title: “Flight Supply Strategy — Aggregated Reference Document” category: Supply Strategy status: Draft version: “Consolidated (v1.0)” created: 2026-02-25 sources:

• Complete Findings
• Enterprise Dossier v1
• Enterprise Dossier v2
• Strategic Dossier Expanded related:
• “Complete Findings”
• “Duffel vs Verteil”
• “Wego Build Blueprint”

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Flight Supply Strategy — Aggregated Reference Document

Version: Consolidated (v1.0) Date: 2026-02-25 Decision Status: Pending — OTA vs NDC/DAI vs Hybrid under evaluation Sources: Complete Findings, Enterprise Dossier v1, Enterprise Dossier v2, Strategic Dossier Expanded

Table of Contents

1. Executive Summary
2. Industry Structure & Distribution Evolution
3. Meta-Search Platform Mechanics
4. Supply Strategy Options Overview
5. OTA Model — Deep Dive
6. NDC / Direct Airline Integration — Deep Dive
7. Hybrid Model — Controlled Evolution
8. Supplier Landscape
9. Enterprise Architecture Blueprint
10. Concurrency, Fan-Out & Timeout Strategy
11. Algorithmic Design
12. Resilience Architecture
13. Financial Modeling Framework
14. Payment, Refund & Chargeback Risk
15. SLA Modeling & Reliability Math
16. Reconciliation & Finance Ops
17. Observability & Monitoring
18. Governance & Risk Framework
19. Scenario Modeling
20. Decision Framework & Executive Evaluation
21. Strategic Conclusion & Next Steps

1. Executive Summary

This document consolidates all findings from four separate strategy analyses evaluating three flight supply paths:

This is not a technical preference decision. It is:

• A capital allocation decision
• An operating model decision
• A risk envelope decision
• A margin structure decision
• A long-term strategic positioning decision

No path has been selected. This document provides the full analytical foundation for a board-level decision.

[!IMPORTANT] For a concise overview of the three models, see Complete Findings. This document provides the deep technical and financial detail.

2. Industry Structure & Distribution Evolution

flowchart LR
    GDS[GDS Era] --> OTA[OTA Expansion]
    OTA --> META[Meta-Search Growth]
    META --> NDC[NDC / Airline Retailing]
    NDC --> HYBRID[Hybrid Supply Models]

Key Macro Drivers

• Airline distribution cost pressure — airlines want to reduce GDS fees ($8–12/segment)
• Dynamic pricing & continuous pricing models — real-time yield management
• Retail merchandising push by airlines — bundles, ancillaries, branded fares
• Margin compression in affiliate channels — CPC rates declining industry-wide

Incentive Alignment & Power Dynamics

Distribution Layers

flowchart LR
    Airline --> GDS
    Airline --> NDC
    GDS --> OTA
    OTA --> Meta
    NDC --> Aggregator
    Aggregator --> Meta

[!NOTE] The industry is evolving from GDS-centric distribution to multi-channel distribution. Airlines increasingly favor NDC for lower distribution costs and richer content, but GDS remains dominant for coverage breadth.

3. Meta-Search Platform Mechanics

Meta-search platforms:

1. Aggregate supply from multiple providers (OTAs, airlines, aggregators)
2. Normalize and deduplicate itineraries
3. Rank and display comparable flight options
4. Redirect users (or optionally handle checkout)
5. Track click attribution for revenue

Key realities:

• Not all airlines are queried directly
• APIs are called in parallel with timeouts and caching
• Prices can change due to offer expiration or inventory changes

Cross-reference: See Wego & Skyscanner Mechanics for real-world implementation examples.

4. Supply Strategy Options Overview

5. OTA Model — Deep Dive

What It Is

Integrate multiple Online Travel Agencies. Users compare prices and are redirected to book on the OTA.

sequenceDiagram
    User->>Platform: Search Flights
    Platform->>OTA APIs: Query inventory
    OTA APIs-->>Platform: Return offers
    Platform->>User: Display comparison
    User->>OTA: Redirect to booking

Platform Responsibilities

• Search UI, filters, and sorting
• Deduplication logic
• Provider comparison
• Redirect tracking

Strengths

• Fastest launch — minimal infrastructure
• Low operational burden — no payment/refund handling
• Capital-light — no working capital exposure

Weaknesses

• Lower margins (CPC/CPA only)
• No booking ownership — users don’t have booking history in your system
• Full dependence on partner reliability

Revenue Model

Revenue = CPC_clicks × CPC_rate
  or
Revenue = Bookings × CPA_commission

Revenue per 1,000 Searches (RPS):

RPS = Searches × CTR × Conversion × Commission / 1000

Example: CTR = 18%, Conversion = 3%, Commission = $12 → RPS = $64.80

6. NDC / Direct Airline Integration — Deep Dive

What It Is

Integration with airline retail APIs using the NDC standard.

