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Performance Metrics in Air Traffic Management Systems. A Case Study of Isavia s Air Traffic Management System. by Hulda Ástþórsdóttir
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1 Performance Metrics in Air Traffic Management Systems A Case Study of Isavia s Air Traffic Management System by Hulda Ástþórsdóttir Thesis Master of Science in Engineering Management May 2013
2 Performance Metrics in Air Traffic Management Systems Hulda Ástþórsdóttir Thesis submitted to the School of Science and Engineering at Reykjavik University in partial fulfillment of the requirements for the degree of Master of Science in Engineering Management May 2013 Supervisors: Þorgeir Pálsson, Professor, Reykjavik University Guðmundur Kristjánsson, Project Manager (R&D), Isavia Examiner: Runólfur Smári Steinþórsson, Professor, University of Iceland ii
3 Abstract Abstract Over several years there has been increasing demand world-wide for more capacity in Air Traffic Management Systems as air traffic has continued to grow. At the same time there is growing demand for quality of the service provided by the Air Navigation Service Providers as well as for lower charges. This has led to efforts by the European Union, through a major initiative called the Single European Sky, to increase the efficiency of Air Traffic Management in Europe. As a result of this development, much emphasis has been put on efforts to control cost and use financial resources in a more efficient way. An important development for this purpose has been the introduction of formal metrics for assessing service provider performance. The airspace controlled by Iceland, the Reykjavík Control Area, spans approximately 5.4 million square kilometres and is mainly oceanic apart from the area over northern Greenland. Isavia is the Air Navigation Service Provider responsible for providing air navigation services in this area. This study is directed at the en-route Air Navigation Service provided in this area. The aims of this thesis are to analyse and evaluate the metrics that are currently used to measure the performance of Air Navigation Service Providers and to develop a system of performance metrics for the Icelandic Air Traffic Management System. In this thesis, performance metrics which have been used in benchmarking Air Navigation Service Providers were studied as well as the factors affecting performance. Several performance metrics are calculated using data from Isavia. The results of the calculations are compared to other oceanic Air Navigation Service Providers. The productivity was also compared to the Maastricht Upper Area Control Centre since this centre provides only en-route Air Navigation Services similar to the oceanic en-route services provided by Isavia. Isavia offers user-preferred tracks in most of its control area. Also radar surveillance is available in a large part of the area. This affords more flexibility to the user but increases the complexity of the air traffic and hence decreases the productivity of the ATM system. Several other factors affect the ATM system performance, such as traffic variability and the size of the Air Navigation Service Provider. All of these aspects are addressed and evaluated in this research. However a direct comparison is difficult as some of this information, apart from the volume of business, is not available for oceanic Air Navigation Service Providers which are used in the comparison. It is concluded that in general the Air Traffic Services being provided by Isavia are very competitive compared with other Oceanic Air Navigation Service Providers. This is based on performance and financial metrics taking into account the effects of complexity and variability of air traffic in the area. Keywords: ATM, Performance, Metrics, Oceanic Airspace, Complexity.
4 Ágrip Ágrip Á undanförnum árum hefur flugumferð í heiminum aukist mikið sem hefur leitt af sér kröfur um meiri afköst í rekstri flugstjórnarkerfa. Á sama tíma eru gerðar auknar kröfur um gæði þeirra þjónustu sem veitt er og lækkun gjalda. Við þessu hefur Evrópusambandið brugðist með því að koma á fót framtaksverkefni um samevrópskt loftrými (e. Single European Sky) til að auka skilvirkni í rekstri flugleiðsögukerfa í Evrópu. Þetta hefur leitt til þess að aukin áhersla hefur verið lögð á að takmarka kostnað og hagræða í rekstri. Mikilvægur þáttur í þessari þróun er innleiðing frammistöðumælikvarða. Íslenska loftrýmið er um 5,4 milljónir ferkílómetra að stærð og er að miklu leyti yfir úthafinu, að undanskildu svæðinu yfir norðurhluta Grænlands. Isavia annast flugleiðsöguþjónustu í íslenska loftrýminu og beinist þetta verkefni að alþjóðaflugþjónustunni sem Isavia veitir. Markmið þessa verkefnis er að greina og meta þá mælikvarða, sem nú eru notaðir til að mæla frammistöðu flugleiðsögukerfa ásamt því að þróa kerfi slíkra mælikvarða fyrir íslenska flugleiðsögukerfið. Í þessu verkefni eru skoðaðir frammistöðumælikvarðar sem hafa verið notaðir til að bera saman frammistöðu flugleisögukerfa ásamt því að skoða þá þætti sem hafa áhrif á samanburðinn. Með gögnum frá Isavia eru reiknaðir nokkrir mælikvarðar fyrir íslenska flugleiðsögukerfið. Niðurstaðan úr þessum útreikningum er borin saman við útkomu hjá öðrum aðilum sem reka flugleiðsögukerfi á úthafssvæði. Framleiðnin var einnig borin saman við framleiðni Maastricht Upper Area Control Centre, þar sem þeir þjóna eingöngu flugleiðsögu í leiðarflugi, en það á einnig við um þá þjónustu sem veitt er á íslenska úthafssvæðinu. Isavia býður upp á sveigjanleika fyrir flugrekendur í vali á flugleiðum innan stærsta hluta flugstjórnarsvæðisins. Ratsjárþjónusta er einnig veitt á stórum hluta svæðisins Þetta hefur í för með sér að flækjustig flugumferðarinnar eykst sem aftur á móti stuðlar að minni framleiðni Nokkrir aðrir þættir hafa einnig áhrif á frammistöðuna, s.s. hversu breytileg flugumferðin er á svæðinu ásamt því hversu mikil flugumferð fer í gegnum svæðið. Í verkefninu er fjallað um þessa þætti og áhrif þeirra skoðuð. Ekki liggja fyrir nægar tölulegar upplýsingar um þessa þætti hjá þeim aðilum sem veita flugleiðsöguþjónustu á úthafssvæðum og því er erfitt að gera beinan samanburð milli þessara aðila. Á grundvelli útreikninga á framleiðni- og fjárhagslegum mælikvörðumvar var lagt mat á framistöðu íslenska flugleiðsögukerfisins. Almenna niðurstaðan er sú að flugleiðsögukerfi Isavia og sú þjónusta, sem veitt er á úthafinu, sé mjög samkeppnishæft við aðra aðila sem veita flugleiðsöguþjónustu á úthafsvæðum að teknu tilliti til þess hve umferðin er flókin og breytileiki hennar mikill frá degi til dags og milli árstíða. Lykilorð: Flugumferðarstjórn, Flugleiðsögukerfi, Frammistöðumælikvarðar, Framleiðni.
6 Acknowledgements Acknowledgements I would like to thank my supervisor Þorgeir Pálsson, for his excellent guidance and continued support. Guðmundur Kristjánsson, Project Manager Research & Development, my contact person at Isavia, I would like to thank for his help in providing data and information related to this thesis. Several people at Isavia came to my assistance in my work. I would like to express by thanks to: Anna Dagný Halldórsdóttir, Project Manager in Finance division Arnar Þórarinsson, Senior System Administrator ATM Systems Arnór Bergur Kristinsson, Projects Manager at Isavia Brandur Guðmundsson, Head of Technical Services ANS, Isavia Guðmundur Karl Einarsson, Air Traffic Controller Guðný Unnur Jökulsdóttir, Finance Manager in Finance division Hjalti Pálsson, Manager - Research & Development Hörður Arilíusson, Air Traffic Controller, CNS & ATM expert Jón Gunnlaugsson, Manager - Safety and Quality Kristján Torfason, System Administrator ATM Systems Magnús Ásbjörnsson, Project Manager EATS Steingrímur Hálfdánarson, Deputy Manager Steinunn Arna Arnardóttir, ATS Procedure Specialist Sigurjón Árni Guðmundsson, Research Engineer, Tern Systems hf. Þórdís Sigurðardóttir, Manager Reykjavik ACC/OACC I would furthermore like to express my thanks to: J. Paul Cripwell, Global Benchmarking Workgroup, CANSO, Denis HUET, Performance Review Unit, EUROCONTROL, Páll Ríkharðsson, Associate Professor, Reykjavik University, Stefanía Bergmann Magnúsdóttir and Þórhallur Jakobsson, Icelandair.
7 Table of Contents Table of Contents Abstract... i Ágrip... i Acknowledgements... iii Table of Contents... iv List of drawings... viii List of Tables... x Abbreviations... xii 1. Introduction Background Statement of the problem Aim and objectives Research Aims Research Objectives Research methodology Outline of the thesis Air Traffic Management in the Reykjavik Control Area Air Navigation Services The Reykjavik Control Area Air Traffic Control Measuring Performance Introduction Performance measurements Benchmarking Performance Measurements in Air Traffic Management Systems Introduction Safety SES Performance Scheme CANSO report The FAA s Oceanic and Offshore Integrated Product Team... 25
8 Table of Contents General comments on safety performance metrics Productivity ACE report CANSO report Naviair productivity indicators Additional comments on productivity metrics Financial Cost efficiency Revenue and other financial metrics Naviair financial metrics Additional comments on the financial metrics Flight efficiency and environmental factors Studies on flight efficiency Performance Review Commission s En-route Extension Flight efficiency metric of SES Performance Scheme NATS fuel efficiency metric The applicability of the flight efficiency metrics in Reykjavik CTA Quality of Service Delay/Capacity Other Quality of Service Metrics Difference in definitions in the ACE and CANSO reports Factors affecting performance Introduction Endogenous Factors Exogenous factors Traffic Variability Complexity Definition of complexity Studies of ATCO workload Eurocontrol s Complexity Score The applicability of the Complexity Score in Oceanic Control Areas Complexity within the Reykjavik Control Area Performance measurements using data from Isavia s Air Navigation Service... 79
9 Table of Contents 6.1 Introduction Selection of the performance measurements to be used Safety Selected Performance Metrics Data analysis and assumptions IFR Flight Hours ATCO in OPS and ATCO in OPS hours on duty Costs Calculation of Performance metrics and Comparison between Oceanic ANSPs Productivity Financial Traffic Variability Results and Discussion Summary of Results Productivity Financial metrics Flight efficiency metrics Complexity metrics Traffic variability Conclusions and Recommendation Revisiting the research aims Conclusions Suggestions for further work References Appendices Appendix I Air Traffic Management system Air Traffic Management Appendix II The Air Traffic Control System at Isavia Surveillance Flight Data Communication Navigation Appendix III List of complexity factors
10 Table of Contents Appendix IV Exchange rates from CANSO s Global Air Navigation Services Performance Report Oceanic ANSPs Appendix IV Purchasing Power Parity exchange rates Glossary of Terms
11 List of Drawings List of Drawings Figure 1.1: Geographical Boundaries of the Reykjavík Control Area Figure 2.1: The structure of Air Navigation Services... 8 Figure 2.2: Boundaries of the domestic airspace Figure 2.3: Division of Reykjavík Control Area into geographical sectors Figure 2.4: NAT OTS tracks 11 Figure 2.5: Radar stations and radar coverage in the Reykjavík Control Area at an altitude of feet Figure 2.6: The traffic pattern in the Reykjavik Control Area Figure 4.1: Overview of the proposals from PRB for Safety KPIs Figure 4.2: Individual parts of Air Navigation Services as defined by Eurocontrol. 39 Figure 4.3: Parameters of the flight efficiency metrics. 42 Figure 4.4: Difference in great circle route and wind optimal route Figure 4.5: En-route Extension as defined by PRC in the Performance Review Report Figure 4.6: The horizontal component of the 3 Di Score. 47 Figure 4.7: Vertical component of 3Di Score Figure 5.1: Air traffic growth Figure 5.2: Controlled flight versus free flight...64 Figure 5.3: Cell configuration Figure 5.4: Definition of interactions...68 Figure 5.5: Calculation of adjusted density Figure 5.6: Vertical interactions Figure 5.7: Horizontal interactions Figure 5.8: Adjusted density calculated for different cell size (40x40 in Centre 1 and 20x20 in Centre 2) Figure 5.9: A scatter diagram of the number of aircraft in the Reykjavik CTA within an hour interval versus the number of ATCOs in operating position 77 Figure 6.1: IFR Flight Hours per ATCO in Operation for the years Comparison of oceanic ANSPs..91 Figure 6.2: The number of aircraft in the area and the number of ATCOs in operational positions per hour of the day. This figure is based on flight data for both domestic and oceanic flights... 93
12 List of Drawings Figure 6.3: Cost per IFR Flight Hour for the year 2011 in USD. Comparison between oceanic ANSPs.. 97 Figure 6.4: Employment Cost for ATCO in OPS per IFR Flight Hour in USD for the year Comparison between oceanic ANSPs Figure 6.5: Employment cost for ATCO in OPS per ATCO in OPS in thousand USD. Oceanic ANSPs Figure 6.6: Cost of Capital and Depreciation as a Percentage of Total Cost for Isavia over the years Figure 7.1: IFR Flight Hours per ATCO in Operation for the years Comparison of oceanic ANSPs Figure 7.2: Cost per IFR Flight Hour for the year 2011 in USD. Comparison between oceanic ANSPs Figure 7.3: Employment Cost for ATCO in OPS per IFR Flight Hour in USD for the year Comparison between oceanic ANSPs Figure 7.4: Employment cost for ATCO in OPS per ATCO in OPS in thousand USD. Oceanic ANSPs Figure I.1: Flow of operational data between Airspace Management, Flow Management, ATC Planning, Separation Service and Aircraft. Adapted from a paper issued in the 5th US/Europe Air Traffic Management R&D Seminar Figure I.2: Division of Reykjavík control area into sectors Figure II.1: Information systems and equipment used in Reykjavik ACC. 136 Figure II.2: Radar stations and radar coverage in the Reykjavík control area at 40 thousand feet Figure II.3: The communication between the ATCC and the Aircraft.. 142
13 List of Tables List of Tables Table 3.1: A list of recommendation for the design of performance measurements.. 18 Table 4.1: Comparison of the definition of revenues and costs in the ACE and CANSO reports Table 6.1: Performance metrics calculated Table 6.2: IFR Flight Hours data as received and as corrected for use in the calculation of performance metrics. 86 Table 6.3: Data elements ATCOs in OPS (Oceanic) in FTE and ATCO in OPS hours on duty. Values used in further calculations are shown in bold.87 Table 6.4: Cost related to the Oceanic ANS service. The costs are expressed in million ISK Table 6.5: Isavia s productivity metrics in Table 6.6: Comparison of IFR Flight Hours per ATCO in OPS between oceanic ANSPs for ANSPs are listed in order of total IFR Flight Hours controlled per year Table 6.7: Contextual data for oceanic ANSPs.. 92 Table 6.8: Financial metrics for Isavia in ISK at 2012 price levels 96 Table 6.9: Comparison of Cost per IFR Flight Hours in oceanic control areas. ANSPs are listed in order of total IFR Flight Hours controlled per year 97 Table 6.10: Employment Cost for ATCOs in Operations per IFR flight hour. For each oceanic ANSP this is expressed in USD using end-of-year 2011 exchange rates. ANSPs are listed in order of total IFR Flight Hours controlled per year 98 Table 6.11: Employment Cost for ATCOs in OPS per IFR Flight Hour. For each oceanic ANSP this is expressed in USD using PPP. Conversion rates are given in Appendix V. ANSPs are listed in order of total IFR Flight Hours controlled per year.. 98 Table 6.12: Employment cost for ATCO in OPS per ATCO in OPS. For each oceanic ANSP this is expressed in USD using end-of-year 2011 exchange rates. ANSPs are listed in order of total IFR Flight Hours controlled per year Table 6.13: Employment Cost for ATCOs in OPS per ATCO in OPS. For each oceanic ANSP this is expressed in USD using PPP. Conversion rates are given in Appendix V. ANSPs are listed in order of total IFR Flight Hours controlled per year 100 Table 6.14: Support Cost Ratio for oceanic ANSPs. ANSPs are listed in order of total IFR Flight Hours controlled per year..102 Table 6.15: Traffic variability, considering air traffic per day and per week. 102
14 List of Tables Table 7.1: Results of the performance measurements for Isavia in hours and ISK at 2012 price levels Table 7.2: Traffic variability in the Reykjavik Control Area (CTA).. 104
15 Abbreviations Abbreviations 3Di Score A/C ACC ACE ACE Report ADS-B ADS-C AFTN AIS ANS ANSP APP ATM ATC ATCO ATCO in OPS ATS ATFM ATFCM ASM CAA CANSO CFMU CNS COM CPDLC CPL CRC DLCS DLSP EU FAA FAB FANS FDPS FIR FIS FL FMS FPL FSFE FTE GBWG GPS 3-Dimentional Inefficiency Score Aircraft Area Control Centre ATM Cost-Effectiveness ATM Cost-Effectiveness Benchmarking Report Automatic Dependent Surveillance Broadcast Automatic Dependent Surveillance Contract Aeronautical Fixed Telecommunication Network Aeronautical Information Service Air Navigation Services Air Navigation Service Provider Approach Control Unit Air Traffic Management Air Traffic Control Air Traffic Controller/Air Traffic Control Officer Air Traffic Controller on operational duty Air Traffic Service Air Traffic Flow Management Air Traffic Flow and Capacity Management Airspace Management Civil Aviation Authority Civil Air Navigation Services Organization Central Flow Management Unit Communication, Navigation, Surveillance Communication Controller Pilot Data Link Communication Current Plan Control and Reporting Centre Data Link Communication System Data Link Service Provider European Union Federal Aviation Administration Functional Airspace Block Future Air Navigation System Flight Data Processing System Flight Information Region Flight Information Service Flight Level Flight Management System Flight Plan Fans Front End Full Time Equivalent Global Benchmarking Workgroup Global Positioning System
16 Abbreviations HF HFDL ICE IFR ICAO IPT INS ISDS KPI MET NAS NAT NAT OTS NATS NM NOTAM OAC PPP PRC PRR PRU SAR SES SOR SESAR SIGMET TMA VFR High Frequency High Frequency Data Link Integrated Controller Environment Instrument Flight Rules International Civil Aviation Organisation The FAA Oceanic and Offshore Integrated Product Team Inertial Navigation System Integrated Situation Display System Key Performance Indicators Meteorological services National Airspace System North Atlantic North Atlantic Organized Track System National Air Traffic Services Nautical Miles Notices To Airman Oceanic Area Control Centre Purchasing Power Parity The Performance Review Commission Performance Review Report The Performance Review Unit Search and Rescue Single European Sky Safety Occurrence Reporting Single European Sky ATM Research Significant Meteorological Information Terminal Manoeuvring Area Visual Flight Rules
17 Chapter 1 Introduction 1. Introduction The overall goal of this project is to develop a system of performance metrics that can be used to describe the performance of the Air Traffic Management System operated by Isavia for controlling air traffic in its area of responsibility in the North Atlantic Region. The project will be aimed at defining these metrics based on a thorough analysis and modelling of the Air Traffic Management system. 1.1 Background The airspace above us is a limited resource which is under the jurisdiction of sovereign states or, in the case of international airspace, governed by the International Civil Aviation Organization (ICAO) 1 as far as civil aviation is concerned. Each state has full control over the airspace above its sovereign territory. Typically Air Navigation Services (ANS) in this airspace are delegated to an Air Navigation Service Provider (ANSP) 2, which in most cases is a state agency or a state-owned organization. Isavia ohf. (Isavia), a state-owned limited liability company, is the designated ANSP for Iceland. Figure1.1: Geographical Boundaries of the Reykjavík Control Area. (Source: Isavia). 1 ICAO is an agency of the United Nations established to promote the safe and orderly development of international civil aviation throughout the world. 2 See Glossary of Terms for further information. 1
