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EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION

EUROCONTROL

EUROPEAN AIR TRAFFIC MANAGEMENT PROGRAMME

Airport CDM Cost Benefit Analysis

Edition Number : 1.4 Edition Date : 11/04/2008 Status : Released Issue Intended for : General Public


Page ii Released Issue Edition Number: 1.4

DOCUMENT CHARACTERISTICS

TITLE


EATMP Infocentre Reference:

Document Identifier Edition Number: 1.4 Edition Date: 11/04/2008

Abstract

Keywords

Contact Person(s) Tel Unit Elisabeth LAGIOS +32 2 729 3390 DAP/AOE

STATUS, AUDIENCE AND ACCESSIBILITY Status Intended for Accessible via

Working Draft General Public Intranet Draft EATMP Stakeholders Extranet Proposed Issue Restricted Audience Internet (www.eurocontrol.int) Released Issue Printed & electronic copies of the document can be obtained from

the EATMP Infocentre (see page iii)

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EATMP Infocentre EUROCONTROL Headquarters 96 Rue de la Fusée B-1130 BRUSSELS Tel: +32 (0)2 729 51 51 Fax: +32 (0)2 729 99 84 E-mail: [email protected] Open on 08:00 - 15:00 UTC from Monday to Thursday, incl.

DOCUMENT APPROVAL

The following table identifies all management authorities who have successively approved the present issue of this document.

AUTHORITY NAME AND SIGNATURE DATE

Please make sure that the EATMP Infocentre Reference is present on page ii.

Airport CDM Project Manager

Elisabeth LAGIOS

Airport Operations Programme

Manager

Eric MIART

Head of Airport Operations and

Environment

Paul WILSON


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DOCUMENT CHANGE RECORD

The following table records the complete history of the successive editions of the present document. EDITION NUMBER

EDITION DATE

INFOCENTRE REFERENCE REASON FOR CHANGE PAGES

AFFECTED

0.1 20/10/2006 1st Draft (review by CDM team)

0.2 27/10/2006 2nd Draft (review by CDM team)

0.3 26/11/2006 3rd Draft (review by CDM team)

0.4 20/12/2006 4th Draft (review by CDM team)

0.5 08/01/2007 5th Draft (review by CDM team)

0.6 09/02/2007 6th Draft (review by CDM CBA team – external stakeholders)

0.7 03/04/2007 7th Draft (including recommendations from Site Specific Workshop – Feb 2007, review CDM team)

0.8 19/04/2007 8th Draft (review by E Miart)

0.9 25/05/2007 9th Draft (including comments E Miart / review by P Wilson)

1.0 10/07/2007 Final Draft – (including comments P Wilson)

1.1 18/09/2007 Minor adaptations requested by APRAG

1.2 24/09/2007 Proposed Issue (adaptations requested by APRAG applied on version sent to AOT/22)

1.3 28/03/2008 Formatting Issues

1.4 11/04/08 Formatting Issues


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CONTENTS

DOCUMENT CHARACTERISTICS.............................................................................ii

DOCUMENT APPROVAL..........................................................................................iii

DOCUMENT CHANGE RECORD..............................................................................iv

1. EXECUTIVE SUMMARY ......................................................................................1

2. INTRODUCTION...................................................................................................5 2.1 Overview Airport CDM ..............................................................................................................5 2.2 CBA Scope and Objectives.......................................................................................................5

2.2.1 Data Sources.....................................................................................................................7

2.2.2 Double Counting................................................................................................................8

2.3 CBA Overview...........................................................................................................................8

2.3.1 EMOSIA Overview...........................................................................................................10

3. BASELINE ASSUMPTIONS...............................................................................12 3.1 Airport Baseline Assumptions .................................................................................................12 3.2 ATC Baseline Assumptions.....................................................................................................12 3.3 Ground Handling Baseline Assumptions ................................................................................12 3.4 Airline Baseline Assumptions..................................................................................................12 3.5 Network Baseline Assumptions ..............................................................................................12 3.6 General Assumptions..............................................................................................................12

4. BENEFITS ..........................................................................................................14 4.1 Benefit Mechanisms................................................................................................................14 4.2 Benefits Trade-offs..................................................................................................................15 4.3 Intangible Benefits...................................................................................................................16 4.4 Results from Trials ..................................................................................................................17

5. OVERALL RESULTS .........................................................................................18 5.1 Return on investment period or payback period .....................................................................18 5.2 Quantitative and qualitative analysis by partner .....................................................................19 5.3 Benefits obtained by partner and total costs...........................................................................20 5.4 Cost Effectiveness ..................................................................................................................20 5.5 Network Benefits .....................................................................................................................21


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6. AIRPORT ............................................................................................................22 6.1 Airport Benefits........................................................................................................................22

6.1.1 Airport Revenue...............................................................................................................22

6.1.2 Airport Operational Efficiency..........................................................................................23

6.2 Airport Costs ...........................................................................................................................23 6.3 Benefits and Costs Key Variables...........................................................................................23

6.3.1 Benefits............................................................................................................................24

6.3.2 Costs ...............................................................................................................................24

6.3.3 Airport Data .....................................................................................................................24

6.4 Operational Examples.............................................................................................................25 6.5 Results from Analysis..............................................................................................................26

6.5.1 Sensitivity Analysis..........................................................................................................26

6.5.2 Probabilistic Analysis.......................................................................................................27

6.5.3 Cash Flow Analysis .........................................................................................................28

7. ATC.....................................................................................................................29 7.1 Benefits ...................................................................................................................................29

7.1.1 Improvement in Working Environment ............................................................................29

7.1.2 Efficiency Increase ..........................................................................................................29

7.1.3 Higher Service Quality.....................................................................................................29

7.1.4 Generic Airport contribution to Network Benefits ............................................................29

7.2 Costs .......................................................................................................................................30 7.3 Benefits and Costs Key Variables...........................................................................................30

7.3.1 Benefits............................................................................................................................30

7.3.2 Costs ...............................................................................................................................31

7.3.3 ATC Variables .................................................................................................................31





8. GROUND HANDLERS .......................................................................................35 8.1 Benefits ...................................................................................................................................35

8.1.1 Improved Efficiency .........................................................................................................35


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8.1.2 Improved Customer Satisfaction .....................................................................................36

8.1.3 Lower Prices (Airline Benefit) ..........................................................................................36


8.3.1 Benefits............................................................................................................................37

8.3.2 Costs ...............................................................................................................................37

8.3.3 GH Variables ...................................................................................................................38





9. AIRLINES ...........................................................................................................42 9.1 Benefits ...................................................................................................................................42

9.1.1 Delay Cost Savings .........................................................................................................42


9.3.1 Benefits............................................................................................................................44

9.3.2 Costs ...............................................................................................................................44

9.3.3 Airline Variables Data......................................................................................................45





10. NETWORK BENEFITS (assumptions only – further study planned 2007-2009)..........................................................................................................49

10.1 Benefits ...................................................................................................................................50

11. ENVIRONMENTAL SUSTAINABILITY ..............................................................52

12. CONTRIBUTION BY EACH AIRPORT CDM ELEMENT TO THE TOTAL BENEFITS ..........................................................................................................55

13. CONCLUSIONS AND RECOMMENDATIONS...................................................56


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14. REFERENCES....................................................................................................57

15. GLOSSARY AND DEFINITIONS........................................................................58

16. APPENDIX A - WORKSHOPS ...........................................................................62

17. APPENDIX B – EMOSIA PROCESS..................................................................63

17.1.1 Common Pitfalls to Avoid ................................................................................................64

17.1.2 Overlooked or Underestimated Costs .............................................................................64

17.1.3 Double Counting..............................................................................................................64

17.1.4 Dealing with Uncertainties...............................................................................................66

17.1.5 Expert Judgement ...........................................................................................................66

18. APPENDIX C – ELABORATION OF ECONOMIC MODELS .............................68 18.1 Influence Diagrams .................................................................................................................68

18.1.1 EMOSIA Models ..............................................................................................................69

18.1.2 Model Spreadsheets .......................................................................................................69

18.2 Running the Models ................................................................................................................70 18.3 Appraisal of Results ................................................................................................................70

19. APPENDIX D – SENSITIVITY ANALYSIS .........................................................71

20. APPENDIX E – PROBABILISTIC ANALYSIS....................................................72

21. APPENDIX F – ANALYSIS AND INTERPRETATION OF RESULTS................73 21.1 Detailed Revision Process ......................................................................................................73

22. APPENDIX G – FORMULAE USED IN COST-BENEFIT ANALYSIS................75 22.1 Net Present Value ...................................................................................................................75 22.2 Benefit Cost Ratio ...................................................................................................................75 22.3 PayBack Period.......................................................................................................................75

23. APPENDIX H – SUMMARY RESULTS TABLE (BASE VALUES) ....................76

24. APPENDIX I – MODEL STRUCTURE - AIRPORT.............................................77 24.1 Functional Description of Airport Model ..................................................................................77 24.2 Model Structure.......................................................................................................................78

25. APPENDIX J – MODEL STRUCTURE - ATC ....................................................79 25.1 Functional Description of ANSP..............................................................................................79 25.2 Model Structure.......................................................................................................................80


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26. APPENDIX K – MODEL STRUCTURE – GROUND HANDLERS......................81 26.1 Functional Description of GH Model .......................................................................................81

26.1.1 Model – Influence Diagram .............................................................................................82

27. APPENDIX L – MODEL STRUCTURE - AIRLINES...........................................83 27.1 Functional Description of Airline Model...................................................................................83

27.1.1 Model – Influence Diagram .............................................................................................84


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1. EXECUTIVE SUMMARY

Airport CDM is here today to assist in bringing airport partners together to help them make better decisions based on more accurate and timely information, creating a shared situational awareness identical for all partners. The list of enablers for the future Air Traffic Management operational concept is long and varied. As part of the DMEAN Framework Programme, Airport CDM is identified as the driver and mechanism to dynamically integrate airports and the Network. The resulting improvements in resource usage, schedule maintenance and flexibility in reacting to events benefits airspace users, airport operators, handling agents as well as air navigation service providers. This CBA reports the results on the European industry level in a Generic CBA drawing on results from the Barcelona, Brussels, Munich and Zurich airports Site Specific CBAs. These latter are the property of the airports concerned.

The Generic CBA is built on the concept of a generic airport assuming the following main characteristics:

Figure 1: Generic airport characteristics

Is Airport CDM for you? What are the required investments and what are the benefits to be expected? Is this really a good deal if you are operating an airline, running an airport or have a ground handling operation? What about ATC, is Airport CDM good for ANSPs? You can find answers to all these questions in EUROCONTROL’s

Airport CDM Cost Benefit Analysis Examining in detail the economics of Airport CDM.


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The analysis assumes that the main airspace users at the airport as well as ATC, the ground handling companies and the airport operator are all on board working according to the CDM process requirements. But the benefits of Airport CDM are not limited to the airport concerned. It is increasingly recognised today that with more airports implementing collaborative decision making, the local benefits expand into the ATM network as a whole, further increasing the positive impact of this way of working. The network benefits have also been studied and are described in detail. The CBA shows clearly that Airport CDM can stand on its own. The benefits identified in this CBA are all attributable purely to Airport CDM and its network effects. Any chance of double counting with other airport related solutions, such as A-SMGCS, has been carefully avoided. The CBA uses a conservative approach, especially where some uncertainty existed. This approach ensured that results were never over-estimated. For example, to calculate the delay savings, only departures were taken into account. When a benefit is shown, you can be sure it is considered as a minimum and in most cases you can expect more positive results. The following is a high level snapshot of the CBA. All findings are further detailed in this CBA document so that you can draw your own conclusions. High Level Results Quick return on investment (payback period) The return of investment in various degrees is available from the second year onwards for all the partners. Airports and ATC achieve their return of investment in the second year of Airport CDM implementation; however, the Ground Handlers and Airlines may already achieve it within the first year of implementation.

-2

0

2

4

6

8

10

12

14

16

ATC GH AIRLINE AIRPORT TOTAL

M E

uro

(Cum

ulat

ive

Net

Ben

efits

)

Year 1Year 2

Year 3

Figure 2: Cumulative Net Benefits (3 years)



Figure 5: Benefits, Investments and Operating Costs

The graph above illustrates how the cumulative1 benefits are higher than the cumulative costs from the second year onwards for all the partners. The main insight is that Airport CDM is very beneficial for the overall community with modest costs. Airlines and GH will achieve the Break Even point in year 1 and the Airports and ATC in year 2. Airport CDM is cost effective for all partners The investment required from any single airport partner is modest and in many cases, existing equipment, facilities and services can be utilised with only limited modifications. On the benefit side, airspace users are on top, followed by the airport operator and the ground handling companies. ATC will see the smallest quantifiable benefit however most of the qualitative improvements in the work processes benefit ATC. The following table below shows the Net Present Value, Benefit to Cost Ratio and Payback Period for each airport partner.

