Global Air Navigation Services Performance Report 2015 - The Industry View

civil air navigation services organisation

Global Air Navigation Services Performance Report 2015 2010 - 2014 ANSP Performance Results The Industry View

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Global ANS Performance Report 2015 The Industry View

The CANSO Global Air Navigation Services Performance Report 2015 is the collective effort of CANSO Member air navigation service providers (ANSP), which participate in this benchmarking effort on a voluntary basis.

Editorial Team Paul Cripwell, NAV CANADA, Chair Global Benchmarking Workgroup (GBWG) Helios - CANSO Performance Benchmarking Project Team Contributors AEROTHAI - Siree Vatanavigkit, Kunthinee Karunratanakul Airways New Zealand - Nigel Fitzhardinge ATNS - Josia Manyakoana, Sibusiso Nkabinde, Mulomoni Nesengani CAAS - Carol Teo, Ho Man Lui CANSO - Eugene Hoeven DANS - Richard Smith FAA-ATO - Dina Dolan, Aleksandra Damsz, Kristin Stadum GACA - Yousef Bagis HungaroControl - Diana Galgoczi Isavia - Sigurleifur Kristjansson JANS - Masaaki Shoji LGS - Liva Krigere, Anda Sivina LPS SR - Bronislava Kubickova NAV Portugal - Nuno Simoes, Ana Pinto, Catia Santos SE Oro Navigacija - Mindaugas Gustys Sakaeronavigatsia - Tamuna Rekhviashvili

Disclaimer This report has been compiled using data provided by the participating ANSPs. In order to facilitate comparability, data for each ANSP has been transformed to be consistent with standard definitions. The resulting data and comparisons have been produced solely for the use by ANSPs, and other interested parties, to assess and appraise performance in air navigation services provision. It is not intended that the data are used for any wider purpose, nor do the data provide a definitive assessment of any number, cost, time period or other metric relating to any ANSP’s process.

December 2015

Published December 2015

Contents

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List of figures Introduction to The Industry View Performance Framework: ANS cost efficiency Methodology Industry View: Charts Global Performance Trends: One-year trend 2013 to 2014 Global Performance Trends: Three-year trend 2011 to 2014

KPI Development

References Acronyms and abbreviations

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LIST OF FIGURES Figure 1 – CANSO ANS Performance Framework

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Figure 2 – Breakdown of Costs per IFR Hours

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Figure 3 – Breakdown of ATCOs in OPS Employment Costs per ATCO in OPS

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Figure 4 – Breakdown of IFR Hours per ATCO in OPS Hours

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Figure 5 – Breakdown of ATCOs in OPS Employment Costs per IFR Hours

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Figure 6 – Chart type 1 example

Figure 7 – Chart type 2 example

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Figure 8 – Costs per IFR flight hour and traffic trend 2013-2014 real Figure 9 – Total cost per IFR flight hour 2013-2014 real

Figure 10 – ATCO employment cost per ATCO in OPS hour 2013-2014 real

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Figure 11 – IFR flight hours per ATCO in OPS hour 2013-2014 Figure 12 – Costs excluding ATCO costs per IFR flight hour 2013-2014 real

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Figure 13 – Revenue per IFR flight hour 2013 – 2014 real

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Figure 14 – Cost per IFR flight hour and traffic trend 2011 to 2014

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Figure 15 – Total cost per IFR flight hours 2011 – 2014 real

Figure 16 – ATCO employment costs per ATCO in OPS hour 2011-2014 real Figure 17 – IFR flight hours per ATCO in OPS hour 2011-2014

Figure 18 – Costs excluding ATCO costs per IFR flight hour 2011 – 2014 real Figure 19 – Revenue per IFR flight hour 2011-2014 real

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© CANSO 2015 All rights reserved. No part of this publication may be reproduced, or transmitted in any form, without the prior permission of CANSO. www.canso.org

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Global ANS Performance Report 2015 The Industry View

Introduction to The Industry View The Industry View is the second part of the CANSO Global Air Navigation Services Performance Report 2015 and should be read in conjunction with part one, The Executive Summary and part three, The ANSP View. The Industry View contains de-identified trend analysis of the data. It provides a view of the industry overall rather than the performance of individual ANSPs, supporting the conclusions presented in the Executive Summary. Identified KPI data is presented in the ANSP View report, although some ANSPs choose to opt out of this section and remain only in the anonymous data presentation.

