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S U M M A R Y The management and planning of airports depends heavily on projections of the future requirements of a wide range of airport users and stakeholders (airlines, passengers, other commercial customers, government and regulators, lenders, and so forth) over a long-term horizon. Airport facilities have long life spans of 20 years or more. Investment decisions such as terminal expansion can lock in the airport to a particular service level and operating cost for long periods of time. Forecasts of future airport activity are thus an essential tool for airport planning and financing decisions. These forecasts provide guidance on future passenger, cargo, and air- craft activity that the airport may face that, when compared to existing capacity, helps define future facility, commercial, and financing requirements. An accurate forecast used to drive investment policy creates significant value for the airport and its users. Conversely, an inac- curate forecast can result in poor timing of investment and lock in higher operating and financing costs. Why Was This Guidebook Written? In recent years, the ability of traditional forecast techniques to produce reliable estimates has come into question. There are numerous examples of unforeseen events and develop- ments that led to weaker traffic than anticipated. Terrorist attacks, economic recession, natural disasters, technological changes, new airline business models, air carrier failures or mergers, and other events have caused dramatic and unexpected shifts in air traffic levels at some airports. While some airports have experienced negative changes in airport activity, others have experienced unexpected strong growth, placing pressure on airport resources. More gradual societal changes, such as the increasing concern about the environmental impact of aviation, can also affect the accuracy of longer-term forecasts. Nevertheless, many airports still rely on traditional forecasts to guide their planning and decision making. One of the challenges of the traditional forecast approach is that it typically treats uncertainties in the future as minor perturbations to the general trend line (normally expressed through low and high scenarios). In reality, few airports find their actual traffic matches these trend forecasts, either in the long-term level of traffic or in the timing at which traffic reaches the critical levels requiring new capacity. Both the level and timing of future traffic is uncertain, and investment decisions based on steady trends can lock in airport costs and service levels in unwanted ways. The purpose of this guidebook is to provide a straightforward and transparent systems analysis methodology to assist airport management in making decisions in the face of an uncertain traffic outlook. The guidebook offers tools for improving the understanding of risk and uncertainty in air traffic forecasting and provides approaches for enhancing the 1
2robustness of airport planning and decision making. It is designed to augment standard master planning and strategic planning approaches with methodologies that directly address risk and uncertainty and allow the incorporation of relevant risk mitigation measures. The guidebook is structured to be accessible to a wide range of users. In addition to this summary, which provides an overview of the issues and methodology: ⢠The main report provides an expanded discussion of the issues and detailed guidance on the use of the methodology, including illustrations of its application using two case studies; and ⢠Technical appendices provide more technical readers with in-depth information on the background research, methodologies, and statistical techniques. Uncertainties Inherent to Airports Some of the uncertainty faced by airports originates from being part of the larger aviation industry, which itself faces risk and uncertainty, and some arises from the specific character- istics and circumstances at individual airports. Both types of uncertainty can affect the overall volume of traffic (total passengers, operations, air cargo) and the type or mix of passengers (domestic versus international, low-cost carrier versus legacy, aircraft mix, and so forth). Common sources of uncertainty are: ⢠Global, regional, or local economic conditions. This can range from national recession to the health of a local manufacturing plant. ⢠Airline strategy. Decisions to expand or contract services or changes to hubbing strategies. ⢠Airline structure. Mergers, restructuring, or failure. ⢠Low-cost carrier growth. The entry and expansion of a low-cost carrier can result in rapid traffic growth. ⢠Technological change. Developments in aircraft technology, air traffic control, and passenger facilitation. ⢠Increased competition from other regional airports. For example, low-cost carrier growth at secondary airports has placed additional competitive pressures on primary airports or competition for air cargo operations. ⢠Regulatory and government policy. Government decisions regarding security require- ments, noise restrictions, emission standards, carbon taxes and caps, and so forth. ⢠Social or cultural factors. Changes in the attitude of society and business towards the use and value of air travel. ⢠Shock events. The September 11, 2001 (9/11) terrorist attacks, the SARS outbreak in 2003, Hurricane Katrina in 2005, and so forth. These types of uncertainty have had implications for airports that depended on conven- tional forecasts to guide their development. This guidebook describes a number of exam- ples where unforeseen events and changing conditions, not accounted for in the original forecasts, have had significant positive or negative impacts on the airport, in many cases changing the economics of the airport due to locked-in capacity decisions. Some of these examples are: ⢠Lambert-St. Louis International Airport: loss of a major carrier. The airport experienced large reductions in passenger traffic due to the collapse of its largest carrier, TWA, leading to excess airport capacity and unused facilities.