Figure 3: Results Summary table

Figure 4 demonstrates the overall benefit to cost ratio of implementing Airport CDM at this Generic airport.

A benefit/cost ratio of 9, shown graphically below, presents a very strong case for implementation of Airport CDM.

The Present Value of the benefits is 91.32 M Euro over 10 years. The overall cost of the project for all partners together is 10.86 M Euro, distributed as follows:

• 3.83 M Euro investment spread over 10 years

• 7.03 M Euro operating costs spread over

10 years

1 Cumulative means that the graph takes into account the results from previous years (i.e., year 2 takes into account the benefits and the costs of year 1)

Figure 4: Benefit/Cost Ratio



It should be noted that a very conservative approach has been applied by partners when estimating their costs. An example of this is operating costs. Some airports strongly believe that once airport partners have completed the implementation of Airport CDM it becomes a new way of working, fully integrated into daily operations and therefore the final results per partner and the overall results of this CBA would be even better. Major qualitative benefits Not every benefit can be expressed in monetary terms. The analysis shows that there are many qualitative benefits which contribute to the general feeling of AIRPORT CDM being beneficial and desirable. A few examples of this are better working environment (ATC), improved customer satisfaction (Ground Handlers), improved overall image (Airport) and higher quality of service (ATC). Even when they cannot be easily quantified at this stage of the project, these benefits may still be very important to decision makers. The contribution of the different CDM elements The Airport CDM project has defined a number of CDM elements, each targeting specific areas of potential operational improvements. The AIRPORT CDM CBA analysis looked into the possibility of establishing which order of implementing the elements, or which combination of elements, would be the most beneficial. As it turned out, once information sharing is in place, the order of implementation or combination of the other elements does not make much of a difference. Conclusion? Implement elements one by one or in combination based purely on the prevailing operational considerations.

In brief…

Airport CDM is a cost effective solution to improve efficiency and predictability in airport operations, benefiting all airport partners. The return on investment period is short and the risk of financial loss is practically non existent. As a minimum, it is strongly recommended that Airport CDM information sharing is implemented at all airports used by commercial aircraft operators. Other AIRPORT CDMelements may be implemented on the basis of identified operational needs. It is important to understand that only airports that have implemented airport CDM will be able to take full advantage of the DMEAN Concept of Operations.



2. INTRODUCTION

2.1 Overview Airport CDM

Airport Collaborative Decision Making (Airport CDM) is a EUROCONTROL initiative whose objective is to integrate airport operations into the ATM Network by:

– Linking inbound and outbound traffic through the airport turn-around process

– Synchronising the passenger management process with the aircraft management process to meet the transport goal

– By adopting a pro-active attitude and anticipating problems before they arise thereby allowing timely solutions

This is achieved by introducing operational procedures based on a new approach to information management.

– Identifying the “owners of relevant information” for each phase of flight

– Ensuring their commitment to deliver it, keep it timely and accurately updated to build a Common Situational Awareness platform

– Enabling decisions for each phase of flight by those best placed along the aircraft management chain

With the high growth forecast in the aviation industry in the coming years and the recent enhancement to the Air Traffic Control (ATC) en-route network such as Reduced Vertical Separation Minimum (RVSM), airports are expected to become the restricting bottleneck to the overall Air Traffic Management (ATM) system. Airport Collaborative Decision Making is one of the new concepts that have been adopted by the ECAC (European Civil Aviation Conference) Transport Ministers in the European Air Traffic Management Strategy for the Years 2000+ (ATM Strategy 2000+). Airport CDM is about enhancing cooperation and coordination by sharing existing information and resources at an operational level between Air Traffic Management, Airlines, CFMU, Ground Handlers, Airports and other service providers, resulting in improved decision making capabilities. The resulting improvements in resource usage, schedule maintenance and flexibility in reacting to events benefits airspace users, airport operators, handling agents as well as air navigation service providers. It is increasingly recognised today that with more airports practicing Airport Collaborative Decision Making, the local benefits expand into the ATM network as a whole, further increasing the positive impact of this way of working.

2.2 CBA Scope and Objectives

The purpose of this Generic CBA is to provide a comprehensive economic analysis of the Costs and Benefits derived from the development, deployment and operation of Airport CDM



in a Generic Airport. In other words, “to establish the economic and financial impact of the implementation of Airport CDM in a Generic Airport”. By Generic Airport we understand an airport with the following characteristics:

Figure 6: Generic Airport Characteristics

The aircraft movements considered for 2006 are 280.000. It is forecasted that the traffic growth will be 4% per year. The average delay per departure movement, including all causes, is 10 minutes. Only departure movements (140.000) are used to calculate delay savings (conservative approach). In order to calculate operating cost savings the following was considered: in 2006 the annual Airport Operating Costs are 300 M Euro and the ATC Operating Costs are 70 M Euro for the same period. The CBA reports the results on the European industry level drawing on results from the Barcelona, Brussels, Munich and Zurich airports Site Specific CBAs. These latter are the property of the airports concerned. The analysis assumes that the main airspace users at the airport are participating in Airport CDM and it considers the ATC, the ground handling companies and the airport operator as the other contributing partners. The costs and benefits for the development, deployment and operation of Airport CDM are estimated for all the partners in the generic airport and results are generated in the form of Net Present Value2, Payback Period3, Benefit/Cost Ratio4, Sensitivity Analysis5, Probabilistic Analysis6 and explanations about the qualitative benefits. The benefits of Airport CDM are not limited to the airport concerned. The network benefits have also been studied and are described in detail in section 10. These benefits come from the improved accuracy of the flow and capacity management and improved service to airspace users, offering them more choices and options. The higher the number of airports participating in Airport CDM, the more substantial this benefit will be. 2 Appendix G 3 Appendix G 4 Appendix G 5 Appendix D 6 Appendix E



This CBA document will be used as a guideline for specific Cost Benefit Analysis that can be performed in airports around Europe helping partners make the best-informed decision for the investment in Airport CDM. The Airport CDM project has defined a number of CDM elements, each targeting specific areas of potential improvements. The AIRPORT CDM CBA analysis looked into the possibility of establishing which order of implementing the elements, or which combination of elements, would be the most beneficial. As it turned out, once information sharing is in place, the order of implementation or combination of the other elements does not make much of a difference. Based on the prevailing operational considerations the airport partner will decide to implement elements one by one or in combination. The evaluation period, that is the span of time of the cash flows that are relevant for the CBA, chosen for the analysis is 10 years, from 2006 till 2016.

2.2.1 Data Sources

The data required to perform the Cost Benefit Analysis for Airport CDM has been obtained from varying sources. Whenever possible, real data from airport partners’ experience in AIRPORT CDM implementation has been obtained. Where there was a lack of such data assumptions had to be made, expert judgment has been used. The CDM team has obtained inputs, feedback and validation from CDM partners through the Site Specific Workshops and Generic Workshops. The process that has been followed includes the following steps:

1. First iteration: interview or ask panel experts to complete a pre-prepared questionnaire

2. Summary of results of first iteration is discussed at workshops with all participating experts. Gaps are filled in with tentative data as required

3. Second iteration: experts are asked to review their initial responses and tentative data on gaps, and final results are determined

Detailed information on expert judgement can be found in section 17.1.5. Other sources of information are:

• Data from other studies • Data from trials (see section 4.4) • Historical data and forecasts • Standard Inputs7 used in the development of previous Cost Benefit Analyses related

to ATM operational improvements

7 EUROCONTROL Standard Inputs Document



2.2.2 Double Counting

Probably the most common problem with large projects in the air transportation industry arises as a result of inter-dependencies between different projects and trade-offs between benefits that lead to double counting of benefits. The difficulty in avoiding double counting comes in making sure that people are aware of the mechanisms through which this occurs, and the relevant information required to assess it. Conversations with other EUROCONTROL Airport Operations Program activities took place in order to avoid double counting. Some insights from the meetings are: • DMEAN & Airport CDM CBAs The DMEAN CBA did not find benefits that would arise from improvements in the ATFCM process. These benefits are attributable to Airport CDM. • Double Counting between Airport CDM and A-SMGCS CBAs: – It was agreed there is only a “benefit” overlap. Scenario: In case an airport has a CFMU

regulation applied due to low visibility:

As a result of A-SMGCS the regulation required will be less severe (throughput is maintained)

CDM will contribute to reduce the time required for return to normal operations and so, the regulation will be applied for a shorter period of time

– This benefit overlap cannot be easily quantified in a Generic CBA as it is highly

dependant on the local airport context. It was agreed to mention this benefit overlap only in qualitative terms

• Cost of delay: – Use of standard delay model / values (based on the Westminster report’s modification)

for the Airport CDM Generic CBA – The Site Specific Airport CDM CBAs will use the values provided by local partners – A-SMGCS and DMEAN CBAs have applied the same values. So, A-SMGCS, Airport

CDM and DMEAN CBAs are harmonized in this aspect

2.3 CBA Overview

Investments in the ATM environment are required continuously in order to maintain safety and reliability, improve the quality of service and match system capacity to the expected traffic growth. The providers of air navigation services, airports, airlines and the financing organisations all need to be convinced of the economic viability of proposed new projects. The decision maker, who is responsible for sanctioning future projects, will require a clear understanding of the advantages and disadvantages of the proposals. While choices between different proposals must draw on experience and judgment, they normally also benefit from systematic economic appraisal. In the face of a variety of diverse projects it is important to ask which represent the right investment.



Cost Benefit Analysis (CBA) is an increasingly important tool in the assessment of investment decisions in the ATM environment. It is a tool for decision makers, used to evaluate whether the investment is economically viable for Partners. There is no formal definition of CBA, but the following interpretation by the FAA meets our needs well:

“Benefit-Cost analysis calls for the examination of all costs related to the production and consumption of an output, whether the costs are borne by the producer, the consumer, or third party. Similarly the method requires an examination of all benefits resulting from the production and consumption of the output, regardless who realizes the benefits”

How this is implemented may vary, but basically all procedures are based on: • Estimating all incremental8 costs by Partner related to the implementation of an

application or service • Estimating all incremental benefits by Partner related to the implementation of an

application or service • Taking full account of the times at which costs are paid and at which benefits accrue • Taking account of uncertainty • Obtaining a figure of merit and performing sensitivity and risk analysis Costs are to be understood as the resources used to generate the outputs, while benefits are the utility to the relevant parties of those generated outputs. CBA is typically conducted as a net present value analysis by cumulating and discounting annual cash flows associated with the proposed project. On the basis of such an approach, other summary statistics such as benefit/cost ratio, pay-off periods and internal rates of return can be determined. In practice things are not usually so straightforward. While costs and most types of benefits can generally be quantified after a little research, an economic breakdown of all the projected benefits can be more elusive due to varying degrees of uncertainty around them. The same approach can get even more complex since intangibles (those costs or benefits not easily quantifiable albeit evident) can also be very relevant for the final decision to be made. On the whole CBA is not only used to evaluate different investment opportunities or alternatives, it is also a valuable tool in many decision making processes helping understand the outcomes in the system produced by the actions of choice subject to study. It provides relevant data to compare and prioritise between the different alternatives under consideration (including the baseline or “do-nothing” option). For a CBA to be effective in comparing projects, it must be applied in a consistent manner. Much of the data is uncertain and expert opinion has been used to estimate benefits arising from the CDM elements, since no firm data exists. Uncertainty has been taken into account by assigning high, base and low values to the uncertain data items. There is an equal probability of the true value exceeding or being less than the base value, a 10% probability of the true value exceeding the high value and a 10% probability of the true value being less

8 Incremental means that the cash flows (costs and benefits) taken into account for the CBA are only cash flows that are different between the situation with Airport CDM implemented and the baseline (situation without Airport CDM implemented).



than the low value. The high and low values are used in a sensitivity analysis of the outcome using the base values. A CBA process can be performed in any phase of the project cycle, and the level of accuracy can vary depending on the needs and/or development conditions. Once the investment decision is made, this kind of analysis can provide useful benchmarking information regarding the execution of the project and the impact for the affected partners. Lastly, and most important, partners are the owners of the Airport CDM CBA process. Inadequate management of this fact will surely yield poor and misleading results that might lead to non optimum decisions. The study uses a top-down CBA methodology approach. A top-down approach uses values that have already been derived for benefits such as the value of a one minute reduction in delay and the value of a cancelled flight. These standard values are in common use for CBAs related to ATM operational improvements and are listed in Ref59. This approach naturally leads to the use of EMOSIA (European Model for Strategic ATM Investment Analysis) methodology for the economic assessment. See next section for a brief introduction to EMOSIA methodology.

2.3.1 EMOSIA Overview

EMOSIA, the European Model for Strategic ATM Investment Analysis, will provide support for the CBA because: • It is an iterative process: steps are repeated up to the point where there is no more

added value to refining the analysis. The process is aimed at decreasing uncertainty and increasing accuracy.

