Scope is fixed at Product × Technology × Application × Channel × Region (7 regions, 30 countries). Units (value/volume) and currency basis are defined upfront. Monthly signals inform quarterly baselines; forecasts run at constant FX unless scenario analysis dictates otherwise.
Shipments count once at vendor→channel dispatch; OEM transfers are not double-counted. Subsidiary inventory is excluded until channel entry. Re-exports are reassigned to country of final use when determinable. Manufacturer self-consumption and bona-fide donations are counted for installed-base integrity.
ASP is captured at distributor level; freight/insurance/import duties inside vendor/channel pricing are included; POS taxes are excluded. Outliers are normalized. Prices are weighted across international, domestic, and China-based vendors by geography and application. For bulk chemicals/intermediates, bulk distributor prices are used.
Brand share = Brand Value ÷ Category Value by geography and channel. In the absence of EPOS, brand value is triangulated from filings and public multi-signal proxies (SRAP/PII/RHI), calibrated to disclosed anchors and bounded by corridor tests.
Trade flows are compiled on HS codes with mirror-stat checks. Adjustments are made for re-exports via known hubs, FOB/CIF valuation differences, and reclassification events. Series are time-aligned and currency-normalized. Apparent consumption closes as Production + Imports − Exports ± Stock Change (where observable).
Revenue and volume are allocated across direct, distributor/wholesale, retail/mass, pharmacy/specialty, e-commerce, and tender/government. Margin stacks are modelled by channel. Leakage (grey/parallel trade) is estimated via guardrails and anomaly detection on pricing and availability.
Nodes are mapped from input to end-use with capacity, utilization, lead times, yield loss, scrap, lane reliability, and inventory policies. Concentration indices and single points of failure are stress-tested under demand and supply shocks. Supplier scorecards reflect quality/on-time/cost/risk metrics.
Method 1: Regression-based models — predictors from production / utilization / trade / capex / approvals / price corridors;stability and residual tests; structural break handling; backtesting. Method 2: Driver growth-rate models — weighted driver growth applied to audited baselines; weights tuned to realized outcomes; revisions on rebases and shocks.
Triangulation: Product Category Analysis; n-per-Population intensity; Economic Envelope guardrails. Outputs include value, volume, installed base, and price scenarios with confidence bands.
Regression accuracy via MAPE with diagnostics; growth-rate models via correlation and backtests, with volatility-basedtolerance bands. Reconciliation closes apparent consumption; price corridors and FX/capacity constraints are tested.
Dual-analyst review is required; change logs capture rationale.
Value = Units × ASP; Installed Base = Σ Shipments − Retirements; Apparent Capacity = Production / Capacity Factor; Brand Share = Brand Value ÷ Category Value; Channel Mix = Channel Revenue ÷ Total; Export–Import Balance = Exports − Imports.
UN Comtrade / ITC Trade Map; Eurostat / PRODCOM; US Census / BEA / BLS; OECD; IEA /EIA / USGS / UNCTADstat; FAOSTAT / USDA; FDA / EMA / PMDA / CDSCO; ClinicalTrials.gov / WHO ICTRP; OICA / ACEA / SIAM; EDGAR / SEMI / GSMA / 3GPP; EU TED / SAM.gov; public retail signals (filings, store locators, circulars, app stores, public social). Lineage cards display pull dates, access type, transforms, confidence tier, and caveats.
Quarterly baselines with monthly micro-updates for high-frequency shifts; rapid shock notes for policy / outage / recall / price spikes. Deliverables include executive memo, workbook / models, 16:9 dashboards with lineage, and a change log. Optional: weekly SRAP / PII / RHI tiles for retail.
Methodology
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