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Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
Incorporating Gate Variability in Airline Block Planning
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Incorporating Gate Variability in Airline Block Planning

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Presentation at AGIFORS SSP May 21, 2013. Reviews variability of gate taxi-out time and how on-time performance improvements can be driven by incorporating taxi variability into block plans.

Presentation at AGIFORS SSP May 21, 2013. Reviews variability of gate taxi-out time and how on-time performance improvements can be driven by incorporating taxi variability into block plans.

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  • 1. AGIFORS SSP 2013Incorporating Gate Operationsinto Schedule PlanningJoshua Marks, CEO+1 703 994 0000 Mobile  josh@masflight.comW W W . M A S F L I G H T . C O M
  • 2. We used masFlight’sanalytics platformAll 2012 flight operations forU.S. mainline carriersGate Characteristicsin Schedule PlanningNew technology makes itpossible to incorporate gatevariability into schedulesBig data can highlight where:• Obstructions or distance drivesignificantly longer taxi-out times• Other gate factors drive variabilitythat impacts on-time performance
  • 3. Block planning is anart based on review of:Taxi-out time historyFlight time historyTaxi-in historyOne-time factorsBig data enables a morescientific approach with:Departure and arrival gatesCompetitive dynamicsIntra-seasonal weatherTail number differences0501001502002505152535455565758595105115125135145155165175185195205215225235CountofFlightsMinutes After Gate DepartureTaxi-Out, Runway Landingand Gate In DistributionDelta LGA-ATL 2012Gate OutLanding TimeGate InBlock Time Planning: From Art to ScienceMuch more is possible today than just taxi and air time analysisModalTaxi Out23 minModalGate Arrival2h 28m
  • 4. 050010001500200025003000350040005 15 25 35 45 55 65 75 85Taxi-Out Time In MinutesUnited Mainline Taxi-Out from SFO GatesCalendar Year 2012 – All Flights5 15 25 35 45 55 65 75Taxi-Out Time in MInutesUnited Taxi-Out from SFO (2012)Domestic (Blue) vs. Int’l (Red)DomesticInternationalMultiple Factors Affect Taxi-Out VariabilityBlocked rampTugs and tow barsGround personnelPush-back distanceDistance to runwayTaxiway factorsConstructionATC and pilot skillsTaxi speedConcurrent runwaysTraffic managementWeatherFlightsFlight Type Alone Doesn’t Reveal Underlying DriversParsing by flight or mission (domestic, international, fleet) doesn’t tell the full storyParsingoperations byflight typedoesn’t revealthe drivers
  • 5. Gate Variability in Taxi Out Time is SignificantUnited’s SFO Operation: 5 min difference in average taxi-out times by pierWest International(Odd gates 91-99)23.5 minutesEast International(Even gates 90-100)21.3 minutesWest Base Domestic(Gates 72-75)21.0 minutesEast Base Domestic(Gates 68-71)18.1 minutesOuter Domestic Pier(Gates 76-77 and 80, 82, 84, 88)18.6 minutesInner Domestic Pier(Gates 81, 83, 85, 87, 89)20.7 minutesData from 2012 All UA SFO Operations
  • 6. Gate Assignments Matter!UA 760 SFO-JFK 10:45am DepartureGate 80*19 minGate 8420 minGate 8122 minGate 8523 minAt hubs, gate choices drive 5 min differences in taxi-out.Gate choice can determine an on-time arrival for 10% of flights.Gate 8218 minGate 8323 min
  • 7. Now consider taxi-out averages at the gate levelUA 760 SFO-JFK 10:45am Departure (2012 departures)Airport teams think about operations…But from a passenger-centric perspective.joshrushing.comMany teams plan for consistency in gating,but operational demands shift assignments.Evidence supports that real improvementscan result from collaboratively integratinggate allocation into block forecasts.
  • 8. 54%48%36%31%21%LAXMIAORDDFWJFKAmerican Hubs43%42%34%33%22%LGADTWATLMSPSLCDelta Hubs62%45%35%33%27%24%12%SFOO…IAHIADE…LAXDENUnited Hubs23%13%9%9%BOSJFKLGBFLLJetBlue Focus CitiesSignificant Variance in Taxi Time by GateCreates an Opportunity to Improve OTPWe reviewed the difference in average taxi-out time at keyhubs, measuring the spread between the fastest and slowest gates.46%31%22%21%21%20%17%BWILAXM…DALPHLLASPHXSouthwest Focus CitiesNarrow ramps, tight piers andintersections are key drivers ofgate-level taxi out variability.Less significant variabilityobserved forAlaska, Frontier, and VirginAmerica hubs