18 Chapter 1 Introduction The control of oceanic airspace outside the territory of member states is delegated by ICAO to certain member states. In the North Atlantic (NAT) Region ICAO has delegated the Air Navigation Services (ANS) to seven states including Iceland. The airspace controlled by Iceland, the Reykjavík Control Area (Reykjavik CTA), spans approximately 5.4 million square kilometres. The Reykjavik CTA comprises the Reykjavik Flight Information Region (FIR) and the Sondrestrom Flight Information Region, see figure 1.1 (Isavia, 2012a). 3 The Sondrestrom FIR is not under Icelandic territory and the control of the FIR by the Reykjavik Area Control Centre (ACC) stems from a joint agreement with Denmark. In continental Europe the airspace has been divided into control areas in accordance with the borders between the states. However over Belgium, the Netherlands, Luxembourg and northwest Germany the upper airspace is controlled by the Maastricht Upper Area Control Centre (MUAC) operated by Eurocontrol. This means that when an aircraft is flying across Europe it passes through several control areas, each managed by a different ANSP. This way of managing the air traffic is the cause of major inefficiencies. 4 The general rule with respect to the charges for the air navigation services provided by ANSPs is that it is calculated on the basis of the cost incurred in providing the service. The users of the services, i.e. airlines and private aircraft, are charged through a system of enroute charges and approach and/ or landing fees for their use of these services to recover the costs involved. It is in the interest of the airlines to decrease these charges and/or to improve the services being provided by the ANSPs in order to minimize their costs in a very competitive market. The increasing demand for more capacity, higher quality and lower charges together with increasing air traffic has led to efforts by the European Union to increase efficiency in the Air Traffic Management in Europe without jeopardizing safety. This effort has resulted in the concept called Single European Sky (SES) 5. The European Union has passed two SES packages to create a legislative framework for European aviation. The SES packages include five interrelated pillars : the performance-based regulatory framework, the safety pillar, the technological contribution, the human factor and the optimization of the airport infrastructure (European Commission, 2012). With the SES came the initiative of organizing airspace into Functional Airspace Blocks (FAB) 6, according to traffic flows rather than to national borders. An important part of the means to obtain increased efficiency is set forth in the SES regulations in terms of performance measurements and performance targets. Eurocontrol 7 has 3 The Reykjavik Area Control Centre (ACC) provides Air Traffic Services within the Reykjavik FIR while in the Söndreström FIR Reykjavik ACC provides Area Control Service, Flight Information, Service and Alerting Service above FL 195 (Flugmálastjórn Íslands, 2011). 4 When compared to US airspace where there is a single ANSP there are 13% fewer Air Traffic Controllers (ATCOs) in US than in Europe but they control 70% more flight hours (Eurocontrol & FAA, 2010). 5 See Glossary of Terms for further information on SES. 6 See Glossary of Terms for further information on FAB. 2
19 Chapter 1 Introduction for several years gathered information from the ANSPs of member states and issues annually reports showing the result of several performance indicators which have been selected for this purpose. Eurocontrol and the European Commission have prepared a European Air Traffic Management Master Plan (European Commission; Eurocontrol, 2009) for gradually implementing the SES. In this plan, a list of Key Performance Indicators has been defined. Another organization, CANSO 8, has also suggested performance indicators for use in evaluating performance in the provision of air navigation services and annually issues a benchmarking report on Air Navigation Services Performance. Even though Isavia is not part of the European Union, the SES regulations have been introduced in part in Iceland through the European Economic Area Agreement. EC 1070/2009 has however not been implemented in Iceland and hence the SES II requirements are not yet applicable in Iceland. As regards the Functional Airspace Blocks (FAB) 9, Iceland withdraw from the NEFAB 10 project in The implementation of SES II into the EEA agreement is under consideration. As mentioned before the largest part of the flight information regions under Icelandic control are delegated through agreements which have to be taken into account when entering a co-operation such as NEFAB. When EC 1070/2009 has been fully implemented in Iceland, Isavia will have to provide the necessary information for the evaluation of its performance. 1.2 Statement of the problem For every company it is necessary to measure the performance of its processes and business activities in order to be able to assess whether the company is achieving its goals and heading in the right direction towards its future vision for the company. In this context performance measurements are primarily for use within the company. Performance measurements are also used to evaluate how a company is performing with respect to similar companies. It is necessary for ANSPs to be able to know their strengths and weaknesses in comparison to other ANSPs. As for Isavia it is of great importance to be able to put a value to their service and to monitor their performance in general. The delegation of oceanic airspace is at each time based on current situation. The oceanic airspace within the Reykjavik CTA has been under Icelandic control for a long period of time. The future delegation of this airspace depends on several factors; among them are the 7 European Organization for the Safety of Air Navigation is an intergovernmental organization made up of 39 Member States and the European Community. 8 CANSO is an organization which represents the interests of Air Navigation Service Providers worldwide. 9 See Glossary of Terms for further information on FAB. 10 North European Functional Airspace Blocks, see Glossary of Terms for further information. 11 For further information see: 3
20 Chapter 1 Introduction safety, quality and cost of the service provided by Reykjavik ACC. It is therefore important for Isavia to monitor their performance in this area and strive to increase it. The airspace controlled by Isavia is shown in Figure 1.1. Compared to the average size 12 of the controlled airspaces in Eurocontrol member states the Reykjavik CTA of 5.4 million km 2 is very large. The oceanic airspace within the Reykjavik CTA is larger than any oceanic airspace under the control of Eurocontrol s members states (Performance Review Unit (PRU), 2012). If the Reykjavik Control Area is compared with other oceanic control areas, Isavia provides more service by offering more flexibility in the choice of flight routes than is normally available. The main reason for this is that a part of the airspace has radar coverage. The radar coverage allows less separation between aircraft than possible when procedural separation is used, as is usual for oceanic airspace. This increases the possibility of adjusting flight routes in accordance with requests from airlines. Whereas most oceanic ANSPs offer fixed tracks for flight routes with little possibilities to change the route of the aircraft 13, Isavia is able to offers flexible routes. The airlines will therefore have more possibility to choose their preferred route and to make changes of their cleared 14 routes. This also means that the traffic will become more complex to control when compared to traffic on fixed tracks. If on the other hand the Reykjavik Control Area is compared with the airspace in continental Europe there is much more air traffic in continental Europe than in the North Atlantic and the complexity is also much greater. All these factors will make benchmarking difficult, because some factors will not be directly comparable between control areas and service providers. When comparing two ANSPs with respect to cost the type and level of service provided and the complexity of the traffic must be taken into account. 1.3 Aim and objectives The aims and objectives of this research were mainly defined through discussions with Isavia personnel and in cooperation with my supervisor. On the other hand some limitations had to be made to the initial scope of the project resulting in the following aims and objectives Research Aims The aims of this research are: To analyse and evaluate the metrics that are currently used to measure the performance of ANSPs. 12 The average size of controlled airspace (including oceanic airspaces) in Eurocontrol member states is about 591 km For example to climb up to higher heights in order to decrease fuel consumption. 14 For explanation see clearance in Glossary of Terms. 4
21 Chapter 1 Introduction To develop a system of performance metrics for the Icelandic Air Traffic Management (ATM) System operated by Isavia, based on an analysis and modelling of the ATM System. To identify the need for additional data, that may not be collected at this point in time and to define how such data could be collected Research Objectives The objectives of this research are to: Prepare a description of the ATM system at Isavia, focusing on the flow of information within the system. Gather data on existing performance measurements currently used or being suggested for use by ANSPs in Europe. Make a suggestion for a list of performance metrics to measure the performance of the ATM System operated by Isavia. Map out in details how these metrics are calculated from data available at Isavia and list any additional data that need to be gathered on a regular basis. Calculating the metrics using data from Isavia. Evaluate how the performance has changed over a time period Compare the performance metrics calculated for Isavia with metrics from other ANSPs. 1.4 Research methodology The research methodology of this thesis is a case study. It involves gathering information on the ATM system at Isavia and drawing up a functional diagram showing the information flow between the various components of the Air Traffic Management System as well as preparing a written description of the system and its parts. This involves an explanatory case study where the information gathered in several meetings with Isavia s personnel and through material provided by Isavia is analysed. This part of the study was performed in cooperation with a fellow student (Unnur Þorleifsdóttir). The result of this study can be found in Annex I. The research furthermore involved studying performance metrics which have been used by other ANSPs and gather information on how they are calculated. An evaluation of the applicability of these performance metrics for Isavia is based on this study. 1.5 Outline of the thesis The thesis starts with an introduction of Air Traffic Management in the Reykjavik Control Area in chapter 2, where emphasis is on the factors that are of importance to this study of performance measurements. A more detailed description of the Air Traffic Management 5
22 Chapter 1 Introduction System at Isavia is found in Appendices I and II. In the following chapter no. 3 is an introduction of performance measurements in general. The main study of performance metrics and the factors affecting performance in Air Traffic Management is presented in chapters 4 and 5. In these chapters the metrics are defined and evaluated with respect to their applicability for the evaluation of Air Traffic Management in the Reykjavik Control Area. In chapter 6 a selection of performance metrics are calculated using data from Isavia followed by chapter 7 where the results are presented and discussed. Chapter 8 provides a discussion and summary of the results of the research performed and conclusions and recommendations for further research. As the subject of the thesis is within a specialized area of Air Navigation Services there are many concepts which are new to the general reader. In order to facilitate the reading there is a Glossary of Terms at the end of the thesis in addition to the list of abbreviations which precedes this chapter. 6
23 Chapter 2 Air Traffic Management in the Reykjavik Control Area 2. Air Traffic Management in the Reykjavik Control Area One of the objects of this thesis was to study the Air Traffic Management (ATM) systems at Isavia to gain an understanding of the system which performance is under consideration. This study was performed in co-operation with a fellow student Unnur Þorleifsdóttir and the results can be found in Appendix I and II. We gathered information on the system from our mutual thesis advisor and from our meetings with personnel at Isavia. In this chapter a brief description will be provided of how Air Traffic Management is implemented and carried out by Isavia with emphasis on those factors that affect the performance of the ATM System and especially those aspects which are different from other Air Navigations Service Providers (ANSP). For more detailed description of the Isavia ATM system reference is made to Appendices I and II. 2.1 Air Navigation Services Air Navigation Services (ANS) includes five broad categories of services provided to air traffic during all phases of operation (area control, approach control and aerodrome control). These services are: Air Traffic Management (ATM), Communication services, Navigation services and Surveillance services (CNS), Meteorological services for air navigation (MET), Aeronautical Information Services (AIS) and Search and Rescue (SAR) (ICAO, 2001). Further division of these services is shown in Figure 2-1; an explanation of the terms in each box in the figure can be found in Glossary of Terms. 7
24 Chapter 2 Air Traffic Management in the Reykjavik Control Area Air Navigation Services (ANS) Communications, Navigations, Surveilance (CNS) Air Traffic Management (ATM) Meteorological Services (MET) Aeronautical Information Services (AIS) Search & Rescue (SAR) Communication Services Air Traffic Services (ATS) Air Traffic Flow Management (ATFM) Airspace Management (ASM) Navigation Services Air Traffic Control (ATC) Flight Information Service (FIS) Alerting Service Surveilance Services Area Control Approach Control Aerodrome Control Figure 2.1: The structure of Air Navigation Services. (Source: Performance Review Unit) Of the Air Navigation Services shown in Figure 2-1 Isavia provides most of the services except the Search and Rescue which is in the hands of the Icelandic Coast Guard and the Meteorological Service which is mainly provided by the Icelandic Met Office. Furthermore, Isavia does not perform all aspects of Air Traffic Flow Management as performed by the Central Flow Management Unit (CFMU) 15, e.g. Isavia does not allocate slot time. However, the planning of the capacity within the Reykjavik Control Area (Reykjavík CTA) which is one aspect of Air Traffic Flow Management is performed by Isavia in the Reykjavik Area Control Centre (Reykjavik ACC) (see Flow Management in Appendix I). The major part of the operation at Reykjavik Area Control Centre (Reykjavik ACC) lies however in the en-route Air Traffic Control (ATC) including CNS services. Furthermore the control of the international traffic is the dominant part of the ATC service provided by Reykjavik ACC. For this reason the main focus of this study is on these parts, i.e. the Area Control and CNS service. As in many companies there is not a clear cut between departments and it should therefore be noted that these services are an integral part of the whole ANS system and the boundaries are not as clear as indicated by the boxes in Figure The Reykjavik Control Area In the Reykjavik ACC both domestic and international air traffic 16 approach control of international air traffic is at Keflavik airport. is controlled. The 15 See Glossary of Terms for further information. 16 Both over- flight traffic (i.e. traffic that transits through the CTA) and the en-route international traffic to and from Iceland. 8
25 Chapter 2 Air Traffic Management in the Reykjavik Control Area The boundary between the international en-route airspace (the oceanic airspace) and the domestic airspace is defined in the AIP Iceland (Flugmálastjórn Íslands, 2011) and are as shown in figure 2.2. The upper limit of the domestic airspace is at flight level 245. Figure 2.2: Boundaries of the domestic airspace. (Source: Isavia) For the purpose of calculating charges in the Joint Financing Agreement, a flight is considered to have entered the domestic airspace at 220 kilometres from the Icelandic airport. Section III, point 10 of the agreement is as follows: The distance factor (d) is equal to one-hundredth of the great circle distance, expressed in kilometres, between the aerodrome of departure within, or the point of entry into, the airspace of the Reykjavik and Søndre Strømfjord FIRs and the aerodrome of first destination within, or the point of exit from, that airspace. The entry and exit points are the points at which the lateral limits of the airspace are crossed by the route of the aircraft. The distance to be taken into account is reduced by a notional 100 kilometres for each take-off and for each landing on the territory of the Søndre Strømfjord FIR and the Faroe Islands and 220 kilometres for each approach and each departure from airports in Iceland. (ICAO, 2010) International air traffic to Iceland is therefore considered to have exited the international airspace at 220 kilometres (about 120 NM) from the Icelandic airport. The airspace in the Reykjavík Control Area (Reykjavík CTA) is divided into geographical sectors as is necessary to divide the traffic load into smaller units that can be controlled by one or two Air Traffic Controllers (ATCOs). Four lateral sectors have been defined in the Reykjavík CTA: North sector, East sector, West sector and South sector as can be seen in Figure 2-2. When traffic load increases, further division of these sectors may be necessary. 9
26 Chapter 2 Air Traffic Management in the Reykjavik Control Area The sectors are then further divided by flight levels in such a way that each Control Workstation (CWS) controls specified flight levels within the geographical sector. There are five radars which service the Reykjavik CTA. Where there is radar coverage radar surveillance can be provided. Figure 2.3: Division of Reykjavík Control Area into geographical sectors. (Source: Isavia). The Reykjavík Control Area is free route airspace, i.e. air traffic is normally not required to follow predefined routes. There have however been defined fixed routes which are used under certain conditions such as the Blue Spruce routes 17. Large portion of the air traffic over the North Atlantic Ocean follows tracks which are defined every 12 hours. This track system is called North Atlantic Organized Track System (NAT OTS)(IVAO, 2012). Over the North Atlantic Ocean strong westerly winds, often referred to as the jet stream, prevail. The jet stream affects the air traffic and the airlines plan their flight routes with the aim of maximizing tail winds and minimizing head winds. The position of the NAT tracks 17 Routes where the aircraft is at all times within VHF range of a land station (Flugmálastjórn Íslands, 2011). 10
27 Chapter 2 Air Traffic Management in the Reykjavik Control Area varies from day to day depending primarily on the location of the jet stream. Some days some or all of the OTS tracks enter the Reykjavik CTA. More frequently the OTS tracks are outside Reykjavik CTA. These fluctuations cause somewhat unpredictable variation in air traffic in the area. In 2010, the NAT tracks for traffic heading west entered the Reykjavik control area 111 days while the NAT tracks for traffic heading east entered the Reykjavik control area only 6 days (Isavia, 2012b). Figure 2.4 shows the air traffic at noon on a day where the major part of the OTS tracks lies within the Reykjavik CTA. There are five OTS tracks issued; these are indicated with a line in the figure. Figure 2.4: NAT OTS tracks. (Source: Isavia) Airlines which plan to fly within the airspace where the tracks have been defined will be given flight routes which follow one of these tracks (unless they plan flights which are crossing the tracks). In other areas within the Reykjavík CTA aircraft routes can be planned in accordance with requests from airspace user, often called random routes 18. The random meaning that the plans of the airspace user are generally not known until they file a flight plan. In free route airspace the flight routes are certainly not random since each request for a flight route must be considered with respect to other air traffic and other conditions before a flight plan is accepted. By using fixed tracks the traffic control becomes more manageable by allowing a larger number of aircraft to be controlled by each ATCO. In control areas where the traffic is 18 Random routes are routes which are not predefined and published; they are based on the requests from the airlines on a per flight basis. 11