KPI

Numerator

List of KPIs The following table lists the key performance indicators (KPIs) that are presented in this report. Four KPIs are presented in levels 1 and 2 of the CANSO Performance Framework – included later in this report – which are: cost efficiency; ATCO employment cost per ATCO hour; ATCO hour productivity; and cost excluding ATCO employment costs per IFR flight hour.

In addition, the report also includes unit air navigation services (ANS) revenue per IFR flight hour. While ANS revenues do not give the entire picture of revenue streams relevant for the ANSP they do provide an indication of profitability and price.

Denominator

1 Year

3 Years Figures 12, 13

1

Cost efficiency

Costs

IFR flight hours

Figures 6, 7

2A

ATCO employment cost per ATCO hour

Employment costs for ATCOs in operations

ATCO in operations hours

Figure 8

Figure 14

2B

ATCO hour productivity

IFR flight hours

ATCO in operations hours

Figure 9

Figure 15

2C

Cost excluding ATCO employment costs per IFR flight hour

Costs excluding ATCO employment costs

IFR flight hours

Figure 10

Figure 16

P1

ANS revenues per IFR flight hour

ANS revenues

IFR flight hours

Figure 11

Figure 17

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Performance Framework : ANS cost efficiency The cost efficiency data presented in both The Industry View and The ANSP View is structured around the CANSO Performance Framework which draws on the work of the EUROCONTROL Performance Review Unit (PRU).

As a higher level discussion of performance,

The Industry View only includes Levels 1 and 2 below. The ANSP View provides a more detailed picture and includes the three levels of the framework shown below. This may be expanded in future years depending on the demands of Members.

Figure 1 - CANSO ANS Performance Framework The framework is designed as a tool that will enable ANSPs to better understand the drivers of the trends in their cost efficiency performance1.

Level 1: The unit cost (cost per IFR hour) of ANS provision, presenting an indication of cost efficiency.

Level 2: This defines the key contributors to the unit cost, which are the costs of providing

the service, broken down into ATCO employment cost and remaining costs (total cost,

less ATCO employment cost).

1

‘Cost’ here refers to the cost incurred by air navigation service providers in providing ATM services and facilities.

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Global ANS Performance Report 2015 The Industry View

Level 3: Breaks down ATCOs in operations (OPS) productivity and ATCOs in OPS employment

costs per ATCOs in OPS hour into the constituent parts, to provide detail on IFR hours,

annual working hours and employment cost per ATCO in OPS. The high level indicator is broken down into three indicators which together drive the change in unit cost. A decrease in cost per IFR flight hour must be caused by at least one of: a decrease in ATCO employment cost per ATCO in OPS hour (2A); an increase in ATCO hour productivity (2B); or a decrease in other costs per IFR flight hours (e.g. reduction in non-staff operating costs or depreciation costs).

The relationship between the two levels is shown below. Dividing ATCO employment costs per ATCO hour (2A) by ATCO hour productivity (2B) gives ATCO employment costs per IFR flight hour.

Summing this figure with all other costs per IFR flight hour (2C) gives unit cost per IFR flight hour (1).

Analysis of the three Level 2 indicators therefore provides a picture of the drivers of the high level unit cost indicator. This gives an important insight into areas for performance improvement.

Figure 2 - Breakdown of Costs per IFR Hours In Level 3, ATCOs in OPS employment costs are broken down into three indicators which drive ATCOs in OPS employment costs per ATCO in OPS hour (2A) and ATCOs in OPS productivity (2B) and thus also ATCOs in OPS employment costs per IFR hour (2A/2B).

Figure 3 - Breakdown of ATCOs in OPS Employment Costs per ATCO in OPS

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ATCOs in OPS employment costs per ATCO in OPS hour (2A) can be calculated by dividing the unit employment cost per ATCOs in OPS (3A) by the average number of hours worked per ATCOs in OPS (3B):

Figure 4 - Breakdown of IFR Hours per ATCO in OPS Hours

ATCOs in OPS productivity (2B) can be calculated by dividing the average number of hours controlled per ATCO in OPS (3C) by the average number of hours worked per ATCO in OPS (3B).

Level 3 also provides a different way of breaking down the drivers for ATCOs in OPS employment cost per IFR flight hour. ATCOs in OPS employment costs per IFR flight hours can also be calculated by dividing the average unit employment cost per ATCOs in OPS by the average number of IFR hours controlled by each ATCO in OPS.

Figure 5 - Breakdown of ATCOs in OPS Employment Costs per IFR Hours

These levels represent the initial structure for the KPIs in this report. This will be developed in future years to include other KPIs that underlie the currently reported KPIs. However, this will be dependent on both the currently available data within the submission system, and the ability to define and collect new data elements.

