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					       EUROPEAN ORGANISATION
   FOR THE SAFETY OF AIR NAVIGATION

                                                    EUROCONTROL




 Airport CDM Cost Benefit Analysis




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




EUROPEAN AIR TRAFFIC MANAGEMENT PROGRAMME
                                   Airport CDM Cost Benefit Analysis



                       DOCUMENT CHARACTERISTICS


                                              TITLE


                  Airport CDM Cost Benefit Analysis

                                                 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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                                    Airport CDM Cost Benefit Analysis




                       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: eatmp.infocentre@eurocontrol.int

                       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




Edition Number: 1.4                           Released Issue                                 Page iii
                                Airport CDM Cost Benefit Analysis




                         DOCUMENT CHANGE RECORD

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



EDITION     EDITION     INFOCENTRE                                                    PAGES
                                                   REASON FOR CHANGE
NUMBER       DATE        REFERENCE                                                   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)
                                      6th Draft (review by CDM CBA team –
  0.6     09/02/2007
                                      external stakeholders)
                                      7th Draft (including recommendations
  0.7     03/04/2007                  from Site Specific Workshop – Feb 2007,
                                      review CDM team)
  0.8     19/04/2007                  8th Draft (review by E Miart)
                                      9th Draft (including comments E Miart /
  0.9     25/05/2007
                                      review by P Wilson)
                                      Final Draft – (including comments P
  1.0     10/07/2007
                                      Wilson)
  1.1     18/09/2007                  Minor adaptations requested by APRAG
                                      Proposed Issue (adaptations requested
  1.2     24/09/2007                  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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                                                  Airport CDM Cost Benefit Analysis




                                                        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

   7.4       Operational Examples.............................................................................................................31
   7.5       Results from Analysis..............................................................................................................32

          7.5.1     Sensitivity Analysis ..........................................................................................................32

          7.5.2     Probabilistic Analysis.......................................................................................................33

          7.5.3     Cash Flow Analysis .........................................................................................................34


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

   8.2      Costs .......................................................................................................................................36
   8.3      Benefits and Costs Key Variables...........................................................................................36

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

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

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

   8.4      Operational Examples.............................................................................................................38
   8.5      Results from Analysis..............................................................................................................38

         8.5.1     Sensitivity Analysis ..........................................................................................................39

         8.5.2     Probabilistic Analysis.......................................................................................................39

         8.5.3     Cash Flow Analysis .........................................................................................................40


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

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

   9.2      Costs .......................................................................................................................................43
   9.3      Benefits and Costs Key Variables...........................................................................................43

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

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

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

   9.4      Operational Examples.............................................................................................................45
   9.5      Results from Analysis..............................................................................................................46

         9.5.1     Sensitivity Analysis ..........................................................................................................46

         9.5.2     Probabilistic Analysis.......................................................................................................47

         9.5.3     Cash Flow Analysis .........................................................................................................48


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


     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.
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




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                                                                Airport CDM Cost Benefit Analysis




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.


                                              16
           M Euro (Cumulative Net Benefits)




                                              14

                                              12

                                              10
                                                                                                            Year 1
                                              8
                                                                                                            Year 2
                                              6
                                                                                                            Year 3
                                              4

                                              2

                                              0
                                                   ATC          GH          AIRLINE       AIRPORT   TOTAL
                                              -2


                                                         Figure 2: Cumulative Net Benefits (3 years)




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The graph above illustrates how the cumulative 1 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.


                                                                     Figure 4: Benefit/Cost Ratio

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                                                         Figure 5: Benefits, Investments
                                                                          and Operating Costs
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)




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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 CDM
  elements 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.




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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




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                                  Airport CDM Cost Benefit Analysis




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 Value 2 , Payback Period 3 , Benefit/Cost Ratio 4 ,
Sensitivity Analysis 5 , Probabilistic Analysis 6 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




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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 Inputs 7 used in the development of previous Cost Benefit Analyses related
          to ATM operational improvements




7
    EUROCONTROL Standard Inputs Document




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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.




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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 incremental 8 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).




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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 Ref5 9 . 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




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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.




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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 year 10

3.6                   General Assumptions
       •    Discount rate to be used is 8%
       •    No tax rate being used
10
     Data to be further studied




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    •    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.




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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.2 11 ).

11
     Airport CDM Benefit Mechanisms Document




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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)




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                                                                 Capacity 1
          delay (time)




                                                                                       Capacity 2




          Delay reduction




                                                   Additional movement
                                                   maintaining delays constant




                                                         A                    (number of flights)




                            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.




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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.




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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.

