NP-RM-01 · Inventory & Yield Optimization

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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	Ingest booking & flown data from PSS	Revenue Management Analyst	Amadeus Altéa PSS	Daily booking transactions, flown coupon data, no-show records	Cleansed booking data feed loaded into RM data warehouse	Data completeness ≥ 99.5% of all PNRs reconciled within 2 hours of departure	N	N
1.2	Enrich data with competitive fare & schedule feeds	Revenue Management Analyst	OAG Schedule Analyser	Competitor published schedules, OAG fare feeds, MIDT booking data	Competitive context dataset appended to demand input files	Competitive fare parity check completed for 100% of O&D pairs within planning horizon	N	N
1.3	Run O&D demand forecast model	Revenue Management Analyst	Amadeus SkyCAST	Cleansed booking data, competitive context, seasonal index, special-event calendar	O&D demand forecast by booking class for 330-day horizon	Forecast MAPE ≤ 15% at O&D level for departures within 30 days	N	N
1.4	Validate forecast accuracy against holdout set	Senior Revenue Management Analyst	AWS Redshift	O&D demand forecast, 30-day actuals from previous cycle	Forecast accuracy report; approved or rejected forecast	Forecast MAPE ≤ 15%; rejection triggers reforecast within 4 hours	Y	Y
Phase 2 2.1	Define booking class hierarchy and nested buckets	Revenue Management Configuration Analyst	Amadeus Revenue Management (NRM)	Approved fare class structure from Pricing team, ATPCO filed classes	Booking class hierarchy configuration in NRM (Y, B, M, H, Q, K … buckets)	100% of ATPCO-filed fare classes mapped to NRM booking classes before schedule activation	N	N
2.2	Set authorization unit (AU) levels per fare class	Revenue Management Analyst	Amadeus Revenue Management (NRM)	O&D demand forecast, fare class hierarchy, historical sell-up curves	Initial AU limits loaded per booking class per flight	AU initialisation completed for 100% of flights ≥ 90 days prior to departure	N	N
2.3	Validate fare class mappings against ATPCO filings	Revenue Management Configuration Analyst	ATPCO	NRM booking class configuration, ATPCO fare tariff tables	Validated or flagged class mapping; exceptions escalated to Pricing team	Zero GDS availability mismatches attributable to class mapping errors post-activation	Y	Y
2.4	Activate nested inventory controls in Altéa	Revenue Management Analyst	Amadeus Altéa PSS	Validated AU levels from NRM	Live nested availability published to Altéa and GDS channels	Availability synchronisation latency Altéa → GDS ≤ 5 minutes	N	N
Phase 3 3.1	Run EMSRb / O&D seat allocation optimisation	Revenue Management System	Amadeus Revenue Management (NRM)	AU levels, demand forecast, fare values, seat capacity	Optimised AU recommendations per booking class per flight leg	Revenue per available seat kilometre (RASK) improvement ≥ 2% vs baseline AU	N	N
3.2	Review and approve AU recommendations	Senior Revenue Management Analyst	Amadeus Revenue Management (NRM)	NRM-generated AU recommendations, market performance dashboard	Approved or manually overridden AU file	Analyst review cycle ≤ 90 minutes per market cluster; override rate ≤ 20%	Y	Y
3.3	Apply approved AU updates to live inventory	Revenue Management Analyst	Amadeus Revenue Management (NRM)	Approved AU file	Updated live availability across all GDS and direct channels	AU update applied to 100% of affected flights within 30 minutes of approval	N	N
Phase 4 4.1	Monitor booking pace against forecast curve	Revenue Management Analyst	Tableau	Real-time booking data from Altéa, forecast pace curve	Pace deviation alert for flights outside ±10% of forecast	Analyst response to pace deviation alert ≤ 2 hours for departures within 14 days	Y	N
4.2	Apply sell-up action or open lower classes	Revenue Management Analyst	Amadeus Revenue Management (NRM)	Pace deviation alert, current AU levels, fare class sell-up elasticity data	Revised AUs triggering sell-up (close lower classes) or stimulation (open lower classes)	Yield improvement ≥ 1.5% per sell-up intervention vs control flights	N	N
4.3	Update bid prices for O&D revenue integrity	Revenue Management System	Amadeus Revenue Management (NRM)	Real-time load factors, revised demand signals, network connection values	Updated bid price vector published to Altéa for itinerary acceptance control	Bid price refresh cycle ≤ 4 hours for flights within 7 days of departure	Y	Y
4.4	Manage group booking displacement impact	Groups & Allotments Revenue Analyst	Amadeus Altéa PSS	Group booking request (≥10 pax), current individual seat availability	Group AU block allocated or declined; displacement cost calculated	Group displacement cost ≤ 8% of group revenue contribution on affected flights	Y	Y
Phase 5 5.1	Capture post-departure spill and spoilage actuals	Revenue Management Analyst	AWS Redshift	Flown manifest from Altéa, final booking class loads, denied boarding records	Spill / spoilage report by flight and booking class	Spill (denied boardings) ≤ 1.5% of passengers carried; spoilage (empty seats in high class) ≤ 3% of capacity	N	N
5.2	Evaluate forecast model performance and recalibrate	Senior Revenue Management Analyst	Amadeus SkyCAST	Spill / spoilage report, forecast vs actual load factor comparison	Updated SkyCAST model parameters; recalibration report	Model recalibration completed within 5 business days of departure; MAPE improvement ≥ 1 pp per calibration cycle	Y	N
5.3	Publish yield performance report to stakeholders	Revenue Management Manager	Tableau	RASK actuals, load factor, yield, spill/spoilage KPIs from Redshift	Weekly yield performance report distributed to VP Revenue Management and Network Planning	Report published within 2 business days of week close; RASK vs budget variance explained for all markets > ±3%	N	N

