Are you being served? Reinventing the airport check-in experience
As airports handle record numbers, crowded check-in halls are becoming more commonplace, prompting airports to rethink their approach to space, resources and passenger experience.
Common-use terminals are gaining popularity as an efficient way to accommodate more travellers. With multiple airlines sharing airport space including counters and bag drops, airports can manage resources better to meet demand and improve throughput.
It’s time for a holistic approach
Sharing resources presents its own challenges. How can airports optimise the check-in process for efficiency while smoothing the travel experience? How do they balance the needs of full cost and low service airlines in one terminal? And, how do they adapt to growing preferences for online or self-service check-in?
Without a holistic view of check-in areas and the right insight tools, it’s challenging to achieve the right quality/cost balance for airline customers and passenger experience. The shift to common-use resources, therefore, requires a new approach.
Typically, hall allocation is stacked in favour of heavy-hitter airlines – not towards the best use of available space.
When allocating check-in resources, consider the entire terminal. Collect and analyse queue formation data, plus processing rates by counter and airline, to identify congestion or safety issues. As well as being used for allocating a fixed resource, a holistic view also helps determine the optimum location for self-check-in kiosks
Predicting passenger behaviour
Traditional check-in models allocate static desks per flight for three hours. This results in uneven capacity management. Data from Dolby and Holder Consulting suggests that fixed counter timeframes cause a 40 per cent decrease in capacity, require 22 per cent more handling agents, and cost 22 minutes in lost dwell time.
By layering show-up profiles with check-in preferences per flight, airports can more accurately predict resource demand. Keflavik Airport, for example, successfully adjusted worker shifts based on forecast arrival/wait times, optimising costs and services.
Automating resourcing decisions
With sophisticated, often conflicting check-in resource planning considerations, intelligent allocation tools enable airports to automatically balance resource availability and predicted demand with factors like airline preferences and service level agreements.
Models are optimised for maximum efficiency, for instance, grouping airlines by ground handler to reduce baggage errors. Passenger experience factors, like walk time, can also be addressed by coordinating resource allocation from check-in to gate.
Intelligent automation both optimises resources for blue-sky days and allows for flexible planning for unexpected events and improved impact forecasting. When Sydney Airport implemented a holistic approach to check-in together with automated resource allocation, capacity increased by 15 per cent.
Incentivising better throughput
Directly linking resourcing to billing allows airports to demonstrate the financial and efficiency benefits of resource-sharing to airline partners, whose early engagement is critical in any operations process transformation.
Differentiated charge structures can also be used to incentivise airline efficiency including the uptake of dynamic counter allocation and self-serve check-in kiosks. For instance, Auckland Airport differentiates charging for check-in services to distinguish between traditional counters, common-use versus dedicated bag drop facilities.
Happier passengers, more efficient airports and airlines
This holistic, predictive collaboration approach to check-ins helps reduce queues and improve the passenger experience – and happy travellers tend to spend more time and money in concessions.
Airports and airlines win too. More fluid check-in resource usage and efficiency gains enable airports to defer expansion investments and introduce common-use self-check and baggage drops, further increasing capacity
A holistic terminal approach really is a common solution for all.