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78 This chapter presents a highlight of the key factors that will lead to a successful airport data collec- tion effort. 8.1 The Importance of Good Data Recognizing the significant financial investment often required for terminal or process improve- ments, it is beneficial to support the decisions and planning with data that has been gathered in a technically rigorous manner. Doing so will also increase the likelihood of stakeholder âbuy-in.â 8.2 Typical Airport Passenger Processes The most common processes observed at an airport include passenger check-in/ticketing, pas- senger and bag security screening, FIS (international arrivals processing), baggage claim, and air- port boarding and deplaning. While some processes have stayed fairly static, others are characterized as dynamic due to evolving technology, security protocols, and changing passen- ger characteristics and behavior. 8.3 Confirm Need for Data and Feasibility of Data Collection Although data collection costs are minor relative to construction costs, they are not immate- rial. Additionally, time constraints may make the execution of a data collection effort very diffi- cult. Finally, from a logistical perspective, there may be challenges to gathering data on some passenger-related processes due to security or proprietary issues. For these reasons, one should always explore whether extant data might already exist and consider the degree to which the data would be used in decision making in order to weigh the potential benefit of conducting the study against its cost. 8.4 Study Team Airport data collection efforts are organized around a study team, including a project man- ager, survey manager, research and statistical expert, survey assistant, data analyst, administra- tive support, and data collection staff. Depending on the size and duration of the study and the qualifications of team members, some staff members may have multiple roles. C H A P T E R 8 Summary
Summary 79 8.5 Airport Specific Metrics When analyzing processes, one is largely focused on entities (typically, passengers and bags); resources (such as an agent or ticket kiosk); and processes (a function performed on an entity by a resource). The processing rate is defined as the number of entities processed by a single resource in a given unit of time and can only be expressed from the perspective of the resource. A pro- cessing time is the duration of a transaction from the perspective of either the entity or the resource. Failure to operationally define entities, resources, and processes at the start of a research project will limit the value of the collected data. 8.6 Sampling Techniques for Airport Data Collection While there are many sampling approaches that can be used in gathering data at an airport, the overarching goal is to ensure the sample reflects the population of interest to allow the research to make inferences about the population. The challenge then becomes avoiding con- venience samples (where individuals are included because theyâre available) and instead ensuring that each element in the sample has an equal (or at least known) chance of being selected. The first step in obtaining a representative sample is defining the study population. This is accomplished by identifying the entities, resources, and processes of interest, the location, and the time period. When the desire is to obtain processing rate information, data collection is often scheduled during a peak period. Peak periods can be identified by examining airport activity sta- tistics, published flight schedules, or asking informants (i.e., knowledgeable airport, airline, or government personnel). The sample size is primarily based on balancing the amount of risk or error one is willing to tolerate relative to available resources (time and money). If one is interested in subgroups of pas- sengers or processes, samples will need to be stratified, increasing the sample size and cost. 8.7 Action Plan The action plan includes defining roles and responsibilities within the study team, framing relationships between the study team and sponsors/clients, determining who will staff the sur- vey, determining how many staff are needed, selecting the data collection method, and schedul- ing specific data gathering periods. There are several options for data collection staffing, including enlisting airport personnel, employing consultant staff, using college interns, hiring temporary staff, and using a market- research firm. Each has its advantages and disadvantages. A typical study will need at least two months lead time, although this would increase directly with the complexity and magnitude of the data collection effort. There are several data collection technologies, including basic paper and pencil; hand-held devices (PDAs); video monitoring; and video capturing software. The advantages and disadvan- tages of each method should be considered relative to the type, complexity, and amount of data being collected. Attention should be given to providing the appropriate level of staff. Consideration should be given to not only the duration, complexity, and amount of data being collected, but to other issues, including facility layout, lines-of-sight, and anticipating contingencies.
8.8 Managing and Implementing Data Collection It is strongly recommended that, to answer many of the questions above, a site visit and pilot test be done prior to actual data collection. This will allow refinement of the action plan. To help ensure a successful data collection event, a staff training session is also necessary. During the training, the study purpose should be overviewed, procedural and management issues should be addressed, and actual training should be conducted. Finally, during the actual data collection effort, the management team should monitor data collectors to make sure procedures are being followed and address any unforeseen issues that may arise. 80 Airport Passenger-Related Processing Rates Guidebook