28 Chapter 2 Air Traffic Management in the Reykjavik Control Area controlled by using fixed tracks instead of allowing random routes the efficiency of the ATC operation will increase, i.e. larger number of aircraft can fly in the area without increasing the number of controllers. Although the fixed tracks solve the problem of excess demand they limit the possibilities of the airlines to choose their preferred route (which may be different from the track routes) and to make changes of their cleared 19 routes. This in turn will increase the fuel consumption and hence the cost and pollution. 2.3 Air Traffic Control The main objectives of the Air Traffic Control (ATC) operation are to ensure separation of aircraft from each other and from objects on the ground as well as expediting and maintaining an orderly and efficient flow of air traffic. Air Traffic Control is performed by a complex system where practically all decision making is made by air traffic controllers. Isvia s ATC systems are mainly in-house systems which have been adapted to the special circumstances within the Reykjavik CTA. The ATC systems include: Flight Data Processing System (FDPS) Radar Data Processing System (RDPS) Integrated Situation Display System and Voice Communication System A further description of each of these systems and their interaction can be found in Appendix II. By using the ATC systems the ATCO can monitor all aircraft in his/her sector with respect to separation minima based on surveillance data, position reports and estimated and projected aircraft position and velocity. The ATCO communicates with the pilot, receives requests for changes in the aircraft profile and provides instructions, clearances and advice regarding flight conditions (Subotic, 2007)(Flugmálastjórn Íslands, 2011). In the area where radar coverage is available the ATCO can monitor aircraft with high accuracy 20. Thus the minimum separation between two aircraft is significantly smaller while they are under radar control. This is the case because the state 21 of an aircraft is accurately determined by the radar surveillance system or by ADS-B when this service will be available For explanation see clearance in Glossary of Terms. 20 The radar data arrives at 10 second intervals. 21 The state of the aircraft includes it s position, velocity (e.g. ground speed and course) and altitude. 22 This new service is expected to be available in the end of
29 Chapter 2 Air Traffic Management in the Reykjavik Control Area In areas where there is no radar coverage, pilots report their position with regular intervals through voice or data link communications often through a remote communications centre. In such cases the ATCO uses so-called procedural separation rules. The separation minimum for procedural separation is much greater than in radar separation 23. The reason for this is that the procedural separation is based on less accurate position information. The response time for the ATCO and the pilot is also longer in procedural separation as they are normally not in direct voice contact with each other. When the aircraft is not within radar coverage the communication between the pilot and the ATCO goes through a Radio Operator at Iceland Radio at Gufunes who serves as an intermediary. 24 Figure 2.5: Radar stations and radar coverage in the Reykjavík Control Area at an altitude of feet. (Source: Isavia) Figure 2.5 shows the radar coverage in the Reykjavik CTA. In the South and East sectors there is extensive radar coverage. Most of the air traffic through these sectors can take advantage of radar separation while in the West and North sectors procedural separation is maintained. A more detailed description of the separation rules that apply in the Reykjavik CTA can be found in Annex I. 23 See Separation Service in Appendix I. 24 See Communication in Appendix II for further explanation. 13
30 Chapter 2 Air Traffic Management in the Reykjavik Control Area The pilot may request changes to the cleared profile, such as altitude, route or speed changes. When the ATCO receives such requests he considers other traffic in the area and obtains acceptance of changes at the sector boundaries. Having taken this into account the ATCO will either reject the request or issue a clearance including based on the new profile.( route, flight level and speed). The presence of the radars (and later ADS-B) in the busiest part of the Reykjavik Control Area makes it different from other oceanic Flight Information Regions (FIR). In most oceanic FIR s only procedural separation is available which does not offer much flexibility with respect to the flight routes or changes thereto. In many cases where there is procedural separation in oceanic airspace the flight route is cleared through the entire FIR. Any conflicts are resolved before the aircraft enters the oceanic airspace. In such cases the ATCO s work will mainly be to monitor the aircraft position throughout the flight. As the complexity of such work is not high, each ATCO can control a larger number of aircraft than would be possible in a more tactical operation. As opposed to this, in airspace where there is radar coverage the ATCO has more opportunities to respond to requests for changes in the flight route such as a request for increased altitude. This is possible because the separation between aircraft may be decreased and the update frequency is much higher than in the case of procedural control. This increases the possibility of providing service to the airlines which can choose more economical flight routes for their aircraft. This is of particular importance for long-haul flights where fuel consumption can be reduced by choosing a flight profile which is optimal with respect to wind and the weight of the aircraft throughout the flight. Providing radar services increases the workload on the ATCO as more complex tasks must be executed. Figure 2.6 shows the pattern of traffic flow through the Reykjavik CTA. About 25% of the traffic is on its way to and from Iceland. The most substantial traffic however is proceeding between Europe and North-America. Due to the position of the jet stream mentioned above the westbound traffic is considerably greater than the east bound traffic (74% and 25% respectively in 2011). 14
31 Chapter 2 Air Traffic Management in the Reykjavik Control Area Figure 2.6: The traffic pattern in the Reykjavik Control Area. (Source: Isavia). A large part of the traffic over the North Atlantic Ocean is strongly dependent on the jet streams as mentioned before. Hence, the forecasted wind will influence the route chosen i.e. whether the route will lie within the Reykjavik CTA or not. The traffic within Reykjavik CTA can therefore vary a lot between days. Since this is based on the weather it is difficult to predict with more than several hours of lead-time what the traffic will be. Furthermore the traffic in the Reykjavik CTA is seasonal; there is clearly a significant increase in traffic during the summer months from June to September as compared to the winter months (Isavia, 2011a). Both of these factors increase the variability of the traffic and hence introduce a challenge in manning positions in order to ensure that the number of staff on duty is sufficient to control the traffic without having too many which will incur extra cost. 15
32 Chapter 3 Measuring Performance 3. Measuring Performance 3.1 Introduction There are a large and increasing number of articles and books on how to run a business successfully. Of course they do not agree on a single road to follow towards that end. In Strategy Safari (Mintzberg, Lampel, & Ahlstrand, 1998) 10 different schools of strategy are listed which an organization can adopt in its pursuit towards better performance. Following one or the other of these strategies managers must develop performance metrics intended to measure how well the strategy is working. Without going into details this chapter contains an introduction of performance measurements in general followed by a chapter on benchmarking since one of the objectives of this thesis is to look into the benchmarking efforts which have been made in the field of Air Traffic Management (ATM). 3.2 Performance measurements Measuring performance is an integral part of doing business. For profit-making organizations the ultimate performance metric is whether the business is returning a profit; without profit the business cannot continue in the long run. But measuring profit alone is not sufficient; there are several other considerations which should be taken into account in the long run. Perhaps the organization could do better, perhaps the business is too focused on present profit at the cost of future gain and/or resources are being misused. Measurements can be used to induce better performance; the challenge is to find the right metrics, implement these and to develop the best means for using the results. Measuring the wrong parameters and using the results in an incentive system can have disastrous effects as has been learned from the last economic crisis. In this context it is appropriate to quote William Bruce Cameron : not everything that counts can be counted, and not everything that can be counted counts (Cameron, 1963). The types of measures that are commonly used in business today can be divided into three main categories (Anupindi, Chopra, Deshmukh, Van Mieghem, & Zemel, 2006): 1. Financial measures. These are the traditional accounting measurements which organizations use for the evaluation of their financial performance. For most organizations these measures can be found in annual reports and describe absolute performance (revenues, costs, net income, profit), performance relative to asset utilization (accounting ratios like Return on Assets and Return on Investment) and financial strength (cash flow). 2. External measures. These measures focus on the market (how the organization is performing compared to competitors) and the customers (how to attract and retain 16
33 Chapter 3 Measuring Performance customers). Performance metrics in this category could be for example market share, customer satisfaction and customer loyalty. 3. Internal measures. These are intended for measuring the operational performance, how well the systems of the organization are performing. The operational metrics need to be linked to the financial and external metrics. These metrics can be very different from one organization to another. An example of internal performance metrics could be number of stock outs per year, which influence both the financial metrics (lost sale) and the external metrics (customer dissatisfaction). System performance metrics can in certain cases be defined in order to compare performance between similar systems as is done in benchmarking. Performance measurements are often linked to the strategy of organizations. A well-known framework for performance measurements is the Balanced Scorecards (Kaplan & Norton, 1992) which suggests that organizations should translate their strategic goals into performance measurements and the measurements should be balanced. Following a research Kaplan and Norton found that using only financial performance metrics was not enough; these metrics should be balanced with other metrics which are drivers of future financial performance. The metrics which are drivers of future gain are in their opinion operational metrics of customer satisfaction, internal processes and the organization s innovation and improvement activities. In order to obtain balanced measurements Kaplan and Norton suggest that organizations use the following questions as guidance: How do we look to our shareholders (financial perspective)? What must we excel at (internal business perspective)? How do our customers see us (the customer perspective)? How can we continue to improve and create value (innovation and learning perspective)? The Balanced Scorecard has been widely used but implementing a performance system of this type is not always straightforward and should be considered carefully. If it is to be successful several factors have to be considered. It is important that the metrics are carefully chosen, the implementation planned, the use of the measurements considered, etc. The main learning point from the Balanced Scorecard is that that you should not use financial metrics alone and that they should be balanced against other factors which are important to the success of the organization. There are several studies and articles which give recommendation as to the design of performance measurements and performance frameworks. Neely, et. al. have in a literature review (Neely, Richards, Mills, Platts, & Bourne, 1997) gathered together some of the recommendations which have been given for the design of performance measurements, the recommendations are listed in table
34 Chapter 3 Measuring Performance Recommendations for the design of performance measurements (Neely, Richards, Mills, Platts, & Bourne, 1997). Performance measures should: - be derived from strategy - be simple to understand - provide timely and accurate feedback - be based on quantities that can be influenced, or controlled, by the user alone or in cooperation with others - reflect the business process i.e. both the supplier and customer should be involved in the definition of the measure - relate to specific goals (targets) - be relevant - be part of a closed management loop - be clearly defined - have visual impact - focus on improvement - be consistent (in that they maintain their significance as time goes by) - provide fast feedback - have an explicit purpose - be based on an explicitly defined formula and source of data - employ ratios rather than absolute numbers - use data which are automatically collected as part of a process whenever possible - be reported in a simple consistent format - be based on trends rather than snapshots - provide information - be precise be exact about what is being measured - be objective not based on opinion Table 3.1: A list of recommendation for the design of performance measurements Furthermore Neely et. al. suggests that for each metric a data sheet is prepared containing the following information: Title (a title which explains what is measured) Purpose (the rationale behind the measure) Relates to (the business objectives which the measure relates to) Target (the goal for the measure and the time limit for achieving it) Formula (the data elements and how the metric is calculated) Frequency of measurement (how often the measure is performed and reported) Frequency of review (how often the metric is re-evaluated) Who measures? (the person who collects the data and reports the results) Source of data (specification of the raw data for each data element) Who owns the measure? (the person accountable for performance improvements) What do they do? (a description of how the measure will help to improve performance) 18
35 Chapter 3 Measuring Performance Who acts on the data? (the person/team who reacts to a positive or negative results) What do they do? (define how to react to positive or negative results of the measure) Notes and comments (any additional information) Several additional suggestions have been made since this article was published. Phelps prepared in his book (Phelps, 2004) a metrics audit where the metrics are evaluated against four headings. Performance metrics should: clarify strategy capture real performance drivers promote joined-up management (ensure that metrics do not conflict and do not lead to managers playing the system) be useful for performance management (used for reward and appraisal systems) Under these headings Phelps has prepared 18 statements which the metrics should be measured against in order to evaluate their effectiveness. Phelps emphasizes the need to distinguish between metrics which are drivers on one hand and outputs on the other hand and similarly between metrics which measure present value and metrics that measure future value. Although it is very valuable information to know the profit of last year or last month, that information alone does not help organizations to increase its future profits. It is important that performance metrics provide information on the current status. However metrics which help the organization increase their performance next month and in the future should also be included. Managers should therefore ask themselves what factors will be driving future performance. In order to address this issue, organizations need to find out what are the drivers behind the performance they wish to achieve. One way to do this is to use data mining, i.e. to line up several metrics which managers suspect will influence a certain output metric and to use regression or other data mining models to find which metrics are most significant. An example of this method can be found in Smart Business Metrics (Phelps, 2004, page 49-52). While the above recommendations on how to design performance metrics were probably made considering for-profit organizations, operating in a competitive market, some of them will also apply to companies in a market where there is regulated monopoly. There are however several factors which differ for these different types of working environments. Looking for example at the Air Navigation Service Providers (ANSPs), such as Isavia, the customers are the airlines which in most cases cannot choose between different service providers. The airlines can only on rare occasions bypass certain air traffic control areas in order to avoid high charges. It is however not like the ANSPs can exploit their monopolistic position as there are several stakeholders which affect their operation. For Isavia the stakeholders are: Airlines, Aircraft owners, Airline passengers, The Icelandic Civil Aviation Administration, International Civil 19
36 Chapter 3 Measuring Performance Aviation Organization (ICAO), the Icelandic government, Eurocontrol and other service providers, especially those adjacent to the Reykjavík Control Area. On the other hand the ANSP s have obligations to service all aircraft in their control area and cannot choose to service only part of their customers or part of the control area. There are also several other obligations that are defined by laws and regulations which the ANSPs must adhere to and can be costly for smaller units to satisfy. 3.3 Benchmarking In benchmarking organizations compare their performance with their prior performance or with the performance of other organizations in the same industry. Comparing own performance with performance within the same industry can be useful where there is a forum for sharing information on best practices. In that case you can learn better ways of operating your organization from the successful practices of others (Neely, 2002). Many large companies, especially those that are made up of many business units use bestpractice benchmarking for increasing their performance (Neely, 2002). Benchmarking which are simply collecting indicators do not necessary help per se in enhancing performance, they do however give an indication of how one enterprise is performing in comparison to others and that is in itself valuable information. It would however be best if you could also learn why someone is doing better than the rest. Companies in a competitive market are constantly comparing themselves to the rivals on the market and trying to do better. For organizations operating in a market where there is regulated monopoly the drive from the competition is lacking. In such cases benchmarking may be attractive. If there is only a single monopoly in some given industry in the country or a region international benchmarking can be beneficial. However there may be additional factors which differ between countries and make the comparison difficult. Examples of such factors are the population, labour market, economic situation and geographical variables such as weather and geographical location. There are however great opportunities of co-operation between monopoly organizations and sharing of best practices, even though direct comparison of numbers do not apply. Furthermore common performance indicators can be useful for regulators or supervisory bodies to monitor performance of monopolies especially where these have been agreed by independent benchmarking companies or organizations. An example of such benchmarking is The International Transmission Operations & Maintenance Study (ITOMS ) provided by UMS Group, an international management consulting firm. ITOMS is an association of international transmission companies that work together under guidance from UMS Group. The purpose of ITOMS is to compare performance and practices within the transmission industry worldwide and to identifying and 20
