NP-RM-10 · Competitive Fare Monitoring & Response

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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 ATPCO competitor fare feed	Revenue Management Analyst	ATPCO	Scheduled ATPCO Fare Update (FU) and Fare Distribution (FD) transmissions	Structured fare change dataset by O&D, booking class, and carrier	Feed latency ≤30 min from ATPCO publication; 100% O&D coverage on monitored routes	N	N
1.2	Scrape OTA & metasearch displayed fares	Pricing Intelligence Analyst	OAG Schedule Analyser	Automated scrape schedule for key O&D markets; ATPCO baseline fare dataset	Displayed-price dataset including taxes, carrier surcharges, and ancillary bundling	Scrape coverage ≥95% of tier-1 competitive routes; data freshness ≤60 min	N	Y
1.3	Detect and flag material fare changes	Revenue Management System	PROS RM	Combined ATPCO and OTA fare datasets; pre-configured alert thresholds by market tier	Prioritised alert queue: fare changes ≥10% on tier-1 routes, ≥15% on tier-2	False-positive alert rate ≤5%; mean time to analyst notification ≤15 min from ingestion	Y	N
Phase 2 2.1	Analyse competitor O&D fare positioning	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Flagged fare alert; historical competitor fare trend data from data lake	Competitive positioning report: own fare vs. competitor by cabin, booking class, and departure window	Analysis turnaround ≤2 hr for tier-1 alerts; ≤8 hr for tier-2	N	N
2.2	Assess impact on O&D demand forecast	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Competitive positioning report; current NRM demand forecast and booking curve	Demand sensitivity estimate: projected booking-curve shift under current and revised fare scenarios	Forecast accuracy within ±5% MAPE post-response on monitored O&Ds	N	Y
2.3	Classify response urgency and route tier	Revenue Management Analyst	Tableau / Power BI	Demand impact estimate; route revenue contribution ranking; days-to-departure	Urgency classification: Immediate (≤4 hr), Same-day, Scheduled review	Immediate-class alerts actioned within 4 hr in ≥90% of cases	Y	N
Phase 3 3.1	Evaluate inventory availability and load factor	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Urgency classification; current fare bucket availability by flight and departure date	Inventory health snapshot: available seats by fare bucket, current load factor, revenue-per-available-seat-mile (RASM)	Load factor target ≥83% on relevant departure; RASM ≥ route budget	N	N
3.2	Model fare response scenarios in NRM	Revenue Management Analyst	PROS RM	Inventory health snapshot; competitor fare structure; elasticity parameters from historical data	3–5 response scenario outputs: match, undercut, hold, selective open/close by booking window	Scenario modelling completed within 1 hr of escalation; ≥3 scenarios produced per alert	N	Y
3.3	Review and approve response strategy	Senior Revenue Manager	Amadeus Revenue Management (NRM / AltéaRM)	Modelled response scenarios; route revenue budget; commercial policy guardrails	Approved response strategy with rationale, fare targets, booking-class assignments, and validity period	Approval cycle ≤2 hr for immediate-class alerts; sign-off documented in NRM audit trail	Y	N
Phase 4 4.1	File revised fares via ATPCO submissions	Pricing Analyst	ATPCO	Approved response strategy; current fare tariff record for affected O&Ds	ATPCO fare submission batch: new or amended fare basis codes, amounts, and effective dates	ATPCO filing completeness 100% for approved O&Ds; filing-to-effective lag ≤3 hr (next ATPCO update cycle)	N	N
4.2	Configure fare rules, restrictions, and RBDs	Pricing Analyst	ATPCO	Approved response strategy; existing rule categories (Cat 2, 3, 5, 14, 15, 35)	Updated fare rules: advance purchase, minimum stay, combinability, blackout dates, refund conditions	Zero ATPCO rule validation errors on submission; rules audit-compliant with IATA Resolution 024	N	Y
4.3	Verify fare distribution across GDS channels	Distribution Analyst	Sabre GDS	ATPCO effective fare update notification; test O&D city pairs	GDS distribution verification report: fare visible and correctly priced in Sabre, Travelport, and Amadeus GDS	Fare parity confirmed across ≥3 GDS within 60 min of ATPCO effective time; zero pricing discrepancies on spot-check O&Ds	Y	Y
4.4	Activate fares in PSS inventory and NDC	Distribution Analyst	Amadeus Altéa PSS	GDS verification sign-off; NDC API Gateway configuration	Live fare availability confirmed in Altéa inventory and NDC API offer response	NDC offer response includes new fare within 30 min of Altéa activation; booking class availability aligned with approved strategy	N	Y
Phase 5 5.1	Monitor booking velocity post-response	Revenue Management Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Live booking stream from Altéa PSS; pre-response booking curve baseline	Booking velocity dashboard: actual vs. forecast bookings by fare bucket, hourly cadence for 24 hr post-activation	Booking pace recovery to baseline curve within 24 hr on ≥80% of actioned O&Ds	N	N
5.2	Assess revenue impact against route budget	Senior Revenue Manager	AWS S3 / Redshift	48-hr post-response booking and revenue data from Redshift data lake; route budget targets	Revenue impact report: incremental revenue vs. estimated dilution cost; net yield delta	Net yield delta ≥0% vs. pre-response baseline within 48 hr; RASM maintained ≥ route budget	Y	N
5.3	Conduct post-action review and update playbook	Revenue Management Analyst	Tableau / Power BI	Revenue impact report; response timeline audit trail from ATPCO and NRM	Post-action review record: strategy effectiveness score, lessons learned, and updated competitive response playbook entry	Post-action review completed within 5 business days for tier-1 alerts; playbook updated within 10 business days	N	N

