Data collaboration across airport checkpoints

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Neil Norman, chief executive at Human Recognition Systems (HRS), highlights some of the key issues preventing airports from creating a unified passenger journey

There is a groundswell in the aviation industry about how we address the tri-problem of processing growing passenger numbers through existing terminals, efficiently meeting the demands of evolving security threats, and keeping the passenger happy and spending.

The first wave of solutions to meet these problems has landed in the form of checkpoint automation and biometrics. But with multiple vendors serving each checkpoint along the journey, how is the airport to achieve a unified view of the passenger journey and what is the lost opportunity in not achieving the best passenger experience?

The problem starts (and ends) with procurement

Airports run on procurement cycles, meaning that equipment is introduced on a phased basis, typically defined by a single stage or area of the passenger journey, rather than all in one go. This inevitably results in checkpoint solutions from multiple vendors with varying levels of automation and introduces varied methods of operation, manual exceptions processing and support to process passengers through the airport.

With such expensive price tags on a lot of checkpoint hardware, it’s understandable that airports want to exploit each asset for as long as they can. However, it’s also clear that such an approach is not an efficient or effective way to manage and operate checkpoints and ultimately results in a sub-optimized set of passenger processes which, when added together, delivers a poor passenger experience and reduces time (and money) being spent in retail.

The current approach to procurement across airports ultimately means that it’s quite normal to have different providers across e-gates, bag drop and kiosks. This throws up the immediate problem of standalone systems not talking to each other, each with their own user interface and manual exception processes.

When you add the challenge that airlines will also have some say in which checkpoints are put into place, the airport is left with a mix of checkpoint systems to support and maintain, leaving the IT department with an often very limited view of technical faults or performance issues that could have a knock-on effect on the wider passenger journey.

Visibility across all checkpoint vendors is a rarity, with oversight often limited to very basic operational aspects, such as “Is it alive?” There is a lack of detailed insights as to collective, cross-vendor throughput, and passenger flow performance data is limited to the transactional level.

In short, when things go wrong, as they invariably do, it’s difficult to identify the cause quickly and when a fault affects the most important function of the airport – getting people through the terminal to catch their flight (with enough time to shop) –automation doesn’t sound such a good idea anymore.

Such a segmented approach results in different airport functions having no ability to flex based on real-time operational need or regulatory changes. In an ideal world, they’d be able to have a single, overarching view that enables them to identify problems across their checkpoint estate and optimize performance by, for example, proactively adjusting lane capacity, steering manpower to the right areas of the operation, or technologically slowing passenger through-flow at one checkpoint area to relieve pressure in a particular area of the terminal.

For the majority of airports, the holistic picture doesn’t exist, and that affects overall passenger experience. The length of time a passenger is spending at each checkpoint is a huge factor in understanding how they feel, and it’s important for airports to access data that might help them recognize where improvements could be made. Ultimately, delays at any checkpoint will reduce the amount of time a passenger has to enjoy their airport experience – i.e. more time spent queuing leads to less money being spent.

Checkpoint hardware and biometrics continue to evolve

It is a huge risk for airports to procure checkpoint, biometric and software infrastructure from a single vendor, especially when considering the constantly evolving landscape of checkpoint hardware solutions available to the market, the continued oscillation around biometric choice, and the simple fact that some companies are good at e-gates, whereas others excel in bag-drop machines and so on. Inevitably, an airport will end up with varied checkpoint machines, all with their own software control and approach, which is not a recipe for collaboration across the passenger journey.

So, accepting that an airport is going to end up with expensive checkpoint hardware across multiple vendors, you are left with the challenge of getting them all to play nicely together. At its core, the checkpoint is a physical assembly of components, each performing a particular function (read a passport, take a biometric, open a gate), that are brought together in concert with a localized workflow software sat on a small PC hidden in the casing. The vendor is then forced to hardwire this into external software platforms, such as an airline departure control system (DCS) or airport operational database (AODB), but ultimately, it’s an extension of the e-gate or kiosk.

In summary, you’re either a checkpoint hardware manufacturer or a software product provider, but you can’t have a foot in both camps if operating in a multi-vendor environment ensuring an open standards, agnostic approach.

Data sharing

Software is the solution that binds the hardware together, aligning all systems to provide an effective way to manage checkpoints across an airport by providing a single view of both passengers and checkpoints. Automating processes allows a breadth of data to be made available for all transactions by passengers to help airports to identify trends, e.g. timing issues at bag drop resulting in longer queues through security. This enables proactive responses, rather than waiting for queues to build.

There’s a lot of emphasis placed on airports when it comes to effective checkpoint management but, actually, there is a shared responsibility between airports and airlines to share data. Currently, the two stakeholders operate independently and there isn’t a shared approach nor central repository to store data.

Changing the way airports and airlines communicate could result in aligned checkpoints, faster processes and an altogether more efficient end-to-end journey for the passenger. And, what’s more, this single view of the passenger journey could be shared with that other all-important stakeholder, the passenger themself.

There are airports already doing a great job – London Gatwick, for example, has recently come out top in the Civil Aviation Authority’s passenger survey into the best airport security screening experiences, cutting queue times to just four minutes by implementing biometric processes at its checkpoints to improve the passenger experience, all underpinned by a robust, single, agnostic software passenger platform. It was the first in the world to implement the single-token end-to-end biometric passenger journey approach and today operates a multi-vendor checkpoint and biometric infrastructure, all fully integrated and sat on a single digital passenger ID platform.

Collaboration plus rich data equals new insights and opportunities

With increasing traffic at airports worldwide, and the overall dissatisfaction with the experience thrown in, there is a growing need for a change in the status quo to encourage more data sharing to provide a better solution for everyone – airlines, airports and, most importantly, passengers.

Being able to view every transaction made at every checkpoint for each passenger creates a richness of information that enables trends to be identified is key to understanding and optimizing checkpoint processes. This deeper level of knowledge will allow airports to drive improvements, both in terms of performance and passenger experience, and achieve the ultimate aim of having a single view of checkpoints and the passengers moving between them.

But, more than this, through collaboration a new level of personalization and customer-centric information can be realized. And, when you further correlate this information with retail spend, or localized influencers such as traffic or weather, we are able to not only proactively inform the operation, but adjust personalized service propositions that get us closer to delivering the Uber model to the traveling passenger.

November 21, 2017

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