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Global ANS Performance Report 2015 The Industry View

Methodology Principles and terminology Correction for inflation: all financial items included in this report are corrected for inflation.

Unless stated otherwise reference to costs implies real costs. Real costs are calculated for each country using the country specific inflation rate for each year taken from the IMF World Economic Outlook database. Values are inflated to 2014 real prices using an inflation index.

Exchange rate conversion: the analysis is based on national currency figures. The use of trends means that there is no need to convert data and avoids any distortion caused by changes in the exchange rate.

Where figures are stated in USD, data are converted using the 2014 average exchange rates from Oanda.

Equal weighting of all providers: averages and index figures are calculated by equally weighting all participating members.

Trend analysis Sample size: for analysis of costs and revenues, the sample size is defined by the set of ANSPs that submit sufficient data to calculate that particular KPI. Inclusion in the 2013-2014 data analysis requires data submission for 2013 and 2014.

Inclusion in the 2011-2014 data analysis requires data submission for 2011 and 2014.

Separation of continental and oceanic data: due to the different nature of providing oceanic compared to continental services, ANSPs that provide both oceanic and continental services are considered as two separate services. This will lead to greater weight given to ANSPs that provide both services. However, the continental and oceanic services are presented separately.

This is to retain a sample that is representative of the data, while keeping the distinction clear in the analysis.

Growth rates: growth rates are calculated as the compound annual average growth rate (CAGR), taking the nth root of the total percentage growth rate, where n is the number of years in the period being considered.

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Industry View: Charts This section includes the detailed charts showing the trend performance of reporting ANSPs over the period 2013-2014 and 20112014. The charts are preceded by a discussion of the new data presentation and how it should be interpreted.

How to use the charts There are two types of scatter plots presented here, showing anonymised trend performance across the five main indicators,

the first four following the CANSO Performance Framework: —— Cost per IFR flight hour (1) —— ATCO in OPS employment cost per ATCO in OPS hour (2A) —— ATCO in OPS productivity (2B) —— Costs (excluding ATCO in OPS employment costs) per IFR flight hour (2C) —— ANS Revenues per IFR flight hour

Chart key 2

2

Note that for the ANS revenue per IFR flight hour a decrease is denoted in purple. This is to differentiate between the two quadrants. As noted in the key messages the current data on ANS revenues are not sufficiently understood to make judgements on performance.

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Global ANS Performance Report 2015 The Industry View

Chart type 1 Shows distribution to change in cost per IFR flight hour compared to change in traffic.

—— The change in traffic (e.g. IFR flight hours) is presented on the x axis and the change in cost per IFR flight hour on the y axis

Figure 6 - Chart type 1 example

Example ANSPs: i. Increase in cost per IFR flight hour in the context of an increase in IFR flight hours. ii. Decrease in cost per IFR flight hour in the context of an increase in IFR flight hours. iii. Decrease in cost per IFR flight hour in the context of a decrease in IFR flight hours. This is especially notable in an industry where cost flexibility is difficult to manage. iv. Increase in cost per IFR flight hour in the context of a decrease in IFR flight hours.

—— The dotted line shows the average change in cost per IFR flight hour across the sample —— The bottom half below the x-axis shows a decrease in cost per IFR flight hour —— This distinction is shown using the colour coding

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Chart type 2 Shows the change in the two factors making up the indicator (e.g. costs/ IFR flight hours).

—— The denominator (e.g. IFR flight hours) is presented on the x axis and the numerator (e.g. costs) on the y axis —— The dotted line shows where the percentage change in the denominator is equal to the percentage change in the numerator and therefore where the indicator remains constant

—— The half to the bottom right of the dotted line always shows a reduction in the indicator —— This equates to a worsening in performance for cost/IFR flight hour indicators but an improvement in performance for the productivity indicator —— This distinction is shown using the colour coding

Figure 7 - Chart type 2 example Example ANSPs: Increase in cost per IFR flight hour due to: i. An increase in costs greater than the increase in flight hours ii. An increase in costs and decrease in flight hours iii. A decrease in flight hours greater than the decrease in costs

Decrease in cost per IFR flight hour due to: iv. A decrease in costs greater than decrease in flight hours v. A decrease in costs and increase in flight hours vi. An increase in flight hours greater than increase in costs

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Global ANS Performance Report 2015 The Industry View

Global Performance Trends: One-year trend 2013 to 2014 This section presents the one-year trend charts between 2013 and 2014. The order of the charts follows the performance framework: level 1 and level 2.

