NP-RM-03 · Overbooking Policy Management

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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 booking & no-show history from PSS	Revenue Management Analyst	Amadeus Altéa PSS	Departed flight records, booking logs, check-in data — rolling 24 months	Raw no-show and cancellation dataset by flight, fare class, and booking channel	Dataset completeness ≥99% of departed flights	N	N
1.2	Segment data by route, DOW, fare class, season	Revenue Management Analyst	AWS Redshift	Raw no-show dataset from Altéa PSS export	Segmented no-show rate matrix with confidence intervals per cluster	Minimum 90 observed flights per segment for statistical significance	N	Y
1.3	Run no-show forecast model and validate accuracy	RM Data Scientist	Amadeus Revenue Management (NRM / AltéaRM)	Segmented no-show matrix, demand forecasts from AltéaRM	No-show show-up curve per flight cluster; model accuracy report	Forecast vs. actual no-show rate MAPE ≤5%	Y	N
1.4	Calibrate show-up curve by fare class and lead time	RM Data Scientist	Amadeus Revenue Management (NRM / AltéaRM)	Validated no-show forecast model; approved show-up curves	Calibrated show-up probability curves published to AltéaRM overbooking module	Show-up curve refresh cycle ≤30 days for high-frequency routes; ≤90 days for seasonal routes	N	N
Phase 2 2.1	Generate recommended OB factors by flight segment	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Calibrated show-up curves; target load factor ≥83%; denied boarding cost assumptions	Recommended overbooking factor per flight segment with expected IDB rate	Expected IDB rate ≤0.05 per 10,000 enplaned passengers (DOT Part 250 benchmark)	N	N
2.2	Apply DOT 14 CFR 250 regulatory cap and fare rule check	Revenue Compliance Manager	ATPCO	Recommended OB factors; ATPCO fare conditions (refundability, cancellation fees)	Compliance-reviewed OB factor set; flag for non-refundable fare interactions	100% of OB factors within DOT involuntary bump compensation trigger thresholds	Y	Y
2.3	Approve and publish booking limits to PSS inventory	Director of Revenue Management	Amadeus Altéa PSS	Compliance-reviewed OB factor set; Director sign-off	Authorised overbooking limits loaded into Altéa inventory control per flight	Limit publication latency ≤4 hours ahead of booking horizon open; 100% of flights have an active OB limit	N	N
Phase 3 3.1	Monitor booking pace vs. authorised OB limits	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Live booking feed from Altéa PSS; authorised OB limits	Booking pace dashboard with oversale risk flags per flight	Alert response time ≤15 minutes of threshold breach detection	N	N
3.2	Detect and triage oversale threshold breach	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Booking pace alert; current bookings vs. authorised limit	Oversale risk classification (low / medium / high) with recommended action	False positive rate ≤10% of alerts triaged as high-risk	Y	Y
3.3	Adjust OB level or close booking class dynamically	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Oversale risk classification; updated show-up probability at current booking depth	Revised OB factor or booking class closure instruction applied to Altéa PSS	OB adjustment applied within 30 minutes of triage decision; no flight departs with OB factor >20% above baseline	N	N
3.4	Escalate high-risk oversale flights to RM Supervisor	RM Supervisor	Amadeus Revenue Management (NRM / AltéaRM)	High-risk oversale flag; passenger manifest; connecting itinerary exposure	Escalation note with recommended corrective action; decision to hold or reduce OB	Escalation-to-decision cycle time ≤1 hour; 100% of high-risk flights reviewed by T-24h	N	Y
Phase 4 4.1	Identify oversold flights at check-in closure	Airport Gate Agent	SITA Airport Management System (AMS)	Final check-in count; boarded passenger list; aircraft capacity	Confirmed oversale count and list of checked-in passengers eligible for VDB/IDB	Oversold flight identification completed ≥30 minutes before departure	N	Y
4.2	Solicit and screen volunteers for VDB compensation	Airport Gate Agent	Amadeus Altéa PSS	Oversold count; gate board call; compensation parameters from RM Supervisor	Confirmed volunteer list with accepted compensation; rebooked itineraries in Altéa	VDB rate ≥80% of oversale situations resolved without IDB; average VDB compensation cost ≤$350	Y	N
4.3	Process involuntary denied boarding per 14 CFR 250	Airport Gate Agent / Supervisor	Amadeus Altéa PSS	Confirmed oversale after VDB exhaustion; passenger priority matrix (status, fare, check-in time)	IDB passenger list; denied boarding compensation (cash/voucher at DOT-mandated 400% of OW fare, max $1,550)	IDB processing completed ≥15 minutes before door close; 0 IDB passengers with connecting flights missed due to rebooking delay	N	Y
4.4	Issue compensation and confirm rebooking for IDB/VDB pax	Airport Gate Agent	Amadeus Altéa PSS	IDB/VDB passenger list; approved compensation values; next available flight inventory	Compensation vouchers/cash issued; confirmed rebooking on next available service; IDB event logged	100% of IDB passengers offered confirmed rebooking within 2 hours; compensation issued at gate before passenger departs	N	N
Phase 5 5.1	Compile post-flight IDB/VDB statistics and cost data	Revenue Management Analyst	AWS Redshift	Altéa IDB/VDB event logs; gate agent reports; compensation cost records	IDB/VDB summary report: count, cost, route, fare class, DOW breakdown	Report generated within 48 hours of flight departure; 100% event capture rate	N	N
5.2	Review denied boarding KPIs against policy thresholds	Director of Revenue Management	Tableau	IDB/VDB summary report; rolling 12-month trend; DOT Part 250 benchmark (0.05 IDB per 10k pax)	KPI review decision: policy adequate or recalibration required	IDB rate ≤0.05 per 10,000 enplaned passengers; VDB cost ≤$350 average per event	Y	N
5.3	Submit DOT quarterly denied boarding compliance report	Revenue Compliance Manager	DOT Air Travel Consumer Report Submission Portal	Validated IDB/VDB statistics; carrier passenger enplanement totals	Filed DOT Part 250 quarterly report; internal compliance archive record	100% on-time filing by DOT deadline (30 days after quarter end); zero restatements	N	N

