1. August 22, 2012Trends in U.S. AirlineOn-Time PerformanceAGIFORS Operations 2012 PresentationJoshua MarksExecutive Director, AAIEdmund OtubuahDirector of Aviation Products, masFlightRyan Leick, Ph.D.Associate Professor, Utah Valley University4833 RUGBY AVENUE SUITE 301 BETHESDA MD 20814

2. Study Overview 2012: outstanding operations performance Why is this happening? We test possible causes Weather conditions System capacity and demand Carrier airport and ops changes Strategic schedule padding vs. trimming Are the improvements sustainable?AGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 2 3. Data Analysis & MethodologyOur study dataset combines DOT, FAA andmasFlight data for exploratory analysisOur study covered the period from January 2009 through May 2012 andincorporated 37 million flight records, hourly weather and FAA OPSNET data. Data SetContentsRecords Analyzed Detailed information about flights Flight Records31.8 million (2009-2012) ASQP + FLIFO + masFlight Direct Feeds Airport CapacityQuarter-Hourly Airport Operational Detail 9.4 million (2009-2012) Flight SchedulesOAG airline schedules 42 months (2009-2012) Weather Reports Hourly METAR and precipitation data 49 airports (2009-2012)AGIFORS 2012 TECHNICAL PRESENTATION SLIDE 3 4. Observed Improvements in On-Time Performance SECTION 24A M I FR I R S N 0 1V I A T IC H N I N S T I T U T E E N T 0 1 1 O N L R I G H T S R E S E R V E DGE OCA 2 A 2 TE ON CAL PRES 2ATI ALSLIDE 4 5. 2012 is clearly an anomaly why?Operational performance as measured by DOTwas significantly better than recent history.DOT ASQP for 1Q 2012: 85.5% on-time mainline vs. 77-80% Q1 2009-2011 80.7% on-time regionals vs. 74-77% Q1 2009-2011 Cancellations 1.2% vs. 1.9%-3.2% Q1 2009-2011 Taxi-out times over 2 hours down 71% YOY Taxi-in times over 1 hour down 31% YOY Decrease of 4.7% in flights (reported pool change) Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 5 6. Its not the industry gaming DOTAll carriers showed improvements in non-reported flight operationsReported operations and non-reported operations each rose 3.4 pp Airline Reported Flight Operations Non-Reported Flight OperationsOTD% % RepQ1 2009 Q1 2012Change Q1 2009Q1 2012 Change WN 100.0%82.8% 84.6% +1.8 ppDL/NW61.3%84.5% 88.7% +4.2 pp 83.0% 87.0%+4.0 ppUA/CO41.5%81.2% 81.0% -0.2 pp 76.8% 78.1%+1.3 pp AA79.6%79.5% 84.7% +5.2 pp 79.3% 83.7%+4.4 pp US45.3%86.1% 90.0% +3.9 pp 78.6% 81.7%+3.1 pp B687.4%81.3% 83.0% +1.7 pp 82.6% 83.1%+0.5 pp AS51.3%79.2% 87.3% +8.1 pp 81.3% 86.8%+5.5 pp HA95.3%94.6% 94.3% -0.3 pp 59.3% 84.5% +25.2 pp FL96.5%81.7% 92.7%+11.0 pp 57.4% 93.0% +35.6 ppGroup64.1%82.7% 86.1% +3.4 pp 78.7% 82.1%+3.4 pp Reported flight operations are DOT Part 234 operations (domestic flights) operated by carriers with at least 1% of domestic scheduled-passenger revenue excludes key regional carriers; Non-reported flights include international flights to/from the U.S. and most regional carriers Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 6 7. Fewer flights were impacted this winter There was a 23% decline in flights impacted by delays in Q1 2012. But when flights were impacted, minutes of delay declined by just 1%. Number of Delayed Flights And When Flights Impacted, Dropped Across Categories Delay Minutes declined 1.1% Q1 09-11 Average Q1 2012 Q1 09-11 AverageQ1 2012112.940.5 40.137.9 37.2 Minutes of Delay per Impacted FlightDelays per 1,000 flights scheduled 91.7 87.332.282.130.570.872.3 24.723.0 11.88.6 CarrierWeather Airspace Late CarrierWeatherAirspaceLate InboundInboundSource: masFlight, DOT Part 234 Flight DataAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 7 8. Cause Analysis SECTION 38A G I FR I R S N 0 1V I A T IC H N I N S T I T U T E E N T 0 1 1 O N L R I G H T S R E S E R V E DME OCA 2 A 2 TE ON CAL PRES 2ATI ALSLIDE 8 9. Possible Drivers of ImprovementWe explore the following drivers: Weather events Maximum and realized runway capacity Aggregate flight schedules and demand Aircraft turn times and airport gate buffers Changes in block components (taxi-out, air-time, taxi-in)Systemwide: we include reported