CANSO Workshop on Operational Performance. LATCAR, 2016 John Gulding Manager, ATO Performance Analysis Federal Aviation Administration

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2 CANSO Workshop on Operational Performance LATCAR, 2016 John Gulding Manager, ATO Performance Analysis Federal Aviation Administration

3 Workshop Contents CANSO Guidance on Key Performance Indicators Software and Database Enablers Metric Demonstrations Reporting Results ANSP Initiatives Improving Operational Efficiency

4 CANSO Guidance on Operational Performance

5 CANSO Report on Operational Performance 21 defined Operational Indicators spanning all phases of flight 2 indicators recommended as priority measures (Capacity, Efficiency) Recommend process to identify if delay/inefficiency is ANSP- Attributable

6 Key Factors in Recommendations Does the KPI have demonstrated use? Legislation, Service Charter, Pay Incentive Cost Benefit work Scope of ANSP Control Control all phases of flight vs. specific phase Role of Network Manager

7 ANSP Management and Operational Metrics Are ANSPs making the most efficient use of capacity? What are the constraints in the system? Are ANSPs providing efficient flight trajectories to operators? How do ANSPs respond to questions of schedule delay and on-time performance?

8 Metric Inter-Dependencies ANSP Investment Traffic Management Initiatives Airspace Design Schedule Peaks Crew Scheduling Equip problems, etc. Flight Efficiency & Delay ATC/ATM performance New Technology Operator Schedules & Flight Preferences Capacity & Airport Infrastructure Weather Airport Maintenance Airport Expansion Other Drivers Low Visibility High wind Convective weather

9 Software and Database Enablers

10 Data Automation Required Capability for establishing Capacity Values Ability to process trajectory data Ability to calculate the demand placed on a facility Ability to attribute delay or inefficiency to a cause code.

11 Establishing Capacity Provides reference benchmark for ANSP performance ANSP cannot land more than a facility can except Capacity can vary Fleet Mix Weather Airport Maintenance How detailed should capacities be?

12 Recording Delay and Delay Causation Which facilities are causing the constraint? Tower, TRACON, Enroute facility What was the causal reason for constraint? Weather, Equipment, Runways, Staffing, Volume/Capacity How was Delay Managed? Miles in Trail, Ground Hold, Airborne Holding What were Minutes of Delay and Flights affected?

13 Metric Demonstrations

14 Capacity Key Performance Indicators Capacity Traffic facility is able to handle over a period of time (hourly) Derived based on assumptions of runway dependencies, separation/speed on final and fleet mix Simulations Observed from actual data (throughput) Capacity Utilization/Efficiency Ratio of Observed Throughput to minimum of demand or declared capacity Declared capacity can vary by condition

15 Capacity KPI Declared Rate, Max Throughput

16 Capacity Utilisation KPI Formula: Number of Arrivals The lesser of the Arrival Demand or the Airport Arrival Capacity Rate Demand (D) Capacity (C) Accommodated Demand (AD) Capacity Efficiency % (AD/C) % (AD/C) % (AD/D) % (AD/D)

17 Calculating Demand Same Process for Determining an un-impeded trajectory, can be used to estimate demand 8.0% 7.0% 6.0% Benchmark Time 13.6 Minutes 5.0% Percentage 4.0% 3.0% 2.0% 1.0% 0.0% Travel Time 40nm to Touchdown PHL Large Aircraft Flight Demand is from Benchmark Arrival Time (un-impeded time) until Actual Arrival Time

18 Flight Efficiency KPI Terminal Area Actual Trajectory compared to Ideal, or best achieved

19 Terminal Measure 8.4 Minutes Average Inefficiency Jan 15, :30-12:45pm 8 Arrivals in 15 Minutes 50 Flights Active within 15 Minutes 40 nm 100 nm

20 System Behavior Measured by En-Route KPIs Are Operators Filing Longer/Shorter Distances? Are Operators Flying Longer/Shorter Distances? Are Flight Plans more Variable or more Flexible?

