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CHAPTER 5 The Self-Tagging Decision-Making Tool User Guide Overview This report includes two spreadsheet tools to support the decision-making process: an Assess- ment Tool and a Simulation Tool. These tools address the subjective, qualitative aspects and the objective, quantitative aspects of the implementation of self-tagging. The Assessment Tool guides the user through the different subject areas and specific items that will need to be addressed in an implementation. This tool organizes the prerequisites taken into account by the reference airports and enables the user to determine which are relevant to their airport. The tool will rank and pri- oritize the different elements, which can help determine the complexity of the implementation and scope of the project for the airport. The Simulation Tool enables the users to input their own specific data to determine the impact of self-tagging on space, flow, and resource requirements. These impacts can be quantified and evaluated as part of a cost/benefit analysis. The purpose of the Assessment Tool is to provide the user with the qualitative information required to understand the scope of the potential self-tagging initiative. It allows the user to input data that describes the airport's unique characteristics, business drivers, and operating environ- ment and provides an Assessment Report that details the appropriate strategies, prerequisites to implementation, and pros and cons of self-tagging. This report is built by the ranking and pri- oritization of the multiple prerequisites identified in the airport site visits and industry surveys. The full list of Assessment Report content is included as Appendix C. The user can use the Assess- ment Tool to run reports on different implementation strategies, for example a pilot trial, single market, or full airport installation. This qualitative assessment report can be used to help scope the implementation requirements. Figure 7 shows the opening screen of the Assessment Tool. The purpose of the Simulation Tool is to provide the user with the quantitative information required to forecast the impact of the self-tagging initiative on passenger processing. It allows the user to input data that describes the specific passenger processing environment to be simu- lated, including processor throughput times, resource availability, flight information, passenger demographics, and physical space allocation. This data is used to create a throughput and queue model, which shows the demand versus the capacity for processor resources over time, and a space model, which shows the variances between the current space allocation and the space requirements for the simulated environment. The model can be used to calculate the resources and space required for self-tagging and traditional check-in, as well as kiosk, rework, and bag drop-off. The user can input multiple scenarios to illustrate the impact and support a cost/ benefit analysis. The Simulation Tool is not intended to provide design-level output and does not address optimum layout for improving passenger flow and congestion. Variables such as pas- senger dwell time, entrance points, physical obstructions, counter configurations, queue dimen- sions, and baggage system induction points will all affect the layout design and are beyond the scope of this product. In addition, this tool does not address the impact of passenger self-tagging 23