2013-2014

Sample Size: 34

Cost efficiency Indicator 1: Cost per IFR flight hour

Formula: Total cost/IFR flight hours

Figure 8 - Costs per IFR flight hour and traffic trend 2013-2014 real Figure 8 plots the change in real unit costs against change in traffic between 2013 and 2014. The change in real unit costs is put into the context of the change in traffic: for example, those in the top right hand quadrant experienced a real increase in unit costs and an increase in IFR flight hours.

Average unit costs across all ANSPs increased by 0.47% in real terms between 2013 and 2014 and

44% of ANSPs experienced increasing unit costs in real terms.

Furthermore, 79% of the sample experienced an increase in IFR flight hours. Of those experiencing increasing traffic, 41% increased their real unit cost. Of those experiencing decreasing traffic, 57% increased their real unit cost.

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Figure 9 - Total cost per IFR flight hour 2013-2014 real

The second chart (Fig. 9) shows traffic and costs as the two drivers of real unit cost per IFR flight hour. Those to the left and above the black dotted line experienced an increase in unit cost per IFR flight hour.

65% of the sample increased their real total costs between 2013 and 2014, whereas 79% of the sample increased their IFR flight hours.

Of those increasing their cost per IFR flight hour, 73% experienced an increase in their IFR flight hours and 7% of ANSPs decreased their real costs.

Of those decreasing their cost per IFR flight hour, 16% experienced a decrease in their IFR flight hours and 42% of the sample increased their costs.

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Global ANS Performance Report 2015 The Industry View

2013-2014

Sample Size: 32

Cost efficiency Indicator 2A: ATCO employment cost per ATCO in OPS hour Indicator 2B: ATCO hour productivity

Formula: ATCO in OPS employment costs/ ATCO in OPS hours Sample Size: 34 Formula: IFR Flight Hours/ATCO in OPS Hours

The following two graphs (Fig. 10 and Fig. 11) present the two ATCO employment cost indicators (2A and 2B) using the same style as above: i.e. breaking each indicator down to give the numerator (y axis) and denominator (x axis) as the two drivers.

Figure 10 - ATCO employment cost per ATCO in OPS hour 2013-2014 real 53% of ANSPs experienced an increase in employment cost per ATCO hour.

65% of the sample increased their total ATCO employment cost between 2013 and 2014, and the same proportion of the sample increased the number of ATCO hours.

Of those experiencing an increase in employment cost per ATCO hour, 47% experienced an increase in their ATCO hours and 17% of the sample decreased their ATCO employment costs. Of those experiencing a decrease in employment cost per ATCO hour, 13% experienced a decrease in their ATCO hours and 40% of the sample increased their employment cost.

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Figure 11 - IFR flight hours per ATCO in OPS hour 2013-2014

53% of ANSPs increased their IFR flight hours per ATCO hours.

79% of the sample increased their IFR flight hours between 2013 and 2014, whereas 65% of the sample increased the number of ATCO hours.

Of those experiencing an increase in IFR flight hours per ATCO hour, 39% experienced an increase in their ATCO hours and 11% of the sample decreased their IFR flight hours. Of those decreasing their IFR flight hours per ATCO hour, 6% decreased their ATCO hours and 69% of the sample increased their IFR flight hours.

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Global ANS Performance Report 2015 The Industry View

Sample Size: 34

2013-2014 Cost efficiency Indicator 2C: Costs excluding ATCO in OPS employment costs per IFR flight hour

Formula: Costs excluding ATCO in OPS employment costs/IFR Flight Hours

Figure 12 - Costs excluding ATCO costs per IFR flight hour 2013-2014 real In addition to ATCO employment costs, which are covered in indicators 2A and 2B, the cost per IFR flight hour is driven by non-ATCO employment costs, non-staff operating costs, depreciation costs and capital costs. All of these items are captured within this category. The weight of this category within ANS provision costs varies between providers.

Unit support cost increased for 44% of ANSPs from 2013 and 2014.

50% of the sample increased their support costs between 2013 and 2014, whereas 21% of the sample decreased their IFR flight hours.

Of those increasing their support cost per IFR flight hour, 93% experienced an increase in their IFR flight hours and 27% of the sample decreased their support costs. Of those decreasing their support cost per IFR flight hour, 32% experienced a decrease in their IFR flight hours and the same proportion of the sample increased their support costs.

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2013-2014

Sample Size: 30

ANS Revenues Indicator P1: ANS revenue per flight hour

Formula: ANS revenue/IFR flight hours

Figure 13 - Revenue per IFR flight hour 2013 – 2014 real The four previous figures (Fig. 10, 11, 12, 13) give an overview of the cost efficiency performance between 2013 and 2014. Within the context of performance, we also consider the trend in ANS revenues and its comparison with traffic trends.

