Sales Performance Reporting & Analytics
Network Planning & Scheduling › Sales & Distribution · 17 L4 steps · 5 phases · 5 decision gates · Updated 2026-03-18 21:43
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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 sales transactions from PSS and GDS feeds | Sales Data Engineer | Amadeus Altéa PSS | Daily booking, ticketing, and revenue transactions from Altéa | Raw sales transaction file (PNR, fare basis, channel, O&D) | Data extraction completeness ≥99.5% of daily transactions | N | N |
| 1.2 | Ingest GDS booking and yield data via settlement files | Sales Data Engineer | Sabre GDS | Sabre PRISM BSP settlement files and Travelport agency booking reports | Consolidated GDS channel dataset with agency, fare, and yield fields | GDS data ingestion within 4 hours of BSP file receipt | N | Y |
| 1.3 | Validate data quality and apply cleansing rules | Sales Data Analyst | AWS Glue | Raw PSS and GDS transaction datasets | Quality-scored dataset; rejected records quarantine file | Data quality score ≥98% (nulls, duplicates, invalid fare codes <2%) | Y | Y |
| 1.4 | Load cleansed data to analytics data warehouse | Sales Data Engineer | AWS Redshift | Validated and cleansed sales transaction dataset | Populated sales_fact and channel_dim tables in Redshift | Load completion within 2 hours of data quality sign-off; zero load failures | N | Y |
Phase 2 2.1 |
Configure KPI targets and alert thresholds in BI platform | Sales Analytics Manager | Tableau | Annual commercial plan targets (revenue, load factor, yield by route/channel) | Configured KPI thresholds and RAG alert rules in Tableau | 100% of approved KPI targets loaded before reporting cycle open | N | N |
| 2.2 | Build channel and revenue performance dashboards | Sales Analytics Manager | Tableau | Redshift sales_fact tables; KPI threshold configuration | Channel performance dashboard (GDS, NDC, direct, corporate) and revenue dashboard | Dashboard refresh latency ≤15 minutes from data load completion | N | N |
| 2.3 | Validate dashboard figures against source system totals | Sales Data Analyst | SAP S/4HANA Finance (FI/CO) | Tableau dashboard revenue totals; SAP AR revenue recognition ledger | Reconciliation sign-off report; variance log if delta >0.5% | Dashboard-to-SAP revenue variance ≤0.5% before stakeholder distribution | Y | Y |
Phase 3 3.1 |
Analyse GDS channel yield and cost-per-booking | Distribution Analytics Analyst | Sabre GDS | GDS segment dataset; published GDS booking fee schedule | Cost-per-booking report by GDS (Sabre / Travelport / Amadeus) and market | GDS net yield ≥$0.08/RPM after distribution cost deduction | N | N |
| 3.2 | Assess NDC and direct channel conversion rates | Distribution Analytics Analyst | NDC API Gateway | NDC API search-to-book funnel data; direct website booking data | NDC/direct conversion funnel report with drop-off analysis | NDC channel conversion rate ≥2.8%; direct web conversion ≥4.5% | N | N |
| 3.3 | Review corporate and TMC account performance vs contract | Corporate Sales Manager | Sabre GDS | Sabre PRISM corporate account booking volumes; contracted revenue commitments | Corporate account scorecard; list of accounts below commitment threshold | ≥90% of corporate accounts at or above 80% of contracted volume target | Y | Y |
Phase 4 4.1 |
Analyse fare class mix and RASK by route and market | Revenue Analytics Analyst | Amadeus Revenue Management (NRM) | Closed booking data by fare basis and O&D from Altéa NRM | Fare mix report: premium vs discount share, RASK by route | Average RASK ≥$0.145; premium fare class share ≥22% of total revenue | N | N |
| 4.2 | Monitor load factor and yield trends vs prior year | Revenue Analytics Analyst | AWS Redshift | Current period and prior year sales_fact data from Redshift | Load factor and yield trend report; YoY variance by route, season, and channel | Load factor ≥83%; yield variance to prior year within ±5% | N | N |
| 4.3 | Identify routes and segments below revenue performance target | Network Revenue Manager | Tableau | RASK and load factor report; network revenue target thresholds from commercial plan | Underperformance flag list: routes with RASK <target for ≥2 consecutive periods | Zero routes with RASK <80% of target unaddressed beyond two consecutive reporting cycles | Y | Y |
Phase 5 5.1 |
Produce budget variance and forecast deviation analysis | Sales Finance Analyst | SAP S/4HANA Finance (FI/CO) | Actuals from SAP AR; approved budget and rolling forecast from SAP CO | Variance analysis pack: actual vs budget vs forecast by revenue line | Variance commentary complete for all lines deviating >±3% from budget | N | N |
| 5.2 | Compile executive management reporting pack | Sales Analytics Manager | Power BI | Channel performance, fare mix, RASK, load factor, and variance reports | Monthly sales performance deck with KPI scorecards and narrative commentary | Management pack distributed by business day 5 of the following month | N | N |
| 5.3 | Assess exceptions and determine escalation requirement | VP Sales & Distribution | Power BI | Management reporting pack; KPI RAG status from Tableau | Escalation decision: confirmed exception list for board or commercial committee | 100% of Red-rated KPIs reviewed within 24 hours of report distribution | Y | N |
| 5.4 | Distribute reports and archive reporting cycle artefacts | Sales Data Analyst | AWS S3 | Final approved management pack and all source reports | Reports distributed to stakeholders; artefacts archived in S3 with version tag | 100% of reports archived within 1 business day; distribution list accuracy ≥99% | N | Y |
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