NP-PF-04 · Fare Rules & Restriction 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	Initiate fare rule design from revenue strategy	Senior Pricing Analyst	Amadeus SkyWORKS	Revenue strategy directives, competitive fare analysis from OAG Schedule Analyser	Fare rule design brief with scope, markets, and effective dates	Rule design brief turnaround ≤3 business days from strategy directive	N	N
1.2	Define advance purchase and ticketing time limits	Pricing Analyst	ATPCO Online (Publisher)	Fare rule design brief, competitor AP restriction benchmarks from OAG	Draft ATPCO Category 5 (Advance Purchase) and Category 7 (Ticketing) rule parameters	AP/TTL restriction accuracy ≥99.5% match to approved design brief	N	N
1.3	Set minimum stay, blackout dates, and seasonality	Pricing Analyst	ATPCO Online (Publisher)	Revenue management seasonality directives, Amadeus Revenue Management (NRM) demand curves	Draft ATPCO Category 6 (Minimum Stay), Category 2 (Day/Time), and blackout date rule set	Seasonal restriction accuracy ≥99%; blackout date coverage = 100% of designated periods	N	N
1.4	Define change, cancellation, and refund rules	Senior Pricing Analyst	ATPCO Online (Publisher)	Commercial policy directives, DOT 14 CFR Part 259 refund regulation requirements	Draft ATPCO Category 16 (Penalties), Category 31 (Voluntary Changes), and Category 33 (Voluntary Refunds) parameters	DOT 24-hour hold/refund rule compliance = 100%; change fee accuracy ≥99.8%	N	Y
Phase 2 2.1	Code fare rules in ATPCO category format	ATPCO Rule Specialist	ATPCO Online (Publisher)	Approved fare rule design brief with all restriction parameters	Coded ATPCO fare rule record covering applicable Categories 2–35	First-pass coding accuracy ≥97%; coding cycle time ≤4 hours per rule set	N	N
2.2	Validate rule combinability and fare construction logic	ATPCO Rule Specialist	ATPCO Online (Validator) / Amadeus Altéa PSS (test environment)	Coded ATPCO rule record	Combinability validation report; list of rule conflicts requiring recode	Zero Category 10 combinability errors at filing; validation first-pass rate ≥95%	Y	Y
2.3	Simulate fare rule impact across booking scenarios	Revenue Analyst	Amadeus Altéa PSS (test environment) / PROS RM	Validated ATPCO rule record, sample booking scenarios across all active fare classes	Rule impact simulation report; revenue effect estimate by market	Simulation coverage ≥90% of active fare class/market combinations; revenue deviation from target ≤2%	Y	N
2.4	Obtain commercial sign-off on rule parameters	Head of Pricing	ServiceNow (approval workflow)	Rule impact simulation report and validated ATPCO rule record	Approved rule set with digital sign-off record and effective date authorisation	Approval turnaround ≤1 business day; escalation rate <5% of submissions	Y	N
Phase 3 3.1	Submit fare rules to ATPCO for publication	ATPCO Rule Specialist	ATPCO Online (Publisher)	Commercially approved and validated fare rule record with effective date	ATPCO submission confirmation with effective date/time stamp	On-time filing rate ≥98%; filing lead time ≥4 hours before effective time (ATPCO minimum)	N	Y
3.2	Monitor GDS fare rule uptake and display accuracy	Pricing Analyst	Sabre GDS / Travelport GDS / Amadeus GDS	ATPCO publication confirmation; effective date and time	GDS display verification report across all three distribution channels	GDS rule display accuracy ≥99.5% within 2 hours of ATPCO effective time	Y	Y
3.3	Validate NDC channel fare rule presentation	Digital Distribution Analyst	NDC API Gateway / Airline direct booking engine	Filed ATPCO rule record, NDC offer/order API response	NDC rule compliance report; GDS/NDC parity assessment	NDC rule display accuracy ≥99%; NDC-to-GDS rule parity ≥99.5%	Y	Y
Phase 4 4.1	Monitor fare rule adherence in issued tickets	Revenue Integrity Analyst	Amadeus Altéa PSS / Revenue Integrity module	Issued ticket records from BSP/ARC settlement data	Rule violation exception report with ticket-level detail	Fare rule violation rate <0.5% of issued tickets; ADM (Agency Debit Memo) rate <0.1% of BSP transactions	Y	Y
4.2	Audit ATPCO rule records against published policy	Pricing Compliance Analyst	ATPCO Online (retrieval) / internal pricing policy database	Filed ATPCO rule records, current commercial policy documentation	Compliance audit report; prioritised list of rule-to-policy discrepancies	Rule accuracy vs. policy ≥99.8%; monthly audit cycle; critical discrepancy resolution ≤2 business days	Y	N
Phase 5 5.1	Receive and triage waiver and override requests	Revenue Integrity Analyst	Amadeus Altéa PSS (OSI/SSR entries) / CRM	Customer or agency waiver request; IROPS or operational disruption notification	Triaged waiver request with approval recommendation	Waiver triage time ≤4 hours; auto-approval rate for standard waivers ≥70%	Y	Y
5.2	Apply approved rule override and document exception	Revenue Integrity Analyst	Amadeus Altéa PSS / ServiceNow	Approved waiver decision record	Rule override applied to PNR; exception record created in ServiceNow	Override processing time ≤2 hours for approved waivers; 100% of exceptions documented in ServiceNow within 24 hours	N	Y
5.3	Analyse exception patterns and update rule parameters	Senior Pricing Analyst	Tableau / AWS Redshift	Exception records, waiver volume reports from ServiceNow, ADM data from BSP	Rule optimisation recommendation; updated rule design brief if exception threshold exceeded	Exception pattern review cycle = quarterly; rule update trigger = >2% waiver rate on any single rule	Y	N

