Airline Intelligence

Airline Intelligence is a domain assembly: not a single flat vocabulary, but a modular system of 8 bounded contexts that model an airline's entire decision surface.

Why this exists

Airlines run on fragmented systems: PSS for bookings, RMS for revenue management, separate crew, fuel, disruption, and finance platforms. Each system has its own vocabulary, its own truth. No one sees the whole picture.

BASAL with Airline Intelligence turns that fragmentation into a unified intelligence layer. Every flight, route, booking, disruption, crew assignment, and fuel decision connects in one causal model.

The domain assembly

Core: Airline Enterprise Intelligence

Shared concepts that every module needs: airline, flight, route, sector, airport, aircraft, leg, schedule, passenger booking, revenue item, cost item, disruption event, crew duty, payment, operating period, KPI, forecast, actual outcome.

8 Bounded Contexts

Network & Schedule: Route economics, frequency, seasonality, aircraft assignment, airport pair performance

Revenue & Commercial: Bookings, fares, ancillaries, channels, load factor, yield, RASK

Operations & OTP: Delays, cancellations, turnaround, on-time performance, station performance, recovery patterns

Disruption: Root cause, cost attribution, reaccommodation, compensation, downstream effects, disruption package outcomes

Crew: Rosters, utilization, legality, salary cost, productivity, disruption impact on crew

Fuel & Flight Cost: Uplift, consumption, tankering, route fuel efficiency, fuel price exposure

Finance & Treasury: P&L mapping, cost allocation, working capital, FX exposure, settlement timing, payment orchestration

Benchmarking: Anonymized peer comparison, percentile performance, disruption benchmarking, cost efficiency benchmarks

Mechanisms: where intelligence lives

Mechanisms matter more than nouns. This is where BASAL becomes intelligent instead of descriptive:

• delay_propagation: how a single delay cascades through aircraft rotations
• missed_connection_cascade: passenger reaccommodation chains from one disruption
• disruption_cost_amplification: how operational events create financial damage
• crew_legality_constraint: when legal limits force expensive crew swaps
• route_seasonality_effect: seasonal demand patterns affecting route economics
• fuel_tankering_tradeoff: when carrying extra fuel saves money vs. costs weight
• working_capital_lag: settlement timing effects on cash position
• cost_allocation_distortion: when shared costs mask true route profitability
• schedule_reliability_erosion: gradual degradation of network resilience

The questions it answers

The domain ships with canonical intelligence questions:

• What is the true profitability of this route after disruption costs, fuel variance, and allocated crew costs?
• Which delays create the highest downstream financial damage?
• Which disruption patterns are predictable 24 hours ahead?
• Which channels produce the best net revenue after refunds, payment costs, and FX effects?
• Which crew patterns reduce resilience or increase recovery cost?
• How does actual route performance compare to historical baseline and peer benchmark?

KPI Grammar

The domain includes a formal KPI vocabulary layer, because airline teams often use the same words differently:

Each KPI includes: formal definition, unit, scope, time basis, aggregation rule, known caveats, and source lineage.

Source-system lineage

Every extracted fact carries provenance:

• Source system (PSS, RMS, crew, finance, treasury)
• Extraction confidence
• Normalization status
• Business effective time vs ingestion time
• Reconciliation state

Trust comes from lineage. In airline intelligence, this is not optional.

Companion ecosystem

This domain is designed to work with the full BASAL product suite: