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Process Flow Diagram (BPMN)

NP-PF-13 BPMN diagram
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L4 Process Steps

StepStep NameRole / Swim LaneSystem InputOutputKPIDec?Exc?
Phase 1
1.1
Ingest Competitor Fare Data Feeds Pricing Analyst OAG Schedule Analyser Scheduled OAG fare feed subscription; ATPCO tariff updates Raw competitor fare matrix by O&D and cabin class Feed freshness ≤4 hours from ATPCO filing event N N
1.2 Pull GDS Availability & Lowest Bookable Fare Pricing Analyst Sabre GDS O&D list flagged for monitoring; date range parameters Live availability snapshot with lowest bookable fare per carrier GDS poll coverage ≥95% of monitored O&Ds per cycle N Y
1.3 Validate and Cleanse Incoming Fare Data Data Engineering Analyst AWS Redshift Raw OAG and GDS fare extracts Validated fare dataset with duplicate, null, and currency-normalised records Data quality score ≥98% (nulls + duplicates < 2% of records) N N
1.4 Gate: Assess Data Quality Threshold Pricing Analyst AWS Redshift Data quality score from validation step Pass / Fail decision; failed batches re-queued for re-ingestion Re-ingestion rate <5% of daily batches Y Y
Phase 2
2.1
Map Competitor Fare Families to Own Fare Basis Senior Pricing Analyst PROS RM Validated competitor fare matrix; own fare basis code library Normalised competitor-to-own fare family crosswalk table Crosswalk coverage ≥90% of active competitor fare codes N N
2.2 Calculate Competitive Price Index by O&D Senior Pricing Analyst PROS RM Normalised fare crosswalk; own published fares from Amadeus Altéa PSS Price index report: own fare as % of competitor median and lowest Price index within ±5% of strategic target band for ≥80% of monitored O&Ds N N
2.3 Identify O&Ds with Material Competitive Fare Gap Senior Pricing Analyst PROS RM Price index report; gap threshold parameters (e.g. >10% above market) Shortlist of O&Ds requiring pricing review, ranked by revenue exposure Shortlist generated within 2 hours of data ingestion cycle completion Y N
Phase 3
3.1
Segment Demand Elasticity by O&D and Cabin Revenue Management Analyst Amadeus SkyCAST O&D shortlist; historical booking curves; own and competitor load factors Elasticity coefficient per O&D segment; price-sensitivity classification (elastic/inelastic) Elasticity model R² ≥0.80 for top-50 revenue O&Ds N N
3.2 Model Revenue Impact of Fare Repositioning Revenue Management Analyst Amadeus Revenue Management (NRM) Elasticity coefficients; proposed fare adjustment scenarios; current inventory by booking class Revenue impact model: expected incremental revenue, load factor shift, and yield impact per scenario Model run time ≤30 minutes per O&D scenario batch N N
3.3 Gate: Revenue Uplift Exceeds Approval Threshold Pricing Manager Amadeus Revenue Management (NRM) Revenue impact model output; threshold: net yield improvement ≥1.5% or incremental revenue ≥$50K/quarter per O&D Approved repricing candidates list; sub-threshold O&Ds shelved or monitored Repricing candidates with confirmed positive revenue case ≥85% of submissions Y N
3.4 Build Fare Repositioning Recommendation Package Senior Pricing Analyst Tableau Approved repricing candidates; revenue impact model; elasticity data Recommendation deck: proposed fare levels, filing strategy, effective dates, and risk summary Recommendation package completed within 1 business day of gate approval N N
Phase 4
4.1
Route Recommendation to Pricing Committee Pricing Manager Tableau Recommendation package; pricing committee calendar; approval authority matrix Committee review session scheduled; recommendation circulated for pre-read Committee review turnaround ≤2 business days from submission N N
4.2 Gate: Pricing Committee Approval Decision Director of Pricing Tableau Recommendation package; competitive context brief Approved fare levels and filing parameters; rejected recommendations returned for rework First-pass approval rate ≥70% of submitted recommendations Y Y
4.3 File Approved Fare Changes via ATPCO Fares Filing Analyst ATPCO Approved fare levels; filing parameters (fare basis, rules, Cat-25 conditions, effective date) ATPCO filing confirmation; fare effective date set (typically T+1 or T+7 per ATPCO filing cycle) Filing accuracy rate ≥99.5%; zero Cat-15/Cat-25 rule errors N Y
4.4 Load and Validate Fares in Altéa PSS Fares Filing Analyst Amadeus Altéa PSS ATPCO-filed fare data; Altéa fare loader configuration Fares active in PSS; booking-flow validation completed across all selling channels Fare loading SLA ≤2 hours post-ATPCO effective date; booking-flow validation pass rate 100% N Y
Phase 5
5.1
Monitor Post-Change Booked-Fare Mix Revenue Management Analyst Amadeus Revenue Management (NRM) Newly-loaded fares; booking velocity by class; competitor availability signals Post-change performance dashboard: booked yield vs. target, load factor by class, competitor sell-down rate Monitoring dashboard refreshed every 4 hours; booked yield vs. target tracked from day 1 post-filing N N
5.2 Gate: Evaluate Competitive Position Restoration Pricing Manager PROS RM Post-change price index; booked yield trend; competitor response actions detected Position restored: cycle closed. Position not restored: O&D re-entered into repricing queue Target: competitive price index within ±5% of strategic band within 14 days of fare change effective date Y N
5.3 Publish Intelligence Report and Close Cycle Senior Pricing Analyst Tableau Full cycle data: gap detected, recommendation, approval, filing, post-change outcome Competitive fare intelligence cycle report; lessons-learned log; updated monitoring watch-list Cycle report published within 5 business days of position-restored confirmation N N
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Process Attributes

