CM-01 · Crew Pairing Optimization · Airlines Process Wiki

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Process Flow Diagram (BPMN)

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L4 Process Steps

Step	Step Name	Role / Swim Lane	System	Input	Output	KPI	Dec?	Exc?
Phase 1 1.1	Extract published flight schedule for pairing input	Crew Planning Analyst	Amadeus SkyWORKS	Published SSIM flight schedule file for planning period	Validated flight activity file loaded into crew system	Schedule completeness ≥99.5% of planned departures loaded	N	N
1.2	Load FAR Part 117 and CBA constraint parameters	Crew Planning Analyst	Jeppesen Crew Management	FAR Part 117 regulation set, current Collective Bargaining Agreement	Legal constraint rule set activated in optimization engine	100% rule compliance across all published pairings	N	Y
1.3	Validate fleet type and crew qualification matrix	Crew Planning Analyst	Jeppesen Crew Management	Fleet assignment file, crew qualification and currency database	Qualified crew pool confirmed per aircraft type and domicile	Zero unqualified crew assignments at publish; qualification data currency ≥99%	Y	Y
Phase 2 2.1	Generate candidate duty periods from flight activity	Crew Planning Systems Specialist	Jeppesen Crew Management	Validated flight activity file, crew base and domicile data	Candidate duty period library (50,000+ pairings)	Generate ≥50,000 candidate pairings per iteration; generation run time <30 min	N	N
2.2	Filter candidate pairings against FAR Part 117 limits	Crew Planning Systems Specialist	Jeppesen Crew Management	Candidate duty period library, FAR Part 117 duty and rest limits	Legally filtered duty period library	100% of retained pairings FAR Part 117 compliant; filter pass rate logged	Y	Y
2.3	Enforce crew base and domicile deadhead constraints	Crew Planning Analyst	Jeppesen Crew Management	FAR-filtered duty periods, crew base capacity allocations	Domicile-constrained pairing set with deadhead cost estimates	Deadhead ratio ≤3.5% of total pairing block hours	Y	N
Phase 3 3.1	Execute integer programming pairing optimization	Crew Planning Systems Specialist	Jeppesen Crew Management	Filtered pairing library, cost objective (minimize hotel, deadhead, duty cost)	Optimized pairing solution with full flight coverage	Pairing cost per block hour ≤$22 benchmark; solver convergence within 2 hrs	N	Y
3.2	Validate 100% flight coverage in optimized solution	Crew Planning Analyst	Jeppesen Crew Management	Optimized pairing solution	Coverage validation report; list of uncovered flights if any	100% flight coverage — zero uncovered departures at validation	Y	Y
3.3	Assess hotel and per-diem cost against budget targets	Crew Cost Analyst	Jeppesen Crew Management + SAP S/4HANA Finance (FI/CO)	Optimized pairing plan, hotel contract rate file, CBA per-diem schedule	Crew cost estimate vs. budget variance report	Layover hotel cost ≤$85/night average; total pairing cost within 5% of budget	Y	N
Phase 4 4.1	Run CBA work rule validation on all pairings	Labor Relations Analyst	Jeppesen Crew Management	Optimized pairing set, CBA rules library (versioned)	CBA compliance report with pass/fail per pairing	CBA violation rate <0.5% at initial validation run	Y	Y
4.2	Resolve CBA violations via manual pairing edit	Crew Planning Analyst	Jeppesen Crew Management	CBA violation report, flagged pairings	Corrected pairings with no CBA violations	All violations resolved within 4 hrs; zero violations at final publish	N	Y
Phase 5 5.1	Build crew roster lines from approved pairing set	Crew Rostering Analyst	Jeppesen Crew Management	Approved pairing set, roster period calendar, CBA day-off requirements	Draft roster lines with guaranteed time, days off, and pairing assignments	Average monthly guaranteed-time utilization ≥82% of CBA contractual maximum	N	Y
5.2	Allocate reserve crew coverage by domicile	Crew Rostering Analyst	Jeppesen Crew Management	Draft roster lines, 12-month historical disruption and sick-call rates	Reserve crew allocation plan per domicile and day type	Reserve coverage ratio ≥110% of projected daily sick/IRROP requirement	Y	N
5.3	Publish bid package to crew self-service portal	Crew Scheduling Manager	Jeppesen Crew Management	Finalized roster lines, reserve allocation, CBA bid lead-time requirement	Bid package published for crew seniority-based self-bidding	Bid package published ≥21 days before period start per CBA; 100% of lines posted	Y	Y
5.4	Process crew bids and award by seniority	Crew Scheduling Manager	Jeppesen Crew Management	Submitted crew bids, current seniority list	Awarded roster assignments per crew member	Bid award accuracy ≥99.9%; zero seniority inversion errors	N	Y
5.5	Publish final rosters and sync to PSS	Crew Scheduling Manager	Jeppesen Crew Management + Amadeus Altéa PSS	Awarded bid assignments, PSS crew manifest interface	Published crew rosters; crew manifest updated in Altéa PSS	Roster publication ≥14 days before period start; PSS sync completed within 1 hr	N	Y