• It is an interactive process: data, assumptions, and outputs are discussed with

partners and experts through a permanent and transparent dialogue process. Tools are maintained as simple as possible to avoid them becoming black boxes.

In dealing with uncertainly, EMOSIA allows the undertaking of an initial CBA as early as possible in a project. Therefore, depending on the phase of a project or validation life-cycle a cost benefit analysis can be undertaken with different degrees of detail and granularity, adapting data collection accordingly. By using the sensitivity and risk analysis tools, the process refines the analysis up to the point where continued refinements add no further value to the project case. With a standardised approach and tools you can trace your project and control improvements from phase to phase through a series of initial and extended Cost Benefit Analyses. The EMOSIA methodology is mature enough and generally accepted as a solid ground for elaborating CBA studies in ATM. In the case of CBA for the Airport CDM project, EMOSIA seems to be particularly suitable given the partners involved and the Costs/Benefit drivers to be modelled. 9 EUROCONTROL Standard Inputs Document



Use of the EMOSIA methodology will ensure the following benefits: • Compliance with principles widely used in other organisations, thus being easy to

understand by both occasional and final consumers of the study • Consensus by the European ATM/CNS community • Consistency with other EUROCONTROL reports • Traceability and Transparency of what is happening within the models and why.

Models are white boxes with no restricted information • Reliability demonstrated in other projects that have successfully employed the EMOSIA

methodology EMOSIA aims at helping partners make the best-informed decision for an ATM investment by: • Providing a common baseline • Including uncertainties in the decision process. It models the uncertainty associated with

a decision providing increased insight into the true risks associated with an investment (sensitivity and risk analysis)

• Supporting decision makers during long and multi-phase projects • Involving partners in the analysis EMOSIA provides the following outputs for each partner segment: • Economic and financial indicators, such as Net Present Value, benefit to cost ratio,

internal rate of return, breakeven point and payback period • Sensitivity analysis identifying the most critical variables to the economic success of the

improvement • Risk analysis showing the likelihood of the improvement delivering a certain net present

value • Recommendations for that improvement including focus for further research A detailed description of the EMOSIA process can be found in Appendix B.



3. BASELINE ASSUMPTIONS

Prior to analysis of costs and benefits, the project has to be fully stated and characterised. This requires establishment of baseline assumptions that will guide the overall CBA process. The Baseline Scenario is the alternative choice for continuing with the current approved plans for investment (also known as the “Business As Usual” or “do-nothing” option). It is the reference case against which the project is appraised. It doesn’t imply that all investment initiatives be blocked, but rather what the air traffic business will be if CDM is not implemented. There are a number of assumptions that have been made for the Baseline Scenario. These are not final and thus can be challenged and changed if deemed necessary.

3.1 Airport Baseline Assumptions

• The Baseline Operating Cost for the Airport in 2006 is 300 M Euro • The Operating Cost Growth is equal to 4% as per traffic growth • Implementation duration is equal to 3 years

3.2 ATC Baseline Assumptions

• The ATC Operating Cost in the Airport is 70 M Euro

3.3 Ground Handling Baseline Assumptions

• Operating Cost Growth is 4% • Operating Cost for Ground Handlers affected by CDM is assumed to be between 10%

and 30% of their total operating costs • The operating costs per flight handled are between 1000 and 3000 euros per flight

3.4 Airline Baseline Assumptions

• The Baseline for annual flight growth is 4% • The average cost of delay per minute is 77 euros. For sensitivity analysis purposes a

high value of 100 and a low value of 50 are used • The average delay per movement (all causes) is 10 minutes • Benefits are achieved from 1st year of the project and are fully achieved after 2 years

3.5 Network Baseline Assumptions

• Any ATM tool that can provide 0.5% extra capacity to en-route ATS at a cost of less than 22 million euros per year is cost-beneficial

• The costs of Airport CDM to generate 0.5% increase of en-route capacity is equal 5 M euros per year10

3.6 General Assumptions

• Discount rate to be used is 8% • No tax rate being used

10 Data to be further studied



• Start Year 2006, Final Year 2016 • Aircraft movements (2006): 280.000 • Annual Traffic Growth: 4% • One of the main benefits derived from the implementation of Airport CDM is that it

enables an airport to reduce the number of situations and the duration of a situation where there is loss of capacity

• The more an airport is capacity constrained the greater benefits Airport CDM may bring

The economic models used for the analysis have been designed to allow changes on these assumptions.



4. BENEFITS

4.1 Benefit Mechanisms

In order to develop a credible list of benefits, the benefit mechanisms through which each of the benefits is actually realised have to be described. Benefit mechanisms are causality diagrams that document the changes a given application introduces in the ATM environment and how those changes lead to benefits for the various partners. Benefit mechanisms provide a conceptual framework to work out: the links between application and benefits. The following graph shows a summary of the Benefit Mechanisms for Airport CDM.

Figure 7: Benefit Mechanisms Summary Graph

The full benefit mechanisms document is available as part of the deliverables of this project (ref.211).

11 Airport CDM Benefit Mechanisms Document



Some operational improvements and generic benefits of significance are:

• Better decisions and planning

o Improved stand and gate planning and management at airports o Better en-route capacity management o Efficient use of runway capacity o ATFM and airport slot adherence – avoidance of capacity loss o Less possibility of errors

• Better taxi planning

o Better planning of taxi time o Better pre-departure sequence o Shorter taxi time and waiting before runway access o No waiting in front of occupied gate

• Reduction of delays at the overall ATM system

o More available en-route and airport capacity o Increased airline capacity with the same fleet

If a planned operation deviates from the schedule, additional efforts or resources are required to counteract the deviation. This means that the closer an operation can stay to schedule the cheaper it is overall. AIRPORT CDM helps in maintaining the schedules.

4.2 Benefits Trade-offs

A trade-off usually refers to losing one benefit or aspect of something in return for gaining another benefit or aspect. It implies a decision is to be made with full comprehension of both the upside and downside of a particular choice. There is a benefit trade-off considered in this Cost Benefit Analysis. One of the main benefits derived from the implementation of Airport CDM is that it enables an airport to reduce the number of situations and the duration of a situation where there is a loss of capacity:

• Baseline Capacity 1 – situation with loss of capacity • Capacity 2 – situation with reduced loss of capacity

The situation with Capacity 2 may:

• bring either additional flights or • reduce delays or • a combination of both (see Fig.8)



Figure 8: Benefit Trade-Offs Representation

The benefit trade-off between delay and additional movements has been analysed and discussed. As agreed in the 3rd Generic Workshop the benefits that will be measured are delay reduction as the main benefit and consider additional movements only in terms of flight cancellation-avoidance (point A - graph above). Flight cancellation avoidances are included in the calculations as these are flights that are not accommodated in the baseline (situation without Airport CDM) but will be accommodated with Airport CDM. Apart from the delay reduction and flight cancellation avoidance some airports have pointed out that the number of movements could be 5-10% lower but with Airport CDM it is feasible to maintain the current number.

4.3 Intangible Benefits

As far as possible all benefits are expressed in monetary terms in order to be compared against the costs. At the same time it should be noted that a benefit need not be quantifiable to be recognized as a real benefit. In the Airport CDM CBA development process, some benefits could not be quantified. There were several reasons for this (availability of time and resources, difficulty in finding a consensus on a yardstick for measurement, etc.) In such cases, effort was placed on assessing the benefit in quantitative terms (e.g. physical units). Whenever such quantification was too difficult or impossible, all qualitative or intangible benefits were exhaustively enumerated, documented, explained and justified. Even though intangible benefits cannot be quantified, they may still be very important for decision makers, hence the need to properly document them.

(number of flights)

delay (time) Capacity 1

Capacity 2

Delay reduction

A

Additional movement maintaining delays constant



4.4 Results from Trials

The information provided in this CBA document comes from expert judgment and also from current activities in the case of the airports that have already implemented Airport CDM. There are also airports that are currently conducting trials with CFMU to prove the relevant CDM concept elements. Some conclusions that have arisen from the trials are the following:

• Local operational community becomes increasingly familiar with the Airport CDM

procedure • Enhanced pushback truck allocation and usage • Enhanced ground handling processes and systems • Proven decrease in taxi times (reduced controller workload, fuel and emissions) • FUM and DPI Exchange runs stable • Necessary adjustment of procedure • FUM increases ELDT quality => enhanced airport operation planning • Enhanced airline operations planning processes

Further information from trials will be incorporated in next iterations of this document.



5. OVERALL RESULTS

The CBA shows clearly that Airport CDM is a solid investment. The benefits identified in this CBA are all attributable purely to Airport CDM and its network effects. Any chance of double counting with other airport related solutions, like A-SMGCS, has been carefully avoided. The CBA uses a conservative approach. Especially where some uncertainty existed, this approach ensured that results were never over-estimated. For example, to calculate the delay savings, only departures were taken into account. When a benefit is shown, you can be sure it is considered as a minimum and in most cases you can expect more positive results. It should be noted that this conservative approach has also been applied with partners estimating their costs. An example of this is operating costs. Some airports strongly believe that once airport partners have completed the implementation of Airport CDM it becomes a new way of working, fully integrated into daily operations. Examples of these operational costs are training, operational procedures adaptation, coordination activities essential to the functioning and further evolution of Airport CDM, identification and development of new system requirements and participation on systems evaluations. Currently some airports prefer to maximise the costs estimation to ensure safer results. If operational costs are reduced or eliminated, the final results per partner and the overall results of this CBA would be even better.

5.1 Return on investment period or payback period

The return of investment in various degrees is available from the second year onwards for all the partners. Airports and ATC achieve their return of investment in the second year of Airport CDM implementation; however, the Ground Handlers and Airlines may already achieve it within the first year of implementation.

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ATC GH AIRLINE AIRPORT TOTAL

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(Cum

ulat

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Net

Ben

efits

)

Year 1Year 2Year 3

Figure 9: Cumulative Net Benefits (3 years)



The graph above illustrates how the cumulative12 benefits are higher than the cumulative costs from the second year onwards for all the partners. The main insight is that Airport CDM is very beneficial for the overall community with modest costs. Airlines and GH will achieve the Break Even point in year 1 and the Airports and ATC in year 2.

5.2 Quantitative and qualitative analysis by partner

The following table below shows the Net Present Value, Benefit to Cost Ratio, Payback Period and the qualitative benefits for each airport partner.

Figure 10: Results summary table (incl. qualitative benefits)

Each airport partner results are analysed in detailed in sections 6 to 9 of this document.

12 Cumulative means that the graph takes into account the results from previous years (i.e., year 2 takes into account the benefits and the costs of year 1)



5.3 Benefits obtained by partner and total costs

The benefits obtained by partner and the total costs incurred each year of the project are represented in the following graph.

Figure 11: Benefits by partner and total costs

The main insight is that costs are very small comparing with benefits, but quite constant through the implementation and post-implementation phases.

On the benefit side, airspace users are on top, followed by the airport operator and the ground handling companies. ATC will see the smallest quantifiable benefit but most of the qualitative improvements in the work processes benefit ATC.

5.4 Cost Effectiveness

The investment required from any single airport partner is modest and in many cases, existing equipment, facilities and services can be reused with only limited modifications required. A benefit/cost ratio of 9 is shown graphically below; this means that the total benefits of implementing Airport CDM are 9 times higher than the total costs. The overall cost of the project for all partners together is 10.86 M Euro, distributed as follows: • 3.83 M Euro investment spread over 10

years • 7.03 M Euro operating costs spread over

10 years

-5

0

5

10

15

20

25

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

M Euro

GH ATC AIRLINE AIRPORT Costs

Figure 12: Benefit/Cost Ratio

Figure 13: Benefits, Investments and Operating Costs



The Present Value of the benefits (excluding network benefits) is 91.32 M Euro over 10 years. After completing the analysis it is still difficult to define exactly the cost attribution to Airport CDM as sometimes costs are derived from the combination of different initiatives.

5.5 Network Benefits

Airport CDM is more than airport benefits. The improved predictability benefits the entire ATM network. The benefits come from more accurate flow and capacity management and the improved service to airspace users, offering more choices and options. The greater the number of airports participating in Airport CDM, the more substantial this benefit will be. See section 10 for more details.



6. AIRPORT

6.1 Airport Benefits

For the Airport operator the following benefits have been identified:

• Benefits rely on:

Airport revenue - Based on the net revenue realised through additional flights and passengers (additional movements – flight cancellation avoidances).

Airport image - The perception among passengers describing the experience of

arriving or departing from a certain airport. The community perception of the airport in terms of what it does to reduce emissions (noise, etc.). This revenue will not be quantified.

It is accepted that the airport image will be improved due to improvements in punctuality (operating according to schedule) and predictability in adverse conditions as a result of Airport CDM.