37 Chapter 3 Measuring Performance share best practices. One of the participants in ITOMS is the Icelandic company Landsnet which operates Iceland s electricity transmission system. Benchmarking of performance indicators is also performed between ANSPs by two different organizations. As mentioned before Eurocontrol 25 has for several years gathered information from the ANSPs of member states and issues annually reports, the ATM Cost-Effectiveness (ACE) Benchmarking Report, showing the result of several performance indicators which have been selected for this purpose. Another organization, CANSO 26, has also suggested performance indicators for use in evaluating performance in the provision of air navigation services and annually issues a benchmarking report on Air Navigation Services Performance. 25 European Organization for the Safety of Air Navigation is an intergovernmental organization made up of 39 Member States and the European Community. 26 CANSO is an organization which represents the interests of Air Navigation Service Providers worldwide. 21
38 Chapter 4 Performance Measurements in Aviation 4. Performance Measurements in Air Traffic Management Systems 4.1 Introduction This chapter serves the purpose of gathering together performance metrics which have been used or proposed for the evaluation of the performance of Air Traffic Management (ATM) systems and services. European Organization for the Safety of Air Navigation (Eurocontrol) 27 is an intergovernmental organization made up of 39 member states and the European Community. Within Eurocontrol are several commissions, bodies and units; among them are the Performance Review Commission (PRC) and the Performance Review Unit (PRU) 28. As indicated by their name the PRC and PRU objectives are to review performance of ATM systems within the member states. The PRU gathers information from member states and annually prepares a benchmarking report, the ATM Cost-Effectiveness (ACE) Benchmarking Report (ACE report), which shows several performance indicators of the Air Navigation Service Providers (ANSPs). Furthermore, PRC annually prepares a report which is an assessment of Air Traffic Management in Europe, the Performance Review Report (PRR). The PRC, with the support of the PRU, has been designated by the European Commission as the Single European Sky (SES) 29 Performance Review Body and will as such take key responsibilities in the implementation of the SES Performance Scheme. In the SES Performance Scheme there are four performance areas where Key Performance Indicators have been defined for the first reference period ( ). Civil Air Navigation Services Organization (CANSO) is an organization which represents the interests of ANSPs worldwide. Within CANSO there is a Global Benchmarking Workgroup (GBWG), which has been gathering data from those CANSO member states participating in the benchmarking activity. GBWG has prepared annual reports for six years, the Global Air Navigation Services Performance Report (CANSO report). The ACE report and the CANSO report are both benchmarking report with the purpose of harmonizing the performance metrics used within this area and comparing performance between ANSPs using these metrics. Both Eurocontrol and CANSO offer some kind of forum for best practice sharing. The Federal Aviation Administration (FAA) Oceanic and Offshore Integrated Product Team (IPT) has studied performance metrics for oceanic Air Traffic Management (ATM) within the US National Airspace System (NAS). The results of that study and suggested performance 27 See also Glossary of Terms. 28 See Glossary of Terms for further information on PRC and PRU. 29 See Glossary of Terms for further information on SES. 22
39 Chapter 4 Performance Measurements in Aviation metrics were reported in 2004 (Wu, Hamrick, Karakis, & Merkle, 2004). Some of the metrics suggested by IPT are mentioned in this chapter. Most of them can be defined as quality of service metrics. The Danish ANSP, Naviair, has in the Business Plan for made their Key Performance Indicators (KPIs) publicly available. These KPI s are an example of metrics not intended for benchmarking with other ANSPs but rather as means for achieving their strategic goals. Naviair has defined their mission and vision. In order to realize the mission and to implement the vision Naviair has defined 4 sub-strategies and 8 critical success factors. On this basis they have defined 26 KPIs. Naviair uses Balance Scorecard to define their KPIs (Naviair, 2010). In this chapter some of Naviair KPIs will be mentioned for comparison with the benchmarking indicators. The ACE and CANSO reports are the main source documents for this study of metrics used for benchmarking performance in ATM. There are several ways to categorize the metrics currently used into performance areas. In the SES Performance Scheme there are four areas defined for EU-wide targets, these are: Safety, Environment, Capacity and Cost-Efficiency. In the SESAR 30 Performance framework this has been expanded into seven areas: Capacity, Cost Effectiveness, Efficiency, Flexibility, Predictability, Safety and Environmental Sustainability. CANSO defines four performance areas: Safety; Productivity; Cost-effectiveness; and Price, Revenue and Profitability. The GBWG has plans to add the following performance areas: Environment, Air Traffic Complexity, Density and Quality of Service and Human Resources (CANSO Global Benchmarking Workgroup, 2012). In this thesis the performance areas are divided into: Safety, Productivity, Financial, Flight Efficiency and Environmental Impact, and Quality of Service. This division of areas is selected in order to include all areas from the CANSO report, although the Cost-effectiveness and Price, Revenue and Profitability are combined into one area, namely Financial. In this chapter a brief description of each performance area will be provided and some of the performance metrics which have been suggested or used are described. The data elements that are required for calculating the metrics are discussed in more details in Glossary of Terms. All data elements used to calculate the performance indicators represent data for a whole year. 4.2 Safety Safety is of utmost importance in aviation. For every change that is made in ATM systems, safety must always be considered as it cannot be jeopardized in the pursuit of greater efficiency or effectiveness. 30 SESAR stands for Single European Sky ATM Research, see Glossary of Term for further information on SESAR. 23
40 Chapter 4 Performance Measurements in Aviation It is however not possible to optimize safety as such. If one seeks to ensure 100% safety in ATM that could only be achieved by grounding all aircraft. When considering the ATM system as a whole, safety can be considered as a constraint when optimizing the system performance with respect to other factors such as capacity, cost and efficiency. In order to ensure an acceptable level of safety, standards and regulations have been implemented. Although increasing safety is always on the agenda, any measures taken in that direction must be weighed against the effect that it has on costs, efficiency and the level of service provided to the airspace users SES Performance Scheme In the SES Performance Scheme 31, Key Performance Indicators (KPIs) for Safety are introduced. These metrics were adopted prior to the first reference period, (European Aviation Safety Agency, 2011): 1. Effectiveness of safety management. 2. Application of the harmonized severity classification of the Risk Analysis Tool 32 to allow harmonized reporting of severity assessment of: a. Separation minima infringements b. Runway incursions c. ATM special technical events. 3. Reporting of just culture 33. According to the Performance Scheme, states have to monitor and publish these Safety KPIs during the first reference period ( ). There are however no targets set for KPIs in this period. Figure 4.1 show the suggestions for safety indicators made by the Performance Review Body (PRB) for the second reference period ( ) (Performance Review Body, 2012). 31 See Glossary of Term for more information on SES Performance Scheme. 32 Risk Analysis Tool is a tool aimed to harmonize the way member states and ANSPs classify and analyze ATM safety occurrences. See also 33 See Glossary of Terms for further information on just culture. 24
41 Chapter 4 Performance Measurements in Aviation Figure 4.1: Overview of the proposals from PRB for Safety KPIs. (Source: PRB) CANSO report In the CANSO 2012 report there are four safety KPI s listed (CANSO Global Benchmarking Workgroup, 2012): 1. IFR-IFR 34 losses of separation. 2. Runway incursions. 3. Safety Management System (SMS) maturity. 4. Safety culture. CANSO gathers safety data from its members but these data are confidential and therefore not published The FAA s Oceanic and Offshore Integrated Product Team In an article from 2004 the FAA Oceanic and Offshore Integrated Product Team (IPT) suggested several metrics directed at Oceanic ANS (Wu et al., 2004). The following performance metrics may be classified as safety metrics: 1. Operational errors the number of operational errors that occur in the oceanic center and the cause of errors. 2. Altitude change requests due to weather the number of requests and the response time. 3. Deviation requests the number of requests for lateral deviation from the cleared flight plan due to weather and the response time. 34 IFR stands for Instrument Flight Rules, see Glossary of Terms. 25
42 Chapter 4 Performance Measurements in Aviation This article is from 2004 but further information on results or development of these metrics could not be found General comments on safety performance metrics Direct comparison of Safety KPI s between ANSP s is difficult and such comparison can have discouraging effect on the reporting of incidents. How incidents are defined and categorized with respect to severity affects the number of incidents reported. The Safety Regulation Commission 35 estimates that only half of the incidents that occur are reported (Performance Review Commission, 2011). The introduction of a Safety Management Systems, Just Culture 36 and harmonized severity classification has been established to address these factors. By harmonizing the severity classification and taking measures to induce reporting of incidents the comparison of safety metrics will become more realistic. Another factor which affects the comparison of safety metrics is the time it takes to investigate the incidents. Even if reports of incidents are published the publication may be delayed, depending on the severity of the incident and the speed of investigation in each state. This can make the comparison between states difficult. Furthermore, safety metrics may be available later than other performance metrics. This is a disadvantage since in the evaluation of performance, different performance areas should be considered at the same time. It is important to know as soon as possible if a positive change in one performance metric has negative effect on safety. Even though it may be difficult to accurately compare the safety KPIs between ANSPs they are still very important KPIs for comparison and guidance within each ANSP. In chapter the safety metrics for the ATM system within Isavia are listed. 4.3 Productivity When considering the ATM system as a whole the productivity of the system would, in the big picture, be the output of the system divided by all inputs to the system. There are several candidates to be considered as an output of an ATM system. The output could for example be considered as: The number of aircraft controlled. The number of controlled flight hours. The number of controlled kilometres. The number of directions/requests from the control centre. 35 The Safety Regulation Commission is an independent body to the EUROCONTROL, established for the multilateral development and harmonization of ATM safety regulations within the European Civil Aviation Conference (ECAC). 36 See Glossary of Terms for further information on Just Culture. 26
43 Chapter 4 Performance Measurements in Aviation The input can be defined as all the personnel, facilities, equipment and systems (software and hardware) in monetary or other terms which are provided in order to produce the output. Large part of these inputs such as facilities, equipment and systems are fixed, i.e. they do not change with the demand for more output in the short run. The main contributor to changes in productivity is therefore the variable input which is mainly the personnel required to produce the demanded service (the output). A large factor in the employment cost within the ATM systems is the employment cost of air traffic controllers (ATCOs). The number of ATCOs required on duty in Air Traffic Control (ATC) is dependent on the air traffic load, i.e. the demand for ATC. When looking at the input to the ATM system it is therefore logical to look at the contribution of work from the ATCOs. This contribution can be measured in number of ATCOs (in full time equivalence) or the working hours. It should be noted that some ATCOs also work on other duties and are therefore not always working in air traffic control. ATCOs are therefore divided into ATCOs in Operation (ATCO in OPS) and ATCOs on other duties. With this in mind productivity can be defined in several ways, for example using either flight hours or flown kilometres as output and using either ATCO in OPS hours of duty or number of ATCO in OPS as input. The productivity indicators from the ACE and CANSO reports and Naviair are listed in chapters ACE report The following metrics are calculated for each ANSP in the ACE 2010 report: (4.1) (4.2) In ATCO-hour Productivity the Composite Flight Hours are defined as: Composite gate-to-gate flight-hours = (En-route Flight-Hours)+(0,26 x IFR Airport Movements) (4.3) (Performance Review Unit, 2011). This is done to account for different definitions between ANSPs of when the en-route phase of the flight ends and the approach and landing starts, see also chapter 4.7. As mentioned previously the focus of this study is on the international en-route flight within the Reykjavik Control Area (CTA). Airport movements are therefore not taken into account and the Composite Flight Hours will become equal to the En-route Flight Hours when calculating ATCO-hour Productivity. The En-route Flight Hours are found by taking the difference between the time when an aircraft enters the Reykjavik CTA and the time of exit from the Reykjavik CTA. ATCO in OPS hours on Duty are defined as the total annual working hours of each ATCO working on operational duties (in ATC operations) both in Area Control Centers (ACC) and in Approach Control Units (APP). The number of hours can for example be found by using 27
44 Chapter 4 Performance Measurements in Aviation the difference between the clock-in and clock-out time for each ATCO in OPS or other methods giving similar results. 37 When considering the en-route productivity only ATCOs working in ACC should be considered, not the ones working in APP. The ATCO-hour productivity is measuring how many composite flight hours (the output) each ATCO working hour (the input) will produce and therefore the goal is to increase this indicator. Each ANSP has little influence on the number of flight hours flown in their territory and therefore need to control the ATCO hours in order to increase the productivity. There are two main factors which can be addressed in order to increase the productivity. One is directed at the work procedures of the ATCOs and the other is adjusting the number of ATCOs on duty to fluctuations in air traffic demand. As the technology has advanced, ATC systems have been developed further to make the work of the ATCOs easier and to facilitate more efficient procedures. This has enabled each ATCO to monitor greater amount of air traffic, while maintaining or increasing safety of the procedures. This can greatly affect the productivity and should be under constant consideration together with general review of procedures in order to increase performance. ATCOs are not a flexible workforce which can follow economic cycles. It is not possible to lay off ATCOs when there is a dip in the air traffic and then re-hire them when there is an increase in the traffic demand. ANSPs must use other means to adapt to fluctuation in air traffic. This can be done by using overtime and arranging shifts to adapt to the traffic pattern in each control unit. Using ATCOs on other projects is also possible in order meet fluctuation in air traffic demand. These measures to adapt to variation in traffic will however increase costs. ATCOs are expensive workforce and should therefore not be used excessively on other duties. Obtaining realistic air traffic forecasts is also a factor which is of importance when adjusting the workforce to the air traffic demand. The metric ATCO-hours on Duty per ATCO per Year is calculated for the Area Control Centers (ACC). ACC ATCOs in OPS is the number of ATCOs working in Full Time Equivalent (FTE) 38 on operational duties in the area control centre. This metric gives the average annual working hours of each ATCO in OPS and hence the utilization of each ATCO in OPS. As there is a lot of cost involved in training and educating each ATCO in OPS, it is of importance to measure their contribution to the ATC operation. Clearly the ANSP would like to maximize this number. This is however only possible up to a point as too high work load for an extended period of time can have negative effect on health and general well-being of the staff. Too high a workload could result in increase in sick days and/or higher turnover of ATCOs. Therefore these factors must be considered as well. Different legislation in each country can also affect this metric, as there may be different rules on work-hours and overtime. 37 See definition of Air Traffic Controller in Operation in Glossary of Terms. 38 See Glossary of Terms for further explanations. 28
45 Chapter 4 Performance Measurements in Aviation In addition to this, sector productivity (flight-hours per sector-hour) and staffing per sector (ATCO-hours per sector-hour) are calculated in the report but will not be dwelt on in this thesis CANSO report In the CANSO 2012 report, the following productivity metrics are listed: 1. Continental a. b. (4.4) (4.5) 2. Oceanic a. (4.6) 3. Continental and Oceanic a. Average Annual Working Hours for ATCOs in OPS There is a difference between the definition of IFR hours defined in the ACE report and the IFR hours defined in the CANSO report, (see chapter 4.7 for explanations). In order to account for this difference one minute is added to the IFR Flight Hours according to the ACE report for each take-off and/or landing (a total of two minutes for the flights which starts and ends within the same control area) to be comparable with the IFR Flight Hours from the CANSO report. In the CANSO report performance metrics are considered separately for continental and oceanic airspaces. Looking at the results of these productivity metrics in the CANSO report it turns out that for the same ANSP the productivity is much higher in the oceanic control areas than in continental control areas. The continental traffic is denser and more complex than the oceanic traffic. This is mainly due to the many airports and the complexity of the air traffic around them but also because of the many boundaries between different control areas. In contrast most of the oceanic air traffic is directed into parallel tracks throughout the flight which are more easily controlled. It should be noted here that within the Reykjavik CTA such track systems are under normal conditions only used for the NAT tracks, see chapter 2.2. According to the CANSO report the metric IFR Flight Hours per ATCO in OPS for continental air traffic controlled by NATS (UK) was 922 in 2010, while the same metric for the oceanic air traffic controlled by NATS was This means that one ATCO can control on average 922 flight hours of continental air traffic per year while in the oceanic air traffic the productivity is almost tenfold. For this reason it is reasonable to conclude that when comparing performance within the Reykjavik CTA to other control areas, one should consider performance in other oceanic areas. 29
