Hub Airport 4.0 – How Frankfurt Airport Uses Predictive Analytics to Enhance Customer Experience and Drive Operational Excellence
In this article, an overview is given of several recent projects at Frankfurt airport that broke new ground by using predictive analytics and adopting innovative approaches to tackle commercial and hub specific operational challenges with big data analytics. The first exemplary project focused on the design and implementation of a comprehensive passenger flow management solution, which resulted in reduced waiting times leading to significantly increased customer satisfaction. Furthermore, the Smart Data Lab concept is presented, an agile approach to investigate business opportunities with predictive analytics which has been successfully applied to various topics such as recognizing trends in retail revenues.
- 1.R. Felkel and D. Klann, “Comprehensive passenger flow management at Frankfirt Airport,” Journal of Airport Management, vol. 6, no. 2, pp. 107–124, 2012.Google Scholar
- 2.ACI World Airport IT Standing Committee, “Best Practice on Automated Passenger Flow Measurement Solutions,” 27 August 2015. [Online]. Available: http://www.aci.aero/media/2c9abef1-ae58-40ed-9d33-4bdd925aee89/NGQA3Q/About%20ACI/Priorities/Facilitation/Best-Practice-on-Automated-Passenger-Flow-Measurement-Solutions.pdf.
- 3.C. Mayer, R. Felkel and K. Peterson, “Best practice on automated passenger flow measurement solutions,” Journal of Airport Management, vol. 9, no. 2, pp. 144–153, Winter 2014–15.Google Scholar
- 4.“Google Play – FRA App,” Goolge, [Online]. Available: https://play.google.com/store/apps/details?id=com.infsoft.android.fraapp&hl=de. [Accessed 09 08 2016].
- 5.“iTunes AppStore – FRA App,” Apple, [Online]. Available: https://itunes.apple.com/de/app/frankfurt-airport-fra-airport/id453191399?mt=8. [Accessed 09 08 2016].