                                             16

                                             14
          M Euro (Cumulative Net Benefits)




                                             12

                                             10
                                                                                                           Year 1
                                             8
                                                                                                           Year 2
                                             6
                                                                                                           Year 3
                                             4

                                             2

                                             0
                                                  ATC          GH         AIRLINE        AIRPORT   TOTAL
                                             -2


                                                        Figure 9: Cumulative Net Benefits (3 years)




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The graph above illustrates how the cumulative 12 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)




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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.

                   25

                   20

                   15

             M Euro10

                    5

                    0
                         2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
                    -5

                                  GH ATC AIRLINE AIRPORT Costs

                         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           Figure 12: Benefit/Cost Ratio
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
                                                       Figure 13: Benefits, Investments and
                                                                 Operating Costs




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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.




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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)




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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.




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6.3.1 Benefits


                           Ops Cost
                           Avoidance


                Ops Cost               Ops Cost               Value of   Cancellations
                 growth                  2006                  cancel      Avoided
                                                                flight




                            Ops Cost                              New revenues
                            avoidance                         (avoided cancellations)




                                             Benefits




6.3.2 Costs



          Develop                Project                    Annual IT            Annual Ops
          Software             Management                 Improvement              Costs
                                                             Costs



              One-Off Implementation Costs                     IT              Operating Costs
                                                          Improvements




                                   Investment Costs




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




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Name                   Units         Description                                  High    Base    Low     Source
Operating Cost         Decimal       Operating Cost Growth Rate in                                        Expert
Growth                 Fraction      baseline                                      4%       4%     4%     Judgment
Operating Cost         millions of   Operating costs for Baseline                                         Generic Airport
2006                   euros                                                       350     300     250    Assumption
Operating Cost         decimal       The % reduction in operating costs,                                  Expert
                                     when fully implemented.
Avoidance %            fraction                                                                           Judgment
                                                                                   4%       2%     0%
                                                                                                          (Airport specific
                                                                                                          CBAs)
Benefits Lag           years         The lag between implementation start                                 Expert
                                     and benefits start and implementation
                                                                                    1       1       1     Judgment
                                     end and benefits achieved at full
                                     operating capability
Implementation         years         The duration of the ground/space                                     Expert
                                     implementation period. (Input a non-
Duration                                                                            3       3       3     Judgment
                                     zero number, even if associated costs
(Imp Duration)                       are zero).
 Value of cancel       Euros         Includes Commercial Revenues                                         EMOSIA
 flight for the                                                                    800     600     300    models
 airport
 Cancellations         Number of                                                                          Expert
 avoided               flights                                                     250     200     150    Judgment
                                                                                                          (Airports Data)
Develop software       M Euros       During implementation period                                         Data from site
                                                                                   0.3     0.25    0.2    specific airports
Project                M Euros       1 Million in 4 years                                                 Data from site
management                                                                          1       1       1     specific airports
Annual IT              M Euros       Per year                                                             Data from site
Improvement                                                                       0.125     0.1    0.08   specific airports
Costs
Annual Operating       M Euros       Per year.                                                            Data from site
                                     This cost is considered as high by
Costs                                                                                                     specific
                                     some of the airports (based on
                                     comments from Generic Vs Site                                        airports.
                                     Specific Workshop). It is left in order to
                                     include the views of all the airports         0.6      0.5    0.4
                                     studied as part of the generic report.
                                     (e.g. high cost in case airport buys a
                                     new system and attributes investment
                                     to CDM)


     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).




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      •   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.


                    NPV           €M 29.9


                  B/C Ratio          8



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




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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 curve 13 . 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




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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).




                   60

                   50

                   40

                   30
          M Euro




                   20

                   10

                    0
                         2006   2007   2008   2009    2010     2011    2012   2013   2014     2015
                   -10


                                  Figure 16: Cumulative cash flow analysis




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7.                    ATC


7.1                   Benefits
The following benefits have been identified for ATC:

       -    Predictability
       -    Punctuality
       -    Efficiency
       -    Network effects

The benefits for ATC 14 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.




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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            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.