While ANS revenues do not give the entire picture of revenue streams relevant for the ANSP they provide one indicator of profitability and price.

Average change in unit revenue was 6.7% with 69% of the sample increasing their real unit revenue between 2013 and 2014.

83% of ANSPs increased their total real ANS revenues between 2013 and 2014, whereas 79% of the sample increased their IFR flight hours.

Of those increasing their unit revenue, 65% experienced an increase in IFR flight hours and 5% of the sample decreased their revenue.

Of those decreasing their unit revenue, 11% experienced a decrease in IFR flight hours and 89% of the sample increased their revenue.

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Global ANS Performance Report 2015 The Industry View

Global Performance Trends: Three-year trend 2011 to 2014 This section looks at the three-year trend from 2011 to 2014. The three-year view was chosen as a compromise between a higher sample size and the number of years over which the trend analysis is done. Costs are again adjusted for inflation using a three-year inflation index.

A longer term view on cost efficiency performance is especially important in industries such as air traffic management (ATM) where costs may be inflexible over a one-year period. A threeyear view gives more scope for service providers to adjust to traffic trends or to implement measures to improve cost efficiency.

This section follows the presentation and order used in the one-year trend section. To ease comparability with the previous section the data is presented in compound annual growth rates (CAGR)3. The use of a CAGR rate shows clearly the overall trend between 2011 and 2014, however it extracts from the fluctuations that may have taken place over the intervening years, which are likely also to be important in understanding performance trends.

The sample size is smaller than for the oneyear trend analysis as a lower number of ANSPs submitted data in all years from 2011 and 2014 compared to just 2013 and 2014.

3

The compound annual growth rate is calculated by taking the nth root of the total percentage growth rate, where n is the number of years in the period being considered.

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2011-2014

Sample Size: 30

Cost efficiency Indicator 1: Cost per IFR flight hour

Formula: Total cost /IFR flight hours

Figure 14 - Cost per IFR flight hour and traffic trend 2011 to 2014

Figure 14 plots the change in real unit costs against change in traffic between 2011 and 2014. The change in real unit costs is put into the context of the change in traffic: for example, those in the top right hand quadrant experienced a real increase in unit costs in the context of an increase in IFR flight hours.

Average unit costs across all ANSPs decreased 0.3% in real terms between 2011 and 2014 and

53% of ANSPs experienced increasing unit costs in real terms.

Furthermore, 70% of the sample experienced an increase in IFR flight hours. Of those experiencing increasing traffic, 52% increased their real unit cost. Of those experiencing decreasing traffic, 55% increased their real unit cost.

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Global ANS Performance Report 2015 The Industry View

The second chart (Fig. 15) shows traffic and costs as the two drivers of real unit cost per IFR flight hour. Those to the left and above the black dotted line experienced an increase in unit cost per IFR flight hour.

Figure 15 – Total cost per IFR flight hours 2011 – 2014 real

60% of the sample increased their real total costs between 2013 and 2014, whereas 70% of the sample increased their IFR flight hours.

Of those increasing their cost per IFR flight hour, 69% experienced an increase in their IFR flight hours and 0% of ANSPs decreased their real

costs. Of those decreasing their cost per IFR flight hour, 44% experienced a decrease in their IFR flight hours and 14% of the sample increased their costs.

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2011-2014

Sample Size: 28

Cost efficiency Indicator 2A: ATCO employment cost per ATCO in OPS hour

Formula: ATCO in OPS employment costs/ ATCO in OPS hours

Indicator 2B: ATCO hour productivity

Formula: IFR Flight Hours/ATCO in OPS Hours

Figure 16 - ATCO employment costs per ATCO in OPS hour 2011-2014 real

64% of ANSPs experienced an increase in employment cost per ATCO hour.

67% of the sample increased their employment cost between 2011 and 2014, whereas 64% of the sample increased the number of ATCO hours.

Of those experiencing an increase in employment cost per ATCO hour, 67% experienced an increase

in their ATCO hours and 17% of the sample decreased their ATCO employment costs. Of those experiencing a decrease in employment cost per ATCO hour, 40% experienced a decrease in their ATCO hours and 50% of the sample increased their ATCO employment costs.

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Global ANS Performance Report 2015 The Industry View

Figure 17 - IFR flight hours per ATCO in OPS hour 2011-2014

47% of ANSPs increased their ATCO productivity as measured by IFR flight hours per ATCO hours.