Airport operational efficiency - The common situational awareness obtained

through CDM will help achieve better use of airport resources (manpower and equipment) through better information and anticipation. The benefits are the savings on operational costs (e.g. operational cost increases at a lower rate than it does currently) or reduction of inefficiencies by a certain percentage.

Airport punctuality - contributes to improving airport image which leads to revenue increases (not quantified). Airport CDM, as it improves punctuality, has helped Airports to go up in the punctuality valuation.

Information about Environmental Benefits can be found in section 11. In general, expert judgment has been used to estimate potential benefits.

6.1.1 Airport Revenue

As specified in the Benefit mechanisms (Ref.2) the implementation of Airport CDM elements will provide the airport with better decisions leading to improved usage of the available resources. Increased resource availability enables the reduction of cancelled flights. This means more traffic and more revenue. Refer also to section 4.2 (benefits Trade-offs). In order to calculate the benefit the following data was used:

Benefit Number of movements increased (due to Airport CDM implementation)



6.1.2 Airport Operational Efficiency

Better use of resources enables increased utilisation. Airport productivity improvements are supported by better resource utilisation. Productivity improvements translate to decrease in airport operating costs. In order to calculate the benefit the following data was used:

Benefit Operating Cost avoidance

This data is to be provided in %. Experts had highlighted that it is very hard to establish a link between staff cost avoidance and Airport CDM as the shifts are organised at least two weeks in advance on the basis of the airport schedule. While there is no real buffer built into the shift complements, very accurate schedules would help in optimising the dispositions of all resources. However it was accepted that Airport CDM can have an impact on operating costs. Taking into consideration the projected traffic growth rate (4% per annum), with Airport CDM it should be possible to serve the higher traffic with basically the same resources longer, which will mean that operating costs that would be incurred in the future if Airport CDM is not implemented can be delayed in time or avoided completely.

6.2 Airport Costs

The Investment cost is the sum of: • One-Off Implementation Costs: one-off implementation costs incurred during the

implementation period, such as training and program management

Cost Project Management Personnel Cost for Development Software

• IT Improvements

Cost Annual IT Improvements

• Operating Cost: maintenance and other costs incurred

Cost Annual Ops Costs

6.3 Benefits and Costs Key Variables

This section describes the name of the variables affecting benefits and costs and the detailed data used in the economic models.



6.3.1 Benefits

6.3.2 Costs

6.3.3 Airport Data

The following table shows the data used in the calculation of results:

Investment Costs

Annual Ops Costs

Develop Software

Operating Costs One-Off Implementation Costs

Annual IT Improvement

Costs

IT Improvements

Project Management

Benefits

Ops Cost 2006

Ops Cost avoidance

Ops Cost growth

Ops Cost Avoidance

New revenues(avoided cancellations)

Cancellations Avoided

Value of cancel flight



Name Units Description High Base Low Source Operating Cost Growth

Decimal Fraction

Operating Cost Growth Rate in baseline 4% 4% 4%

Expert Judgment

Operating Cost 2006

millions of euros

Operating costs for Baseline 350 300 250

Generic Airport Assumption

Operating Cost Avoidance %

decimal fraction

The % reduction in operating costs, when fully implemented. 4% 2% 0%

Expert Judgment (Airport specific CBAs)

Benefits Lag years The lag between implementation start and benefits start and implementation end and benefits achieved at full operating capability

1 1 1 Expert Judgment

Implementation Duration (Imp Duration)

years The duration of the ground/space implementation period. (Input a non-zero number, even if associated costs are zero).

3 3 3 Expert Judgment

Value of cancel flight for the airport

Euros Includes Commercial Revenues 800 600 300

EMOSIA models

Cancellations avoided

Number of flights

250 200 150 Expert Judgment (Airports Data)

Develop software M Euros

During implementation period 0.3 0.25 0.2

Data from site specific airports

Project management

M Euros 1 Million in 4 years 1 1 1


Annual IT Improvement Costs

M Euros Per year

0.125 0.1 0.08 Data from site specific airports

Annual Operating Costs

M Euros Per year. This cost is considered as high by some of the airports (based on comments from Generic Vs Site Specific Workshop). It is left in order to include the views of all the airports studied as part of the generic report. (e.g. high cost in case airport buys a new system and attributes investment to CDM)

0.6 0.5 0.4

Data from site specific airports.

6.4 Operational Examples

The operational examples are given as a proof of concept of the benefits derived from Airport CDM.

• Reduced delays and hence greater predictability leads to higher utilisation of staff resources since rosters can be organised to meet demand. As a result, staff employment cost will be reduced (overtime or buffer will be reduced).

• The airport operator will have available all the information related to the departure

and arrival sequence. This results in a significant improvement in the planning capability for further operations and also allows better quality information to be dispatched to relevant partners (i.e., passengers and handling agents).



• Having knowledge about departure sequence should improve the allocation of stands and gates by the Airport Operator.

• The Collaborative Management of Flight Updates element improves the collaboration

processes between Aircraft Operators, Airport Operators, ATC and CFMU. The operational efficiency of these partners will be improved as a result of having updated information.

6.5 Results from Analysis

The Expected Net Present Value of the investment for the airport is equal to 29.9 million Euros.

6.5.1 Sensitivity Analysis

The diagram below shows the relative sensitivity of the uncertain variables of the model. In this case almost all the variance is explained by one variable:

• Operating Cost Avoidance %

Figure 14: Sensitivity analysis

NPV

€M 29.9

B/C Ratio

8



There is a need to concentrate efforts in studying the % of Operating Cost that Airport CDM helps in avoiding. See Appendix D for an explanation of Sensitivity Analysis.

6.5.2 Probabilistic Analysis

The risk of the project is evaluated by means of a cumulative probability curve13. It should be read as follows: the Y axis value gives the probability to get up to the X outcome value (in million euros); or in an equivalent way, the (1-Y) probability to get the X outcome value or more. Under the assumptions of the model the cumulative probability curve reveals that there is approx. 80% probability of having a positive result, which means that it is a very safe investment with very limited risk associated to it. There is a 50% probability of obtaining a result of 30 M Euro or higher.

Figure 15: Probabilistic Analysis

See Appendix E for further explanation of the Probabilistic Analysis.

13 The probabilistic approach used in this review is based on the construction of a decision tree where every possible outcome of the project is weighed with its associated probability; the sum of every possible outcome given the probabilities is used to build the cumulative probability curve



6.5.3 Cash Flow Analysis

The following figure shows the cumulative net cash flow. With this curve one can assess the breakeven year (the intersection with the X axis) and estimate the payback period (the period which lasts to just before the costs are offset by the benefits).

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Figure 16: Cumulative cash flow analysis



7. ATC

7.1 Benefits

The following benefits have been identified for ATC:

- Predictability - Punctuality - Efficiency - Network effects

The benefits for ATC14 are detailed in the next 3 sections. The network benefits are treated separately in Section 10.

7.1.1 Improvement in Working Environment

Better decisions and planning of ATC operations improve ATC productivity, which is the relationship between production of an output and the resource inputs used in accomplishing the task, applied specifically to the operation of an ANSP. This productivity translates to lower workload and the probability of errors being reduced. This benefit is considered as a safety benefit although it cannot be quantified.

7.1.2 Efficiency Increase

Airport CDM helps to increase predictability consequently this better use of resources will possibly lead to cost avoidance (the impact of this possible cost avoidance has been analysed in the sensitivity analysis). Airport CDM could make more use of data link which may lead to further reduction of frequency congestion.

7.1.3 Higher Service Quality

The better predictability of take-off times will lead to higher service quality. In that respect, if the operation in the Airport (Airport, ANSP, ground handler) is more effective due to Airport CDM the airport is more attractive to airlines and as an indirect effect it can mean more traffic and income for the Airport from the airport fees and more passengers and for the ANSP more income from the extra route and landing charges. For a hub airport and its users, punctuality is very important.

7.1.4 Generic Airport contribution to Network Benefits

The ANSPs emphasised the benefits of the network effects if Airport CDM is operational at many airports in Europe. There are about 20,000 flights in Europe each day. Benefits will grow as the number of airports implementing Airport CDM increases, so the en-route capacity may proportionally

14 When ATC is mentioned the report refers to the “tower” only and not the ANSP in general.



increase. As a consequence some of the Network Benefits could be claimed as direct contribution to the network by the local ANSPs at the CDM airports

7.2 Costs

The Investment cost is the sum of: • One-Off Implementation Costs: one-off implementation costs incurred during the

implementation period, such as training and project management.

Cost IT Costs

• Operating Cost: Maintenance costs.

Cost Maintenance of Airport CDM systems



7.3.1 Benefits

Benefits

Operating Cost Avoidance

Ops Cost Growth

Percentage Improvement

(CDM)

Ops Costs



7.3.2 Costs

7.3.3 ATC Variables

The following table shows the data used in the calculations of results.

Name Units Description Values Source Maintenance Thousands

of euros Annual maintenance costs. This cost is considered as high by some of the airports (based on comments from Generic Vs. Site Specific Workshop). It is left in order to include the views of all the airports studied as part of the generic report.

95 85 75


IT Costs M Euros

0.3 0.2 0.15 Data from site specific airports

Ops cost saving thanks to CDM (percentage improvement)

Decimal Fraction

Low range equals 0; it shows the impact of not achieving operational cost savings. 2% 1% 0%

CBA Team

BL Ops Cost M Euros Baseline Operating Costs 80 70 60

CBA Team assumption

Ops Cost growth Decimal Fraction

4% 4% 4%

Expert Judgement


The operational examples are given as a proof of concept of the benefits derived from CDM.

• ATC can better anticipate the effects of adverse conditions and also reduce their effect on the ATM network

• Airport CDM could contribute to a more efficient use of data link and further reduction

of frequency congestion and hence obviate the need for additional clearance delivery positions

Investment Costs

Maintenance of CDM systems IT Costs



• The Flight Update Message is more effective than traditional movement messages, providing more accurate arrival information earlier (benefit to all partners)

• A collaborative pre-departure sequence enables ATC to take user preferences into

account • Accurate taxi times increase the accuracy of calculations in which taxi times are used,

improving predictability (benefit to all partners)

• Airport CDM helps to avoid problems and consequently costs. It is envisaged that a non-CDM scenario the ATC problems are higher than in an Airport CDM scenario.


The Expected Net Present Value of the investment for the ATC is equal to 3.79 million Euros. The benefit cost ratio is equal 6.


The diagram below shows the relative sensitivity of the uncertain variables of the model. In this case almost all the variance is explained by one variable:

• Operating Cost Avoidance % (percentage improvement CDM) This variable is crucial as depending on it the results can be positive or negative. There is a need to concentrate efforts in studying the % of Operating Cost that Airport CDM helps in avoiding. See Appendix D for explanation of the Sensitivity Analysis.

Figure 17: Sensitivity analysis

NPV

3.79 €M

B/C Ratio

6




The risk of the project is evaluated by means of cumulative probability curve15. It should be read as follows: the Y axis value gives the probability to get up to the X outcome value (in million euros); or in an equivalent way, the (1-Y) probability to get the X outcome value or more. Under the assumptions of the model the cumulative probability curve reveals that there is approx. 80% probability of having a positive result, which means that it is a very safe investment with very limited risk associated to it.

Figure 18: Probabilistic analysis


15 The probabilistic approach used in this review is based on the construction of a decision tree where every possible outcome of the project is weighted with its associated probability; the sum of every possible outcome given the probabilities is used to build the cumulative probability curve





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8. GROUND HANDLERS

Some of services provided by Ground Handlers are shown below: Passenger Services

• lounges and VIP services • passenger assistance • check-in, gate and transit • ticketing

Ramp & Logistics

• baggage transportation • aircraft loading and unloading • ramp support • pushback • de-icing • operation control • load planning • supervision • ground equipment maintenance

8.1 Benefits

For the Ground Handlers the following benefits have been identified:

8.1.1 Improved Efficiency

Airport CDM procedures will definitely have a positive impact on ground handling performance. The reliability of the resource planning and staff allocation will be improved with an operation closer to scheduled times. In future there might be no need to plan additional time buffers for staff to cover delayed outbound flights. Airport CDM facilitates the making of better decisions enabling ground handlers to improve their efficiency; this improved efficiency enables higher productivity and thus higher revenue or reduction/avoidance of operating cost, i.e., higher utilisation of resources leads to a reduction of current operating costs (like those generated by conflicts in resource allocation) and avoidance of future operating costs, (less need to hire staff and buy equipment thanks to higher utilisation of existing resources). The reduction in % of flights delayed will decrease the volatility of resources needed and as a result impacts the redundancy required and therefore the cost of providing the service. In case of push-backs the truck spends 15 minutes as an average with one aircraft while the actual process is only 5 minutes – so there is a good potential for improvement, maybe 1/3 of the current time can be saved as a result of Airport CDM. Obviously if they can plan a more efficient operation, this can mean fewer resources needed for a given number of operations.