7.3.1 Benefits


                    Percentage               Ops Costs                Ops Cost
                   Improvement                                         Growth
                      (CDM)




                                    Operating Cost Avoidance




                                             Benefits




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  7.3.2 Costs

                Maintenance of CDM systems                                       IT Costs




                                              Investment 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   Annual maintenance costs.                                               Data from
                                    This cost is considered as high by
                        of euros                                                                            site specific
                                    some of the airports (based on
                                    comments from Generic Vs. Site               95           85     75     airports
                                    Specific Workshop). It is left in order to
                                    include the views of all the airports
                                    studied as part of the generic report.
IT Costs                M Euros                                                                             Data from
                                                                                 0.3         0.2     0.15   site specific
                                                                                                            airports
Ops cost saving         Decimal     Low range equals 0; it shows the                                        CBA Team
                                    impact of not achieving operational
thanks to CDM           Fraction
                                    cost savings.                                2%          1%      0%
(percentage
improvement)
BL Ops Cost             M Euros     Baseline Operating Costs                                                CBA Team
                                                                                 80           70     60     assumption
Ops Cost growth         Decimal                                                                             Expert
                        Fraction                                                 4%          4%      4%     Judgement



  7.4                   Operational Examples
  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




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      •   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.

7.5              Results from Analysis
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.

                    NPV           3.79 €M

                  B/C Ratio          6


7.5.1 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 % (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




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7.5.2 Probabilistic Analysis
The risk of the project is evaluated by means of cumulative probability curve 15 . 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

See Appendix E for further explanation of the 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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7.5.3 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).




                   7

                   6

                   5

                   4
          M Euro




                   3

                   2

                   1

                   0
                        2006   2007   2008   2009    2010    2011    2012   2013   2014   2015
                   -1


                                Figure 19: Cumulative cash flow analysis




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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.




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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            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.




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8.3.1 Benefits


                                    Ops Cost per       Percentage Ops
                                    Handle Flight      cost influenced
                                                           by CDM


                       Percentage                                        Ops Cost
                      Improvement                                         Growth
                         (CDM)




                                       Operating Cost Avoidance




                                             Benefits


8.3.2 Costs

                                          IT Cost per year




                                       Investment Costs




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  8.3.3 GH Variables


      Name            Units          Description             High            Base   Low          Source
Percentage Ops        %                                                                         CBA Team
cost influenced by                                             30             20     10         based on
CDM                                                                                             expert info
Operating Cost        %                                                                         Expert
Growth (aircraft                                               4%            4%     4%          Judgment
towing)
Percentage            %          % of reduction in Ops                                          Expert
                                 Cost thanks to CDM
Improvement                                                    7%            5%     3%          Judgment
(CDM)
Operating Cost        Euros                                                                     Other
per Handle Flight     per                                     3000           2000   1000        studies –
                      flight                                                                    1st CBA
IT Cost per year      M Euros    Annual IT cost per year                                        Site
                                                              0.25           0.2    0.15        specific
                                                                                                Airports


  8.4                Operational Examples
  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

  8.5                Results from Analysis
  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




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8.5.1 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 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


8.5.2 Probabilistic Analysis
The risk of the project is evaluated by means of cumulative probability curve 16 . 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.


16
   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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                               Figure 21: Probabilistic analysis

See Appendix E for further explanation of the Probabilistic Analysis.

8.5.3 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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                        30

                        25

                        20
               M Euro




                        15

                        10

                        5

                        0
                             2006 2007 2008 2009 2010 2011 2012 2013 2014 2015


                                     Figure 22: Cumulative Cash Flow




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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.

      •       Delay 17 – 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.




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          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                   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.




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9.3.1 Benefits


                              Delay
                            Reduction


                   Cost 1 min                Delay                 Value of      Cancellations
                    of delay              Expected               cancel flight     Avoided
                                         without CDM




                                Delays                                  New revenues
                                                                     (avoid cancellations)




                                                  Benefits


9.3.2 Costs

        Project        Training          Ops admin
      Management                         and travel




                    Full-time function       Flight dispatch     Travel Costs          Systems
                      dedicated to               staffing                             (Software)
                       ATC/FLOW




                                           Operating Costs                          Implementation
                                                                                        Costs




                                          Investment Costs




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  9.3.3 Airline Variables Data


  EMOSIA                 Units        Description              High       Base       Low          Source
   Name
Baseline          Movements      Only departure
                                 movements are taken to
Annual                                                                                         Generic Airport
                                 calculate delay savings      140000      140000     140000
Movements                        (conservative approach)                                        Assumption
(departure)
Ann Flight        decimal        The annual flight growth
Growth            fraction                                      4%            4%      4%      Expert Judgment