and non-reported flightsGranular: we build data up from individual flight detailsAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 9 10. Winter there wasnt much of it! Change in Snow Events 1H 2012 vs. 1H 2009-2011 Worse winter at ANC, SEA, PDX PDX26% Better winter everywhere else: SEA 17% MSP -18% NYC -72%; DC/PHL -30%; ORD -20% Midwest -20%; SE almost noneIAD -25%BWI-33% Less impact from fog, mist, rain MDW -33% DTW -34% Fog/mist: Houston -30%, BOS-38% Atlanta -27%, Chicago -24% SLC -41% PHL -52% Western U.S: 30-40% reduction in LGA -67%rainy days and IFR impactJFK -71% EWR -78% WX/NAS cancels down 85%CLT -83%IAH-100%with corresponding changeATL-100%in on-time arrival numbersSource: masFlight, NOAA METARsAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 10 11. Throughput Went Up Where It CountsChange in Average Departure/Arrival Rates vs. Size of Airport First Half 2012 vs First Half Average 2009-2011 20.0% Bigger TPA MEM (+12.8%) CLT Airports(+11.2%)(+10.9%)IAH More (+8.4%) ORD ATLEfficient DFW (+4.3%) (+3.4%) (+3.6%) 0.0%Less FLLBWI Most airports saw significant improvement inEfficient(-7.8%) (-8.6%) realized runway capacity and throughput-27% change in time when schedules exceeded capacityCVG (-15.1%)Implies less time waiting for departure at key hubs and leads to lower taxi-out times -20.0% Airport Departure Demand, Low to High Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 11 12. Taxi-out time and on-time arrivalsComparing Change in Outbound OTA(Percentage Points) vs. Change in Taxi-Out Time, Q1 2009 vs. Q1 2012Increase in Logical relationshipoutbound A14% between taxi-out timeand on-time arrivals System-wide decrease10.410.3 9.2in taxi-out times 8.58.36.36.23.5 Some change in taxi-out time likely due to -2.0-2.0DOT 3-hour rule -0.6-1.2-3.9 -2.0-6.8 -6.8 Decrease in Taxi-out (mins) BOS CLT DCA EWR JFKLGAORDPHL Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 12 13. Block Time Changes No evidence found of systemic block-time enhancement across airlines that could explain the change in DOT metrics. Carriers showed definite block time changes (both positive & negative) Delta, JetBlue and American are clear outliers DOMESTICBlock Time Block TimeMARKET IncreasedDecreased Airline Hub Comparison (Q1 2009 vs. Q1 2012) Airline PAIRSRoutes Mean RoutesMeanRoutes withRoutes with ANALYZED Change Change Block DecreaseBlock IncreaseDL1,088760 +4.5 m 328-3.4 m AA - LAXUS 593 362 +3.5 m 231-3.4 m AA - MIAUA1,186614 +3.6 m 572-3.8 m AA - ORDAA - DFWAS 202 113 +4.8 m 89 -2.5 mDL - SLCWN 800 392 +2.1 m 408-2.5 mDL - MSPFL 218 95+3.4 m 125-3.4 mDL - DTWB6 195 62+2.7 m 133-4.3 mDL - ATLAA 575 211 +3.6 m 364-3.2 m -150-100-500 50100 150 Markets Analyzed Source: masFlight (Domestic marketed flights)AGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 13 14. Flights are landing earlier vs. scheduleComparing Landing Times and Scheduled Arrival TimesQ1 2009 (Blue) vs. Q1 2012 (Red), for U.S. Reporting Carriers 45,000 40,000Flights are landing at destination 35,000 airports earlier relative toFlights per Minute Early Q1 2012 scheduled arrival times 30,000Q1 2009 25,000 Suggests that block padding 20,000 could be partial driver 15,000 Earlier landing relative 10,000to scheduled arrival time5,000Source: masFlight 0051015202530 35 40 45 505560Minutes Early - Runway "On" Time before Scheduled Gate Arrival Time Q1 2009 Q1 2012 Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 14 15. Carrier strategies for gate utilization variedMany factors drive the number of flights that land to occupied gates,but we observed strategic and tactical differences across key hubs.Percentage Point Change in Flights Percent of Flights (24-hour) that Land to Occupied GatesThat Land to an Occupied Gate (March 2012 vs. March 2009) (Domestic, March 2012) LAX4.9 IAH 9.7% SFO4.8LAX9.3% PHX2.8SFO 9.1% SEA2.0DEN7.4% DTW1.7PHX 7.3%CLT1.4 DFW7.1%IAH 1.3 ATL 7.0% LGA0.8LGA 5.7%JFK 0.8DTW4.6% EWR 0.7CLT 4.6%IAD 0.4EWR4.6% PHL0.1 JFK4.4% DEN0.0MSP3.1% MSP -0.9SEA 2.9% SLC-1.2 PHL2.2%ATL-4.6 IAD2.0% DFW-5.8 SLC1.4%Includes domestic flights by reporting and non-reporting