5-6 times a day an aircraft is delayed because of the lack of a push-back truck (which may be idling somewhere else and could not be repositioned) resulting in 2-3 minutes delay for the flight – this can be solved with Airport CDM. Due to the current lack of proper information the approximate loss of handling agent time is 10%; Airport CDM will be able to improve this situation. On the other hand in peak-hours less than 5% of the time spent can be saved due to Airport CDM. 5% is used as the average time that can be saved by the Ground Handlers assuming that this will mean 5% avoidance of operating cost from 2006 till 2016. The Ground Handler operating cost that may possibly be influenced by Airport CDM will be about 10 to 30%.

Benefit Operating Cost avoidance = 5%

8.1.2 Improved Customer Satisfaction

Increase in the quality of the service they offer to their customers due to the possibility of exchanging information in real time.

8.1.3 Lower Prices (Airline Benefit)

Increased productivity could enable ground handlers to lower their prices. Lower Ground Handler costs may result in lower airline costs where the environment is competitive. This benefit is qualitative at this stage of the analysis.

8.2 Costs

IT Cost is between the following range 150,000 – 250,000 Euros per year for all the Ground Handling companies in the airport.





8.3.1 Benefits

8.3.2 Costs

Investment Costs

IT Cost per year

Benefits

Ops Cost Growth

Operating Cost Avoidance

Percentage Improvement

(CDM)

Ops Cost per Handle Flight

Percentage Ops cost influenced

by CDM



8.3.3 GH Variables

Name Units Description High Base Low Source

Percentage Ops cost influenced by CDM

%

30 20 10 CBA Team based on expert info

Operating Cost Growth (aircraft towing)

%

4% 4% 4% Expert Judgment

Percentage Improvement (CDM)

% % of reduction in Ops Cost thanks to CDM 7% 5% 3%

Expert Judgment

Operating Cost per Handle Flight

Euros per flight

3000 2000 1000 Other studies – 1st CBA

IT Cost per year M Euros Annual IT cost per year

0.25 0.2 0.15 Site specific Airports


The operational examples are given as a proof of concept of the benefits derived from CDM. • Improved pushback productivity thanks to better utilisation of staff • Reduced inactive time due to inefficiencies (i.e. less wasted time by ground vehicles) • Reduction of (indirect) operating costs as a result of reduction of delays • Knowledge of the precise status of arriving aircraft well in advance will optimise

handling of flights • Having knowledge about departure sequence should improve the allocation of stands

and gates by the Airport Operator • More accurate information (e.g. FUM) will bring benefits to the GH operation


The Net Present Value of the investment for the GH is equal to 16.87 million Euros.

NPV

€M 16.87

B/C Ratio

14




The diagram below shows the relative sensitivity of the uncertain variables of the model. In this case almost all the variance is explained by three variables:

• Operations affected by CDM • Operating cost per flight handled • Percentage Improvement (CDM) – Percentage operating cost saving thanks to CDM

See Appendix D for an explanation of the Sensitivity Analysis.

Figure 20: Sensitivity Analysis


The risk of the project is evaluated by means of cumulative probability curve16. It should be read as follows: the Y axis value gives the probability to get up to the X outcome value (in million euros); or in an equivalent way, the (1-Y) probability to get the X outcome value or more. Under the assumptions of the model the cumulative probability curve reveals that there is no risk of actually losing money in this project, thus even in the worst case scenario the results will be higher than 0. There is a 50% probability of obtaining a result of 15 M Euro or more.




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Figure 22: Cumulative Cash Flow



9. AIRLINES

9.1 Benefits

The benefits are: • Cost savings: all savings that can be made on the current airline direct operation cost

(DOC), namely:

o Unpredictable Delay Savings o Structural Delay Savings: savings by reducing structural delay, buffer time that the

companies add to the planned flight time, in order to accommodate statistically foreseeable delays.

o ANS Charges Savings: due to effort from ANSPs to reduce the cost of the ATM service. The ANS charges will group en-route charges and landing fees (this data will come from the ANSP analysis). Due to the small costs in relation to total cost to the ANSP the change in the charges has been ignored.

The passenger opportunity costs represent an estimate of the value which an airline places on the time of its passengers and is the amount an airline would have to spend in order not to lose passengers. The passenger value of time is considered to be implicitly included in the cost of one minute of delay and is therefore not added on top of it. Information about Fuel Cost Reduction and Environmental Benefits can be found in section 11.

9.1.1 Delay Cost Savings

Delay reduction has been identified as one of the main benefits for an airline in an airport with Airport CDM elements implemented. Airlines could also decide to reduce the buffer in their schedules thus obtaining Structural Delay Savings. Delay cost savings or avoidance are savings that result from shorter ground, airborne and associated reactionary delay (delay that is a consequence of previous ATM delay). The modelling of delay over several years can also include delay that airlines incorporate into their schedules from one year to the next. This delay is less costly than the unpredictable delay. Assuming that in the medium/long term delay is reduced to an optimum level (that is a level of optimum trade-off between investing in more capacity and the delay cost caused by the lack of that capacity) the delay benefit from then onwards will be assessed as delay avoidance instead of actual delay reduction.

• Delay17 – change in minutes of ground, airborne and reactionary unforeseen delay. Airborne delay is assumed to include re-routings. Delay is assumed to include the cost of missed connections and the effects of returning to operations after adverse

17 A delay is the difference between a Scheduled Time of a flight event and the Actual Time of that event. This difference is generally expressed in minutes.



conditions. Reduce taxi times may also be a reason for delay reduction in some cases although it is not the only reason.

• Flight cancellations – reduction in flight cancellations as a result of the operational improvement introduced by Airport CDM elements. Flight cancellations happen when there is excessive delay. The value of cancelled flights stated in the “Standard inputs 2005” document of EUROCONTROL is 6380 euros per cancelled flight.

The data for cost of a minute of ground and airborne delay and for a flight cancellation can be obtained from the “Standard Inputs” document of EUROCONTROL. However, these values are overall averages; the average cost of delay per minute is 77 Euros (based on a study made by EUROCONTROL revising a previous study made by the University of Westminster). CDM implementation can bring a 3% improvement in terms of delay at the Airport. The 3% of delay improvement can lead to a reduction of 3% of buffer time in the long term (qualitative at the moment).

9.2 Costs

The Investment cost is the sum of: • Implementation Costs: systems (software) • Operating Cost:

• Full time function (full time employee) dedicated to ATC/FLOW • Flight dispatch staffing • Travel Costs for meetings





9.3.1 Benefits

9.3.2 Costs

Investment Costs

Training Project Management

Ops admin and travel

Travel Costs Full-time function dedicated to ATC/FLOW

Flight dispatch staffing

Systems (Software)

Operating Costs Implementation Costs

Benefits

Delay Expected

without CDM

Delays

Cost 1 min of delay

Delay Reduction

New revenues (avoid cancellations)

Cancellations Avoided




9.3.3 Airline Variables Data

EMOSIA Name

Units Description High Base Low Source

Baseline Annual Movements (departure)

Movements Only departure movements are taken to calculate delay savings (conservative approach)

140000 140000 140000 Generic Airport Assumption

Ann Flight Growth

decimal fraction

The annual flight growth 4% 4% 4% Expert Judgment

Average Delay Reduction

decimal fraction

CDM implementation in can bring a 3% improvement in terms of delay at the Airport.

4% 3% 2% Expert Judgement

Baseline delays: current average delays per movement

Minutes Based on average departure delay per movement for the last 20 months 11 10 9

Data from CODA (average in an airport like this)

Delay growth = Ann Flight Growth

Decimal fraction

we assume a % increase in delays equal to 4% per year until 2016 if AIRPORT CDM is not implemented (same as traffic)

4% 4% 4% CBA team

Cost of 1 min delay

Euros

100 77 50 Review of

Westminster study (EUROCONTROL)


Euros per flight

7000 6380 5800 Standard Inputs

EUROCONTROL Full-time function dedicated to ATC/FLOW

M Euros

full-time function dedicated to ATC/FLOW -Including Project Management, training, Ops admin and travel


Flight dispatch staffing

M Euros per year

Annual


Travel Costs M Euros per year

Annual 0.005 0.0045 0.003 Site specific

Airports Cancellations avoided

Number of flights

250 200 150 Expert Judgement

(Airports Data) Systems (Software)

M Euros = Annual Implementation (Ann. Imp. M Eur) 0.25 0.15 0.05 Site specific

Airports


The operational examples are given as a proof of concept of the benefits derived from CDM:



• Pre-departure sequence can be optimised, better ground movement and more efficient take off order, less idling on the ground

• More capacity maintained during adverse conditions and the return to normal

conditions is faster. Both mean major cost savings

• Optimisation of gate utilisation and other ground resources. The effects of late incoming or departing flights and missed connections are reduced

• In a more predictable system, the CFMU can improve its calculations, hence less

buffer is built in and this can increase capacity • Greater predictability leads to higher utilisation of staff resources since rosters can be

organised to meet demand. As a result, staff costs will be reduced


The Net Present Value of the investment for the Airlines is equal to 29.39 million Euros.


The diagram below shows the relative sensitivity of the uncertain variables of the model. In this case almost all the variance is explained by 4 variables:

• Average delay reduction • Cost of 1 minute delay • Baseline (situation without Airport CDM) of delays minutes per flight • Cancellations avoided

NPV

€M 29.39

B/C Ratio

8



Figure 23: Sensitivity Analysis

See Appendix D for explanation of the Sensitivity Analysis.


The risk of the project is evaluated by means of cumulative probability curve18. It should be read as follows: the Y axis value gives the probability to get up to the X outcome value (in million euros); or in an equivalent way, the (1-Y) probability to get the X outcome value or more. Under the assumptions of the model the cumulative probability curve reveals that there is no risk of actually losing money in this project, thus even in the worst case scenario the results will be higher than 0. There is a 50% probability of obtaining a result of 29 M Euro or more. See Appendix E for further explanation of the Probabilistic Analysis.







0

10

20

30

40

50

60

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

M E

uro




10. NETWORK BENEFITS (ASSUMPTIONS ONLY – FURTHER STUDY PLANNED 2007-2009)

The DMEAN Framework Programme is a collaborative network approach. It supports all partners in delivering operational improvements to unlock Europe’s potential capacity. As part of the DMEAN Framework Programme, Airport CDM is identified as the driver and mechanism to dynamically integrate airports and the Network. ATFCM needs precise data to calculate demand correctly. Improved information also results in improved flow and capacity management as eventual restrictions can be minimised. The Network benefits will be derived from:

• Demand calculation accuracy: more accurate information on traffic demand contributes to more effective flow and capacity management. Better view of demand enables the appropriate ATFCM measures to be taken (e.g. re-routing, level capping, etc.) with the potential to better use the available capacity and provide more freedom of choice to aircraft operators (e.g. rerouting versus delay or other user preferences).

• The choice should result in a positive net result for the airline. Making use of the

choices/options being offered by the CFMU results in improved planning, enhanced decision making and decreased airline operating costs.

Such benefits will grow as the number of airports implementing Airport CDM increases. The Gate-to-gate philosophy is appropriate: if you contribute to the whole ATM via Airport CDM there is a positive network effect (currently there is no information from the first airport on departure although this would be very important for transfer passengers and to try to avoid reactionary delays). Does more accurate and timely information expected to be provided by Airport CDM contribute to improved flow and capacity management? It is indeed confirmed by the CFMU that more accurate and timely information is expected to bring improvements. Concept versus method: from the perspective of the CBA, the method of delivery of more accurate and timely information (e.g. the DPI and FUM message exchange) is not of particular significance. For the CBA team, the only important consideration was that there is a concept element in Airport CDM that would provide more accurate and timely information to the partners, including the CFMU. Benefits can accrue as a result of better information exchange on the basis of appropriate procedures, it not being necessary to consider what these procedures will be. In other words, the concept is “stronger” in this case than the method as such. It is important to highlight that benefits will grow as the number of airports implementing Airport CDM increases. The exchange of messages with CFMU is expected to be the enabler for the integration of the airport in the ATM Network, one of the 6 areas of improvement of the DMEAN Framework Programme. This message exchange, together with the other benefits will further improve ATFCM.