46 Chapter 4 Performance Measurements in Aviation The metric IFR Flight Hours per ATCO in OPS calculates how many IFR flight hours each ATCO can control on average per year. IFR Flight Hours per ATCO in OPS hour is similar to the metric ATCO-hour productivity used in the ACE report. Comparing the metric ATCO-hour productivity used in the ACE report to IFR Flight Hours per ATCO in OPS it is clear that they are different although they are basically measuring the same thing (the ATCO s productivity). In the first one the denominator is ATCO hours but in the second the denominator is number of ATCOs. Mathematically the CANSO s metric IFR Flight Hours per ATCO in OPS is equal to the ACE report s metric ATCO-hour productivity times the Average Annual Working Hour for ATCOs in OPS. Looking at the two reports for the year 2009 the ATCO-hour productivity for NAVIAIR was 0,93 while the IFR Flight Hours per ATCO in OPS was flight hours/year. Both metrics give valuable information but it is likely that the ATCO hours on duty is more accurate information than the number of ATCOs in operation per year. It can be difficult to find the exact number of ATCOs in OPS, especially where there are several ATCOs who work on other duties as well as in operation. The number of ATCOs in OPS is a mean for a whole year and is therefore less accurate number compared with ATCOs hours which in many cases can be obtained from time recording systems. Both these metrics can be used to measure productivity and compare between years within the ANSP as well as comparing to other ANSPs. It is very important to monitor how changes in procedures will affect this metric to see how performance can be improved. It can also be useful for estimating the need for recruiting ATCOs on operational duties based on forecasted air traffic demand Naviair productivity indicators Naviair, the Danish ANSP, published in 2010 its business plan for 2010 to The following indicators which relate to productivity are defined under the category Internal Processes in Naviair s Balanced Scorecard: 1. Disposition efficiency En-route (operations) (4.7) 2. Disposition efficiency Tower/Approach 39 (operations) Naviair sets the targets for the en-route Disposition efficiency to be greater than while the target for the Tower/Approach Disposition efficiency is set to be greater than The term en-route operation refers to the number of flights while the term tower/approach operations refers to airport movements, i.e. take-off and landings (Naviair, 2010). Although number of flights per year can be defined as an output of the ATC system and is often used when considering traffic demand, it could be preferable to use flight hours or (4.8) 39 For Copenhagen airport. 30
47 Chapter 4 Performance Measurements in Aviation kilometres flown when calculating the productivity. The reason is that the flying time in the control area is very different between flights. In 2011 the number of flights in the Reykjavik CTA was about , the time flown in each flight in the area was from less than a minute to several hours, and about flights were less than 5 minutes in the Reykjavik CTA. If however the average flight hours per flight do not change between years then using number of flights instead of flight hours should lead to the same conclusion Additional comments on productivity metrics The productivity metrics are of great importance as they affect the total ATCO in OPS employment costs which are a considerable part of the total cost. It is a great challenge for the ANSP s to match the number of ATCO s employed and on duty to the traffic demand. In order to ensure safety the work load of each ATCO must be considered. The ATCO can spend only limited consecutive time at the controller workstation as the work demands much concentration. There is also a limit of how much traffic he/she can control at the same time. To address this, the airspace is divided into sectors which are manageable by one person or a team, depending on how this is organized in each ANSP. In the Reykjavik ACC the ATCO is under normal conditions in working position for a maximum 90 minutes, followed by a 30 minute break. Variation in air traffic demand and the complexity of the air traffic are factors which can affect ANS performance, although researches have not shown a correlation between ANS performance and these factors (Performance Review Commission, 2011). The number of available ATCOs at the control centres must be able to meet the traffic peaks. If that is not the case the ANSP is forced to constrain the traffic flow into its control area. Comparing two ANSPs with same average air traffic but one with low variation in air traffic and the other with high variation in air traffic, it is clear that the ANSP with higher variation in air traffic is forced to employ greater number of ATCOs, other things being equal. Also, it is evident that an ATCO controlling air traffic through parallel tracks with procedural separation can control much larger number of aircraft than ATCO controlling free flight air traffic with radar separation (see also chapter 2.3.). As the number of ATCOs required for these different traffic patterns and situations are different, it will affect productivity. Further discussion on the factors affecting performance can be found in chapter 5. In some areas, especially where traffic is dense the productivity of the ATM operation is increased by using fixed tracks as mentioned earlier. This should however be avoided where possible since this may result in less optimal routes from the point of view of the aircraft operation. Suboptimal routes increase fuel burn and therefore the cost for the user as well as CO 2 emission which has negative environmental effect. Whereas most oceanic ANSPs offer fixed tracks for flight routes with little possibilities to change the route of the aircraft 40, 40 For example to climb up to higher heights in order to decrease fuel consumption. 31
48 Chapter 4 Performance Measurements in Aviation Reykjavik ACC offers flexible routes. With flexibility in routing airlines will have more possibility to choose their preferred routes and to make changes to their cleared 41 routes. 4.4 Financial The increasing demand for lower charges together with increasing air traffic has led to efforts from the EU, via the SES regulations, to increase efficiency in the Air Traffic Management in Europe. As a result of this, much emphasis has been put on efforts to control cost and use funds in a more efficient way. Generally the ANSP s revenues are received through charges for the Air Navigation Services they provide. These charges are normally calculated on the basis of the forecasted cost of providing the service (corrected with respect to actual cost of the previous year). The users of the service, mainly airline companies, are charged for their use to cover the cost involved. Charging rules within the European Union are not the same as the rules which apply in the international airspace controlled by Reykjavik ACC. Air navigation service charges for the international civil air traffic controlled by Reykjavik ACC are decided in the Agreement on the Joint Financing of Certain Air Navigation Services in Iceland (Joint Financing Agreement). The charges for the international route Air Navigation Services is split into two parts: A charge for each crossing. The charge depends on whether the crossing is defined as full crossing or not. Crossing between Europe and Canada or the United States is considered full crossing. In 2012 the charge for full crossing was 32,73 GBP. Charges for flights which are not considered a full crossing is lower and the rules relating thereto can be found in AIP Iceland (Flugmálastjórn Íslands, 2011). A charge based on distance flown in the Reykjavik CTA. This charge is equal to the product of a distance factor and a unit rate. The distance factor is equal to onehundredth of the great circle distance between the entry and the exit point of the Reykjavik CTA, expressed in kilometres. More details of the distant factor can be found in the AIP Iceland. In 2012 the unit rate was 10,33 GBP. Flights flying below Flight Level 285 within the Reykjavik CTA and all flights in and out of airports located in Greenland are charged half the unit rate (Flugmálastjórn Íslands, 2011). The charging rules within EU are defined in the Commission Regulation (EC) No 1794/2006 of 6 December 2006 laying down a common charging scheme for air navigation services. Without going into details of these charging rules it should be mentioned that the en-route charges are equal to the product of a unit rate and a service unit, where the service unit is a multiplication of an aircraft weight factor and a distance factor. The main difference of the variables used in the en-route charges within EU and the Reykjavik CTA is the weight of the aircraft which is not included in the international enroute charges of the Reykjavik CTA (although it is a factor in the landing charges and the 41 For explanation see clearance in Glossary of Terms. 32
49 Chapter 4 Performance Measurements in Aviation domestic en-route charges). Also the EU en-route charges do not include the fixed charge per flight and therefore the en-route revenues do not depend on the number of flights. In this chapter the financial metrics are divided into Cost efficiency and Revenue and other financial metrics Cost efficiency When comparing costs between companies or between time periods within the same company it is preferable to express the cost in relative terms. Increase in total cost is not necessary a bad sign if the output (the goods and/or services) has also increased. The main focus in this chapter is on the cost of providing a specific service per service unit. The service unit in this relation is variously air traffic (number of flights), flight hours or airport movements. The term used for this metric is either cost efficiency or cost effectiveness. In the SES Performance Scheme cost efficiency is used while in the ACE and CANSO reports the corresponding metric is cost effectiveness SES Performance Scheme For the first reference period ( ) a Cost-efficiency KPI is defined as: The En-route ANS Provision Cost is defined in accordance with the Charging Schemes of SES. The Forecasted Traffic is given in Service Units 42 which are used for the calculation of route charges within the Eurocontrol Charging Area. The Service Unit is a multiplication of an aircraft weight factor and a distance factor. In this metric the same output is used for reference as is used when calculating the en-route charges. It should however be noted that as for en-route traffic, the weight of the aircraft does not affect the air traffic control in any way. An increase in average aircraft weight would however result in a better cost-efficiency metric without any actual increase in efficiency ACE report The following metrics which can be categorized as cost efficiency indicators are calculated for each ANSP within Eurocontrol in the ACE 2010 report: (4.9) (4.10) (4.11) (4.12) 42 The service units are defined in accordance with the definition in Annex IV of the Commission Regulation (EC) No 1794/2006 of 6 December 2006 laying down a common charging scheme for air navigation services 33
50 Chapter 4 Performance Measurements in Aviation (4.13) (4.14) (4.15) (4.16) The definition of the data elements used in the above metrics can be found in Glossary of Terms. The costs are expressed in in the ACE report and the employment costs are also expressed in Purchasing Power Parity 43 (PPP) in order to take into account the different standards of living between the states. With the first metric effort is made to measure the cost effectiveness of the whole ATM and CNS 44 systems whereas in the second the cost effectiveness of the en-route part is measured and in the third metric the cost effectiveness of the terminal part is measured. The Gate to Gate ATM/CNS Costs is equal to the sum of the En-route ATM/CNS Costs and the Terminal ATM/CNS Costs. The Composite flight hour is derived from both the Total Flight Hours and Airport IFR Movements (see formula (4.3) above). As this study is only considering the en-route traffic the En-route Cost Effectiveness is the most relevant of the first three metrics. It measures the average ATM/CNS cost per flight hour. This cost is linked to the en-route charges 45, a decrease in this cost will, other things being equal, eventually lead to lower charges. It is therefore of importance to consider ways to decrease the outcome of this metric and to monitor the metric for changes in ATM/CNS operation. In Europe staff cost is 62,9% of total ATM/CNS provision cost of which 50% is employment cost for ATCO s in OPS. The other 50% is the employment cost for support staff (Performance Review Unit, 2011). It is therefore important to monitor the staff cost and the fourth, fifth and sixth metrics are intended for that. The ATCO in OPS employment cost is measured both as per ATCO hour giving the average cost per hour and per Composite Flight Hour (per output). When the ATCO in OPS employment costs is monitored it is important to notice if a decrease in the costs results in an increase in other costs and therefore the Support Cost is monitored as well. In the Support Costs the Employment Costs for ATCO in OPS has been subtracted from the ATM/CNS Provision Costs. The Support Cost Ratio has the advantage of giving a number which is not related to any currency and is therefore easier in comparison between countries. A decrease in support cost 43 Purchasing Power Parity is an adjustment of the exchange rate so that a basket of the same goods in two different countries has the same price. See also Glossary of Terms. 44 Communication, Navigation, Surveillance. 45 The charges are dependent on flown kilometers which in turn are the product of the flight hours and speed. 34
51 Chapter 4 Performance Measurements in Aviation ratio should indicate more cost-effectiveness, other things being equal. The support cost ratio should however not be considered alone since a low ratio could be caused by high ATCOs employment costs CANSO report The following metrics which can be categorized as cost efficiency indicators are calculated in the CANSO 2012 report: 1. Continental a. (4.17) b. (4.18) c. (4.19) 2. Oceanic a. (4.20) b. Empl. Cost for ATCOs in OPS per IFR Flight Hour (4.21) c. Empl. Cost for ATCOs in OPS per ATCO in OPS (4.22) 3. Continental and Oceanic a. (4.23) b. Empl. Cost of ATCOs in OPS as a Percent of Operating Cost (4.24) c. Empl. Cost of ATCOs in OPS as a Percent of Total Cost (4.25) The oceanic metrics are calculated for six ANSPs in the CANSO report, namely FAA ATO (USA), NAV CANADA, NATS (UK), NAV Portugal, Airways New Zealand and ATNS (South Africa). The CANSO s oceanic and continental metrics are identical except for the data used to calculate them. 35
52 Chapter 4 Performance Measurements in Aviation The oceanic flight is by definition an en-route flight and the Cost per IFR Flight Hour is therefore similar to the En-route Cost Effectiveness metric from ACE report. The definition of cost 46 and IFR flight hours 47 is however not exactly the same and therefore these metrics cannot be directly compared but they are meant to capture the same performance element. Furthermore the En-route Cost Effectiveness metric from ACE report is not calculated for oceanic air traffic. CANSO s Empl. Cost for ATCOs in OPS per IFR Flight Hour is also similar to the metric from the ACE report called ATCO Employment Cost per unit of Output (see formula 4.14), especially when only en-route traffic is considered and the Composite Flight Hours becomes equal to IFR Flight Hours. The annual employment cost per ATCO in OPS is an interesting metric to compare between states. This cost is not easily controlled by the ANSPs although it may reflect the use of overtime in the operation. Overtime may however be caused by a variability in air traffic in the area. 48 Those ANSPs having high ATCO employment costs have more incentive to increase the ATCOs productivity to reduce the number of ATCO required for each controlled flight hour Revenue and other financial metrics This chapter covers some of the revenue and capital expenditures measures as well as financial ratios presented in the ACE and CANSO reports ACE report 1. En-route ANS revenues + Terminal ANS revenues (4.26) 2. Gate-to-gate ANS total capital expenditure (capex), (data from ANSP) In the ACE report both the total revenues and costs are listed for each ANSP. Since most of the ANSPs are operating on the basis of cost recovery the difference of costs and revenues is usually little. That can however happen when the air traffic is different from forecasted traffic, but then the under or over recovery is adjusted two years later. The total annual ANSP revenues may be considered as a measure of the size of the ANSP, as well as the annual IFR flight hours controlled by the ANSP, and is therefore useful when comparing the performance between different ANSPs. The Gate-to-gate ANS total capital expenditures indicates the amount of investments made by the ANSP. In the ACE report the total capital expenditure is divided into capital expenditures for systems and equipment assets, land and building assets and intangible assets. If the investments are sound, capital expenditure can indicate future increase in performance. 46 See Chapter for further information on the difference in cost definitions. 47 See Chapter for further information on the difference in IFR Flight Hours definitions 48 See Chapter 5.2. for more information on traffic variability. 36
53 Chapter 4 Performance Measurements in Aviation Capital expenditures are often considered as a percentage of total revenues or costs since they should be in right proportion, not too high and not too low. When considering capital expenditures it may give wrong indication if considered only for one year as investments may vary between years and larger investments may take several years. In the ACE 2010 report the planned cumulative capital expenditures for the period is calculated as percentage of total ANS revenues in The total planned cumulative capital expenditures for the Eurocontrol states participating in the benchmarking was 69% of the 2010 total ANS revenues. For some ANSPs this percentage was over 100%, indicating plans for large investments (Performance Review Unit (PRU), 2012). Continued low capital expenditures for several years may indicate stagnation as systems and buildings are not renovated and may become obsolescent. Continued low capital expenditures can lead to higher future costs and lost opportunities to improve performance. Too high capital expenditures may on the other hand indicate financial risk. At Isavia, all investments related to the international air traffic services must be approved by ICAO in accordance with the Joint Financing Agreement CANSO report 1. Continental a. Example Consolidated Price per 1000 KM Flight for A = (data from ANSP) 50 b. (4.27) 2. Oceanic a. (4.28) 3. Continental and Oceanic a. Return on Equity (ROE) 51 = (4.29) b. Return on Assets (ROA) 52 (4.30) c. (4.31) The CANSO oceanic metric Total ANS Revenue per IFR Flight Hour is similar to the metric Cost per IFR Flight Hour except that the cost is defined for ATC/ATFM 53 and CNS services whereas the revenues are defined for all ANS services. Also, there might be a difference in 49 Here, A320 refers to the type of aircraft, A320 from Airbus. 50 As this metric is intended for continental flight it is not relevant in this study. See definition in Glossary of Terms. 51 Further information on ROE can be found in Glossary of Terms. 52 Further information on ROA can be found in Glossary of Terms. 53 Air Traffic Flow Management; see Glossary of Terms for further information. 37