Identification

Process IDNP-PF-13
L1 DomainNetwork Planning & Scheduling
L2 ProcessPricing & Fare Management
L3 NameCompetitive Fare Intelligence
L4 Steps18 across 5 phases
Decision Gates5 (all with iteration loops)
Exceptions5 documented

Swim Lanes (Roles)

Pricing Analyst
Data Engineering Analyst
Senior Pricing Analyst
Revenue Management Analyst
Pricing Manager
Director of Pricing
Fares Filing Analyst

Systems & Tools

OAG Schedule AnalyserSabre GDSAWS RedshiftPROS RMAmadeus SkyCASTAmadeus Revenue Management (NRM)TableauATPCOAmadeus Altéa PSS

Key Performance Indicators

Ingest Competitor Fare Data FeedsFeed freshness ≤4 hours from ATPCO filing event
Pull GDS Availability & Lowest Bookable FareGDS poll coverage ≥95% of monitored O&Ds per cycle
Validate and Cleanse Incoming Fare DataData quality score ≥98% (nulls + duplicates < 2% of records)
Gate: Assess Data Quality ThresholdRe-ingestion rate <5% of daily batches
Map Competitor Fare Families to Own Fare BasisCrosswalk coverage ≥90% of active competitor fare codes
Calculate Competitive Price Index by O&DPrice index within ±5% of strategic target band for ≥80% of monitored O&Ds
Identify O&Ds with Material Competitive Fare GapShortlist generated within 2 hours of data ingestion cycle completion
Segment Demand Elasticity by O&D and CabinElasticity model R² ≥0.80 for top-50 revenue O&Ds

Airline-Specific Risks & Pain Points

OAG data reflects filed fares, not real-time availability — lowest bookable fare may differ; requires GDS cross-check
GDS screen-scraping agreements restrict query frequency; high-volume polling risks Sabre rate-limit suspension
Multi-currency fare records require real-time FX normalisation; stale FX rates distort price-index calculations
Repeated feed failures during ATPCO filing windows (Mon/Fri peaks) delay competitive response by 24-48 hours
Unbundled competitor fares (ancillary-stripped) inflate apparent price gap; true total-price comparison requires ancillary fee modelling
PROS RM price-index module requires manual refresh when own fares are updated mid-cycle; automated trigger not yet configured

Inputs / Outputs

Primary InputScheduled OAG fare feed subscription; ATPCO tariff updates
Primary OutputCompetitive fare intelligence cycle report; lessons-learned log; updated monitoring watch-list
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