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Process Attributes

Identification

Process IDNP-RM-03

L1 DomainNetwork Planning & Scheduling

L2 ProcessRevenue Management

L3 NameOverbooking Policy Management

L4 Steps18 across 5 phases

Decision Gates5 (all with iteration loops)

Exceptions6 documented

Swim Lanes (Roles)

Revenue Management Analyst

RM Data Scientist

Revenue Compliance Manager

Director of Revenue Management

RM Supervisor

Airport Gate Agent

Airport Gate Agent / Supervisor

Systems & Tools

Amadeus Altéa PSSAWS RedshiftAmadeus Revenue Management (NRM / AltéaRM)ATPCOSITA Airport Management System (AMS)TableauDOT Air Travel Consumer Report Submission Portal

Key Performance Indicators

Extract booking & no-show history from PSSDataset completeness ≥99% of departed flights

Segment data by route, DOW, fare class, seasonMinimum 90 observed flights per segment for statistical significance

Run no-show forecast model and validate accuracyForecast vs. actual no-show rate MAPE ≤5%

Calibrate show-up curve by fare class and lead timeShow-up curve refresh cycle ≤30 days for high-frequency routes; ≤90 days for seasonal routes

Generate recommended OB factors by flight segmentExpected IDB rate ≤0.05 per 10,000 enplaned passengers (DOT Part 250 benchmark)

Apply DOT 14 CFR 250 regulatory cap and fare rule check100% of OB factors within DOT involuntary bump compensation trigger thresholds

Approve and publish booking limits to PSS inventoryLimit publication latency ≤4 hours ahead of booking horizon open; 100% of flights have an active OB limit

Monitor booking pace vs. authorised OB limitsAlert response time ≤15 minutes of threshold breach detection

Airline-Specific Risks & Pain Points

Altéa PSS history exports require manual scheduling; ad-hoc pulls risk data truncation beyond 13-month rolling window

Thin markets (<5 flights/week) produce unreliable segment-level no-show rates; pooled estimates inflate overbooking risk

NRM show-up model requires retraining after major schedule restructures; post-COVID demand patterns invalidated legacy curves for 18+ months

Fare class proliferation (Basic Economy vs. flexible fares) requires separate show-up curves; legacy model treats all economy as one class

NRM OB optimiser does not natively model denied boarding compensation cost per DOT 14 CFR 250 tiers; analyst must manually adjust factors to avoid regulatory overshoot

Non-refundable Basic Economy fares have near-zero pre-departure cancellations, artificially inflating apparent show-up rates; ATPCO Rule 35 interactions must be hand-checked

Inputs / Outputs

Primary InputDeparted flight records, booking logs, check-in data — rolling 24 months

Primary OutputFiled DOT Part 250 quarterly report; internal compliance archive record

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