54 Chapter 4 Performance Measurements in Aviation ANS revenues and ANS costs even though for most of the ANSPs all cost is eventually recovered. The metric Cost of Capital and Depreciation as Percent of Total Cost is representing the investments made by the ANSPs. Increase in investments will increase the cost of capital and the depreciation as well. Cost of capital is the cost of debt and equity capital. ANSPs may finance new investments in different ways. In the CANSO report the cost of capital is defined in the following way: The Cost of Capital falls into two categories. The first is the interest paid to the providers of debt capital. The second is the appropriate cost of capital applied to equity capital. 1. For ANSPs with both categories, the cost of capital is the interest expense on debt capital plus the cost of capital on equity built into the ANSP charges. 2. For ANSPs with only debt capital, the cost of capital is the interest expense. 3. For ANSPs with only debt capital where the interest expense is born by the government and not reflected in the accounts of the ANSP, the cost of capital can be computed by applying the interest rate on overall government borrowing to the ANSP capital. (CANSO Global Benchmarking Workgroup, 2012) It should be noted that the rate of return can be very different between states because of different risk and accessibility of funds. The available rate of return also varies between years within the same state due to effects of economic cycles within states. This will affect the cost of capital and distort comparison between ANSPs and between years within the same ANSP Naviair financial metrics The following metrics and their definition can be found under the category Financial in Naviair s Balanced Scorecard: 1. En-route revenues: Operational revenues except revenues from the Danish Civil Aviation Administration and the Danish Meteorological Institute. 2. Revenues on fee for ATC at CPH 54 : Revenues on fee for ATC at CPH and Roskilde Airports. 3. Revenues on fee for ATC at Billund: Revenues on fee for ATC at Billund Airport. 4. Staff charges: Naviair s staff charges. 5. Other operating expenses: Naviair s other operating expenses. Naviair has set targets for each of this metric (Naviair, 2010). For the three revenue metrics reference is made to comments here above on such metrics. When considering the Staff charges and the Other operating expenses it should be noted that they are not represented in relative terms (per output) such as per IFR flight hours. As mentioned earlier it would be 54 Copenhagen Airport. 38
55 Chapter 4 Performance Measurements in Aviation easier to compare between time intervals if they would be relative since increase in operating expenses is not necessary negative if they are direct result of increase in air traffic. It is interesting to note that Naviair does not distinguish ATCO employment cost from other staff charges. They have however set the target for ATCO on other duties to be less than 70 (in 2009 ATCOs in en-route operation were 7.260) in order to limit the use of such expensive workforce in other operation Additional comments on the financial metrics Although the definitions are similar between the ACE and CANSO reports there is some difference as to the service included when calculating the revenues and costs. Figure 4.2 shows how ANS is divided into sub-categories according to a definition by Eurocontrol. This definition is provided as a guidance for the ANSPs within Eurocontrol when gathering data for the ACE report. In the ACE report the total costs refers to the costs of providing ATM and CNS services. Air Navigation Services (ANS) Communications, Navigations, Surveilance (CNS) Air Traffic Management (ATM) Meteorological Services (MET) Aeronautical Services (AIS) Search & Rescue (SAR) Communication Services Air Traffic Services (ATS) Air Traffic Flow Management (ATFM) Airspace Management (ASM) Navigation Services Air Traffic Control (ATC) Flight Information Service (FIS) Alerting Service Surveilance Services Area Control Approach Control Aerodrome Control Figure 4.2: Individual parts of Air Navigation Services as defined by Eurocontrol (Eurocontrol, 2008). In the ACE report ATM/CNS costs do not include: Costs for providing service relating to oceanic ANS, military operational air traffic and Aerodrome Flight Information Service at smaller regional aerodromes. MET costs. Regulatory and supervisory service costs. Eurocontrol costs. 39
56 Chapter 4 Performance Measurements in Aviation Payments to other ANSPs or states for delegated services. In the CANSO report the costs are divided into Oceanic and Continental for those ANSP providing both services. In the report the cost is defined as ATC/ATFM provision cost but according to J. Paul Cripwell, a member of the GBWG, CNS costs are also included. As there is a variation between states how the MET cost is accounted for and whether the service is provided for within the ANSPs, MET cost is excluded in costs. Furthermore the cost does not include costs for providing service relating to Flight Service Stations which provide traffic advisories services. Both reports define revenues for ANS, the revenues stated for a particular ANSP should therefore be the same in both reports. In order to see whether these definitions of costs are comparable, ACE 2009 report and CANSO 2010 report were compared as they both cover data for the year Eight ANSPs which only provide continental ANS service were used in the comparison. The results can be found in table 4.1. Revenues Canso 2010 ACE 2009 Revenu per Total Total Total IFR flight ANSP flight hour revenues revenues revenues in hours (USD) (USD) in '000 '000 Difference in M NAVIAIR (Denmark) Finavia (Finland) AENA (Spain) DSNA (France) LFV (Sweden) PANSA (Poland) Romatsa (Romania) LPS (Slovac Republic) Costs Canso 2010 ACE 2009 IFR flight Cost per flight Total Costs Total Costs ATM/CNS Difference ANSP hours hour (USD) (USD) in '000 costs in '000 in M NAVIAIR (Denmark) Finavia (Finland) AENA (Spain) DSNA (France) LFV (Sweden) PANSA (Poland) Romatsa (Romania) LPS (Slovac Republic) Exchange rate from Canso 2010 report: 1 USD = EUR Table 4.1 Comparison of the definition of revenues and costs in the ACE and CANSO reports. The Total Revenues in the table were calculated from IFR Flight Hours and Revenue per Flight Hour from the CANSO report and the result converted into Euros. Costs were 40
57 Chapter 4 Performance Measurements in Aviation calculated in similar way using data from the CANSO report. From the table it is clear that the reporting of cost and revenue is not exactly the same for these reports, the difference is up to 47 million which is about 6%. This should be kept in mind when making a comparison between ANSPs, it cannot be taken literally. It is likely that there will always be some variation because of errors and different interpretation in the definition of data elements. 4.5 Flight Efficiency and Environmental Factors For each flight, a trajectory with as little deviation from the optimum trajectory is sought in order to optimize fuel burn and flight time which affect the cost to airspace users and pollution. Optimum trajectory from the viewpoint of the flight operator is the trajectory where the cost is minimized with respect to wind, aircraft weight, route charges and perhaps other internal factors such as crew shifts and schedules of other flights. There are however also limiting factors which the operators must consider such as flight level capping and fixed tracks available. The flight plan filed by the flight operator might therefore not represent their optimal trajectory as it would be if their flight would be the only flight in the control area. In the flight efficiency metrics mentioned in this chapter the Great Circle 55 route has been used to represent the optimal trajectory, because of the calculation complexity of using wind optimal trajectories. The validity of this assumption will be considered in this chapter. The flight efficiency metric aims to measure, for each flight, the deviation from the optimum trajectory. Decreasing this deviation will result in less fuel burn and the metric is therefore categorized as an environmental metric since less fuel burn means lower CO 2 emission to the atmosphere. It is also possible to categorize Flight efficiency as a quality of service metric for the airspace users because of the benefits from less fuel burn. Noise in the terminal area and at airports is also an environmental factor but will not be dwelt on in this thesis as the focus is on oceanic en-route air traffic. As fuel cost has increased over the years, fuel burn has become more important and much emphasis has been placed on finding solutions which decrease fuel burn of aircraft. The flight efficiency has not been introduced as a metric for comparison between ANSPs. The ACE and CANSO reports do not include any flight efficiency metrics. The PRC has however developed a metric to calculate vertical en-route flight efficiency called flight route extension and there is a flight efficiency metric in the SES Performance Scheme. Furthermore NATS UK has developed a fuel efficiency metric called 3DiScore. In chapters these metrics will be explained but first a brief discussion on studies on flight efficiency will be provided in chapter Studies on flight efficiency There are two main sources of flight inefficiency: 55 See Glossary of Terms for more information on the Great Circle. 41
58 Chapter 4 Performance Measurements in Aviation Horizontal inefficiency, where the trajectory flown is longer in kilometres than in optimal trajectory. Vertical inefficiency, where the altitude flown at each time is not the optimum altitude. There are mainly two reasons for vertical inefficiency: o Flight level capping, e.g. the optimal cruising flight level is not available. o Suboptimal climb and descent. In the climb phase the aircraft is kept at suboptimal flight levels mainly for air traffic control operational reasons. (Performance Review Unit, 2008). In a seminar paper from 2005 results of studies of flight efficiency carried out by Eurocontrol and the FAA were introduced and compared (Kettunen et al., 2005). Both these studies focused on the horizontal flight efficiency considering the difference in actual distance flown and the great circle distance 56. The terminal area was defined as 50 NM circle from the airport in both studies, see figure 4.3. Figure 4.3: Parameters of the flight efficiency metrics. (Source: (Kettunen et al., 2005)) The Eurocontrol study showed that the actual flown distances were about 10% greater than the great circle distances, whereas the FAA study showed 6-8% excess in distance of flight. Both studies indicated that large part of the inefficiency lies in the terminal areas, which can be explain by the restrictions set in terminal areas due to congestion around the airports. It has been pointed out that using great circle distance as a reference route, may not give the correct results as it may not be the optimal route. This may especially apply for long distance hauls where the optimal route is calculated on the basis of several factors such as wind and the weight of the aircraft. In the FAA study only flights in the range of km were used. The reason for this, as stated in the paper, was that for longer flights, wind affects the choice of routes. For this reason the FAA study decided not to include flights longer than km as that could result 56 Great circle distance is the shortest distance between any two points on the surface of a sphere (Wikipedia contributors, 2012). 42
59 Chapter 4 Performance Measurements in Aviation in difference in distance which is not related to inefficiency but rather the difference between the wind optimal route and the great circle route. Using the wind optimal route when calculating flight efficiency instead of the great circle distance will increase the calculation complexity enormously which is the reason why the great circle route has been used to estimate the optimal route. While this approximation may be justified for short distances, that is not the case for long distance flights. A study performed at Ames Research Center 57, examining flights across the United States showed that the time difference between wind optimal routes and the great circle routes was on average 7 minutes (M. R. Jardin, 2004). During periods of strong jet stream this difference went up to an hour in flight time. An example of the difference can be seen in figure 4.4. Figure 4.4 shows three different routes of the flight between New York and San Francisco: the great circle route, the wind-optimal route and the route according to the flight plan. The wind optimal route is 10 minutes shorter in terms of flying time than the great circle route. Figure 4.4: Difference in great circle route and wind optimal route. Source: (M. Jardin, 2003) As can be seen from this figure the great circle distance is in this case far from being the optimal route and using that route as a reference for the Flight efficiency metric would give erroneous result. In 2011 the average IFR flight hours in the Reykjavik CTA were about 1 hour and 43 minutes and the average kilometres flown were km which is longer than the reference value of km FAA used in their study mentioned above. The maximum IFR flight hours per flight in the Reykjavik CTA went up to 3 hours and 45 minutes in Because of the effect of the jet stream in the North Atlantic oceanic airspace and the long average distance flown in the Reykjavik CTA it can be concluded that the great circle route would not be a good proxy for optimal route through the Reykjavik CTA. 57 The Ames Research Center is a NASA research center. 43
60 Chapter 4 Performance Measurements in Aviation Performance Review Commission s En-route Extension The En-route Extension as defined by the PRC is an indicator similar to Flight Efficiency calculated in the research described above in chapter It calculates the difference in the distance between the Actual route (A) and the Great Circle route (G). The reference route (the great circle route) is calculated as if the aircraft were the only one in the system, without the usual restrictions applied. It therefore describes a theoretical performance which is unachievable in a real situation but can give guidance as to how performance can be improved (Performance Review Commission, 2012). Airport B C G A R A Actual route (A) Direct Course (D) 512,6 NM Direct route extension 497,7 NM 3,0 % En-route extension 4,6 % R D C 40 NM Great Circle (G) 490,0 NM TMA interface 1,6 % Airport A Figure 4.5: En-route Extension as defined by PRC in the Performance Review Report. Figure 4.5 describes how the En-route Extension is calculated. A circle with a radius of 40 NM 58 from the airport centre is defined as a terminal area and is not included in the calculation. The En-route extension is divided into two parts: Direct route extension and TMA interface. The optimal flight, giving zero En-route Extension, would be the flight where the aircraft would depart from Airport A, go through point C, follow the Great Circle course (G) and enter the terminal area of Airport B at point C. TMA interface (Terminal Manoeuvring Area interface) is the difference between Direct course (D) and Great circle (G) and describes the inefficiency of the terminal area. The TMA interface measures the effect of going through point R of the terminal area instead of point C. Without any detours in the terminal area the TMA interface would be contributing zero to the En-route extension. In that case R would coincide with C and the Direct Course (D) would be identical with the Great Circle course (G). 58 In the 2011 Performance Report this was changed from 30 to 40 to harmonize performance indicator with the flight efficiency metric in the SES Performance scheme. 44
61 Chapter 4 Performance Measurements in Aviation Direct route extension is the difference between Actual route (A) and the Direct course (D). The Direct route extension was in 2011 the larger contributor to the En-route extension, 3%, while the TMA interface was 1,6%, giving total of 4,6% average En-route extension. This means that on average each flight was 4,6% longer (512,6 NM/949,3 km instead of 490,0 NM/907,5 km) than if it would have followed the Great Circle route. By using the Great Circle as a reference in the En-route extension, it is presumed that the Great Circle route is the best route although it is acknowledged that it may not be the case when the route is optimized with respect to wind, route charges, aircraft weight etc. As mentioned in chapter this assumption may not be valid especially in long distance haul. It is therefore noteworthy that the average flight distance in Europe mentioned here above is 949,3 km while the cut-off distance of km was used by FAA in their studies mentioned in chapter In PRR 2010 it is mentioned that the average Great Circle distance has been increasing over the years, in 2005 it was about 825 km (Performance Review Commission, 2011; page 67). This indicates that for increasing number of flights the Great Circle route may not be the optimal route and one would therefore find it appropriate that the error from this assumption would be evaluated in some way, but no such evaluation could be found in the PRR Flight efficiency metric of SES Performance Scheme The performance scheme of the Single European Sky (SES) is set forth in EU regulation no. 691/2010. In Annex I, Section 1, Item 2.1 it is stated that: For the first reference period: The first European Union-wide environment KPI shall be the average horizontal en route flight efficiency, defined as follows: the average horizontal en route flight efficiency indicator is the difference between the length of the en route part of the actual trajectory and the optimum trajectory which, in average, is the great circle, en route is defined as the distance flown outside a circle of 40 NM around the airport, the flights considered for the purpose of this indicator are: (a) all commercial IFR (Instrumental Flight Rules) flights within European airspace; (b) where a flight departs or arrives outside the European airspace, only that part inside the European airspace is considered, circular flights and flights with a great circle distance shorter than 80NM between terminal areas are excluded. (The European Parliament and the Council of The European Union, 2010). This flight efficiency indicator corresponds to the En-route extension which has been used by the PRC and is described in chapter In the regulation it is stated that the reference trajectory (route) should be the optimum trajectory which in average is the great circle. 45
62 Chapter 4 Performance Measurements in Aviation For the first reference period ( ) of the Performance Scheme there is no mandatory Environmental KPI for the ANSPs or Functional Airspace Blocks (FAB) 59. A stakeholder survey was performed for the preparation for the second reference period of SES Performance Scheme, SES II Performance Scheme Summary of Initial Stakeholder Views on RP2. Here are some of the suggestions that were made of how this indicator might be improved (Eurocontrol, 2011a): Vertical dimension of the indicator to be considered. Use of Actual route rather than flight plan route. Taxi time (Taxi-out, Taxi-in) 60. Holding time 61. Wind optimal route rather than shortest route (great circle). As a proposal of an alternative for measuring flight efficiency one suggestion was Number of direct given by controller. There are no further explanations of these suggestions in the survey. According to Denis Huet, Head of Project Office within PRU, it is proposed to add a vertical flight efficiency indicator for the second reference period for monitoring purposes only. Proposals for the second reference period are however not finalized NATS fuel efficiency metric NATS, the ANSP of the United Kingdom, has developed what they call the 3-Dimentional Inefficiency Score (3Di Score). The purpose of the 3Di Score is for NATS to be incentivized for improving fuel efficiency (Nutt, 2012). In the 3Di Score, flight profiles are compared to optimal trajectories which follow the great circle route and cruise at requested level. The 3Di Score has a horizontal component, similar to the En-route Extension (chapter ), called track extension (H). The track extension compares the Actual route to the Great Circle distance, see figure See further information on FAB in Glossary of Terms. 60 See explanations in Glossary of Terms. 61 See explanations in Glossary of Terms. 46
63 Chapter 4 Performance Measurements in Aviation Figure 4.6: The horizontal component of the 3 Di Score. (Source: (Nutt, 2012)) There is however a difference between the track extension (H) and the En-route extension, as the track extension does not exclude a 40 NM radius at the airports and uses instead the first and last point of radar contact. Furthermore the track extension (H) is the excess distance flown as a portion of the Great Circle Distance: The track extension is therefore a number without unit, the optimal value is zero. (4.32) The 3Di Score also includes a vertical component, called vertical inefficiency (V). In the vertical inefficiency the vertical components of the trajectory flown is compared to an optimal trajectory which has unrestricted climb and descent phase and the requested flight level in cruise phase. For each step, s, the vertical inefficiency, V s, is calculated on the basis of the duration of the step, the flight level of the step, the total flight time and the reference flight level. The calculation of the vertical inefficiency is shown in figure 4.7. The figure is obtained from a published decisions of the British Civil Aviation Authority (CAA) regarding the Flight Efficiency Metric (Civil Aviation Authority, 2011). The formula for the vertical flight inefficiency is: = ( ) (4.33) 47