70% of the sample increased their IFR flight hours between 2011 and 2014, whereas 63% of the sample increased the number of ATCO hours.

Of those experiencing an increase in IFR flight hours per ATCO hour, 29% experienced an increase in their ATCO hours and 21% of the sample decreased their IFR flight hours.

Of those decreasing their IFR flight hours per ATCO hour, 6% decreased their ATCO hours and 62% of the sample increased their IFR flight hours.

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2011-2014

Sample Size: 30

Cost efficiency Indicator 2C: Costs excluding ATCO employment costs

Formula: Costs excluding ATCO employment costs/IFR Flight Hours

Figure 18 - Costs excluding ATCO costs per IFR flight hour 2011 – 2014 real

In addition to ATCO employment costs which are covered in indicators 2A and 2B, above, the cost per IFR flight hour is driven by non-ATCO employment costs, non-staff operating costs, depreciation costs and capital costs. All of these items are captured within this category. The weight of this category within ANS provision costs varies between providers.

37% of ANSPs faced increasing unit support costs.

50% of the sample increased their support costs between 2011 and 2014, whereas 30% of the sample decreased their IFR flight hours.

Of those increasing their support cost per IFR flight hour, 82% experienced an increase in their IFR flight hours and 27% of the sample decreased their support costs. Of those decreasing their support cost per IFR flight hour, 37% experienced a decrease in their IFR flight hours and 63% of the sample increased their support costs.

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Global ANS Performance Report 2015 The Industry View

2011-2014

Sample Size: 28

ANS Revenues Indicator P1: ANS revenue per IFR flight hour

Formula: ANS revenue/IFR flight hours

Figure 19 - Revenue per IFR flight hour 2011-2014 real

The four previous figures (Fig. 16, 17, 18, 19) give an overview of the cost efficiency performance between 2011 and 2014. Within the context of performance, we also consider the trend in ANS revenues and its comparison with traffic trends.

While ANS revenues do not give the entire picture of revenue streams relevant for the ANSP they provide one indicator of profitability and price.

Average change in unit revenue was 2.1% with 57% of the sample increasing their real unit revenue between 2011 and 2014.

68% of ANSPs increased their total real ANS revenues between 2011 and 2014, and 68% of the sample increased their IFR flight hours.

Of those increasing their unit revenue, 53% experienced an increase in IFR flight hours and 12% of the sample decreased their revenue.

Of those decreasing their unit revenue, 18% experienced a decrease in IFR flight hours and 45% of the sample increased their revenue.

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KPI Development This section looks at possible KPIs that might be developed for future reports. We have received feedback on which metrics provide real value for ANSPs as comparative tools, as well as those that are difficult to track or are of limited interest. We use this information to shape the focus of future reports.

It is difficult to incorporate metrics that are useful for all ANSPs because of their diversity. For a KPI to provide value to all of the ANSPs there must be a balance between being so high-level that it fails to provide meaningful insight, and being so specific that it is of limited interest as a comparative tool for ANSPs. We are exploring new contextual data metrics to provide tools to allow this direct comparison between ANSP services. It is clear that service provision comes in many different forms, and every ANSP has a slightly different approach due to the unique circumstances of each ANSP. So we have decided to focus on creating new KPIs in certain areas that ANSPs would like to see tracked. Three of these are discussed below – including a summary of the areas and some suggested, future KPIs. Other areas of interest will be discussed in the future according to the requests of Members.

Tower and approach productivity We currently use IFR hours per ATCO hour for productivity but this measure does not properly account for tower and approach controllers, since it is based on IFR hours with no recognition of the level of workload during those hours. It is recognised that tower and approach involve a higher frequency of communication during a shorter period of time. This alone signifies a higher workload. It means that ANSPs with a higher proportion of tower and approach activity will, assuming equality otherwise, appear less productive in the current KPI (IFR flight hours/ ATCO in OPS hours).

In the longer term we will explore the creation of a composite output measure that captures both IFR hours and airport movements controlled.

This year the group collected data to calculate separate area control centre (ACC) and approach/tower (APP/TWR) productivity metrics: Tower productivity = IFR Movements/Tower ATCO Hours Approach productivity = IFR Movements/ Approach ATCO Hours This illustrates the decision, both to use IFR movements for these KPIs and to make a distinction, wherever possible, between tower and approach ATCOs. However, there will also be a combined tower and approach productivity metric, which will be especially useful for ANSPs which will struggle to separate Approach ATCO hours and Tower ATCO hours.