3 ⢠Baltimore/Washington International Thurgood Marshall Airport: significant change in traffic mix. The airport experienced a significant shift in traffic mix due to the downsizing by US Airways and the growth of Southwest Airlines, causing underutilization of the inter- national terminal and congestion in the domestic facilities. ⢠Louis Armstrong New Orleans International Airport: large natural disaster. The New Orleans region was devastated by Hurricane Katrina in the summer of 2005, which resulted in an immediate and substantial loss in passenger traffic that has not yet been recovered. ⢠Bellingham International Airport: unexpected upside traffic growth. Bellingham Inter- national Airport has experienced much higher than forecasted traffic growth largely as a result of the entry of low-cost carrier Allegiant Air. ⢠Zurich Airport and Brussels Airport: collapse and restructuring of the main hub airline. Both airports experienced a similar event involving the collapse of a home carrier that was replaced, but only partially, by a smaller restructured airline. Both airports saw traffic decline dramatically, which was then followed by varying degrees of recovery. ⢠Washington Dulles International Airport: widely fluctuating traffic volumes. Over the last decade, the airport experienced extreme fluctuations in traffic volumes, due largely to market entries and exits of diverse air carriers as well as economic downturns and the 9/11 terrorist attacks. This has made forecasting challenging and resulted in large changes in the airport outlook. How to Better Address Uncertainty in Air Traffic Forecasting The traditional approach to addressing uncertainty in air traffic forecasting is to supple- ment the base-case forecasts with high and low forecasts. These do convey that there is uncertainty in the forecast and provide a rough, although typically narrow, range of likely outcomes. Other standard approaches include the use of what-if analysis, which generally looks at the impact of a single event, and sensitivity analysis, which examines the impact of varying key assumptions or model parameters. However, these approaches provide airport planners and investors with only a cursory understanding of the risk profile facing the airport and offer little information on the vari- ous factors that may influence traffic development. Furthermore, due in part to the limited insight they provide, the findings from these approaches are rarely incorporated into the planning process in any meaningful way. The research for this guidebook has identified additional methodologies that can be used in air traffic forecasting to provide richer information on the implications of risk and uncertaintyâinformation that can feed directly into the planning process. The selection of forecasting techniques will depend on the needs and resources of the airport, but may include: ⢠Delphi or formal elicitation methods. These are a broad set of techniques incorporating input from subject matter experts and stakeholders; they allow risk factors to be identified and their impacts explored. ⢠Scenario analysis. A large number of separate scenarios can be developed and played out to assess the impact of different sets of events occurring together. These scenarios can be built on the findings from the Delphi/elicitation methods. ⢠Monte Carlo. A statistical simulation technique that makes use of randomization and probability statistics to generate an often wide range of possible traffic outcomes and provide estimates of the probabilities of such outcomes. Monte Carlo analysis has become much more accessible to general users thanks to the availability of specialized statistical software packages.