  • 9. Variability + Delays = OpportunityBecause behavioral change is needed, focus on hubswhere gate adjustments can drive maximum OTP gains.AA-DFWAA-JFKAA-LAXAA-ORDAA-MIAAS-PDXAS-SEAB6-BOSB6-FLLB6-JFKB6-LGBDL-ATL DL-DTWDL-LGADL-MSPDL-SLCUA-DENUA-EWRUA-IADUA-IAHUA-LAXUA-ORDUA-SFOUS-CLTUS-DCAUS-PHLUS-PHXWN-BWIWN-DALWN-LAXWN-LASWN-MDWWN-PHLWN-PHXFL-ATLF9-DENNK-FLLVX-LAXVX-SFO5.0%7.0%9.0%11.0%13.0%15.0%0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%CRITICALFLIGHTS(SAT+10TO+20)TAXI OUT VARIABILITY AMONG DEPARTURE GATES (Average taxi-out difference, fastest vs. slowest gates)2012 Comparison: Variability of Departure Taxi-Out Time Among Gatesvs. Percent of Critical Flights (Arrival 10-20 mins after scheduled time)Box 3:Block-gate coordination matters:High impact + High variabilityBox 1:Gates don’t matter(much)Box 2:General SchedulingIssues
  • 10. Possible solutions:Taxi faster from the problem gates.Incentives, fuel and maintenance, etc.Allocate flights to gates during planning.Reduce airport discretion in managing flows.Both are viable – but both requirecross-functional coordination in the airline
  • 11. Food for Thought #1: Taxi Faster!Coordinating with flight operations to increase taxi-outspeed when departing specific gates.Southwest does it!-23%-12%-7%-7%-4%-2%-1%4%19%31%-40% -30% -20% -10% 0% 10% 20% 30% 40%DeltaUS AirwaysAlaskaUnitedSpiritAmericanJetBlueFrontierVirgin AmericaSouthwestRelative Taxi Speed (Narrowbodies Only)at U.S. Stations (2012)Versus other airlines at each airportWN averages31% fasterat each airportthey serveWhile Delta lagssignificantlybehindYou can change flightand ground behavior• AirTran pilots adoptingSouthwest practices?• Delta’s taxi-out improvementinitiatives are focused on this• Surgical approachBWI-FLL 2009 2010 2011 2012AverageTaxi-Out13.5 min 13.4 min 13.0 min 12.4 min
  • 12. Food for Thought #2: Gate Arbitrage?If you are willing to restrict flights to groups of gates...Then can you shift block time from fast to slow gates?The ConceptDivide airport gates into three buckets based ontaxi-out times and variabilityFastest third: Reduce block times for departuresMiddle third: No change for departuresSlowest third: Increase block timesObjective is to keep overall block times neutraland benefit from “fitting the curve” of taxi-out times
  • 13. Food for Thought #2: Gate Arbitrage?Method: Restrict flight assignments to specific color boxes –and adjust block times for each color set accordingly.Gate 41IncreaseGate 43IncreaseGate 45No ChangeGate 47ANo ChangeGate 47BNo ChangeGate 49ANo ChangeGate 48ASubtractGate 46ANo ChangeGate 42BNo ChangeGate 42AIncreaseGate 40IncreaseGate 48BSubtractGate 44SubtractAA LAX T-4
  • 14. Food for Thought #2: Gate Arbitrage?If you are willing to restrict flights to groups of gates...Then can you shift block time from fast to slow gates?What we found from applying this methodLos Angeles(American)Denver(Frontier)San Francisco(United)29,000 flights in sample setLow variance of taxitimes across gatesShifting 1 minute from best gatesto worst drove marginal (< 0.1%)change in on-time arrivalsNo material benefits.Without variability,no impact.23,100 flights in sample setModerate variance oftaxi-out across gatesShifting 5 minutes from best gatesto worst drove small shift (0.5%)in on-time arrivalsSmall but tangible gain,but may not beworth the effort.36,500 flights in sample setHigh variance of taxitimes across gatesSame 0.5% gain from neutralblock, but surgical block addscan drive 1% gain in OTPAdding block bygate set drives amaterial gain.
  • 15. Food for Thought #2: Gate Arbitrage?If you are willing to restrict flights to groups of gates...Then can you shift block time from fast to slow gates?ConclusionsIf you have high variability of taxi-out timesacross gates at a hub, particularly within the same pierAnd if the number of flights where assigning gates willmake a material difference in on-time performanceThen assigning flights to specific gate sets andadjusting blocks can potentially drive OTP gains
  • 16. Communication is KeyHow do you persuade…Airport teams to change gate assignment priorities?Flight operations to focus on taxi speed and routes?Management to embrace how big data visibility canaddress small issues that add up to big OTP changes?It takes focus to coordinate and prioritizeat the cross-department level required.
  • 17. ConclusionsBig Data focusesgate performanceMultiyear analysis canfocus attention onspecific gate problemsDefine controllablefactors & partiesGate issues can beaddressed but requirecross-functional inputGate taxi variabilityis material in OTPFive-minute averagedifferences in taxi timein the same pierLow-hanging fruitat key hubsMany critical flights +high gate variability =OTP opportunityIncreasing taxi-outspeed is one way…Encourage groundand pilot actions tospeed push & taxi… block adjustmentby gate is anotherFolding taxi-out timeinto gate allocationdrives improvementsSchedule planning should visualize the potentialand seek buy-in across flight and airport operations

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