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Process Attributes

Identification

Process IDNP-RM-01

L1 DomainNetwork Planning & Scheduling

L2 ProcessRevenue Management

L3 NameInventory & Yield Optimization

L4 Steps18 across 5 phases

Decision Gates7 (all with iteration loops)

Exceptions5 documented

Swim Lanes (Roles)

Revenue Management Analyst

Senior Revenue Management Analyst

Revenue Management Configuration Analyst

Revenue Management System

Groups & Allotments Revenue Analyst

Revenue Management Manager

Systems & Tools

Amadeus Altéa PSSOAG Schedule AnalyserAmadeus SkyCASTAWS RedshiftAmadeus Revenue Management (NRM)ATPCOTableau

Key Performance Indicators

Ingest booking & flown data from PSSData completeness ≥ 99.5% of all PNRs reconciled within 2 hours of departure

Enrich data with competitive fare & schedule feedsCompetitive fare parity check completed for 100% of O&D pairs within planning horizon

Run O&D demand forecast modelForecast MAPE ≤ 15% at O&D level for departures within 30 days

Validate forecast accuracy against holdout setForecast MAPE ≤ 15%; rejection triggers reforecast within 4 hours

Define booking class hierarchy and nested buckets100% of ATPCO-filed fare classes mapped to NRM booking classes before schedule activation

Set authorization unit (AU) levels per fare classAU initialisation completed for 100% of flights ≥ 90 days prior to departure

Validate fare class mappings against ATPCO filingsZero GDS availability mismatches attributable to class mapping errors post-activation

Activate nested inventory controls in AltéaAvailability synchronisation latency Altéa → GDS ≤ 5 minutes

Airline-Specific Risks & Pain Points

Altéa PSS coupon reconciliation latency can delay same-day close files by up to 4 hours, compressing the overnight optimisation window

MIDT data lags actuals by 3–5 days, reducing confidence in competitor load factor estimates for near-term departures

SkyCAST demand models trained on pre-2020 data underweight volatile post-COVID travel patterns; requires periodic manual seasonality overrides

Redshift query contention during peak batch windows can delay accuracy checks, pushing AU updates past the 02:00 optimisation deadline

Misalignment between ATPCO fare basis codes and NRM class definitions causes availability mismatches in GDS displays, leading to revenue leakage

Manual AU overrides by market analysts outside NRM create version conflicts; no audit trail for override rationale increases regulatory audit risk

Inputs / Outputs

Primary InputDaily booking transactions, flown coupon data, no-show records

Primary OutputWeekly yield performance report distributed to VP Revenue Management and Network Planning

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