4These forecasting approaches are not necessarily intended to produce more accurate fore- casts; they are designed to provide a greater understanding and awareness of future uncer- tainty. This understanding can then be used in the planning process as well as for providing input to strategic analysis and financial analysis. Incorporating Flexibility into Airport Planning The enhanced forecasting techniques provide the greatest value when combined with a planning process that seeks to achieve maximum flexibility in the face of an uncertain future. A number of conceptual and practical approaches have been developed in airport master and strategic planning that allow greater flexibility and diversification. Many of these approaches come under the umbrella of real options. Like financial options, a real option is the right, but not the obligation, to take a certain course of action. Real options apply this approach in the real, physical world rather than the financial world (although real options still have financial implications). The concept started to develop in the 1970s and 1980s as a means to improve the valuation of capital-investment programs and offer greater managerial flexibility to organizations. Real options and real options analysis are used in many industries, particularly those undertaking large capital investments (e.g., oil extraction and pharmaceutical). The use of the real options concept and its related analytical techniques is not prevalent as a concept in airport planning and design. However, some of the design choices made by airports do encapsulate the ideas behind real options. Examples of real options or flexible airport planning are: ⢠Land banking: Reserving or purchasing land for future development to allow for the option of expanding the airport as traffic grows. ⢠Reservation of terminal space: Similar to land banking, this involves setting aside space within the terminal for future use (e.g., for security processes). The space can be designed in such a way that it remains productive in the short term (e.g., using it for retail that can be removed easily). ⢠Trigger points/thresholds: The next stage of development goes ahead only when prede- termined traffic levels are reached. ⢠Modular or incremental development: Building in stages as traffic develops. This avoids the airport committing to a large capacity expansion when it is uncertain when and how the traffic will develop. At the same time, the airport can respond to strong growth by adding additional modules. ⢠Common-use facilities/equipment: For example, common-use terminal equipment (CUTE), common-use self service (CUSS), common gates, lounges, and terminal space. ⢠Linear terminal design and centralized processing facilities: These allow the greatest flexibility for airport expansion since they are more easily expandable in different direc- tions and allow flexibility in the face of changing traffic mix. ⢠Swing gates or spaces: Can be converted from domestic to international traffic (or between types of international traffic) on a day-to-day basis. ⢠Non-load-bearing (or glass) walls: As with swing gates, terminal space can easily be con- verted from one use to another. ⢠Use of cheap, temporary buildings: Allows the airport to service one type of traffic (e.g., low-cost carriers) while keeping options open to serve other types (e.g., full service or transfer). An example is Amsterdam Schipholâs low-cost carrier pier. ⢠Self-propelled people movers (e.g., buses) rather than fixed transit systems: The service is easier to expand, contract, and redirect.
5 ⢠Air service development: A diversification/hedging strategy to increase the range of carri- ers and routes operated at the airport to reduce exposure to a particular carrier or market. ⢠Development of non-aeronautical revenues and ancillary activities: Revenue diversifi- cation as a risk mitigation strategy. By relying less on aircraft operations and passenger enplanements, airports can reduce their systemic revenue uncertainty associated with the air travel industry. The greater flexibility that real options provide can have significant value to a decision maker. However, real options sometimes (but not always) impose a cost. The trade-off between the real optionâs value and its cost will determine whether to go ahead with the option. Various analytical approaches have been developed to evaluate and value real options, some of which have been incorporated into this guidebook. A General Framework and Methodology for Addressing Uncertainty in Future Airport Activity At the core of this guidebook is a systems analysis framework and series of related meth- odologies for addressing uncertainty in airport decision making. The framework and related methodologies have been developed from research on forecasting techniques and flexible planning. The systems analysis framework and related methodologies are designed to assist airport decision makers with: ⢠Identifying and characterizing risks (threats or opportunities), including their plausibility and magnitude; ⢠Assessing the impact of these threats and opportunities (i.e., determining what could happen, to which air facility, and when it might occur); and ⢠Developing response strategies to avoid or lessen the impact of threats or foster the real- ization of opportunities. The methodology in this guidebook is designed to be general enough to accommodate a variety of airports and projects and to be scalable in order to match the methodology with the resources and needs of the airport. It has the ability to allow planners to consider a broad range of events and risks and to help them anticipate possible changes that may follow. It is not designed to replace the master planning process or any other planning or decision- making processes. Instead, the approach augments existing approaches with methodologies that allow airport planners to better analyze risk and uncertainty and incorporate relevant mitigation measures into the planning process. As illustrated in Figure S-1, the systems analysis framework is composed of five key steps. Each step can be executed at differing levels of quantitative detail depending on airport and project size, scope, and complexity. The five steps are: 1. Identify and quantify risk and uncertainty. Using a combination of data-based and judgment-based methodologies, the first step identifies and attempts to quantify risks and uncertainties facing the airport. The ultimate output from this step is a risk register that summarizes what is known about each risk and can feed this information into the other steps of the process. The guidebook identifies risk factors that have affected airports in the past and provides techniques to identify additional risks specific to the airport and to quantify their implications. 2. Assess cumulative impacts. This step involves analysis and modeling to assess the combined impact of the identified risks and the implications for traffic development.
