At FMI we define scope across Product, Technology, Application, Channel, and Region covering seven regions and thirty countries. Our unit basis for value and volume along with currency treatment is set upfront so that comparisons stay consistent across automation hardware and software lines. Monthly indicators feed into quarterly baselines, and forecasts run at constant FX unless scenario work calls for a different path. Segment trees are locked before data enters the system and any revision passes through formal change control.
We count shipments once at the point where vendors dispatch automation components or systems to channels or end users. OEM transfers are not counted twice because attribution stays with the brand on the finished unit. Subsidiary inventory enters only when it moves into the channel. Known re export corridors in industrial equipment are reassigned to the country of final use when that route is visible. Installed base integrity is maintained by including manufacturer self-consumption and bona fide donations.
ASP is captured at the distributor level. Freight, insurance, and import related duties inside vendor or channel pricing are included while point of sale taxes remain outside our calculation. Outliers are normalized and pricing is weighted across international, domestic, and China based vendors using mixes tied to geography and application. Bulk distributor prices guide estimates for industrial chemicals or intermediates used in automation production.
Brand share follows Brand Value divided by Category Value. Where EPOS is unavailable, we triangulate brand value from filings, tender records, distributor catalogs, and public multi signal proxies. Corridor checks ensure that minimum shares align with capacity and shipment evidence while maximum shares remain feasible against price and volume logic.
We compile trade flows using HS codes with mirror statistics to identify gaps. Adjustments address re exports through major automation hubs along with FOB and CIF valuation gaps and classification changes. Time alignment and currency standardization are applied before apparent consumption is closed using Production plus Imports minus Exports with stock change included when observable.
Revenue and volume are distributed across direct sales, distributor or wholesale networks, aftermarket or retail, e commerce or marketplace channels, system integrators, EPC players, and government or tender routes depending on the automation category. Margin stacks are built for each channel, and leakage is assessed through price corridor checks and availability anomalies. Where automation relies on spares, consumables, or service packs, attach rate models are used to quantify linked demand.
We map automation supply chains from components and subassemblies through system integration and end use. Capacity, utilization, cycle time, yield, scrap, lead time, lane reliability, and inventory policies are modeled using operations data. Concentration indicators expose reliance on specific suppliers or geographies and single point exposures are stress tested with demand and supply shocks. Scorecards track supplier quality, delivery performance, cost movement, and risk indicators.
Our regression-based structure uses predictors such as production, utilization, trade flows, capex cycles, order books, price corridors, approvals, and policy variables that shape industrial automation demand. Transformations are introduced only when out of sample accuracy improves. Stability checks and break tests are run and models are retained only after backtesting.
A second structure applies driver growth rates to audited baselines. Weighted growth is used where series are sparse or volatile, and weights are tuned to realized outcomes without overfitting. Revisions occur when drivers rebase or when shocks shift the trajectory. Triangulation uses product category analysis, per population intensity of automation adoption, and an economic envelope that bounds demand within realistic budget and macro conditions.
Regression accuracy is evaluated using MAPE, residual diagnostics, and stability tests. Growth rate structures are validated through correlation checks and backtests against earlier vintages with tolerance bands calibrated to volatility in automation categories. Reconciliation ensures closure of apparent consumption, and we test price corridors as well as FX and capacity boundaries. A second analyst reviews and signs off each cycle, and our change log records the rationale behind every update.
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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