Visual Flight Rules Hours and Movements The addition of visual flight rules (VFR) activity would lead to greater understanding of productivity for those ANSPs where VFR activity is significant. VFR movements are a much more comparable statistic than VFR hours and thus any future KPI is likely to use movements instead of hours. However, some ANSPs have indicated that it is difficult to collect VFR data.

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Global ANS Performance Report 2015 The Industry View

Frontline Service Staff The purpose of this new KPI is to include the relative level of effort by personnel that are “one step back” from the ATCOs. ANSPs are requested to submit data on the number of staff classified in line with the EUROCONTROL Specification for Economic Information Disclosure as: C8 – Air traffic control (ATC) assistants are employees assigned to perform non-traffic control functions in an ATC unit. This includes flight data assistants but excludes technical support staff.

C9 – Non-ATCO full time equivalents (FTE) which fulfil the requirements of the operational ATM without being administrative or technical support. These functions might include, inter alia, development of ATC procedures, airspace design, incident investigation and development of operational requirements, as well as staff working on flight information service (FIS) positions that do not hold a valid ATCO licence.

C10 – Technical support staff which are undertaking maintenance, monitoring and control for on-going operational activity.

C11 – Technical support staff that are undertaking work intended to improve safety, capacity, efficiency or quality of service in the future. Such work would include planning, research and development and the implementation of new systems.

The initial KPI is: Frontline Service Productivity = IFR Hours / (C8 + C9 + C10 + C11) Due to outsourcing, it may be difficult for ANSPs to be certain of the accuracy of their data.

However, for the KPI to be useful, especially as

a trend, it is sufficient that each ANSP uses the same method when collecting the data each year as it did the year before.

In the future this KPI may be included, especially as a trend, but it is not included in this report. However, the relevant data has been collected to allow for trend data to be available as soon as possible.

The reason for following this KPI as a trend is to track the impact of the anticipated increase in technology on frontline staff. It will be interesting to track this metric for an extended period of time because, as frontline staff cannot be changed quickly, it may give us a better idea of the results of ANSPs changing their frontline staff structure than the data for each year.

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References EUROCONTROL Specification for Economic Information Disclosure V2.6 EUROCONTROL Specification for Economic Information Disclosure V3.0 Oanda exchange rate data: www.oanda.com/currency/historical-rates/ IMF World Economic Outlook database: www.imf.org/external/pubs/ft/weo/2014/01/weodata/download.aspx

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Global ANS Performance Report 2015 The Industry View

Acronyms and abbreviations

ACC ANS ANSP APP ATC ATCO ATM CAGR CANSO FIS FTE GBWG IFR IMF KPI OPS TWR USD VFR

Area control centre Air navigation services Air navigation service provider Approach control Air traffic control Air traffic control officer Air traffic management Compound annual growth rate Civil Air Navigation Services Organisation Flight information service Full time equivalent Global Benchmarking Workgroup Instrument flight rules International Monetary Fund Key performance indicator Operations Tower United States Dollar Visual flight rules

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CANSO Members CANSO – the Civil Air Navigation Services Organisation – is the global voice of air traffic management (ATM) worldwide. CANSO Members support over 85% of world air traffic. Members share information and develop new policies, with the ultimate aim of improving air navigation services (ANS) on the ground and in the air.

CANSO represents its Members’ views to a wide range of aviation stakeholders, including the International Civil Aviation Organization, where it has official Observer status. CANSO has an extensive network of Associate Members drawn from across the aviation industry. For more information on joining CANSO, visit www.canso.org/joiningcanso.

