Airline Intelligence
Coming soonDomain
Unified airline decision economics — operations, revenue, disruptions, crew, fuel, and finance in one model
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:
| KPI | Definition | Unit | Scope |
|---|---|---|---|
| CASK | Cost per available seat kilometer | currency/ASK | route, fleet, network |
| RASK | Revenue per available seat kilometer | currency/ASK | route, fleet, network |
| Load Factor | RPK / ASK | % | flight, route, network |
| OTP | Flights departing within 15 min of schedule | % | station, route, network |
| Yield | Revenue / RPK | currency/RPK | route, fare class |
| Disruption cost/flight | Total disruption cost / flights affected | currency/flight | station, cause |
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:
| Product | Companion | Purpose |
|---|---|---|
| Refine | Airline Extraction Companion | Detect airline concepts in messy operational text, reconcile vendor naming, classify disruption causes |
| Lens | Executive Airline Lens | Route profitability, OTP, fuel efficiency, benchmark movement |
| Lens | Disruption Economics Lens | Root causes, cost attribution, recovery success, forecasted risk |
| Council | Disruption Tradeoff Protocol | Cancel, delay, or recover — multi-metric decision |
| Council | Route Decision Protocol | Reduce, re-time, or exit, with full economics |
| Routine | Route Profitability Refresh | Daily recalculation of true route economics |
| Routine | KPI Drift Audit | Detect when KPI definitions shift across teams |
Airline Intelligence is a domain assembly: install the core, then add subdomains as needed. Start with Network + Commercial + Operations for immediate value. Add Disruption, Crew, Fuel, Finance, and Benchmarking as data sources connect.