From why to wow: How airports can use data to improve the passenger experience

When I tell people that I work in airport technology, they often respond with a story about a recent experience with a delay or disruption at an airport that they think can be solved with technology. Despite the issues in airports last year (caused mainly by a lack of staff for baggage handling and security screening), most people don’t jump to examples requiring advanced robotics or autonomous machines. The most frequent gripes relate to data: Why doesn’t the airline know where my bag is? How could the airport not be prepared for my flight’s early arrival when the plane has been in the air for hours? Or, How did it not know that there would be extra passengers today—don’t the airlines tell the airport?

Airports and airlines want to make better use of data

It’s not just the traveling public. Airport and airline business and technology leaders say the same. They lament the lack of data to solve operational issues, they wish they knew more about the preferences of the passengers traveling through the airport, and they want to cut across the silos of the different systems in their airports, with their business partners. And they want to take advantage of the data, such as weather or traffic information, that is available from external providers.

Although it doesn’t get much public visibility, airports have been very successful in sharing data to improve operational processes with other airports, airlines, and ground handling agents (the companies that provide services in the airport to many airlines, such as check-in, bag loading, and flight dispatch). This collaboration has a big impact on efficiency—for example, airport collaborative decision-making (or A-CDM) reduces airport delays by 10 percent and CO2 emissions by 7.7 percent.

Airports want to take this much further. They see how data is transforming industries, with airlines such as Korean Air and Ryanair using Amazon Web Services (AWS) to forecast preventative maintenance and onboard catering; a great example is Ryanair’s Panini Predictor. They can imagine their airport operations and the passenger experience improving with accurate forecasting, personalization, and easy data sharing across all stakeholders. It’s not surprising that the Airport Council International (ACI) recently said, “Airport data sharing and collaboration is the key to improving passenger satisfaction.”

Airports are building data platforms

Many airports have recently built data platforms on AWS, including Nice Côte d’Azur in France. Unlike an airport operational database (or AODB), which is typically a highly structured database with complex business rules, a data platform is a more flexible way to absorb, understand, visualize, forecast, and share different types of information from across the airports’ systems, airlines, and third parties.

Cincinnati Airport uses data for predictive analytics and proactive notifications, which it calls Enterprise Awareness & Situational Exceptions (EASE). EASE collects structured and unstructured data from all parts of the enterprise using AWS services such Amazon Relational Database Service (Amazon RDS), a collection of managed services, and AWS Lambda, a serverless, event-driven compute service. This allows even the most disparate datasets to improve dynamic decision-making. In addition to improving staffing levels for airport processes, Cincinnati Airport can monitor social media for sentiments and respond in near real time if, say, a passenger sends a tweet about a spill. The airport also monitors weather and local traffic so it can both adjust the operational plans and alert passengers.

Changi Airport in Singapore is a great example of using data to improve collaboration and innovation. Working alongside Accenture, an AWS Travel & Hospitality Partner, Changi Airport built a data platform as the foundation of its DIVA innovation lab, which includes its new Concierge app, resulting in better information for passengers, and its Where-To-Clean app for staff, which prioritizes areas of the airport with recent high usage for cleaning.

Siemens Logistics, a global leader in airport baggage-handling systems, also built an aviation data hub on AWS to ingest, analyze, and visualize all kinds of airport operational data. For example, its Baggage360 system uses multiple sources of information to analyze baggage data and forecast baggage flows. “We can monitor baggage flow, predict bag processing times, identify connections at risk, and predict when a bag will be at important process steps,” says Stephan Poser, director, Aviation Data Solutions at Siemens Logistics. “We can even predict when a bag will finally be visible for the passenger on the arrival belt.”

Some airports with data platforms on premises are discovering that as their needs grow, they are limited in their ability to scale and add new services. For example, AWS Partner Wipro recently migrated Toronto Pearson International Airport’s data platform from an on-premises system to AWS to take advantage of scale and agility, and to add new capabilities such as artificial intelligence (AI), machine learning (ML), and near-real-time data ingestion. “Our new Databricks Lakehouse Platform on AWS will help us derive near-real-time business insights from a variety of sources to drive continuous innovation,” says Anudeep Kambhampati, general manager at Wipro Canada.