10.1 Benefits

The predicted main benefit is an increase in en-route capacity of 0.5%. This estimation has been provided by CFMU based on expert judgment and results obtained out of on going trials with the CFMU. Further study is required to achieve a more reliable estimation on potential increase in en-route capacity. As the first validation trials with the CFMU are nearly finalised and additional airports will be soon entering into the message exchange process with the CFMU, we will have by the end of 2008 enhanced data for quantification of additional en-route capacity gains. It is important to notice that in the network capacity only en-route capacity was considered in the network benefits quantification process and not airport capacity. The CFMU has a number of activities running in parallel, all aimed at improving flow and capacity management. In this context, the better exchange of information with the various partners, including aircraft operators and airports, is just one of the paths along which improvements will be realised. As we move into the future, traditional ATFM methods are replaced by the new elements embodied in ATFCM, which will in time deliver a wide range of benefits in the context of flow and capacity management improvements. Some of the improvements will be attributable to better (more accurate and timelier) information. The CFMU has supplied data which in their expert view represented Airport CDM’s expected contributions. These figures will only be based on expert judgment at this time. It was agreed that expert judgment was acceptable though whenever more concrete figures become available, those should be used. In terms of flow and capacity management, the benefits would not come solely from the reduction of delays. Airspace users would benefit to a possibly even greater degree from an increased freedom of choice, where they are able to consider trade-offs to suit their particular business needs in respect of the flights concerned (e.g. less delay but longer route, etc.). In order to convert the 0.5% en-route capacity increase into monetary terms we use some facts stated in the study LINK2000+ Cost Benefit Analysis Review dated 2004, as follows:

• Moving 8 million aircraft costs 6 billion euros. Approximately 4.4 billion of that covers en-route ATS services

• Another fact is that a 0.5% en-route capacity increase, traditionally generates, approximately, a 0.5 % ATM cost increase

• Therefore, any ATM tool that can provide 0.5% extra capacity to en-route ATS at a cost of less than 22 million euros per year is cost-beneficial

• Assuming that the costs of Airport CDM to generate 0.5% increase of en-route capacity is equal 5 M euros per year19

• 17 millions euros are avoided per year • This ANSPs savings will derive in Airline benefit through en-route charges reduction

19 Data to be further studied



The 0.5 % increase of en-route capacity to be achieved will enable overall cost avoidance for ANSPs that will boost the Local partner benefits of implementing Airport CDM (Net Present Value of Network benefits is 73.72 Million Euro).

Network benefits will grow as the number of airports implementing Airport CDM increases.



11. ENVIRONMENTAL SUSTAINABILITY

The principle airport environmental constraints are typically prioritised as (1) noise, (2) air quality and (3) climate change. Air quality and climate change however, are rapidly catching up to noise for some airports and aviation. All of these impacts are relevant to ground operations and can be ameliorated by improvements to ground movement efficiency. It is important to bear in mind that the financial cost of environmental mitigation, environmental constraints and non-optimal operations are borne by the entire industry. Conclusions In qualitative terms Airport CDM will help to deliver improvements in environmental sustainability, principally by reducing engine run time (per flight) and by optimising taxiing efficiency. These operational improvements will also lead to reductions in:

• Noise emissions (disturbance) • Fuel use (finite resource) • Carbon Dioxide (CO2) emission (climate change) • Oxides of Nitrogen (NOx)/ particulates/ unburnt hydro-carbon emissions (air

quality) • Associated mitigation costs (such as noise insulation or compensation) • The likelihood or severity of environmental constraints • The external (societal) costs (health, amenity etc)

• By reducing the occasions, through improved pre-departure planning, that aircraft have to

undergo additional de-icing, Airport CDM may reduce de-icing chemical use leading to reduction on water treatment related operational costs, and in some cases additional taxiing to and from de-icing facilities.

• By optimized use of capacity of existing airfield assets, Airport CDM will delay the need

for new airfield infrastructure with attendant reduction in environmental impacts. To undertake a quantitative assessment for all of these impacts is not possible because the significance of the change will depend on airport specific factors including the proximity of residential development to the airport’s perimeter. However, some quantitative indicators can be determined that give an outline indication of the scale of environmental benefits. The following partial and outline assessment focuses on just the fuel, CO2 and NOx related benefits. To indicate the potential benefits from the reducing in engine running time from Airport CDM, it was decided to examine what benefits would arise by a reduction in taxi time of just 1 minute. To calculate this, a simple fleet mix of representative aircraft categories was selected for the 4 CDM trial airports (Munich, Zurich, Brussels and Barcelona). This was based on aircraft categories for which fuel and emissions data is known, as used in the EUROCONTROL ALACS air quality model. The departure numbers for each aircraft category was derived from 2006 actual flight data for the four CDM trial airports. The fuel emissions indices for this simplified fleet mix were based on the ICAO engine emissions databank (fuel and emissions per second) and an averaging of the values provided for the



more common engine types used by each aircraft category. Expert judgement was used to allocate the actual aircraft types to the equivalent aircraft category. A small percentage of departures by less common or less representative movements such as helicopters, where ignored as insignificant. ICAO engine emissions reference: http://www.caa.co.uk/default.aspx?catid=702&pagetype=90 The fuel and emissions estimates for 1 minute of taxiing at the generic airport were then calculated by a simple pro-rata calculation based on the ratio of movement numbers. Other assumptions used in this outline assessment include:

• Engines are in “as-new condition” (conservative) • Whilst taxiing or holding, engines are in idle power (conservative) • Fuel price is 500 Euros per Tonne (typical value in June 2007) • 1 Tonne of fuel produces 3.15 tonnes of CO2 (a widely used factor) • Airport CDM reduces unnecessary engine running by 1 minute per flight at the

generic airport (This is conservative as tentative results at one trial airport of a 3 minute reduction in holding at the runway threshold from Airport CDM).

An indication of fuel and emissions benefits is illustrated in the table below. Annual departure fuel and emission data for 1 minute of taxiing at the 4 CDM trial airports

Aircraft Type

Number of

Engines

Annual Departure Numbers

Taxi fuel Tonnes

per minute*

Fuel value Euro per minute

Taxi CO2 Tonnes

per minute

Taxi NOX Tonnes

per minute

large jet 2 24.800 793 396.552 882 1,55large jet 3 2.400 92 45.792 20 0,02large jet 4 10.000 440 219.891 279 0,30Medium Jet 2 343.600 9.021 4.510.622 6.897 9,40Medium Jet 4 18.000 572 286.102 36 0,03Regional Jet 2 89.600 1.105 552.487 2.347 2,72Regional Jet 4 60.000 781 390.690 1.100 1,20Small jet 2 19.600 303 151.355 84 0,10Propeller 1 520 0 54 1 0,00Propeller 2 940 1 411 3 0,00Turboprop 1 2.000 1 437 49 0,04Turboprop 2 56.600 141 70.467 657 0,63Turboprop 4 360 1 669 7 0,00TOTAL 628.420 13.251 6.625.529 12.362 16,01* from ICAO emissions data bank - using the weighted average fuel flow rate per second for

the most common engine types for that aircraft type



For the generic airport of 140,000 departures this indicates a pro-rata taxiing fuel and emission rate per minute of

Annual

Departure Numbers

Taxi fuel Tonnes per

minute*

Fuel value Euro per minute

Taxi CO2 Tonnes

per minute

Taxi NOX Tonnes

per minute

140.000 2.952 1.476.042 2.754 3,57

For Europe? A simple pro-rata extrapolation of a 1 minute taxi time saving per flight, for ECAC “Major Airports” (+50k movements per annum), indicates a potential fuel cost benefit of over 120M Euro per annum and a CO2 reduction of around 250K Tonnes per Annum. One CDM airport estimates an average saving of three minutes per flight directly attributed to CDM reducing holding at the runway holding point, so a saving of 1 minute per flight from CDM may be conservative. Additionally, because this assessment does not consider reductions in other atmospheric emissions species, CO2 market value, ground-noise reduction and mitigation costs, the overall environmental benefit assessment is believed to be conservative. However, the base level of average or typical airfield operational efficiency performance is not known. It is probably safe to say however, that if CDM was successfully replicated at a major proportion of European airports, this would probably offer a potential fuel saving worth several tens of Million Euro per annum and a reduction in CO2 of several tens of thousand tonnes per annum. Further there would be other benefits in noise and air quality impacts which are known major causes of constraint on Airports and hence the European ATM system.



12. CONTRIBUTION BY EACH AIRPORT CDM ELEMENT TO THE TOTAL BENEFITS

The Airport CDM project has defined a number of CDM elements, each targeting specific areas of potential improvements (e.g. turn round process, variable taxi times, recovery from adverse conditions, etc.). The CDM CBA analysis looked into the possibility of establishing the order of implementation of the elements, or which combination of elements, would be the most beneficial. Information sharing is by far the most effective element and the incremental additional improvements brought by the other CDM elements are extremely difficult to evaluate individually or in combinations. Once information sharing is in place, the order of implementation or combination of the other elements does not make a significant difference. It is therefore appropriate to implement elements one by one or in combination based purely on the prevailing operational considerations. The analysis has therefore looked at Airport CDM implementation in its totality and not on the basis of individual elements.



13. CONCLUSIONS AND RECOMMENDATIONS

Conclusions The case for Airport CDM is very strong not only from the quantitative point of view but also from the qualitative. Of all the various improvements possible, the introduction of Airport CDM appears to be one of the most important to achieve a quick, cost-effective win-win situation for all partners. The Net Present Value is positive for all the partners. The benefits offset the costs by a factor of 9 and the payback period is between 1 and 2 years for all partners. Regarding the sensitivity analysis the results show that the key uncertainties are related to the key assumptions of the project and the expert judgement given by the airports partners, for example the reduction of delay data provided by the airlines. Each sensitive variable can be studied further to obtain a more accurate picture. Regarding the risk analysis, with the given set of assumptions, the analysis shows that there is very little risk of loosing money for either the Airports and ATC and no risk for Airlines or GH. Consequently, there is no need to undertake further study to reduce uncertainties in the case of the Airlines, GH or Airports but it may be required in the case of the ATC. Recommendations From the perspective of Airport CDM, it is significant that the Cost Benefit Analyses carried out to date shows a compelling case, for all the partners, to implement Airport CDM as a very cost effective operational efficiency enabler. Taking into account the fact the analyses have been based on very conservative assumptions, the results can lead to only one recommendation, namely to start and if possible, to expand or to accelerate the implementation of Airport CDM, as this will increase the overall benefit, including Network Benefits. It is important to understand that only airports that have implemented airport CDM will be able to take full advantage of the DMEAN Concept of Operations. Once the assumptions boundaries are accepted the analysis shows there is small value to gather more information to reduce uncertainty. On the other hand there is a significant value for motivating Airport CDM implementation through, e.g., an incentives scheme to facilitate and accelerate implementation.



14. REFERENCES

Ref 1. Airport CDM Operational Concept Document version 3.0

Ref 2. Benefit Mechanisms Document

Ref 3. Cranfield College of Aeronautics, ´user costs at airports in Europe, SE Asia and the USA´, February 1998, ISBN 1-871564-97-2

Ref 4. EMOSIA User’s Guide Version 1.1

Ref 5. EUROCONTROL Standard Inputs Document 2005

Ref 6. Westminster Study Report, “EVALUATING THE TRUE COST TO AIRLINES OF ONE MINUTE OF AIRBORNE OR GROUND DELAY”, May 2004

Ref 7. LINK2000+ Cost Benefit Analysis Review, 2004



15. GLOSSARY AND DEFINITIONS

Air Navigation Services: This term includes air traffic management (ATM); communication, navigation and surveillance (CNS) services; meteorological services for air navigation (MET); search and rescue (SAR) and aeronautical information services (AIS). These services are provided to air traffic during all phases of operations (approach, ATC and en route) (ICAO Doc 9161/3).

ANS Charges: The sum of En-Route Charges and Landing Charges (including lighting and terminal navigation charges but excluding passenger charges, cargo charges, parking and hangar charges, security charges, noise charges, and other charges on air traffic operations). These charges cover all Air Navigation Services as defined above.

Air Traffic Flow and Capacity Management (ATFCM): A service consisting of tactical and strategic planning activities with the objective of ensuring an optimum flow of air traffic to or through areas during times when demand exceeds or is expected to exceed the available capacity of the air traffic control system. (ICAO Doc 9161/3).

Air Traffic Management (ATM): A systems approach with the objective of enabling aircraft operators to meet their planned times of departure and arrival and adhere to their preferred flight profiles with minimum constraints, without compromising agreed levels of safety. It comprises ground elements and airborne elements which, when functionally integrated, form a total ATM system. The airborne part consists of the elements necessary to allow functional integration with the ground part. The ground part comprises air traffic services (ATS), air traffic flow management (ATFM) and airspace management, where ATS is the primary component. (ICAO 9161/3).

Benefit-Cost Ratio: The ratio of the discounted benefits to the discounted costs. An acceptable project would have a B/C equal to or greater than 1.

Capital Cost Implementation: Investment costs associated with the initial acquisition of equipment and property, for the Operational Improvement Cluster (OI C) implementation. Capital cost implementation distinguishes from Pre-implementation Costs, Replacement Costs, Operating Costs, and One-Off Implementation Costs.

Constant: Quantity that keeps the same value throughout the period of the analysis. This contrasts with a time-series, a variable that is changing over time.

Delay: the CODA definition of delay is, a delay is the difference between a Scheduled Time of a flight event and the Actual Time of that event. This difference is generally expressed in minutes. A delay can be measured on all phases of flight.



