Scope is locked at Product × Technology × Application × Channel × Region (7 regions, 30 countries). Units (value/volume) and currency basis are set upfront. Monthly signals inform quarterly baselines. Forecasts are produced at constant FX unless scenarios require alternatives. Segment trees are fixed before data ingestion; revisions go through change control.
Unit shipments count new products dispatched by vendors to channels or end users. OEM hand-offs are not double-counted; attribution follows the brand on the finished product. Subsidiary inventory is excluded until it enters the channel.
Known re-export corridors are reassigned to the country of final use when determinable. Manufacturer self-consumption and bona fide donations are included to maintain installed-base integrity.
Average Selling Price (ASP) is captured at distributor level and includes freight, insurance, and import/export taxes embedded in vendor/channel pricing; point-of-sale taxes are excluded. Outliers are normalized. Prices are weighted across international, domestic, and China-based vendors using geography- and application-specific sales mixes. For bulk intermediates (e.g., base chemicals), bulk distributor prices are used.
Value equals Units × ASP. Installed base equals cumulative shipments minus retirements using survival curves by class.
Apparent capacity is derived from production, net trade, and a capacity factor (typically 80–90% given operating-day / hour assumptions). Historical values are in current-period USD; forecasts at constant FX unless scenario work specifies otherwise.
Brand share is computed as Brand Value ÷ Category Value for the defined geography and channel set. When EPOS data are unavailable, brand value is triangulated from filings, tender disclosures, distributor catalogs, and public multi-signal proxies. Corridor tests bound the result: minimum share implied by observed capacities/shipments, and maximum share implied by price/volume feasibility.
Trade flows are compiled on HS codes with mirror-statistics for gap analysis. Adjustments address re-exports via hubs, FOB/CIF valuation differences, and reclassification events. Apparent consumption closes as Production + Imports - Exports ± Stock Change (where observable). Outliers are investigated via partner statistics, company disclosures, or customs notes.
Revenue and volume are allocated across direct, distributor/wholesale, retail/aftermarket, e-commerce/marketplace, system integrator/EPC, and tender/government channels as applicable. Margin stacks are modeled by channel; leakage (grey/parallel trade) is bounded via price corridor checks and availability anomalies. Attach-rate models quantify services and consumables where relevant.
Supply chains are mapped from input to end use. Capacity, utilization, cycle time, yield, scrap, lead time, lane reliability, and inventory policies are modeled. Supplier and buyer concentration indices are computed; single points of failure are stress-tested with demand/supply shocks. Scorecards track quality, on-time delivery, cost variance, and risk signals.
Method 1 — Regression-based models: predictors include production/utilization, trade flows, capex, orders/backlog, pricing corridors, approvals/standards, and policy dummies. Transformations are introduced only when out-of-sample performance improves. Stability and break tests are applied; models are back-tested and retained with diagnostics.
Method 2 — Driver growth-rate models: weighted driver growth is applied to the latest audited baseline where series are sparse or volatile. Weights are tuned to realized outcomes without overfitting and revised when drivers rebase or shocks occur. Triangulation uses Product Category Analysis, n-per-Population intensity, and an Economic Envelope to ensure feasibility against macro and budget constraints.
Regression accuracy is tracked via MAPE with residual diagnostics and stability tests; growth-rate models via correlation and backtests versus prior vintages, with tolerance bands reflecting volatility. Reconciliation closes apparent consumption; price corridors and capacity/FX limits are tested. A second analyst signs off; changes are logged with rationale.
The following domain signals are prioritized, each with a defined cadence and lineage card. These augment generic measures to capture sector-specific realities for brand share, channel mix, and forecast behavior.
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; Apparent Consumption = Production + Imports − Exports ± Stock Change.
UN Comtrade / ITC Trade Map; Eurostat/PRODCOM; US Census/BEA/BLS; OECD; IEA/EIA/USGS/UNCTADstat; national statistics offices; EU TED / SAM.gov tender data; sector regulators and standards bodies. Lineage cards include pull dates, access type (public/licensed/consent), transforms, confidence tiers, and caveats.
Quarterly baselines; monthly micro-updates for high-frequency indicators; immediate notes for policy changes, outages, recalls, or spikes. Deliverables include an executive memo, workbook/models, and 16:9 dashboards with lineage chips and a change log.
Methodology
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