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Process Attributes

Identification

Process IDNP-PF-04

L1 DomainNetwork Planning & Scheduling

L2 ProcessPricing & Fare Management

L3 NameFare Rules & Restriction Management

L4 Steps16 across 5 phases

Decision Gates9 (all with iteration loops)

Exceptions8 documented

Swim Lanes (Roles)

Senior Pricing Analyst

Pricing Analyst

ATPCO Rule Specialist

Revenue Analyst

Head of Pricing

Digital Distribution Analyst

Revenue Integrity Analyst

Pricing Compliance Analyst

Systems & Tools

Amadeus SkyWORKSATPCO Online (Publisher)ATPCO Online (Validator) / Amadeus Altéa PSS (test environment)Amadeus Altéa PSS (test environment) / PROS RMServiceNow (approval workflow)Sabre GDS / Travelport GDS / Amadeus GDSNDC API Gateway / Airline direct booking engineAmadeus Altéa PSS / Revenue Integrity moduleATPCO Online (retrieval) / internal pricing policy databaseAmadeus Altéa PSS (OSI/SSR entries) / CRMAmadeus Altéa PSS / ServiceNowTableau / AWS Redshift

Key Performance Indicators

Initiate fare rule design from revenue strategyRule design brief turnaround ≤3 business days from strategy directive

Define advance purchase and ticketing time limitsAP/TTL restriction accuracy ≥99.5% match to approved design brief

Set minimum stay, blackout dates, and seasonalitySeasonal restriction accuracy ≥99%; blackout date coverage = 100% of designated periods

Define change, cancellation, and refund rulesDOT 24-hour hold/refund rule compliance = 100%; change fee accuracy ≥99.8%

Code fare rules in ATPCO category formatFirst-pass coding accuracy ≥97%; coding cycle time ≤4 hours per rule set

Validate rule combinability and fare construction logicZero Category 10 combinability errors at filing; validation first-pass rate ≥95%

Simulate fare rule impact across booking scenariosSimulation coverage ≥90% of active fare class/market combinations; revenue deviation from target ≤2%

Obtain commercial sign-off on rule parametersApproval turnaround ≤1 business day; escalation rate <5% of submissions

Airline-Specific Risks & Pain Points

Pricing strategy changes arrive without lead time, forcing reactive rule authoring that increases first-pass error rates above 5%

ATPCO Category 5 and Category 7 interactions are not validated automatically; misconfiguration creates phantom availability windows or incorrect fare displays across all three GDS channels

Aligning ATPCO Category 6 with Amadeus NRM inventory controls requires manual coordination — no automated sync exists between the RM system and ATPCO rule records

DOT 14 CFR Part 259 requires 24-hour hold or refund capability; ATPCO rule coding must precisely match website policy or exposes the airline to DOT enforcement action and reputational risk

ATPCO's 35-category structure requires deep specialist knowledge; errors in Category 10 (Combinability) cause fare construction failures in GDS that are difficult to isolate and trace post-publication

Interline combinability checks are not fully automated — manual cross-referencing against partner airline Category 10 entries is required; gaps cause booking failures on connecting itineraries and trigger agency debit memos

Inputs / Outputs

Primary InputRevenue strategy directives, competitive fare analysis from OAG Schedule Analyser

Primary OutputRule optimisation recommendation; updated rule design brief if exception threshold exceeded

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