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IT integration in airline business process

IT integration in airline business process. ITAB 2007 Grach Muradyan. General principle. Information Technologies allow airline To be aware of… To understand… To describe… In order to control !!! …but only in case IT is properly integrated in airline business process….

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IT integration in airline business process

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  1. IT integrationin airline business process ITAB 2007 Grach Muradyan

  2. General principle Information Technologies allow airline • To be aware of… • To understand… • To describe… • In order to control !!! …but only in case IT is properly integrated in airline business process…

  3. General principle • Airline industry operates in a dynamic environment • Variety of external and internal factors: • Changes in demand • Competitors actions • Fuel cost, etc… • Impossible to predict all the variations • IT complex should provide airline • Maximum info for planning • Maximum info for ongoing situation / status • Maximum flexibility and best tools to react on the ongoing situation • Minimum time for decision delivery to the market

  4. General principle IT complex should be organized as a system with feedback (“autopilot scheme”) Competitors Objectives & planning Implementation Optimization Control Regulation MARKET Other factors Data collection Data analysis Airline commercial department

  5. Airline IT modules • Objectives and Planning • Revenues and costs planning • Network planning • Schedule generation & optimization (max fleet & crew utilization with given restrictions) • Optimization: Revenue Management • Prognosis, based on the historical data • Availability and overbooking level recommendations • Reporting

  6. Airline IT modules • Implementation • Schedule publication • Connections (ongoing) optimization • Operation and disruptions management • Inventory control • Nesting • Availability • Fares • Levels per class • Rules / limitations • Taxes

  7. Airline IT modules • Control • Revenue Integrity: increasing load factor and efficiency of RM utilization • Time limits • Fake names (“test”, etc..) • Unreal bookings • Unproductive bookings • Distribution (in GDSs) • Married Segment Control • Long Haul availability • Dynamic Availability • Journey Data

  8. Airline IT modules • Data collection (major airline data streams) • Billing Information (BIDT / ABI): bookings on own airline • Marketing information (MIDT): bookings on own + other airlines • Global • Regional • Express • Custom, etc… • Ticketing Data (ATD) • IATA Reporting / Hand Off Tape format files • ET Flight Coupons (LIFT files)

  9. Airline IT modules • Major Data analysis tasks • Commercial analysis • Demand for the airline services • Bookings / cancellations distribution (per markets, flights, cabin / classes, departure dates, etc…) • TAs making passive, test, fake and other unproductive bookings • Revenue / ticketing info • Cashflow / stock control • Interlining • Source for Revenue Accounting systems • Technological analysis • Sales effectiveness (e.g. TK, UN,… levels) • Billing / accounting purposes • Understanding billing of IT service providers • Supporting airline claims

  10. Data analysis examples distribution per month of departure Market and seasonality dependence (RU / Jan)

  11. Data analysis examplesdistribution per month of departure Market and seasonality dependence (DE / Jan)

  12. Data analysis examples distribution per month of departure Market and seasonality dependence (DE / May)

  13. Data analysisapproachFrom global to local • Being aware something is going not the way it was expected (e.g. irregularity)… • Understanding what exactly is happening ? (e.g. bookings jumping in low season) • Finding who exactly and why is doing this ? (POS: country->TA office ID) • Deciding how to resolve the issue ? (technological and commercial actions) • Analyzing how to prevent this happening again ? (e.g. changing airline policy)

  14. Data analysis exampleRegularity in long-term observation( peaks in Jan and Sep net bookings )

  15. Data analysis exampleTA activity split by country & office

  16. Data analysis exampleTA activity split by office

  17. Data analysis example Distribution per month of departure: Jan bookings made by one TA office (“seats freezing”)

  18. Data analysis example Passive bookings made by an office within just one day…

  19. Last but not least… Need for IT policy coordination on top management level • Internal competition (trend) between departments within airline: IT being a TOOL for commerce • Commerce dictates what • IT decides how (the best) • IT proposes new tools / approaches • Permanent control on IT activity: info processing • Regularity • Frequency • Completeness

  20. Thank you !

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