debt_leverage_profile
Net debt ~£600-700M, ND/EBITDA ~2.0-2.5x; 20% rate rise adds ~£12-14M annual interest cost, modest but manageable given EBITDA ~£300M+
Inferred
Agent_Inference
interest_rate_sensitivity
Floating-rate exposure on ~40-50% of debt; 20% rate increase compresses pre-tax profit by ~4-6%, limited hedging disclosed historically
Inferred
Agent_Inference
geopolitical_supply_exposure
Medium intensity; US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Gas turbine/generator components concentrated in Gulf of Hormuz (fuel supply) and Taiwan/SE Asia (power electronics semiconductors)
Inferred
Agent_Inference
international_expansion_readiness
Significant USD, NGN, and ZAR exposure; Nigerian naira devaluations historically caused double-digit revenue translation losses in Africa segment
Inferred
Agent_Inference
geographic_footprint
Operations in 100+ countries; top markets Americas, Europe, Asia-Pacific; Africa/Middle East carry highest sovereign currency devaluation risk (NGN, KES, ZAR)
Inferred
Agent_Inference
commodity_exposure_profile
Medium intensity; commodities: Steel, Aluminum, Copper, Crude Oil (fuel), Rare Earth Elements, Plastics/Resins; geopolitical: US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
Caterpillar and Aggreko's Stamford/Cummins generator supply represents significant input concentration; no single vendor likely >30% but Cat is closest
Inferred
Agent_Inference
business_model_type_primary
Minimal cloud infrastructure dependency; Aggreko is a physical asset rental business; cloud termination would affect back-office only, not operations
Inferred
Agent_Inference
business_model_type_secondary
ERP/fleet management software (SAP-based) is more operationally critical than public cloud; 30-day cloud exit feasible with migration planning
Inferred
Agent_Inference
switching_cost_profile
Low API coupling risk; Aggreko is asset-heavy industrial rental, not API-dependent; customer switching costs are moderate via long-term contracts
Inferred
Agent_Inference
howey_test_risk_index
Fails Howey Test; revenue from equipment rental services constitutes a service contract, not an investment contract; negligible securities classification risk
Inferred
Agent_Inference
regulatory_burden_tier
Medium
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
GDPR exposure moderate; processes customer/operational data across EU jurisdictions; CCPA exposure minimal given B2B industrial focus; compliance costs manageable
Inferred
Agent_Inference
antitrust_exposure_flag
Low-moderate; competes with Agencia, Atlas Copco, APR Energy; no dominant market share globally; no known active antitrust investigations
Inferred
Agent_Inference
regulatory_exposure_profile
Medium burden; regimes: FAA, DOT, OSHA, EPA, ITAR, FTC; Export controls and defense procurement rules create contract concentration risk.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
~60-70% recurring via multi-year contracts and framework agreements; ~30-40% transactional/event-driven; recurring base anchored by utilities and industrial clients
Inferred
Agent_Inference
monetization_vector
Asset rental (day/week/month rates) plus fuel management services and value-added maintenance; long-term project contracts dominate utility and industrial segments
Inferred
Agent_Inference
pricing_architecture
Cost-plus rental pricing with fuel pass-through; stressed by fuel cost spikes and FX; pricing power moderate—customers can defer but rarely self-supply at scale
Inferred
Agent_Inference
pricing_power_rating
Moderate; Aggreko can pass through fuel costs contractually but faces competitive pressure on day-rates; 6/10 pricing power in captive utility markets
Inferred
Agent_Inference
target_gross_margin_bracket
Gross margin ~35-45%; EBITDA margin ~20-25%; equipment rental economics support stable margins but fuel volatility and utilisation rates are key swing factors
Inferred
Agent_Inference
churn_vulnerability_index
No meaningful free-rider problem; services are metered/contracted; some risk of customers investing in permanent infrastructure after temporary contracts end
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is moderately headcount-sublinear; fleet scaling requires technicians but software/logistics optimisation allows margin expansion without proportional hiring
Inferred
Agent_Inference
marginal_cost_of_growth
Primary marginal cost is capital (generator/equipment fleet capex ~£200-250M/year); headcount grows slower than revenue; incremental EBITDA margins improve at scale
Inferred
Agent_Inference
franchise_compliance_risk
Not a franchise model; direct operations globally; compliance drift risk replaced by geographic regulatory fragmentation risk across 100+ country operating jurisdictions
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, CAC economics improve via brand/reputation leverage; key constraint is fleet availability and deployment logistics, not customer acquisition cost
Inferred
Agent_Inference
network_effect_present
No meaningful network effects; utility/value does not increase with more customers; competitive moat is fleet size, logistics capability, and project execution track record
Inferred
Agent_Inference
asset_efficiency_ratio
AI displacement risk low in field operations; AI applicable to fleet scheduling and predictive maintenance, improving utilisation rates by est. 3-5% over 5 years
Inferred
Agent_Inference
recession_resistance_tier
Tier 2 recession resilience; utility/emergency power is defensive but industrial/events segment contracts; 2008-09 and COVID showed ~10-20% revenue declines
Inferred
Agent_Inference
customer_segment_primary
Utilities, national grid operators, and power authorities (~40-50% of revenue); relatively sticky, long-contract customers with critical infrastructure needs
Inferred
Agent_Inference
customer_segment_secondary
Oil & gas, mining, petrochemicals, and industrial manufacturers (~25-30%); more cyclical, exposed to commodity capex cycles
Inferred
Agent_Inference
characteristic_occupations
["11-0000 Management Occupations", "13-0000 Business and Financial Operations Occupations", "15-0000 Computer and Mathematical Occupations", "17-0000 Architecture and Engineering Occupations", "23-0000 Legal Occupations", "33-0000 Protective Service Occupations", "37-0000 Building and Grounds Cleaning and Maintenance Occupations", "41-0000 Sales and Related Occupations", "43-0000 Office and Administrative Support Occupations", "47-0000 Construction and Extraction Occupations", "49-0000 Installation, Maintenance, and Repair Occupations", "51-0000 Production Occupations", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.3 (HIL — ~30% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
Capex ~£200-250M annually; mix shifting toward hybrid/battery and low-emission fleet (future-state) from pure diesel/gas (legacy); transition capex rising as % of total
Inferred
Agent_Inference
sec_cik
null
Inferred
Agent_Inference
ticker
Aggreko was taken private by TDR Capital and I Squared Capital in 2021; no longer publicly listed; previously traded as AGK.L on London Stock Exchange
Inferred
Agent_Inference