Average           decimal        CDM implementation in
                                 can bring a 3%
Delay             fraction                                      4%            3%      2%      Expert Judgement
                                 improvement in terms of
Reduction                        delay at the Airport.
Baseline          Minutes        Based on average
                                 departure delay per
delays:
                                 movement for the last 20                                     Data from CODA
current                          months                         11             10      9       (average in an
average
                                                                                               airport like this)
delays per
movement
Delay growth      Decimal        we assume a % increase
                                 in delays equal to 4% per
= Ann Flight      fraction
                                 year until 2016 if
Growth                           AIRPORT CDM is not             4%            4%      4%         CBA team
                                 implemented (same as
                                 traffic)
Cost of 1 min     Euros                                                                            Review of
delay                                                           100            77     50      Westminster study
                                                                                              (EUROCONTROL)
Value of          Euros per                                                                     Standard Inputs
cancel flight     flight                                       7000           6380   5800
                                                                                               EUROCONTROL
Full-time         M Euros        full-time function
                                 dedicated to ATC/FLOW -
function                                                                                         Site specific
                                 Including Project             0.105          0.09    0.06
dedicated to                     Management, training,                                             Airports
ATC/FLOW                         Ops admin and travel
Flight            M Euros per    Annual
                                                                                                 Site specific
dispatch          year                                         0.315          0.25    0.2
                                                                                                   Airports
staffing
Travel Costs      M Euros per    Annual
                                                                                                 Site specific
                  year                                         0.005      0.0045     0.003
                                                                                                   Airports
Cancellations     Number of                                                                   Expert Judgement
avoided           flights                                       250           200     150
                                                                                               (Airports Data)
Systems           M Euros        = Annual Implementation
                                 (Ann. Imp. M Eur)                                               Site specific
(Software)                                                     0.25           0.15    0.05
                                                                                                   Airports




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




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      •   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



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



                     NPV          €M 29.39


                  B/C Ratio           8



9.5.1 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 4 variables:

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




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                                           Figure 23: Sensitivity Analysis

See Appendix D for explanation of the Sensitivity Analysis.

9.5.2 Probabilistic Analysis
The risk of the project is evaluated by means of cumulative probability curve 18 . 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.




18
   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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                                    Figure 24: Probabilistic analysis



9.5.3 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).




                        60

                        50

                        40
               M Euro




                        30

                        20

                        10

                        0
                             2006 2007 2008 2009 2010 2011 2012 2013 2014 2015



                                Figure 25: Cumulative cash flow analysis




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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.




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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 year 19
       •    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




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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.




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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




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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

                                         Taxi fuel                  Taxi CO2 Taxi NOX
                      Number     Annual              Fuel value
    Aircraft                              Tonnes                     Tonnes       Tonnes
                        of      Departure             Euro per
     Type                                   per                        per          per
                      Engines   Numbers                minute
                                          minute*                    minute       minute
 large jet              2      24.800           793      396.552          882          1,55
 large jet              3       2.400            92       45.792           20          0,02
 large jet              4      10.000           440      219.891          279          0,30
 Medium Jet             2     343.600         9.021    4.510.622        6.897          9,40
 Medium Jet             4      18.000           572      286.102           36          0,03
 Regional Jet           2      89.600         1.105      552.487        2.347          2,72
 Regional Jet           4      60.000           781      390.690        1.100          1,20
 Small jet              2      19.600           303      151.355           84          0,10
 Propeller              1         520             0           54             1         0,00
 Propeller              2         940             1          411             3         0,00
 Turboprop              1       2.000             1          437           49          0,04
 Turboprop              2      56.600           141       70.467          657          0,63
 Turboprop              4         360             1          669             7         0,00
 TOTAL                        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




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

                                                                       Taxi CO2    Taxi NOX
                           Annual       Taxi fuel        Fuel value
                                                                        Tonnes      Tonnes
                          Departure    Tonnes per         Euro per
                                                                          per         per
                          Numbers       minute*            minute
                                                                        minute      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.




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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.




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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.




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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




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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.




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                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




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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.




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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.




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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




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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.




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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,




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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).




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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 follows 20 :

     •    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




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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.




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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)




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                              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.




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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.




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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.




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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.




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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




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



                                                                          Uncertainty Detail
             Collect       Produce Output &                                 & Risk    & Cost
               Prior        Evaluate Output
           Information    Sensitivity To Inputs

                                 Collect           Produce Output &
            Continue?
                          Y     Additional          Evaluate Output
                               Information        Sensitivity To Inputs


                                                     …                        - +
                                                   Continue?
                                                         N

                                                  Final Output
                                                  Final Output


                                                   The End
                                                   The End


                         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.




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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.




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




                                 Figure 31: Summary Results Table




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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.




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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



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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.




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25.2          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 33: ATC Economic Model




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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.




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26.1.1 Model – Influence Diagram
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 34: GH Economic Model




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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.




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27.1.1 Model – Influence Diagram
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 35: Airlines Economic Model




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