6It involves the development of a structural model incorporating uncertainty whose pri- mary purpose is to evaluate the combined effect of multiple risks on airport activity and help define and assess alternative courses of action (response strategies). 3. Identify risk response strategies. Based on the output from Steps 1 and 2, this step iden- tifies risk response strategies that will help avoid or mitigate negative risks and exploit or enhance positive risks. It is often the case that the same strategies can address a broad range of risks. One key finding from this research is that many risk strategies are appli- cable regardless of the risk profile or even the circumstances of the airport. 4. Evaluate risk response strategies. This step undertakes a qualitative and quantitative evaluation of the risk response strategies identified in Step 3 to demonstrate their effec- tiveness and value for money. This may result in revisions to the risk response strategies. The risk response strategies from Step 3 are designed to reduce the likelihood or impact of potential threats and to capitalize on possible opportunities. Inevitably, the choice of a strategy to respond to a particular risk is difficultâin particular, because its effec- tiveness cannot be fully understood until the risk actually occurs. An evaluation of the economic and/or financial value of risk response strategies can be conducted to assist in the selection. The evaluation serves a number of purposes: to identify the highest value Figure S-1. Systems analysis methodology overview.
7 risk response strategy, to demonstrate robustness over a wide range of outcomes, and to determine value for money. 5. Risk tracking and evaluation. This final step is slightly different from the others because it represents an ongoing process of review and revision. Step 5 involves tracking risks and traffic over time and flagging potential issues, taking action prescribed in the risk response strategies if potential risks do materialize, and making revisions to the risk register and risk response strategies. The ultimate aim of Step 5âs risk tracking and evaluation is to foster a high level of risk awareness and responsiveness within the organization. The system analysis methodology provided in this guidebook has a number of goals: ⢠Increase awareness of the degree of risk and uncertainty facing an airport through par- ticipative approaches with the airport management team and other relevant stakeholders. This will encourage a greater consideration of risk and uncertainty within the decision- making process at the airport. ⢠Increase robustness by encouraging planning and design concepts that allow greater flex- ibility to deal with unexpected and unplanned events and circumstances. ⢠Increase readiness by having a reasonable road map to follow should certain events arise. It would not be viable to make investments in anticipation of events that at the time appear fairly unlikely (such as a new carrier arriving). In some cases, airports will have to wait for events to develop. Nevertheless, the methodology provides airports with a considered plan to follow rather than having to scrap an old plan and rapidly come up with a new one (which can potentially lead to poor decision making). A key lesson is that forecasting must take into consideration what can happen in addition to what seems most likely to happen. Forecasts should provide more information on the type, range, and impacts of different future outcomes. The forecasting methods described in this guidebook offer forecasts that are less prescriptive and more informative. It should also be noted that the methodology is based on identified risks. However, there are also unidentified risks that are impossible to anticipate (sometimes referred to as unknown unknowns or black swans). Nevertheless, by applying the methodology in this guidebook, airport planning will be more robust with regard to unanticipated as well as anticipated risks. Furthermore, it should be noted that although much of the material in this guidebook is focused on master planning processes, its methodology can also be applied to strategic, business, and financial planning. The guidebook concludes with recommendations for further development of the systems analysis framework, principally in relation to rare, high-impact events and political risk. While the systems analysis methodology presented here reflects the state of the art in dealing with these two factors, additional research offers the potential for advancing the state of the art.