Order State Machine

stateDiagram-v2
    [*] --> Offered : AirShopping
    Offered --> Priced : OfferPrice
    Priced --> Booked : OrderCreate
    Booked --> Ticketed : Ticketing (Payment Cleared)
    Ticketed --> Changed : OrderChange
    Ticketed --> Refunded : OrderCancel
    Changed --> Ticketed : Re-issued
    Refunded --> [*]
    Offered --> Expired : TTL Timeout
    Expired --> [*]

Offer → Order Lifecycle

flowchart LR
    Search --> AirShopping
    AirShopping --> OfferPrice
    OfferPrice --> OrderCreate
    OrderCreate --> Ticketing
    Ticketing --> OrderChange
    Ticketing --> OrderCancel

sequenceDiagram
    User->>Platform: Search
    Platform->>Airline: AirShopping
    Airline-->>Platform: Offers
    Platform->>Airline: OfferPrice
    User->>Platform: Checkout
    Platform->>Airline: OrderCreate
    Airline-->>Platform: Order Confirmation

Strengths

• Higher margin potential (markup + commission)
• Richer ancillary content
• Airline differentiation
• Brand ownership possible

Weaknesses / Operational Burden

• High technical complexity
• Offer → Order lifecycle handling
• Offer expiration handling
• Refund/change servicing burden
• Payment compliance requirements (PCI)
• Customer support, chargeback handling
• Airline variability in implementation
• SLA compliance

Margin Model

Gross Margin = (Ticket Price × Markup%) + Commission − Payment Fees − Refund Leakage

Why Multiple Integrations Are Needed (Even with NDC)

• Coverage fragmentation (per-airline basis)
• Airline variability in implementation
• Commercial differences
• Resilience and redundancy
• Even with an aggregator like Verteil, multi-sourcing may be required for coverage or leverage

7. Hybrid Model — Controlled Evolution

Recommended Structure

gantt
    title Hybrid Strategy Roadmap
    dateFormat  YYYY-MM
    section Phase 1
    OTA Launch           :2026-01, 6m
    section Phase 2
    Add Selective NDC    :2026-07, 6m
    section Phase 3
    Limited Checkout     :2027-01, 6m

Benefits

• Early revenue with reduced risk
• Gradual margin improvement
• Controlled complexity growth
• Preserves optionality

Decision Gate Formula

Proceed to NDC if:
  Incremental Margin > Incremental Operational Cost + Risk Premium

8. Supplier Landscape

Cross-reference: For a detailed comparison of the two top candidates, see Duffel vs Verteil Supplier Comparison.

9. Enterprise Architecture Blueprint

System Topology (Production-Grade)

flowchart TD
    USER --> EDGE
    EDGE --> API_GATEWAY
    API_GATEWAY --> SEARCH_ORCHESTRATOR
    SEARCH_ORCHESTRATOR --> SUPPLIER_POOL
    SUPPLIER_POOL --> OTA_ADAPTERS
    SUPPLIER_POOL --> NDC_ADAPTERS
    SEARCH_ORCHESTRATOR --> CACHE_CLUSTER
    SEARCH_ORCHESTRATOR --> NORMALIZATION_ENGINE
    NORMALIZATION_ENGINE --> DEDUP_ENGINE
    DEDUP_ENGINE --> RANKING_ENGINE
    RANKING_ENGINE --> RESPONSE_SERVICE
    RESPONSE_SERVICE --> USER

Core Services

Optional Modules (If Checkout Enabled)

flowchart TD
    USER --> CHECKOUT_SERVICE
    CHECKOUT_SERVICE --> PAYMENT_GATEWAY
    CHECKOUT_SERVICE --> ORDER_SERVICE
    ORDER_SERVICE --> AIRLINE_API
    ORDER_SERVICE --> NOTIFICATION_SERVICE

• Order Management Service
• Payment Service
• Refund Engine
• Notification Service

Cross-reference: See Wego Build Blueprint § Architecture for a real-world architecture reference.

10. Concurrency, Fan-Out & Timeout Strategy

Parallel Supplier Query Model

Latency_total ≈ max(Supplier_i_latency)

[!TIP] Total search latency is bounded by the slowest supplier, not the sum of all suppliers. This makes timeout strategy critical.

Timeout Strategy

Fallback Rule: If ≥ 40% suppliers timeout → trigger degraded mode (serve cached results).

Rate Limiting Strategy

• Global rate limit per supplier: 50 RPS per IP, burst: 120
• Adaptive throttling: If latency > P95 threshold → reduce concurrency by 30%

11. Algorithmic Design

Deduplication Logic

ItineraryHash = Hash(Origin + Destination + DepartureTime +
                     ArrivalTime + OperatingCarrier + Cabin + FareClass)

Duplicate Threshold: If PriceDifference < 2% → treat as same cluster → show cheapest.

Ranking Engine (Multi-Factor)

Score = w1 × PriceScore
      + w2 × SupplierReliability
      + w3 × MarginYield
      + w4 × ClickThroughPrediction
      + w5 × HistoricalConversionRate

All factors normalized to 0–1 scale. Weights tuned via A/B testing.