Delay on Formula

Departure OUT - STD

Taxi Out OFF - (OUT + Std Taxi Out)

Take-off OFF - (STD + Std Taxi Out)

En Route ON - (OFF + EET) or ON - ETA

Landing ON - (STA - Std Taxi In)

Taxi In IN - (ON + Std Taxi In)

Arrival IN - STA

Sched Pad (IN - OUT) - (STA - STD)

Discount Rate: An economic measure of the pure time value of money. It should not be confused with the rate of inflation. Although the discount rate can vary from commercial to governmental organisations and from an organisation to another, by convention it has been fixed at 8% (for constant price cash flows) in order to make comparable all the cost benefit analysis and to have a consistent portfolio of Operational Improvement Clusters. Nevertheless, the models will allow the users to make their calculations with their own rate. In practice a rate can be derived from indicators such as the net total return on a panel of shares or the net return on capital employed for a panel of companies.

DMEAN Framework Programme: (Dynamic Management of the European Airspace Network) This Programme aims to deliver additional capacity, release latent ATM capacity, improve flight efficiency and introduce a new concept for the operational planning and management of the European ATM network. It is expected that the principles and processes introduced by DMEAN will last until further improvements can be brought by SESAR in the long term.

DPI: (Departure Planning Information) Information provided to the Central Flow Management Unit with a view to updating information on a given flight used in flow management calculations.

ELTD: (Estimated Landing Time) The estimated time that an aircraft will touch down on the runway.

Expected Net Present Value: The weighted average, using probabilities, of possible NPV.

Flight Path Efficiency: The degree to which an individual flight travels the preferred flight path. Full Operating Capability: The time at which an Operational Improvement Cluster is fully operating, with infrastructure and equipage 100% complete, yielding steady state benefit.

FUM: Flight Update Messages

Ground Costs: Costs associated to a ground system, e.g. new ground simulator, ground simulator upgrade.

Influence Diagram: A graphical representation that shows all the variables that impact the net present value of a project.

Internal Rate of Return (IRR): The IRR is the discount rate that equates the present value of the project’s future net cash flows with the project’s initial outlay. The IRR can be



compared with the rates that could be earned by investing the money in other projects to identify the projects that provide the best value for money.

Landing charges (including lighting and terminal navigation charges): This includes charges and fees collected for the use of runways, taxiways and apron areas, including associated lighting, as well as for the provision of approach and ATC. (ICAO Doc 9562). These charges cover all the Air Navigation Services for the airport phase of operations: any or all phases of aircraft operation involving approach, landing, take-off and/or departure (ICAO Doc 9161/3)

Net Present Value (NPV): The difference between the present value of the cash inflows (additional or incremental costs of a new investment) and the present value of the cash outflows (benefits accruing from the new investment and originating from new revenue opportunities and/or cost savings). The NPV gives the magnitude of a project value.

One-off Implementation Costs: Costs represented by one-off services, one-off operating start-up costs, and other one-off expenditure for the Operational Improvement Cluster (OI C) implementation. They distinguish from Equipage Costs, Ground Costs, and Space costs.

Operating Costs: Expenditure associated to the operating phase of the Operational Improvement Cluster (OI C), comprising staff (operating and support staff, internal or external, civil or military); operations (maintenance and repair, material, supplies, utilities and other services); and overhead (administration, personnel, training).

Operational Environment: An environment in the ATM system such as Ground, TMA, and En-route.

Operational Improvement: A single operational change that improves the performance of the ATM system in terms of capacity, safety, environment, or cost.

Net Revenue/Net Saving: This is the total revenue or total saving diminished with associated costs, direct or indirect. E.g. the social costs should be deduced from the benefit of staff force reduction or savings.

Payback Period: The amount of time that it will take for the cash inflows of a project to cover the cash outflows.

Pre-implementation Costs: Expenditure directly or indirectly associated to an Operational Improvement Cluster (OI C) before the implementation phase of the life cycle. These costs distinguish from Capital Implementation, Capital Replacement, One-off Implementation or Operating Costs. They are e.g.: Research, Development, and Overhead costs.

Present value: The equivalent value of some amount of resources after adjustment for time preference by discounting.

Punctuality: The CODA definition of punctuality is; a flight event is punctual if the difference between the Scheduled Time of a flight event and the Actual Time of that event is within an agreed threshold. A generally agreed time frame is 15 minutes, but this time window can be narrowed or enlarged.

Sensitivity Analysis: An analysis of what would happen to the results of a calculation if one of its input parameters were changed while the others remained the same. A practical way to represent a sensitivity analysis is the tornado diagram. Staff Costs: These costs generally cover two types of costs: operational staff and support staff.



Structural Delay and Structural Delay Savings: Structural delay is delay that is predictable to allow for inclusion in flight schedules and repetitive. Savings in structural delay may bring cost savings for airlines (more efficient operation of their network) but also GA and Military (shorter flight times).

Sunk Costs: Costs already spent or committed before a decision is taken, so that they do not depend on the decision and should not be counted in a CBA that aims to guide the decision.

Tornado Diagram: A diagram that shows the relative impact of the uncertainties in a decision model to the objective of interest, usually net present value. The objective of the tornado diagram is to focus discussion and effort on the critical uncertainties in the decision problem.

Transition Costs: Transition costs occur when it is necessary to maintain parts of the current system during the transition period to a new system. These costs are frequently overlooked in CBA, but should be included in the One-off Implementation Costs.



16. APPENDIX A - WORKSHOPS

The following is a list of workshops; meetings with CDM partners (held in 2006):

• 1st Generic CDM CBA Workshop – 27-28th March, EUROCONTROL HQ • Meeting with the Brussels Airport CDM team – 4th April, BIAC • Visiting the CDM related organisations of SN Brussels – 5th April, SN Brussels • Visiting the Barcelona CDM team – 12th of May, Barcelona Airport • 1st Site Specific Workshop in Munich – 22nd of May, Munich Airport • 2nd Site Specific Workshop in Brussels – 6th of June, Brussels Airport • 2nd Generic CDM CBA Workshop – 13th of June, EUROCONTROL HQ • 3rd Site Specific Workshop in Munich – 29th of June, Zurich Airport • 4th Site Specific Airport in Barcelona – 12th of September, Barcelona Airport • 2nd Site Specific Workshop – 27th of September, Munich • 3rd Generic CDM CBA Workshop – 16th of October, EUROCONTROL HQ • Generic vs. Site Specific Workshop – 3rd March, EUROCONTROL HQ



17. APPENDIX B – EMOSIA PROCESS

The following diagram shows the EMOSIA process step by step:

Figure 26: EMOSIA process

Step 1: In this step you define decision criteria according to your project content and progress, collect data and enter it in the data input tables. Before beginning this step you will have made a qualitative impact assessment and, whenever possible, a quantitative assessment, to elicit the benefit mechanisms. These will gain importance as you progress in that the quality of the analysis will depend on the credibility and tangibility of your case. Step 2: Use the data input tables in step two to enter the data and generate spreadsheet models. Step 3: In this step you analyze sensitivity to identify the variable most critical to the Net Present Value (NPV) of the project. Step 4: In step four these variables are assessed in probabilistic terms to analyze the risk of the project. Step 5: In this step you draw conclusions and make recommendations. You can iterate each of these 5 steps as required. Step 6: At this step you need to look back and iterate.



EMOSIA uses standard tools along with the steps:

• Data input tables • Standard baselines • Standard inputs • Influence diagrams • Spreadsheets • Sensitivity analysis graph (Tornado diagram) • Risk analysis graph (cumulative provability curve)

The CBA team may need also to create their own toolbox: historical data, ancillary models for input into EMOSIA models, simulations, etc.

17.1.1 Common Pitfalls to Avoid

In any CBA process there are a series of commonly made mistakes that will distort the numbers and may prevent the audience from reaching the right conclusions. These have to be understood in order to deliberately avoid incurring them. What follows is a (non exhaustive) list of the most common ones.

17.1.2 Overlooked or Underestimated Costs

Within any project there is a natural tendency to minimize costs because of the optimistic nature and enthusiasm about its objectives. Here follows a tentative list of costs that are often overlooked or underestimated, and which need to be carefully investigated:

• Integration costs (part of RT&D): costs of making different elements work together • Validation and trials (part of RT&D) • Transition costs (part of implementation and operating costs): costs of making two

systems (old and new) working in parallel for a transition period • Certification costs • Simulation equipment upgrades (aircraft operators, ATSP) • Diverse overhead costs • Contingency costs

17.1.3 Double Counting

Probably the most common problem with large projects in the aviation field arises because of inter-dependencies between different projects and trade-offs between benefits that lead to double counting. Take for instance two projects expected to deliver the same benefit. The sum of both individually quantified contributions need not be the contribution of both projects as a whole, because of the law of diminishing returns on the resources put at stake. If each project is expected to provide a 5% increase in en-route capacity considering that all the rest of parameters/environment are kept constant, that doesn’t mean that concurrent implementation of both projects will yield a 10% increase in capacity. Once the bottleneck has been somewhat alleviated, the marginal benefit of the second project will decrease,



because the context for its implementation is now different (the first project has already been accomplished). Another mechanism for double counting arises from incorrect allocation of benefits. When an operational improvement can be applied in the shape of two or more benefits that have a trade-off between them, there is the risk of applying it in full to all of them. Assume for instance that an operational improvement can either reduce in 5% the already collapsed ATC workload or conversely increase 3% airport throughput and consequent revenue. The correct thing to do would be to apply all the savings to either a 5% decrease in ATC operational costs, or to 3% increased airport revenue, or some balanced trade-off between them, but never to both of them in full at the same time. Double counting is a simple concept. The difficulty comes in making sure that people are aware of the mechanisms through which double counting happens, and the relevant information required to assess it. Conversations with other Airport Program activities took place to avoid double counting. Some insights from the meetings are: • Cost of delay:

– Use of standard delay model / values (based on the Westminster report’s modification) for the Airport CDM Generic CBA.

– The Site Specific Airport CDM CBAs will use the values provided by local partners.

– A-SMGCS and DMEAN CBAs have applied the same values. So, A-SMGCS, Airport CDM and DMEAN CBAs are harmonized in this aspect.

• DMEAN & Airport CDM CBAs

– The DMEAN CBA did not find benefits that would arise from improvements in the ATFCM process. Airport CDM is therefore free to claim these benefits

• Double Counting between Airport CDM and A-SMGCS CBAs:

– Everyone agreed there is only a “benefit” overlap. Scenario: In case an airport has a CFMU regulation applied due to low visibility:

– As a result of A-SMGCS the regulation required will be less severe (throughput is maintained)

– CDM will contribute to reduce the time require for return to normal operations and so, the regulation will be applied for a shorter period of time

– This benefit overlap cannot be easily quantified in a Generic CBA as it highly

depends on the local airport context. It was agreed that this benefit overlap is mentioned in the Airport CDM CBA in qualitative terms only (under benefits of “CDM in Adverse Conditions” element).



17.1.4 Dealing with Uncertainties

Whenever possible the assessment of costs and benefits will rely on quantitative data analyses using existing data and/or tools such as simulation models. Expert judgment on benefits and costs is used when such data is not available to fill gaps in knowledge. However, most data about things to happen in the future is uncertain by definition. The treatment of these uncertainties conveys that:

• Uncertainty is a consequence of our incomplete knowledge of the world • To deal with uncertainty we use ranges and probabilities • Probability is the quantitative language for communication about uncertainty

The assessment of costs and benefits will include consistent information about its uncertainty (and confidence). For example, if the assessment is entirely based on judgment by one expert, the level of confidence is lower than if the assessment is backed by relevant fast simulation analyses. If the assessment has already reached a level of detail where probability distributions are used, confidence intervals will have to be provided. Modelling the uncertainty in the cost and benefit outcomes can be done following a simple procedure. In order to characterize uncertain variables for a deterministic sensitivity analysis, experts were asked to assign 3 point ranges to the uncertainties as follows20:

• Lower bound: there is only a 10% chance the actual outcome would be lower

• Base case: there is a 50/50 chance that the actual outcome would be higher or lower

• Higher bound: there is only a 10% chance the actual outcome would be higher The expert judgment on the ranges for these uncertainties were revisited (following the iterative nature of the overall CBA process) in order to provide further detail and make it more precise. Uncertainty variables are included relating to:

• Time • Costs • Benefits units and drivers

17.1.5 Expert Judgement

To improve the accuracy of expert judgment (particularly in estimating quantitative values) a structured method that combines and challenges various judgments should be used not only for the economic but also for the related performance assessments (safety, capacity and environment). The method should meet the following requirements:

• enable consensus • provide credible results • provide consistent and non-biased results

20 Other point ranges may be asked depending on the nature of the variable (its kind of probabilistic distribution) and confidence of the experts about them



Several approaches can be considered:

1. Facilitated and structured workshops with all relevant experts to gather their opinions 2. Delphi technique: a structured group technique where one controls the exchange of

information between anonymous panellists over a number of rounds or iterations of self-administered questionnaires. After each round, the facilitator analyses and statistically summarizes the responses and these summaries are then presented to the panellists for further consideration. In the final round an aggregated statistic (median, average etc.) is taken as the group estimate

3. NGT technique also known as estimate-talk-estimate procedure: this is a technique

that differs from Delphi in that feedback after each iteration is done through verbal interaction between the panellists

The Delphi technique has the positive attributes of interacting groups such as knowledge from a variety of sources and creative synthesis without negative aspects such as conflicts and manipulation of groups. It also has the advantages of not requiring that people based in different geographical locations meet, and of providing a means of communication for experts with diverse backgrounds and frames of reference who would find it difficult to communicate in a traditional group setting. However, to obtain significant results with the Delphi technique it is recommended that a reasonable number of panellists are gathered and that these panellists are independent. This may be difficult to ensure, especially for the longer term. The resources required to develop, test, analyze results, re-develop questionnaires and re-assess results for several rounds are also significant. Another difficulty might be to find a wide enough range of panellists who are available to fill in questionnaires in several rounds. Considering the above remarks a more abbreviated approach than the Delphi technique can be used for strategic performance assessments:

• First iteration: interview or ask panel experts to fill a pre-prepared questionnaire • Summary of results of first iteration is discussed at workshops with all participating

experts • Second iteration: experts are asked to review their initial responses and final results

are determined In the Airport CDM CBA project this abbreviated technique has being followed, with adjustments to different situations as needed.



