We set our scope by laying out Product, Technology, Application, Channel, and Region in a single structured grid that spans seven regions and thirty countries. Our unit basis for value and volume and our currency rules are fixed at the start so that every series aligns before modelling begins. Monthly indicators help shape quarterly baselines. Forecasts stay on constant FX unless scenario work calls for another basis. Segment trees are agreed and locked before data enters the system, and any revision goes through formal change control.
We count unit shipments when vendors dispatch new products to channels or end users. OEM hand offs are not counted twice because attribution stays with the brand on the finished item. Subsidiary inventory is included only when it moves into the channel. Known re export corridors are reassigned to the country where final use occurs when that path can be confirmed. We retain manufacturer self consumption and bona fide donations to protect installed base accuracy.
We measure ASP at distributor level. Freight, insurance, and import or export taxes inside vendor or channel pricing are included, while point of sale taxes stay excluded. Outliers are normalized. We weight pricing across international, domestic, and China based vendors using geography and application mix. Bulk intermediates such as base chemicals follow bulk distributor quotes.
Value is units multiplied by ASP. Installed base is cumulative shipments minus retirements derived from survival curves. Apparent capacity is estimated from production, net trade, and a capacity factor that typically falls between eighty and ninety percent. Historical data are expressed in current period USD, and forward data follow constant FX unless scenarios specify another route.
We calculate brand share as brand value divided by category value for the defined geography and channel set. When EPOS data are missing, we build brand value from filings, tender disclosures, distributor catalogs, and public multi signal reference points. Corridor checks validate the boundaries by testing minimum share signals from capacity or shipment data and maximum share signals from price and volume feasibility.
We compile trade flows through HS codes and apply mirror statistic checks to highlight reporting gaps. Adjustments correct for re exports through hubs, valuation differences between FOB and CIF, and classification shifts. Apparent consumption is closed with production plus imports minus exports and stock change when stock is observable. Outliers are checked against partner statistics, company statements, and customs notes.
We allocate revenue and volume across direct, distributor or wholesale, retail or aftermarket, e commerce or marketplace, system integrator or EPC, and tender or government routes as the category requires. Margin stacks are modelled by channel. Leakage from grey or parallel trade is limited through corridor checks and availability anomalies. Attach rate modelling is used where services or consumables accompany the core product.
We map supply chains from input to final use with attention to capacity, utilization, cycle time, yield, scrap, lead time, lane reliability, and inventory rules. Supplier and buyer concentration indicators show exposure levels. Single point vulnerabilities are tested under supply and demand shocks. Scorecards track quality, delivery behaviour, cost movement, and risk signals.
Method 1 uses regression structures with predictors such as production, utilization, trade flows, capex signals, orders or backlog, pricing corridors, approvals or standards, and policy variables. Transformations are added only when they improve out of sample results. Stability checks and break tests are completed, and models move forward only after full diagnostics and backtesting.
Method 2 applies driver growth rates to the latest audited baseline when series are thin or volatile. Weights are tuned to realized behaviour without overfitting and updated when driver series rebase or shocks appear. Triangulation uses category depth, per population intensity, and an economic envelope to keep scenarios grounded in macro and budget limits.
We track regression accuracy through MAPE with residual and stability diagnostics. Growth rate structures are checked through correlation and backtests against prior vintages, with tolerance bands that reflect category volatility. Apparent consumption closure is required. Price corridors, capacity limits, and FX boundaries are tested for consistency. A second analyst reviews the work, and every change is logged with its 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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