64 Chapter 4 Performance Measurements in Aviation Where T = Total Flight Time, T S = Duration of Step, L=Reference Level and L S =Level of Step as defined in Fig 4.7. Figure 4.7: Vertical component of 3Di Score. In figure 4.7 the blue line represents the optimal trajectory and the read one represents the flight actual profile. The vertical inefficiency is calculated for each phase of the flight, the climb, cruise and the descent. As in track extension, vertical inefficiency is without unit with the optimal value of zero. Although vertical inefficiency for each step, V s, is from zero to one the inefficiency for each phase of the flight is not necessary less than one since the inefficiencies of each step are added together. Using a sample of flights from 2009, a regression analysis was conducted to establish a model where the extra fuel consumption (because of inefficiency) was expressed in terms of the horizontal and vertical components (Civil Aviation Authority, 2011). The model was tested with a test sample of flights. The fuel burn was calculated for a flight with optimal trajectory, which follows the great circle route, cruise at requested level with uninterrupted climb and descent. This was compared with the fuel burn for the actual trajectory which was followed. The reference trajectories were modelled using standard BADA 62 aircraft performance data. The actual trajectory was simulated using the same aircraft performance data and atmospheric assumptions as the reference trajectory. The fuel burn calculations were performed using a model called KERMIT 63. The results of the analysis gave the following 3Di Score: 62 BADA (Base of Aircraft Data), is an aircraft performance model developed and maintained by Eurocontrol. 63 KERMIT (Kerosene Emissions Research Model) is a NATS model which uses data on aircraft performance from the Eurocontrol BADA 3.9 database. 48
65 Chapter 4 Performance Measurements in Aviation (4.34) Where φ is the 3 Di Score, H = Horizontal Inefficiency, V CL = Vertical Inefficiency of the Climb, V CR = Vertical Inefficiency of the Cruise, V D = Vertical Inefficiency of the Descent and β are constants. The constants, which were found by regression analysis, are given in table 4.2. Parameter Coefficient β 1 0,8973 β 2 0,8233 β 3 1,1095 β 4 1,6788 β 5 0,4265 β 6 0,469 β 7 2,9618 Table 4.2: The coefficients of the 3Di Score. The components of φ are additive, φ is therefore not limited from zero to one. As the 3Di Score calculates fuel inefficiency its optimal value would be zero. Daily 3Di Scores were calculated in 2010 giving a range from 15 to 35 units. A trial flight was flown between Heathrow and Edinburgh where the flight route was meant to represent a perfect flight. The perfect flight concept involves an uninterrupted climb to cruise altitude, a direct route in cruise, followed by an uninterrupted descent. This was done to demonstrate that the 3Di could be reduced if you could follow your preferred route. The 3Di Score for the trial flight was 1,4 units (the average on the same route was 22,1) (Nutt, 2012). It was suggested in the CAA decision that the coefficients of the model should be calculated annually by repeating the regression analysis with new flight data. As with PRC s En-route extension it has been criticized that the Great Circle route is used as the reference route instead of the wind optimal route in the 3Di Score (Tate, 2011). This metric is calculated and modelled for flights in the UK airspace and can therefore not be used unchanged for other airspaces. The methodology could however be used for other airspace by using flight data from that airspace. This metric can be useful to assess changes in fuel efficiency between years within a certain control area but would hardly be suitable for benchmarking between countries since the formula for calculating the metric would not be the same. The main difference of the 3DiScore as compared to other flight efficiency metrics are the addition of the vertical component and that it does not omit a circle of 40 NM around the terminal area. 49
66 Chapter 4 Performance Measurements in Aviation The applicability of the flight efficiency metrics in Reykjavik CTA Considering the applicability of a similar metric for the Reykjavik CTA the use of great circle route as a reference would not be advisable, as mentioned before. Using wind optimal routes instead of great circle distance would however increase the calculation complexity. That does however not exclude the possibility of using wind optimal routes when calculating this metric in the future. Also, when considering the vertical inefficiency it should be noted that when in cruise phase a single flight level is not necessary optimal. It is more efficient to start the cruise in one flight level and when the aircraft has lost weight to climb to another flight level(s). When considering only the oceanic international en-route flight in the Reykjavik CTA the vertical inefficiency will be reduced to the vertical inefficiency of the cruise phase. This becomes the issue of obtaining the optimal flight level and the wind optimal horizontal route. A further study of a design of efficiency metric comparing actual routes with optimal route in Reykjavik CTA is warranted. Such metrics are of great value in large control areas where there are opportunities for fuel savings. One might consider introducing a simplified metric which captures the issue of obtaining the optimal flight level as mentioned in chapter below where the metric Altitude Change Requests is mentioned. It is furthermore possible to make the assumption that the requested flight route as defined in the flight plan filed by the flight operator is the optimal route. A metric calculating the percentage of preferred flight routes granted versus flight routes filed would therefore indicate the flight efficiency. There are however several drawbacks of such a metric. It does not calculate the fuel consumption and hence it cannot compare the optimal route to other sub-optimal routes. The flight operator might be granted second best route with little difference in fuel consumption. The flight operator might not request for the optimal route with respect to fuel consumption. Other factors might influence the requests for flight routes. There may be restrictions which limit the selection of flight routes such as predefined tracks or flight level caps. Prior experience of what is allowed/rejected may influence the choice. This may apply especially to requests for altitude change. If the pilot s experience is that such requests are normally rejected he/she may decide not to submit a request for altitude change even though such a change would decrease fuel consumption. When comparing this kind of metric between ANSPs the last point mentioned above could lead to erroneous results. As an example the optimal flight route of a specific operator might differ significantly from the predefined tracks available. 50
67 Chapter 4 Performance Measurements in Aviation The same applies for request of altitude changes. An ANSP which does not often allow changes to flight routes will probably have low number of such requests. If the flight operators/pilots have learnt under what circumstances such requests might be granted, this particular ANSP might have large percentage of altitude change requests granted. A measure of the percentage of altitude changes accepted versus altitude changes requested would therefore not necessarily measure efficiency in fuel consumption, as many aircraft might still fly in sub-optimal flight levels because of preconceptions of the pilots or the flight operator. 4.6 Quality of Service Quality of service to the airspace users is a factor which must be taken into consideration while looking at the performance of ATM systems. It should be considered while taking measures to improve other performance metrics. There are interdependencies between the service provided and cost effectiveness. It is possible to decrease cost by limiting the service provided by the ANSP. In the Reykjavik CTA an example of that could be to introduce fixed tracks resulting in less complex traffic which would require fewer ATCOs. That in turn would decrease the ATCO employment cost but the service to the airspace users would also deteriorate and would probably result in higher fuel cost 64. Demand-capacity balancing is a trade-off between quality of service and costs. If the capacity of the ATC system does not meet the air traffic demand, air traffic will be delayed or other restrictions introduced. That will have negative effect on the airspace users. If, on the other hand, the ATC capacity is higher than the air traffic demand, resources are not fully utilized which has negative effect on the cost efficiency. Furthermore, route structure, handling of requests from pilots and how well equipped the ANS system is, are factors which affect the quality of service provided by ANSPs. The main metrics representing quality of service which have been introduced are based on recorded flight delays and the flight efficiency metrics which were defined in chapter Delay/Capacity When the capacity of ATC service does not meet the air traffic demand aircraft are delayed on ground at the departing airport until the capacity issue has been resolved. A metric capturing delay is therefore also an indicator for ATC capacity. This metric does however hardly apply in the Reykjavik CTA. The reason is that there are not issued specific times (slot times) for entering Reykjavik CTA s airspace. There are several factors which affect the flight time through the oceanic airspace (such as wind and flight speed). An aircraft is usually not held at a departing airport because of air traffic in the oceanic area or at the destination airport across the ocean. 64 Using fixed tracks limits the possibility of the flight operator to use optimal flight route. 51
68 Chapter 4 Performance Measurements in Aviation On the rare occasions when there is too much traffic load in the Reykjavik CTA which cannot be resolved through other means it is possible to decrease the traffic load by requesting limitations on incoming traffic for a specific period of time. Then the Central Flow Management Unit (CFMU) 65 will temporarily limit the traffic into the Reykjavík CTA. It is however only under exceptional conditions, that capacity limits are requested. In 2011 there were no such limitations and there were only few limitations in 2010 due to the eruption in Eyjafjallajökull which caused unprecedented increase in traffic load in the area. In light of this there will be no calculations of delay in the Reykjavik CTA and hence the following metrics are only mentioned for information purposes without any further discussions SES Performance Scheme In EU regulation no. 691/2010, Annex I, Section 2, Item 3.1 the national/fab Capacity KPI is defined as: Minutes of en-route ATFM delay per flight = the difference between the take-off time requested by the aircraft operator in the last submitted flight plan and the calculated takeoff time allocated by the central unit of ATFM. The Performance Scheme includes an EU-wide target for the Capacity KPI ACE report In the ACE report the following capacity metric is indicated for each ANSP: Minutes of ATFM delays > 15 minutes. In the ACE report the cost of ground ATFM delay is estimated for each minute of delay and added to the cost of providing ATM/CNS services in a metric called Economic costeffectiveness. In this way an effort is made to represent the trade-off between the quality of service and the cost FAA Oceanic and Offshore Integrated Product Team The FAA Oceanic and Offshore Integrated Product Team suggested a measurement of delay in the following form: 1. Departure delay - the number of oceanic flights that have departure delays and the amount of time that they were delayed. 2. Arrival Delay the number of oceanic flight that arrive late and the difference between the scheduled arrival time and the actual arrival time.(wu et al., 2004). Unfortunately available information on the work of the FAA Oceanic and Offshore Integrated Product Team are scarce and further information on these metrics was not found. There is also difference between procedures in US and Europe of how capacity problems are resolved. 65 CFMU is operated by EUROCONTROL, see also Glossary of Terms. 52
69 Chapter 4 Performance Measurements in Aviation Other Quality of Service Metrics The FAA Oceanic and Offshore Integrated Product Team (IPT) suggested several metrics directed at Oceanic ANS (Wu et al., 2004). The following performance metrics may be classified as Quality of Service Metrics: 1. Altitude Change Requests - number of requests which are: a. Granted b. Modified c. Not granted or deferred 2. Response Time the difference in time from the receipt of a request and the transmission of the response to an altitude change request. 3. Entry Altitude Flown versus Filed Altitude (predictability) The percentage of flights that entered the airspace where the altitude was: a. Higher than the filed altitude b. Lower than the filed altitude c. As filed These metrics were measured monthly and displayed on a dashboard of histograms to provide a picture of the overall performance of several metrics. The metric Altitude Change Requests is in a way a vertical flight efficiency metric. When considering the oceanic control area (without departure and landing) NAT s vertical flight efficiency metric (see chapter ) reduces to the difference of the optimal flight level and the actual flight level. Here this is addressed in a different way, by counting altitude requests, rather than calculating the difference of fuel consumption between the optimal flight level and the actual flight level. ANSPs might also consider adding other metrics which are not intended for benchmarking in order to evaluate the service they provide and the trends in these services for instance on an annual basis. In the Balanced Scorecard, one of the guidelines for balanced system of performance measurement is the question (see chapter 3.2.): How do our customers see us (the customer perspective)? Metrics which focus on the client can be very useful in order to learn about their views with respect to the services available and any additional service they might appreciate. It is also important to disseminate information about the services available and to make sure the airlines are aware of the value of the services offered. 53
70 Chapter 4 Performance Measurements in Aviation 4.7 Difference in definitions in the ACE and CANSO reports Since Oceanic Air Navigation Services are the main part of the service provided by Isavia, it is important to observe that in the ACE report, data for the provision of service in oceanic areas are not included. The CANSO report divides the performance metrics into Oceanic and Continental. The CANSO 2012 report includes performance measurements from six ANSPs that manage traffic in oceanic airspace, namely FAA ATO (USA), NAV CANADA, NATS (UK), NAV Portugal, Airways New Zealand and ATNS (South Africa). In the ACE report en-route flight-hours are calculated by the Central Flow Management Unit (CFMU) from the flight plans provided by airspace users using so-called CFMU Model III 66 (Performance Review Unit, 2011). En-route flight-hours are in a way comparable with the continental flight-hours as they both are intended to capture the hours controlled by Area Control Centers (ACC) and Approach Control Units (APP). However while in Europe the definition of flight time is the time from a point after take-off to a point before landing, the definition used in the CANSO report is from wheels-up to wheels-down since that is the definition used by many of the ANSP s participating in the CANSO report. The difference has been estimated to be one minute for take-off and one minute for landing (Cripwell, 2012). As a result the flight hours are not comparable between the reports. A document called Eurocontrol Specification for Economic Information Disclosure is a guidance for the ANSPs participating in the benchmarking disclosed in the ACE report. The definition of where the en-route service ends and terminal service starts should be in accordance with definitions used for charging purposes (Eurocontrol, 2008). It is however stated in the ACE report that the definition is different between ANSPs. In order to minimize errors resulting from this the ACE reports uses composite flight hours in their calculations. Composite flight hours are defined in the ACE 2010 report as: Composite gate-to-gate flight-hours = (en-route flight-hours) + (0,26 x IFR airport movements) (Performance Review Unit, 2011). In the ACE reports the financial elements are given in Euros. In the ACE 2011 report, which reports results from 2011, the financial elements used for the calculation of performance metrics are first obtained each year in national currencies. Then they are converted to 2011 prices in their national currency, taking into account the inflation in each country. Finally the elements are converted from national currency to Euros using the 2011 exchange rate. CANSO reports are in US dollars. In the CANSO 2012 report, which reports results from 2011, the exchange rate for the end of 2011 is used for the comparison between ANSPs that year. In the trend analysis for the years a dollar pegged to the 2007 end-of-theyear exchange rate is used. 66 The CFMU Model III gives an approximation to the actual trajectory flown on the basis of the flight plan and updates of the flight plan. 54
71 Chapter 4 Performance Measurements in Aviation In both reports employment costs are also calculated using Purchasing Power Parity 67 exchange rate. As will be described in more detail in chapter there may be some difference in how the ANSPs report their revenue and costs between the ACE report and the CANSO report. 67 Purchasing Power Parity is an adjustment of the exchange rate so that a basket of the same goods in two different countries has the same price. 55
72 Chapter 5 Factors Affecting Performance 5. Factors affecting performance 5.1 Introduction Air Navigation Service Providers (ANSP) have the common purpose of providing Air Navigation Services (ANS) in accordance with international standards and recommended procedures. Consequently, their operation is in many ways similar. However, their working environment may differ considerably. When deciding which performance metrics to use, one of the criteria is that the performance which is measured is controllable by the organization or individuals responsible for carrying out the specific activity. If a party has no control over the drivers affecting a metric, that metric cannot be used to measure the performance of this party, although it may provide valuable information. Often there are several drivers of performance, some of which may be beyond control of the ANSP. The metric IFR flight hours per ATCO hours 68 is for example influenced by several factors. Unexpected decrease in air traffic has great effect on the productivity and may be very difficult to adjust to. On the other hand improvements in working procedures and innovation which enhances ATCOs productivity are controlled by the ANSP. In the ATM Cost-Effectiveness Benchmarking Report (ACE report), published annually by the Eurocontrol s Performance Review Unit, the factors affecting performance are divided into two categories: i.e. endogenous and exogenous factors. In this chapter the endogenous and exogenous factors are discussed and two factors, traffic variability and complexity, are considered further Endogenous Factors Endogenous factors are the factors affecting performance which ANSPs can control. The endogenous factors relate to how each ANSP has built up its air navigation services and how they are managed. The effects of these factors on ATCO productivity vary and sometimes it may be difficult to establish which endogenous factors are affecting productivity and how they affect the productivity. Corporate culture may for instance have great effect on ATCO productivity, while it can be very difficult both to detect the cause-effect relationship and to change the culture in order to increase productivity. On the other hand when new features or procedures in the Air Traffic Management (ATM) systems and/or equipment are introduced it is possible to compare the productivity before and after its introduction, in order to estimates the effect on productivity. 68 Here IFR is an abbreviation of Instrument Flight Hours and ATCO is an abbreviation of Air Traffic Controller (or Air Traffic Control Officer). 56