I was curious why airports have recently embarked on building data platforms. Why now, given that the technology has been around for some time? To help answer this, I talked to Chris Taylor, managing director at Azinq, which has helped over 30 airports across Europe improve their operations with data. “Our customers are rapidly moving to cloud-based data platforms to take advantage of the infrastructure and data services that AWS provides. Airports have long recognized the value of data to understand and improve passenger and stakeholder engagements, but previously, costs and technical barriers have made it difficult for airports to build data platforms. Our Airport Hive platform on AWS makes it much easier for airports to get insights into their operations and gives visibility on how small changes can have big impacts, both financially and for the passenger experience. The scalability and elasticity of AWS helps customers avoid the costs and hassles of on-premise implementations with long-term capacity for growth.”

Data platforms can help solve very specific problems. For example, a major US airport had a challenge with taxis waiting in its short-term parking lot; this meant less space for passengers to park and a loss of revenue for the airport. To overcome this, the airport engaged AWS Partner Slalom to build a data forecasting model using historical flight, weather, and taxi-passenger data to predict the demand of taxis ahead of time and request taxis only when needed. This freed up the parking lot space, resulting in a better passenger experience, and helped the airport to recover approximately $5 million in revenue from improved operations.

Overcoming the challenges to sharing data

One of the challenges for airports is getting access to the necessary data. Airports say that they have difficulty getting the data that they need from all the airlines and companies that operate at their airports. AWS and our Partners are helping airports overcome this obstacle.

At AWS re:Invent 2022, we announced AWS Clean Rooms, which helps customers and their partners more easily and securely match, analyze, and collaborate on their collective datasets—without sharing or revealing underlying data. Each collaborator creates its own data clean room with AWS Clean Rooms and chooses who to collaborate with on which datasets and configures restrictions; collaborators don’t need to maintain a copy of data outside their AWS environment or load it into another platform. When customers run queries, AWS Clean Rooms reads the data where it lives and applies analysis rules so only the data that the collaborators want to share gets shared. A great use case could be an airline sharing data with an airport: the airline creates its own data clean room and the airport runs the query on only the data that the airline wants to share, such as number of passengers onboard a flight.

AWS has been helping airports and airlines collaborate and share data. We see the potential to build airport and airline collaboration by focusing obsessively over the shared passenger experience. For example, we’re taking a hands-on approach with airports to understand specific passenger pain points, help identify the data required to solve it, and work alongside their airline partners to share the data to solve that passenger pain point.

Third-party companies offer data feeds specifically to improve airport operations. For example, Passur provides airports with near-real-time data feeds, including flight positions, flight predictions, and flight-event data through APIs built on AWS. “Airports use our data to improve asset management, capacity planning, and collaboration with airlines,” says Passur’s CEO, Brian Cook. “Our data feeds provide airports with advance notification of delays so they can proactively adjust operations to manage the disruption.” In addition, AWS Data Exchange, where third-party data is easy to find in one data catalog, has thousands of datasets, including weather and flight data.

AWS is known for our unique culture and approach to innovation. We have taken this methodology and adapted it specifically to help customers innovate and solve business problems with data. We call it the AWS Data-Driven Everything Program (D2E). We have helped hundreds of customers using D2E. We recently ran a D2E session for a customer in the travel industry that found it challenging to build a unified view of its customer with rich demographic and behavioral attributes. Our travel industry customer wanted to microsegment its customers to personalize support and improve its net promoter scores (NPS) by more than 20 percent. The outcome of the D2E was an aspirational vision for a customer 360 capability, a plan to build a minimum viable product (MVP) version of the product, and fast-follower features to iteratively deliver improvements to the unified customer profile product.

What’s next?

Airports can get started on building and improving their data platforms. AWS Consulting and Technology Partners can help airports build faster or implement proven solutions. AWS offers a range of services, such as AWS Lake Formation to build a secure data lake platform, Amazon Forecast to forecast business outcomes easily and accurately using ML, and Amazon SageMaker to build, train, and deploy ML models. All AWS customers can reach out to their account manager, who can help them get started and bring in solutions architects and subject matter experts to provide guidance and support. We even have an AWS Professional Services team to help customers and Partners achieve desired business outcomes with AWS.

So, what’s next for airports and data? In part because of the COVID-19 pandemic, recent airport capacity constraints, and the recent advances in technology, I expect it to get much easier for airports to share data and to use this data in a more meaningful way: to forecast capacity issues and put plans in place to address them, to offer personalized services to passengers, and to better collaborate with their business stakeholders.

I look forward to future conversations with people I meet to go beyond, Why don’t airports know…? to being asked, How does the airport know? Not only will the airport know, but the passengers will know too. And they’ll love it.