carriers. Source: masFlightAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 15 16. Observations and Drivers Extremely mild and dry winter increased runway throughput Drove significant change in taxi-out times Little observable change in air-time, taxi-in times Block times show tactical adjustments by carrier Consistent across both reported and non-reported flights Differing strategies by airline Delta consistent addition of block time vs. 2009, across routes JetBlue, American reduction in block times Evidence of airport programs to reduce delays Delta changed assignments and plans at ATL US Airways continued emphasis on early push-back And then theres UnitedAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 16 17. Uniteds anomaly was IT driven UA aircraft turns at IAD, ORD, SFO, DENDistribution of Actual Minutes on Gate Average Change after SHARES switch = +1.8 minutes2,0001,800 8 weeks Unique to s-UA hubs after (s-CO actually shifted left Turns per 100,000 Operations1,600SHARESafter March 3rd change)1,4008 weeksbefore1,200Accounts for -2%SHARES1,000 change OTA% 800 600 The entire distribution shifts right 400 but only at s-UA hubs 200-1001051101151200510 1520 2530 3540 45 5055 606570 7580 8590 95Minutes on GateSource: masFlightAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 17 18. Statistical Analysis SECTION 418A M I FR I R S N 0 1V I A T IC H N I N S T I T U T E E N T 0 1 1 O N L R I G H T S R E S E R V E DGE OCA 2 A 2 TE ON CAL PRES 2ATI ALS L I D E 18 19. Statistical Analysis: Method and Results We used multivariate regression to identify drivers of performanceimprovements across the 2009-2012 time period We analyzed a hybrid dataset of flight records and ASPM Dependent variables: delays, runway rates (ADR, AAR) Independent variables: efficiency, schedules, weather We identified basic relationships that confirmed our suspicion:weather is the most significant explanation of delay changes. Weather is manifested in ADR, departure demand and efficiency which explains 65% of the variation in taxi-time at airline hubs By airport: some weighted to ADR (ATL and LGA), others TFM (IAH and ORD) Per hour, these factors drove a 2.7 minute change in taxi-out timeand a 4.6 minute change in departure delays at the airport Q1 2012: 3 min of taxi change equals about +2% change in OTA performanceAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 19 20. Weather Impact on Arrivals Departures: weather manifests via ADR, demand, efficiency Arrivals: weather and demand are inextricably connected Increased arrival demand exacerbates the impact of weather Arrival demand queues as capacity and efficiency degrade Arrival demand, AAR and weather explain 59% of arrival delay at hubs Arrival delay explains 56% of departure delays What we conclude: 1. Weather impacts inbound capacity, forcing arrival queues 2. Queues cause peaked demand, inbound delays, departure delays 3. Changes in departure demand dont explain delay reduction.AGIFORS 2012 TECHNICAL PRESENTATION SLIDE 20 21. Conclusions SECTION 521A M I FR I R S N 0 1V I A T IC H N I N S T I T U T E E N T 0 1 1 O N L R I G H T S R E S E R V E DGE OCA 2 A 2 TE ON CAL PRES 2ATI ALS L I D E 21 22. What we found What drove the improvement in Q1 2012? We find no compelling evidence of: Carriers gaming DOT reporting metrics Systemic block time padding (but varies by carrier) Day-of operational changes during IRROPS But we do observe: Dry and warm weather over key hubs Low weather impact on inbound flows, so flights land at destinations earlier relative to schedule Low inbound queues, increased gate buffer times higher D0 performance and virtuous cycleAGIFORS 2012 TECHNICAL PRESENTATION SLIDE 22 23. Is it sustainable? Partially sustainable Winter cancellations are safety-, tarmac fine-driven andwill directly correlate to winter severity But D0 focus, gate buffers, and tactical schedule paddingshould improve winter performance relative to 2009-2011time period We expect the IT issues at United will be reduced throughagent training, turn time spacingAGIFORS 2012 TECHNICAL PRESENTATIONSLIDE 23