73 Chapter 5 Factors Affecting Performance The endogenous factors listed in the ACE 2009 report are (Performance Review Unit, 2011): Organizational factors Managerial & financial aspects Internal organizational structure ANSP management o Degree of centralization o Top-management leadership and o Optimization of internal processes actions o Corporate culture o Performance oriented management Extent of in-house ownership and Collective bargaining process activities Financial and accounting aspects o Leasing, renting, owning assets o Business planning process o Research & development policy o Investment policy o Outsourcing non-core activities o Balance sheet structure Human resources o Depreciation policy o Recruitment and training Operational & technical setup, o Staff/management relationships including: o Internal communication Operational organization Relationship with the customers Operational concepts and processes o Arrangements for customer o Airspace and sector design consultation o ASM, ATFM or ATFCM 69 o Disclosure of audited financial o Civil/military arrangements statements Operational flexibility o ATM systems & equipment o Human/system interaction Difference in performance between ANSPs with similar exogenous environment may be explained by varying degree of efficiencies arising from endogenous factors. However the endogenous factors may be affected by exogenous factors. Benchmarking, the comparison between two or more organizations, must therefore been considered in that light. Exogenous factor may for example affect how the ATM systems & equipment are designed. An example of this is the fact that the Reykjavik CTA is partly controlled with radar surveillance and partly by applying procedural separation. This results in a need for tailored solutions for the ATM system instead of commercial off-the-shelf solutions. This also affects the configuration and design of control sectors Exogenous factors When benchmarking performance the exogenous factors affecting performance of the ANSPs must be considered. Some of the exogenous factors are measurable and the ANSPs can be grouped on the basis of such measures and comparison performed within the groups. Other factors which may affect the ANSPs performance are not as obvious such as political and economic environment. The exogenous factors listed in ACE 2009 report are: 69 Airspace Management, Air Traffic Flow Management or Air Traffic Flow and Capacity Management. 57
74 Chapter 5 Factors Affecting Performance Legal & socio-economic conditions Overall business & economic environment o Exchange & inflation rates o Cost of living & market wage rates o Political factors o Taxes on turnover or profit o Accounting standards General labour law and rules governing industrial relations o Working hours o Retirement age o Social security and pensions Value Added Tax application Operational condition Size of the ANSP Traffic complexity o Density of traffic o Structural complexity o Traffic mix Spatial and temporal traffic variability Type of airspace under ANSP responsibility Weather There are several factors on these lists which are of significance for Isavia as they are likely to differ from those of other ANSPs: Exchange & inflation rates Inflation rates have for several years been much higher in Iceland than in the US and in the Euro-zone. In January 2009 the inflation rate in Iceland went up to a peak of 18,6% on an annual basis. From 2007 to 2012 the average annual inflation rate was 7,4%. In this thesis, calculations are performed for the period 2009 to The average inflation rate for that period was 6,7% 70 while at the same time the average inflation rate in US and the Euro-zone was less than 2%. The depreciation of the ISK versus the USD was 46% in the period The fluctuation of the USD ISK exchange rate was great, the difference of maximum and minimum daily values from the average for this period were 39% and 45%, respectively. For the same period the change between the start and end date of the USD-EUR exchange rate was less than 1%. The difference of maximum and minimum daily values from the average for this period was 15% and 14%, respectively. However for the period between and the fluctuation of the USD - ISK exchange rate was much less and similar to the USD - EUR exchange rate. The depreciation of the ISK vs. international currency increases the revenues for the air navigation service of Isavia in the local currency, as by far the largest part of the revenues are in foreign currency. A depreciation of the ISK increases the price of imported goods. As large part of consumer goods are imported or is made of imported raw material this will eventually affect the inflation rate. This may increase the cost of 70 According to information from the Central Bank of Iceland s website. 71 Using daily values from Seðlabanki Íslands and measured by the difference of first and last value of the period. 72 Currency restrictions have been in place for the whole period. 58
75 Chapter 5 Factors Affecting Performance the air navigation service, especially supplies and capital expenses. However, it should be noted that wages do not necessary increase with inflation, at least in the short run. As wages are large part of the ANS costs this may result in mismatch in revenues versus costs and hence cost-recovery. In the case of depreciation of the ISK the effect is over-recovery, while the strengthening of the ISK results in under-recovery. Size of the ANSP The size of an ANSP is usually measured in the number of annual IFR flight hours or, as in the ACE report, the composite flight hours (including part of the IFR airport movements). Total IFR flight hours in Reykjavik CTA in 2011 were , which is less than the flight hours of 18 out of 25 ANSPs in the CANSO 2012 report. Large part of costs is not dependant of the service output (i.e. the IFR Flight Hours) and is fixed. Hence the cost per IFR Flight Hours becomes high when the number of flight hours is low. The control area is also large in comparison with other ANSP which results in higher costs because of extra resources (such as communication equipment) required to service the larger area. Both these factors may affect the cost effectiveness at Isavia in comparison with other ANSPs of different size. High number of flight hours controlled should, under normal circumstances, increase the possibility of economies of scale as fixed cost will be spread over larger number of controlled flight hours. There are however little evidence showing that the larger ANSP have in fact utilized this possibility. That may however be explained by the lack of incentive to reduce cost under cost-recovery regime (Performance Review Unit (PRU), 2013). Type of airspace under ANSP responsibility There is radar surveillance available in a part of the Reykjavik CTA which is rather unusual in oceanic airspace. This affects equipment required, training of ATCOs, sector configuration etc. and will therefore increase costs as compared to control areas with no radar coverage. It also increases the possibilities to offer more service than in non-radar oceanic areas which is beneficial to the airspace users. With additional service, additional costs of providing the ANS service may be introduced although the benefits to the airspace users are likely to outweigh such additional costs. In some control areas there are restrictions due to military operations which have negative effect on the civil air traffic. In the Reykjavik CTA the effect of military operations are minimal. 73 Weather Over the North Atlantic Ocean at high latitude, strong winds from west referred to as the Jet Stream have a dominant effect on the winds aloft. 74 This greatly influences the air traffic flow across the Atlantic Ocean and introduces spatial and temporal variability in air traffic in the Reykjavik CTA as explained further in chapter For further information see Appendix I and II. 74 See Airspace Management in Appendix I. 59
76 Chapter 5 Factors Affecting Performance As the complexity of air traffic is of great importance when comparing productivity between ANSPs a separate discussion on complexity is provided in chapter 5.3. In the ACE 2011 report three exogenous factors are evaluated: the cost of living, traffic variability and traffic complexity. The cost of living is taken into account by calculating the ATCO Employment Costs per ATCO-Hour adjusted using the so-called Purchasing Power Parity (PPP) parameter 75. This method is also used in the CANSO 2012 report when calculating employment cost. Eurocontrol has developed metrics for measuring traffic variability and traffic complexity. These metrics are described in sections 5.2 and Traffic Variability The air traffic demand can vary between years, months, weeks, week-days and within a day. Providing enough personnel each day to ensure safety and a satisfactory level of service without an excessive number of personnel is therefore a challenging task. In the Performance Review Report for 2012 (PRR 2012), traffic variability is calculated as the ratio between the peak traffic and average traffic measured by the number of flights. In 2012 the average variability of daily traffic in Europe (excluding Iceland) was 1,24, i.e. the number of flights on the busiest day was 24% higher than the average traffic. The variability of daily traffic in 2012 was 1,71 in the Reykjavik CTA, as will be further discussed in chapter Seasonal variability is defined in the Performance Review Report as the ratio between the peak weekly traffic and the average weekly traffic. The average seasonal variability in 2012 was 1,15, with the highest value of 1,9 in Palma, Spain. The seasonal variability in 2012 was 1,36 in the Reykjavik CTA. Annual air traffic in Europe has been increasing for several years apart from the downturn in 2001, 2002, 2009 and 2012, as can be seen figure 5.1 from the PRR 2012 (Performance Review Commission, 2013). These downturns are to a large part caused by the global recessions in and Purchasing Power Parity uses a defined basket of goods and services to compare the prices, in national currency, between different countries. Further information on PPP can be found in glossary of Terms. 76 The recovery from recession has been slow and the global GDP growth has been fluctuating. In 2011 and 2012 the GDP growth in advanced economies has been less than 3%, according to the IMF s World Economic Outlook Update of January
77 Chapter 5 Factors Affecting Performance Figure 5.1: Air traffic growth. (Source: PRC) The annual increase is however not evenly spread across Europe and each ANSP must consider the forecasted growth in their control airspace when planning how they will meet the traffic demand. It is difficult to adjust to an unexpected downturn in annual demand for Air Traffic Control (ATC) service. ATCOs are not a flexible workforce, they need several years of training and the training must be maintained regularly to keep the ATC license. Furthermore the ANSP in each country is the only employer for ATCOs and fully trained ATCOs can therefore not be sought from the local employment market when there is sudden increase in air traffic. It is therefore not a realistic option to lay off ATCOs when there is an economic downturn and hire when the air traffic increases. 77 Seasonal variations are different between countries. It is likely that seasonality affects the productivity but when this can be predicted it is possible to minimize the effect for example by using off season time for training and having ATCOs work on special projects during off season periods. In some control areas as in the North Atlantic there is variability in the traffic due to variation in tracks which are defined according to weather conditions each day. In the Reykjavik control area 7,8% of the traffic in 2010 was in organized tracks but there is a great variability in this traffic between days (Isavia, 2011b). This variation is not regular as is the case with the summer traffic and is therefore more difficult to predict in advance. A prediction of the track traffic is made the day before the flight. Control centres in the North Atlantic airspace 77 This is especially applicable in Iceland where it would require additional training because of special circumstances in the Reykjavik CTA. Also, it is likely that the workforce flows more easily between countries in continental Europe than to and from Iceland. 61
78 Chapter 5 Factors Affecting Performance use Preferred Route Messages (PMR) from the larger airlines (such as British Airlines and Delta) to predict air traffic. The PRM messages are received on the day before flight 78. To address the variation between weekdays and within a day and its effect on productivity it is possible to use overtime and arrange the schedule of shifts in such a way that the working hours follow the demand for the ATC service. This may also be addressed by training ATCO for other operational duties while maintaining their license to operate as ATCO. However as the training of ATCOs is costly, the number of ATCOs on other duties should be kept at efficient minimum 79 if possible. 5.3 Complexity A major limiting factor of current ATM systems to meet increasing air traffic is the workload of the ATCOs which is greatly influenced by the air traffic complexity. When comparing the performance indicators such as productivity and cost effectiveness between ANSPs one of the factors that influence the performance of ATCOs is how complex their tasks are, which in turn determines how long it will take to complete each task Definition of complexity In general, complexity is considered to involve some level of difficulty. Definition of complexity in air traffic control is related to the definition of the ATCO s workload, i.e. how different air traffic flows and ATM systems affect the level of difficulty of tasks performed by the ATCOs. In a seminar paper by Meckiff et al. ATCO s workload is assumed to be a function of three elements: firstly the geometrical nature of the air traffic; secondly the operational procedures and practices used to handle the traffic, and thirdly the characteristics and behaviour of individual controllers (experience, orderliness etc) (Meckiff, Chone, & Nicolaon, 1998). In the report Complexity Metrics for ANSP Benchmarking Analysis, by the ACE working Group on Complexity (hereafter called ACE complexity report), the complexity is defined as a notion of additional controller workload beyond that directly associated with the number of flights (Performance Review Commission, 2006). In this report further aspects of the complexity are introduced: ATC procedures-related complexity additional controller workload arising from the concept of operation, ATC procedures in operation, airspace organisation, route structure, etc. Arguably these aspects are mostly internal to the ANSP; 78 See also further information on PRM in Airspace Management in Appendix I. 79 The minimum number of ATCOs on other duties which give sufficient flexibility to adjust to fluctuation in air traffic. 62
79 Chapter 5 Factors Affecting Performance Traffic characteristics complexity additional controller workload arising from the concentration, type or interaction of traffic. Arguably these aspects are mostly external to the ANSP; External complexity additional controller workload arising from the nature or structure of the airspace through which traffic is flying, also deemed to be mainly external to the ANSP (Performance Review Commission, 2006). As the ACE complexity report s main objective is to use the complexity metric for benchmarking purpose, the complexity has been defined narrowly in that context as the external factors affecting the workload Studies of ATCO workload In order to resolve the foreseeable capacity issues stemming from the limits of ATCO workload, several solutions have been suggested to reduce their workload. These solutions include: self-separation (delegation of separation tasks from the air traffic control on ground to the aircraft), reconfiguring sectors in order to decrease complexity, redefining air traffic routes and modifying ATC systems and tools. This has led to considerable amount of research on the factors affecting ATCO workload. Factors affecting ATCO workload are numerous and may not be easy to detect. ATCOs can sense the same traffic pattern in different ways depending on their experience and nature. They may also use different strategies (to resolve foreseeable complex situation) which affect their workload. The factors affecting ATCOs workload may be placed in two main categories. Factors which are controllable by the ANSP or the ATCOs such as sectorisation; working strategy and route structure on the one hand; and factors which are not controllable by ANSPs such as traffic density and traffic mix 80 on the other hand. Some factors may however be of both types, such as the number of crossing points between aircraft. Number of crossing points depends on the flight plans which are based on requests from airlines and are in that sense not controllable by the ANSP. However, in many control areas there are predefined routes which limit the number of crossing points. This limits the available routes and hence the routes specified in the flight plans filed. The crossing points in these control area are therefore indirectly controlled by the ANSP. Route structure is used to decrease air traffic complexity, which may be necessary in some circumstances i.e. when the traffic density and orientation of the traffic patterns exceed a certain level. This does however also limit the choices that airspace users have in order to define their optimal routes. In this chapter the main focus is on research of external factors which in principle are not controllable by the ANSP and how these factors affect workload. Factors which are controllable by the ANSP are of course of importance and a study of those can lead to improvements of performance. Such improvements would probably have a positive effect on one or more of the performance metrics mentions in chapter 4. As the complexity metric for 80 Traffic mix can be different kind of aircraft, different flight rules (IFR/VFR), military versus civil traffic, etc. 63
80 Chapter 5 Factors Affecting Performance benchmarking purposes is meant to account for the different environments that the ANSPs are facing, factors which are controllable by the ANSPs are in general not included. In a report prepared by the Eurocontrol Experimental Centre, a literature review is given on cognitive complexity in air traffic control from 1963 to 2003 (Hilburn, 2004). From the research mentioned it is clear that there are many factors which affect complexity; there are several ways to measure complexity (workload) and various methods of linking these together. The researchers do not agree on a single set of factors linked to complexity and the relationship between factors changes from one sector to another and even within a sector over a period of time. In Annex III, 108 factors which were considered in these research projects are listed. Traffic density is a factor which has been generally viewed as having the greatest influence on ATCO workload. Counting of air traffic has been used to predict ATCO workload and schedule shifts for many years. Several studies have confirmed that traffic density has great influence on ATCO workload. In a study by Hurst and Rose in 1978 it was found that 53% of the variance notable in activity and workload of ATCOs were attributed to traffic density (Hurst & Rose, 1978). It has also been confirmed by several studies that traffic density alone is not a sufficient indicator of workload. This is evident just by considering figure 5.2 (Hilburn, 2004). Figure 5.2: Controlled flight versus free flight. (Source: Eurocontrol Experimental Centre) In figure 5.2 the difference between the structured flight patterns and the free flight patterns is evident. The traffic density is the same in both boxes. It is clear that it is more complicated to detect conflicts in the box to the right although the headings of only four aircraft out of ten have been changed. Research indicates that the factors affecting workload are not necessary linear. In a study by Chatterji and Sridhar a neural network is used to predict low, medium or high workload based on sixteen factors. A simple model using only traffic count could be used to classify low workload accurately. However the accuracy dropped considerably for medium and high workload when only traffic count was used. The classification for the medium and high workload was improved considerably by adding complexity factors to the model. The following complexity factors were used in the model: 64
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