21 Flight Efficiency KPI EnRoute 40nm Actual Flt Plan 100nm

22 Impact of Special Activity Airspace 22

23 Impact of Weather March 481 Flights 8.3 nm Excess Dist. June 363 Flights 32.6 nm Excess Dist.

24 Traffic Management Delay Weather - Wind 19.10% Equipment 6.75% Other 2.89% Runway/Taxi 4.16% Volume 13.25% Weather - Visibility 23.43% Weather - Snow/Ice 5.92% Weather -Rain 0.24% Weather - T-Storms 24.27% Source - FAA OPSNET

25 ATFM Delay by Season/Region March 2014 June 2014

26 Reporting Results

27 Key Performance Indicator Reporting Statistics provide a view How can you trust what is presented? The same KPI can have different forms depending on the question asked. Totals, Averages, Percent above Threshold Change in Airline Network Effects Shift in City-Pair Distribution confuses reporting Role of Related Measures Weather, Airline Schedules, Airport Capacity

28 LGA EWR JFK PHL ORD DCA CLT BOS SFO IAD IAH MSP ATL MIA DEN LAX PHX DTW MDW BWI DFW FLL MCO SEA SAN RDU LAS SLC STL PDX TPA MEM DAL HOU LGA EWR JFK PHL ORD DCA CLT BOS SFO IAD IAH MSP ATL MIA DEN LAX PHX DTW MDW BWI DFW FLL MCO SEA SAN RDU LAS SLC STL PDX TPA MEM DAL HOU Total vs Averages Average Surface Taxi-Out Delay (minutes) ,500,000 2,000,000 Total Surface Taxi-Out Delay (minutes) 1,500,000 1,000, ,000 0 Averages let you compare facilities, but not your facilities contribution to the system Totals will show the priority areas that will have the greatest effect on the system

29 Network Effects Example City Pair 1 has Direct Flight City Pair 2 does not have Direct Flight If traffic Decreases on City Pair 1 and Increases on City Pair 2 The overall system may show a decrease in flight efficiency, even though the ANSP improved performance for both markets

30 Scheduled Arrivals Related Measures Demand/Capacity Sample Airline Schedules - Arrivals Both Schedules have 605 Arrivals In 2015, Airlines adjusted schedules to introduce a new peak at mid-day Local Hour FY14 FY15 Arrival Capacity

31 Scheduled Arrivals Related Measures Demand/Capacity Sample Airline Schedules - Arrivals Both Schedules have 605 Arrivals In 2015, Airlines adjusted schedules to introduce a new peak at mid-day Local Hour FY14 FY15 Arrival Capacity - Good Weather Arrival Capacity - Bad Weather

32 ANSP Examples of Measuring and Improving Performance

33 ANSP Operational Efficiency Initiatives UK National Air Traffic Services Extended Arrival Manager (XMAN) Airways New Zealand ATOMS Performance System New Southern Skies, PBN Implementation

34 Heathrow XMAN & Descent Speed Procedures 1. Neighbouring ATCOs (350nm horizon) apply speed reduction when EGLL delay >=7 mins 2. Swanwick ATCOs apply speed reductions in descent when delay >5 mins Prestwick Copenhagen Shannon Maastricht Reims Karlsruhe Brest

35 Heathrow XMAN & Descent Speed Procedures

36 Airways New Zealand Air Traffic Operational Metric Suite (ATOMS) currently being internally developed Objective: To measure and analyse outcomes to discover exploitable opportunities for improvement. Focused on: Operational performance metrics Delivering customer value Increased capacity Environmental impact/savings Productivity and workforce planning Industry Requested Reports Airlines, Airports New Southern Skies multi-agency program led by CAA

37 Airways New Zealand - ATOMS Currently being achieved through sourcing and developing tools which: Fuse data from multiple sources Deliver a highly mineable database Learn from fine detail Discover service improvement opportunities