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Process Attributes

Identification

Process IDCM-01

L1 DomainCrew Management

L2 ProcessCrew Planning & Rostering

L3 NameCrew Pairing Optimization

L4 Steps16 across 5 phases

Decision Gates8 (all with iteration loops)

Exceptions11 documented

Swim Lanes (Roles)

Crew Planning Analyst

Crew Planning Systems Specialist

Crew Cost Analyst

Labor Relations Analyst

Crew Rostering Analyst

Crew Scheduling Manager

Systems & Tools

Amadeus SkyWORKSJeppesen Crew ManagementJeppesen Crew Management + SAP S/4HANA Finance (FI/CO)Jeppesen Crew Management + Amadeus Altéa PSS

Key Performance Indicators

Extract published flight schedule for pairing inputSchedule completeness ≥99.5% of planned departures loaded

Load FAR Part 117 and CBA constraint parameters100% rule compliance across all published pairings

Validate fleet type and crew qualification matrixZero unqualified crew assignments at publish; qualification data currency ≥99%

Generate candidate duty periods from flight activityGenerate ≥50,000 candidate pairings per iteration; generation run time <30 min

Filter candidate pairings against FAR Part 117 limits100% of retained pairings FAR Part 117 compliant; filter pass rate logged

Enforce crew base and domicile deadhead constraintsDeadhead ratio ≤3.5% of total pairing block hours

Execute integer programming pairing optimizationPairing cost per block hour ≤$22 benchmark; solver convergence within 2 hrs

Validate 100% flight coverage in optimized solution100% flight coverage — zero uncovered departures at validation

Airline-Specific Risks & Pain Points

Schedule changes from network planning arriving <72 hrs before month close disrupt pairing optimization cycles and require costly re-runs

CBA rule amendments negotiated mid-planning cycle require manual rule re-entry into Jeppesen and full re-optimization, adding 8–12 hrs to the planning cycle

Mixed-fleet type-rating transitions (e.g., 737-800 to MAX) create temporary qualification bottlenecks that reduce eligible crew pools by up to 15% during conversion windows

Combinatorial explosion in dense network segments (e.g., 200+ daily departures from hub bases) causes candidate generation times exceeding 4 hrs, compressing the optimization window

Augmented crew rules for ultra-long-haul operations add rule complexity that standard Jeppesen rule builds handle inconsistently without custom coding, requiring manual legal audit

Unbalanced base staffing at thin-market domiciles forces excessive deadheading; Jeppesen does not dynamically rebalance base headcount, requiring manual planner intervention

Inputs / Outputs

Primary InputPublished SSIM flight schedule file for planning period

Primary OutputPublished crew rosters; crew manifest updated in Altéa PSS

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