Supplier Scoring Model

SupplierScore = 0.30 × PriceCompetitiveness
              + 0.25 × SLA
              + 0.20 × MarginContribution
              + 0.15 × LatencyScore
              + 0.10 × MismatchPenalty

Recomputed daily from production metrics.

12. Resilience Architecture

Circuit Breaker Model

flowchart LR
    Request --> Supplier
    Supplier --> Success
    Supplier --> Failure
    Failure --> ErrorCounter
    ErrorCounter --> ThresholdCheck
    ThresholdCheck -->|Exceeded| OpenCircuit
    OpenCircuit --> FallbackSupplier

[!TIP] Half-Open state allows a single probe request through to test recovery before closing the circuit.

13. Financial Modeling Framework

Revenue Per Search (RPS) — Extended

RPS = CTR × Conversion × (Commission + Markup − RefundLeakage − PaymentFees)

Contribution Margin

Contribution Margin = Revenue − Variable Costs

Variable costs include: API costs, payment processing, support per booking, chargeback loss.

Supplier Margin Sensitivity

Incremental Revenue = ΔMargin% × AvgTicket × Volume

Example: +1.5% margin on 100K bookings at $500 avg → $750K incremental revenue.

Financial Model Comparison

quadrantChart
    title Risk vs Margin Profile
    x-axis Low Risk --> High Risk
    y-axis Low Margin --> High Margin
    quadrant-1 NDC Heavy
    quadrant-2 Hybrid
    quadrant-3 OTA Only

Cross-reference: See Revenue Acceleration Addendum for detailed revenue expansion strategies.

14. Payment, Refund & Chargeback Risk

Payment Flow (NDC Checkout)

sequenceDiagram
    User->>Platform: Checkout
    Platform->>PaymentGateway: Authorization
    PaymentGateway-->>Platform: Token
    Platform->>Airline: OrderCreate
    Airline-->>Platform: Confirmation
    Platform->>User: Ticket Issued

Refund Leakage Model

Refund Leakage = RefundRate × AvgTicket × ProcessingLoss%

Example: 12% refund rate × $480 avg × 4% processing loss → $2.30 per booking avg

Working Capital Exposure

Exposure = DailyBookings × AvgTicket × AvgRefundCycleDays

Example: 300 bookings/day × $500 × 18 days → $2.7M exposure

[!WARNING] Working capital exposure is a significant risk for NDC/checkout models. Budget for float and ensure treasury processes are in place before launching checkout.

Chargeback Loss Model

ChargebackLoss = ChargebackRate × AvgTicket × Multiplier

Multiplier includes fees, lost revenue, and operational handling.

Example: 0.8% rate × $500 → $4,000 loss per 1,000 bookings

Operational Comparison

15. SLA Modeling & Reliability Math

Composite Availability

For n suppliers:

Availability = 1 − ∏(1 − Ai)

Example (6 suppliers at 97%):

Availability = 1 − (0.03^6) = 99.999999% theoretical redundancy

Real-world values are adjusted via latency filters.

Error Budget Model

ErrorBudget = 1 − TargetSLA

If Target SLA = 99.5% → Monthly error allowance ≈ 3.6 hours.

16. Reconciliation & Finance Ops

Click Reconciliation

Variance% = |PlatformClicks − PartnerClicks| / PartnerClicks

Escalation threshold: Variance > 4%

Settlement Reconciliation

flowchart TD
    BookingData --> FinanceDB
    PartnerInvoice --> FinanceDB
    FinanceDB --> VarianceCheck
    VarianceCheck --> AuditQueue

Monthly reconciliation required.

17. Observability & Monitoring

Key Metrics

18. Governance & Risk Framework

Supplier Governance

• Quarterly review: SLA, margin, latency, conversion rate, mismatch rate
• SLA penalty clauses in contracts
• Margin renegotiation triggers based on volume thresholds
• Risk audit cadence aligned with board reporting

Termination Criteria

Terminate supplier if: 3 consecutive SLA breaches > threshold.

19. Scenario Modeling

20. Decision Framework & Executive Evaluation

Weighted Score Model

TotalScore_option = Σ (Weight_i × Score_option_i)

Select highest composite score.

Decision Factors

Quick Guide

This is not a technical choice. It is a capital allocation, risk management, and long-term positioning decision.

21. Strategic Conclusion & Next Steps

Recommendation

The Hybrid strategy provides the best balance between speed, risk, margin, and optionality for most startups.

Recommended Evolution Pattern

1. Launch with OTA
2. Optimize unit economics
3. Add selective NDC on high-volume routes
4. Consider checkout only after compliance & ops readiness

Before Final Decision, Leadership Must Define

1. Risk tolerance level
2. Capital envelope
3. Operational readiness
4. Margin ambition
5. 3-year positioning goal

Next Step

Conduct an executive workshop using the weighted scoring model and simulate route-level economics before final approval.

Prepared as a consolidated strategic reference document, aggregating: Complete Findings, Enterprise Dossier v1 & v2, and Strategic Dossier Expanded.

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