18. APPENDIX C – ELABORATION OF ECONOMIC MODELS

Economic models enable a transition between the conceptual scheme of quantifiable costs and benefits to a spreadsheet that actually delivers the sought after numerical results about the project (NPV, charts, etc). The way this is accomplished is through the creation of influence diagrams that model the intrinsic cost-benefit mechanisms of each partners, and can be parameterised with the relevant data identified both for deterministic and stochastic (i.e. uncertain) variables.

18.1 Influence Diagrams

Influence diagrams are composed of a number of graphical elements or shapes known as nodes. Each of the four types of node represents a specific type of information as shown in the following example There are four types of nodes:

• Value – contains instructions for how to calculate the value of the project in various stages

• Deterministic – expresses constant values or equations combining other variables • Uncertainty – expresses a lack of knowledge concerning the distribution of the

variable • Decisions – include the quantities with one or more possible outcomes which can be

manually controlled Each influence diagram highlights:

• The inputs required for the analysis versus the functions used to calculate cost and benefit and to describe the timing of the costs and benefits

• The uncertainties and where they fit in to the analysis model • The inter-relationships between all the variables (inputs and calculations based on

inputs)



Figure 27: Influence diagram example

Influence diagrams provide:

• A deterministic evaluation of the project by identifying the most critical variables and displaying them in a Tornado diagram (see appendix D)

• A probabilistic evaluation of the project by assessing probability distributions of the critical uncertainties (see appendix E)

18.1.1 EMOSIA Models

EMOSIA provides a set of predefined models that can be reused to a great extent since they were explicitly defined for ATM investments in Europe, and benefit from a great consensus by all partners. Any missing models will have to be defined, and inadequate ones will have to be customized for correct economic evaluation for partners. All the models in EMOSIA are based on standard Excel spreadsheet solutions. This ensures that EMOSIA is easy to use, and that the results are understandable by everyone involved in the decision process.

18.1.2 Model Spreadsheets

Influence diagrams translate into Excel spreadsheets that retain all the calculations needed. This is the first level of output – a spreadsheet displaying inputs, intermediate calculations, the NPV and cash flows (outputs). A spreadsheet is generated for each partner.



These Excel spreadsheets can then be used to:

• Validate the data • Produce charts • Calculate additional indicators such as:

o Payback period o Internal rate of return o Benefit to cost ratio

18.2 Running the Models

These spreadsheets will then be fed with the data identified in previous sections in order to generate the numerical results. Different data sets will allow playing What-if with the models in different scenarios.

18.3 Appraisal of Results

Once the Excel spreadsheets and data sets are combined and run, the results have to be appraised as to reach useful conclusions and being able to prepare an adequate action plan. The appraisal of results is typically done by:

• Analysing sensitivity of the results to model variables (Sensitivity Analysis) • Analysing the probabilistic distribution of the results (Risk Analysis)

The purpose of these reports is to provide the decision maker of the project with the best available information and in a structured way, as to allow him to make a well informed decision.



19. APPENDIX D – SENSITIVITY ANALYSIS

Sensitivity analysis examines the sensitivity of the project’s economic performance – its cots and benefits – to the variation of individual parameters in order to identify the most critical issues and the degree of their impact. The most significant parameters to be considered in the conduct of a sensitivity analysis will vary from project case to project case and cannot be brought in advance. The results of a sensitivity analysis are usually presented graphically. Tornado Graphs are the standard tool for this purpose. A Tornado Graph compares the results of multiple analyses. The X-axis is drawn in the units of the expected value (typically NPV), and then for each variable (listed on the Y-axis), a bar is drawn between the extreme values of the expected value calculated from the lower and upper bound values. See the following picture for an illustration. The variable with the greatest range is plotted on the top of the graph, and the remaining variables proceed down the Y-axis with decreasing range. The longest bar in the graph is associated with the variable that has the largest potential impact on expected value, and thus needs careful attention.

Figure 28: Tornado diagram example

The Tornado graph brings attention to the variables that require further attention. In most real projects, the Pareto rule will happen, as 20% of the variables will typically account for 80% of possible expected value excursion.



20. APPENDIX E – PROBABILISTIC ANALYSIS

Probabilistic Risk analysis provides the probability distributions of output magnitudes. The decision-maker can then have a complete picture of all the possible outcomes. These probability distributions can then be used to perform different assessments:

• Determine a correct range for the results • Identify probability of occurrence for each possible outcome

As a result, it is easy to get an overview of the risks involved and a feeling for how they should be addressed. The probabilistic risk analysis is based on Monte Carlo simulation, and that is the reason why the confidence intervals associated with the uncertainties of the model have to be carefully assessed in order to get the results as reliable as they can be. The following picture shows a typical cumulative probabilistic distribution:

Figure 29: Probabilistic diagram example

It shows what is the probability of having a result equal or higher to a value. SD is the standard variation and measures the spread of the data about the mean value.



21. APPENDIX F – ANALYSIS AND INTERPRETATION OF RESULTS

Partner and expert judgment will make conclusions and recommendations for decision makers. These can either lead to a new iteration of the process or to the acceptance of the results.

21.1 Detailed Revision Process

The detailed revision process is intended to improve results by means of an iterative process. The process will typically take place whenever it is required to achieve:

• greater accuracy in the model or data • less uncertainty (dispersion) on the results (potential outcomes)

Accuracy can be improved by refining the models along with the quest of more accurate input data; on the other hand, uncertainty can be reduced by introducing mitigation measures for the risks identified or carrying out studies that reduce uncertainty on different outcomes. Modifying any of these elements requires going through an iteration of Phases 1 to 3. The iteration process typically takes place every time that, once reached this point in the process, the working group considers that there is still value to be added by an extra iteration taking into account the estimated required effort and boundary conditions given (i.e. budget and/or deadlines). These can be justified if there is a need to:

• Upgrade models/data to better resemble reality o Introduce decision making points in the model o Provide more reliable and/or precise input data o Revise confidence intervals for uncertainties o Introduce new partners o other

• Introduce mitigation measures to manage risk o Perform market prospecting studies o Insurance contracts o Contracting clauses o other



The following picture shows the workflow to be followed for the Detailed Revision Process:

Collect Prior

Information

Produce Output &Evaluate Output

Sensitivity To Inputs

Continue?Collect

AdditionalInformation

Produce Output &Evaluate Output

Sensitivity To Inputs

…Continue?

The EndThe End

Final OutputFinal Output

Y

N

Uncertainty& Risk

Detail& Cost

- +

Figure 30: Detailed Revision Process workflow

In a well designed CBA process, the first iteration usually yields results from which most conclusions can be drawn. Only a few iterations are needed to provide stable and reliable results that require no further fine tuning.



22. APPENDIX G – FORMULAE USED IN COST-BENEFIT ANALYSIS

22.1 Net Present Value

The NPV is computed as follows:

NPV = ∑ CFi / ( 1 + r )i

Where: o CFi represents the net cash flow generated by the applications cluster in year

i. It is computed by subtracting the applications cluster costs in year i from the applications cluster benefits in year i. The costs include investment, transition and operating costs

o i represents a year in the applications cluster life cycle and runs from year 0, the year the initial investment is made, to year n, the final year of the applications cluster life cycle

o r represents the annual discount rate used

Summation would normally be over the lifetime of an applications cluster.

22.2 Benefit Cost Ratio

The B/C Ratio is computed as follows:

B/C Ratio = ∑ Bi / ( 1 + r )i / ∑ Ci / ( 1 + r )i

Where: o Bi represents the applications cluster benefits in year i o Ci represents the applications cluster costs in year i

22.3 PayBack Period

The amount of time that it will take for the cash inflows of a project to cover the cash outflows.



23. APPENDIX H – SUMMARY RESULTS TABLE (BASE VALUES)

Figure 31: Summary Results Table



24. APPENDIX I – MODEL STRUCTURE - AIRPORT

24.1 Functional Description of Airport Model

The airport model computes the net present value of the incremental cash flows associated with the investment. It can be described in terms of three sub-models: Cost Model: The cost model keeps track of all the costs associated with implementing a project from an Airport perspective. Pre-implementation costs are incurred prior to the implementation year. Implementation costs are incurred during the implementation period. They include one-time implementation costs, one-off implementation costs and ground/space costs that require capital replacement over time. New Operating costs are also included in this model. Benefits Achieved Model: The benefits achieved model phases in benefits based on the proportion of the implementation period completed. Benefits Model: The benefits model calculates the net benefit for each of the benefit categories. Benefits are phased in based on the benefits achieved model. The primary benefits are operating cost avoidance and net revenues. For the two savings calculations, a baseline and a new situation baseline, based on the investment’s contribution to that benefit category, is computed. More information is in the AIRPORT MODEL that can be found at: http://www.eurocontrol.int/ecosoc/public/site_preferences/display_library_list_public.html The EMOSIA model has been modified to adjust for the specifics of the CDM investment.



24.2 Model Structure

This diagram is a print screen of the real influence diagram used to generate results. You can find explanation on influence diagram in Appendix C.

Figure 32: Airport Economic Model



25. APPENDIX J – MODEL STRUCTURE - ATC

25.1 Functional Description of ANSP

In the cases of ANSPs operating as a cost recovery system, any costs incurred or benefits received from ATM investments are reflected in the charges made to airspace users. ANSPs in Europe are financially based on a cost recovery system, except NATS. The way they recover the costs of any investment is through the charges and the service units are used to calculate the charges. It has been decided that CDM has a very low investment cost which means that the impact in the charges is going to be very low. We can make the assumption that this data is not significant to be taken into account. More information can be found in the ANSP MODEL at: http://www.eurocontrol.int/ecosoc/public/site_preferences/display_library_list_public.html The model computes the net present value of the incremental cash flows associated with the investment. The EMOSIA model has been modified to adjust for the specifics of the CDM investment.



25.2 Model Structure


Figure 33: ATC Economic Model



26. APPENDIX K – MODEL STRUCTURE – GROUND HANDLERS

26.1 Functional Description of GH Model

The GH model computes the net present value of the incremental cash flows associated with the investment. It can be described in terms of three sub-models: Cost Model: The cost model keeps track of all the costs associated with implementing the project from the GH perspective. Benefits Achieved Model: The benefits achieved model phases in benefits and operating costs based on a proportion, Benefits are achieved in 80% the first year and 20% the second year. Benefits Model: The benefits model calculates the net benefit for each of the benefit categories. Benefits are phased in based on the benefits achieved model. The benefits are operating cost avoidance. For the two savings calculations, a baseline and a new situation baseline is used. This model has been created from the scratch for the project.



26.1.1 Model – Influence Diagram


Figure 34: GH Economic Model



27. APPENDIX L – MODEL STRUCTURE - AIRLINES

27.1 Functional Description of Airline Model

The airline model is described as a series of sub-models and a set of timing elements that permeate all the sub-models. The timing elements are used to describe when costs and benefit are incurred. The investment model summarizes the investment cost associated with the investment. Costs come in the form of pre-implementation costs, implementation costs and operating costs. The benefits model summarizes the net benefit. Benefits are captured in terms of delay savings and avoided cancellations. An input into the benefits model is baselines for delay and cancelled flights avoided. The baseline’s scopes the opportunity against which the proposed investment is achieving benefits. The inputs, such as the cost per delay minute, are used to convert benefits to economic terms.



27.1.1 Model – Influence Diagram


Figure 35: Airlines Economic Model