civil air navigation services organisation

Full Members - 88 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —

Aeronautical Radio of Thailand (AEROTHAI) Aeroportos de Moçambique Air Navigation and Weather Services, CAA (ANWS) Air Navigation Services of the Czech Republic (ANS Czech Republic) AirNav Indonesia Air Traffic & Navigation Services (ATNS) Airports and Aviation Services Limited (AASL) Airports Authority of India (AAI) Airports Fiji Limited Airservices Australia Airways New Zealand Albcontrol Austro Control Avinor AS AZANS Azerbaijan Belgocontrol Bulgarian Air Traffic Services Authority (BULATSA) CAA Uganda Cambodia Air Traffic Services Co., Ltd. (CATS) Civil Aviation Authority of Bangladesh (CAAB) Civil Aviation Authority of Botswana Civil Aviation Authority of Mongolia Civil Aviation Authority of Nepal (CAAN) Civil Aviation Authority of Singapore (CAAS) Civil Aviation Authority of the Philippines Civil Aviation Regulatory Commission (CARC) COCESNA Croatia Control Ltd DCA Myanmar Department of Airspace Control (DECEA) Department of Civil Aviation, Republic of Cyprus DFS Deutsche Flugsicherung GmbH (DFS) Dirección General de Control de Tránsito Aéreo (DGCTA) DSNA France Dubai Air Navigation Services (DANS) Dutch Caribbean Air Navigation Service Provider (DC-ANSP) ENANA-EP ANGOLA ENAV S.p.A: Società Nazionale per l’Assistenza al Volo ENAIRE Estonian Air Navigation Services (EANS) Federal Aviation Administration (FAA) Finavia Corporation General Authority of Civil Aviation (GACA) Ghana Civil Aviation Authority (GCAA) HungaroControl Pte. Ltd. Co. Instituto Dominicano de Aviacion Civil (IDAC) Israel Airports Authority (IAA) Irish Aviation Authority (IAA) ISAVIA Ltd Japan Air Navigation Service (JANS) Kazaeronavigatsia Kenya Civil Aviation Authority (KCAA) Latvijas Gaisa Satiksme (LGS)

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Letové prevádzkové Služby Slovenskej Republiky, Štátny Podnik Luchtverkeersleiding Nederland (LVNL) Luxembourg ANA Maldives Airports Company Limited (MACL) Malta Air Traffic Services (MATS) National Airports Corporation Ltd. National Air Navigation Services Company (NANSC) NATS UK NAV CANADA NAV Portugal Naviair Nigerian Airspace Management Agency (NAMA) Office National de LÁviation Civile (OFNAC) Office National Des Aéroports (ONDA) ORO NAVIGACIJA, Lithuania PIA “Adem Jashari” - Air Control J.S.C. PNG Air Services Limited (PNGASL) Polish Air Navigation Services Agency (PANSA) Public Authority for Civil Aviation - Oman (PACA) ROMATSA Sakaeronavigatsia Ltd SENEAM Serbia and Montenegro Air Traffic Services Agency (SMATSA) Serco skyguide Slovenia Control State Airports Authority & ANSP (DHMI) Sudan Air Navigation Services Department Swaziland Civil Aviation Authority Tanzania Civil Aviation Authority Trinidad and Tobago CAA The LFV Group Ukrainian Air Traffic Service Enterprise (UkSATSE) U.S. DoD Policy Board on Federal Aviation Viet Nam Air Traffic Management Corporation (VATM)

Gold Associate Members - 11 — — — — — — — — — — —

Airbus ProSky Anhui Sun Create Electronics Co., Ltd. Boeing Exelis, inc.

FREQUENTIS AG GroupEAD Europe S.L. Inmarsat Plc Lockheed Martin Raytheon Selex ES Thales

Silver Associate Members - 70 — — — — —

42 Solutions B.V. Adacel Inc. Aeronav Inc. Aireon Air Traffic Control Association (ATCA)

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ALES a.s.

Association Group of Industrial Companies “TIRA” Corporation ATAC ATCA – Japan ATECH Negócios em Tecnologia S/A Aveillant Aviation Advocacy Sarl Aviation Data Communication Corp (ADCC) Avibit Data Processing GmbH Avitech GmbH Bayanat Engineering Group Brüel & Kjaer EMS CGH Technologies, Inc. Comsoft GmbH CSSI, Inc. Airbus Defence and Space EIZO Technologies GmbH European Satellite Services Provider (ESSP SAS) Emirates ENAC Entry Point North Era Corporation Esterline Etihad Airways Exelis Orthogon Guntermann & Drunck GmbH Harris Corporation Helios Honeywell International Inc. / Aerospace IDS – Ingegneria Dei Sistemi S.p.A. Indra Navia AS Indra Sistemas INECO Integra A/S Intelcan Technosystems Inc. International Aero Navigation Systems Concern, JSC Jeppesen JMA Solutions Jotron AS LAIC Aktiengesellschaft LEMZ R&P Corporation MDA Systems Ltd. Metron Aviation Micro Nav Ltd The MITRE Corporation – CAASD MLS International College MovingDot NEC Corporation NLR Northrop Grumman NTT Data Corporation PASSUR Aerospace Quintiq Rockwell Collins, Inc. Rohde & Schwarz GmbH & Co. KG RTCA, Inc. Saab AB Saab Sensis Corporation Saudi Arabian Airlines SENASA SITA Snowflake Software Ltd STR-SpeechTech Ltd. Tetra Tech AMT Think Research Limited

Membership list correct as of 11 December 2015. For the most up-to-date list and organisation profiles go to www.canso.org/canso-members