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Process Attributes

Identification

Process IDNP-RM-10

L1 DomainNetwork Planning & Scheduling

L2 ProcessRevenue Management

L3 NameCompetitive Fare Monitoring & Response

L4 Steps16 across 5 phases

Decision Gates5 (all with iteration loops)

Exceptions6 documented

Swim Lanes (Roles)

Revenue Management Analyst

Pricing Intelligence Analyst

Revenue Management System

Senior Revenue Manager

Pricing Analyst

Distribution Analyst

Systems & Tools

ATPCOOAG Schedule AnalyserPROS RMAmadeus Revenue Management (NRM / AltéaRM)Tableau / Power BISabre GDSAmadeus Altéa PSSAWS S3 / Redshift

Key Performance Indicators

Ingest ATPCO competitor fare feedFeed latency ≤30 min from ATPCO publication; 100% O&D coverage on monitored routes

Scrape OTA & metasearch displayed faresScrape coverage ≥95% of tier-1 competitive routes; data freshness ≤60 min

Detect and flag material fare changesFalse-positive alert rate ≤5%; mean time to analyst notification ≤15 min from ingestion

Analyse competitor O&D fare positioningAnalysis turnaround ≤2 hr for tier-1 alerts; ≤8 hr for tier-2

Assess impact on O&D demand forecastForecast accuracy within ±5% MAPE post-response on monitored O&Ds

Classify response urgency and route tierImmediate-class alerts actioned within 4 hr in ≥90% of cases

Evaluate inventory availability and load factorLoad factor target ≥83% on relevant departure; RASM ≥ route budget

Model fare response scenarios in NRMScenario modelling completed within 1 hr of escalation; ≥3 scenarios produced per alert

Airline-Specific Risks & Pain Points

ATPCO batch update cycles (typically 3× daily) create lag vs. real-time OTA price changes; competitor fares visible on GDS before ATPCO reflects them

NDC-sourced fares from competitors bypass ATPCO and are invisible to traditional monitoring tools; requires separate NDC channel scraping capability not standard in OAG

Threshold calibration is static; promotional fare launches by LCCs in thin markets trigger high false-positive volumes that overwhelm analyst queues

NRM lacks a native competitor fare visualisation layer; analysts context-switch between NRM and Tableau dashboards, increasing error risk and analysis time

NRM demand models have limited sensitivity to intraday competitor fare moves on ultra-short booking windows (<72 hr); last-minute price wars require manual forecast override

Revenue contribution rankings in Tableau are refreshed nightly; intraday revenue shifts on high-value routes are not reflected in urgency scoring during the same business day

Inputs / Outputs

Primary InputScheduled ATPCO Fare Update (FU) and Fare Distribution (FD) transmissions

Primary OutputPost-action review record: strategy effectiveness score, lessons learned, and updated competitive response playbook entry

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