Practical lessons from implementing a data-driven approach to passenger flow optimisation and airport capacity management

Daver Malik
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Daver Malik: Deputy Aviation Director (Assistant Chief Information Officer), Phoenix Sky Harbor International Airport, USA

Journal of Airport Management, 2023, vol. 17, issue 3, 218-235

Abstract: While airports have traditionally relied upon historical passenger traffic to plan for future operations, that paradigm is fast changing. Stakeholders, business partners and service providers all need insights into expected passenger activity in advance to better plan and support operations. This paper shares the innovative approach that Phoenix Sky Harbor International Airport (PHX) adopted to create a data-driven picture of passenger activity and utilisation of terminal facilities as part of its digital transformation initiative. It shows practical ways to take advantage of existing investments and data sources to create an end-to-end operating picture of the airport. This approach allows airports to quantify, with data, how ‘busy’ each passenger touchpoint is and how that provides a direct way to assess and improve passenger flow within their facilities. The applied methodology allows the airport to understand and maximise utilisation of its terminal square footage capacity and have a clearer picture of where and when congestion occurs. More importantly, the paper provides guidance on how to ‘quantify’ what that congestion means with data, something that many airports struggle with. With this approach, airports can create a detailed data-driven picture of their environments with the technology infrastructure they already have. Firmly rooted in advanced data analytics and modelling, the paper also illustrates how, by sharing detailed passenger demand data, PHX is empowering its business partners to proactively plan and improve service levels.

Keywords: digital transformation; data; analytics; passenger flow; optimisation; capacity (search for similar items in EconPapers)
JEL-codes: M1 M10 R4 R40 (search for similar items in EconPapers)
Date: 2023
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