provenance state, source, observation period, geography, scope and last-update date. Observed, reported, partner data, modelled and forecast are distinct evidence states and are never presented as interchangeable.
A finding is stated only as strongly as the underlying evidence permits. Claims that remain directional are described as signals or questions rather than conclusions. Superlatives such as largest, leading, first or official are used only when the evidence supports the claim and the supporting source is identifiable.
Survey samples are planned for the segments that will actually be reported. Unsupported segment cuts are not published, and question design is reviewed for leading, double-barrelled or otherwise distorting construction.
Forecasting methodology and accuracy
Every forecast states its horizon, input period, model or projection method, and an uncertainty interval where the evidence supports one. Source ranges remain ranges; the platform does not collapse uncertainty into false point precision simply to make a chart appear more decisive.
Forecasts are logged with the model version and major contributing signals. Where an observed outcome later becomes available, performance is evaluated using measures appropriate to the forecast class, such as absolute error, percentage error, directional accuracy, bias and interval coverage. A model class is not promoted as predictive until it has a documented backtest or comparable validation at the relevant horizon.
Public market forecasts are decision-support signals, not guarantees of sales, investment return, attendance or inventory performance. Company-specific demand forecasting requires sufficiently complete first-party history such as sales, product, inventory, channel, pricing and customer data.
Benchmarks, rankings and opportunity scores
Rankings, scores and indices published by Global Fashion Intelligence Landscape™ represent the analytical methodology of Global Fashion Group™. They are aggregated estimates produced by a stated and published method, are not audited findings, certifications, ratings or statements of fact, and do not imply endorsement, verification or participation by any data provider, licensor or named organization.
Scores are comparable only within the index, edition, cohort and method version in which they were computed. Material changes to weights, coverage rules or source definitions require a new method version and, where historical comparison is offered, recomputation of the comparable series.
Missing inputs reduce evidence coverage; they are not silently filled with invented values. Market Opportunity and similar screens help investors, brands, designers and retailers compare conditions, but they are not recommendations to invest, open a store, launch a collection or allocate inventory without additional due diligence.
Independence and conflicts of interest
Global Fashion Intelligence Landscape™ is owned and operated by Global Fashion Group™, which owns and operates events that appear in its datasets and rankings. Owned properties are identified as such wherever they appear. Index methodologies are fixed and published before computation, are reviewed annually by an independent methodology panel, and are applied identically to owned and non-owned entities. Owned properties are excluded from editorial “top” claims.
Global Fashion Group™ may operate, partner with or commercially support properties that appear in its datasets. Those relationships do not change published scoring rules. Owned or affiliated properties are identified where relevant, no payment purchases a ranking position, and methodologies are fixed before an edition is computed.
Commissioned research is labelled as commissioned. A commissioning or sponsoring party may review factual accuracy concerning information it supplied, but it does not receive approval rights over the method, analytical result or conclusion.
Data governance and client confidentiality
Private Client data is separated by account or tenant and is not used to calculate public benchmarks, train a shared model or inform another client’s analysis unless an explicit agreement says otherwise. Access is limited to the people and systems required to provide the service.
Event, survey and customer records are used in aggregate wherever practical. Small groups are suppressed when publication could create a meaningful re-identification risk, and protected personal attributes are not inferred for attendees or consumers.
Source rights are treated as part of data quality. A dataset is used only within the rights available to the Publisher, with required attribution and retention controls carried into the surfaces that depend on it. Every published metric should be traceable to the records, source period and method that produced it.
AI and model governance
Artificial intelligence may assist with entity matching, classification, summarisation, pattern extraction and forecasting where those methods are appropriate. It is not permitted to invent market figures, sources, citations or client outcomes. Quantitative values shown as observed or reported must originate in registered evidence, not model memory.
Modelled and forecast outputs remain visibly labelled, and material commercial recommendations should be reviewed in the context of coverage, confidence, source recency and the client’s own first-party evidence.
Corrections, updates and version control
Material errors are corrected when identified. A correction record states the date, the affected figure or statement, the nature of the change and whether any historical series was restated. Method changes are versioned rather than silently substituted into an earlier edition.
Potential errors may be submitted to info@globalfashiongroup.org with the subject line CORRECTION. The submission should identify the page, metric or passage and, where available, the evidence supporting the requested correction.
As of this edition, no correction entry is published. When a material correction is required, the current record will be maintained within this standard.
Decision use for investors, brands, designers and retailers
The platform is designed to support market research, screening and commercial decisions: investors can compare category and market conditions; brands can assess entry, channel and customer signals; designers can evaluate market, event and audience context; and retailers can compare demand, destination, digital and physical-retail conditions.
Those outputs are inputs to professional judgment, not substitutes for it. Users should evaluate source definitions, evidence coverage, recency, local regulation, execution capability, product-market fit and their own commercial data before acting on a result.
Review cycle
This standard is reviewed when a material data source, benchmark method, forecasting model, privacy control or AI capability changes, and at least annually. The currently published version governs all Global Fashion Group™ Intelligence & Research surfaces unless a product-specific method document states a stricter requirement.