Our Marketplace Spotlight series focuses on the partners making the Yocova platform come alive – and the digital aviation solutions they provide. In this issue, we hear from Val Goldine, CEO at IOblend, on how operational analytics (OA) enable you to flow information automatically from sensors, systems, data warehouses (DW), etc. to relevant people, systems, tools and apps.
IOblend’s founders have been building and managing complex business intelligence initiatives for decades. With the advent of Big Data, AI and IoT, requirements to process data in real-time and hybrid cloud production environments, made data engineering and management even more complicated and expensive. IOblend’s work has culminated in the creation of a unique software product that dramatically simplifies how data estates are built and maintained. Read on to find out what Val Goldine has to say about better airport operations with real-time analytics….
Tell us the background to your work in operational analytics
“Now that the winter holiday season is upon us, many of us will be using air travel to get to their destinations of choice. This means, we will be going through the airports.
As passengers, we have love-hate relationships with airports. Some have a “wow” factor. They feature impressive architectures and interior designs, made to look like modern works of art. Some are mini-cities, offering everything you can think of inside their sprawling complexes, even ice-rinks and waterfalls. Singapore’s Changi is a prime example, regularly listed as the best airport in the world. They strive to offer more than just funnelling people to and from the boarding gates through the shopping arcades.
The ones that don’t, give us unpleasant experiences of dull grey exteriors, dated interiors, cramped facilities, “in-your-face” shopping, and boring food options. Air travel is stressful in general. Poor airport experience makes it more so. Everyone hates bad airports, dreading flight delays and hoping to get through them as quickly as possible.”
How do airports encourage passengers to spend more time and money?
“Airports primarily make money from passenger services. They collect revenue from both the passengers directly at the point of consumption (e.g. parking, food, shopping, lounge access) and via the airline (or another third-party service provider) for passenger and baggage processing, leases and rent, ramp usage, aircraft parking, navigation services and the runway use.
Passenger fees are often regulated, so the airports turn to other revenue sources. Some are pushing the boundaries of decency with the fees for drop-off and pick-up at the curb side or charging extortionate rates for parking.
While some choose this strategy, other airports invest in creating a more positive passenger experience. New and challenger airports are generally more proactive in this area. Dubai International is one such example.
Most well-run airports just focus on getting the basics right. Get the passengers through the stressful parts (check-in, security, immigration and boarding) with as little fuss as possible. Then give them space to relax and provide a variety of quality shopping, food and service outlets. The passengers reward them with more spend.”
How do they decide what works?
“Airports use plenty of data when developing their services. They track the number of cars going through the car parks and the amount of time they spend there (short/medium/long term), for example. They also have stats on what proportions arrive by mode of transport, so they can then determine what to charge for parking/drop-off.
Airports collect shop data to understand sales. Data from cafés, bars and restaurants drive insights into the customer spend and preferences with regards to their food and drink choices.
Passenger data is usually done via surveys and tends to drive longer term planning.
With all the data the airports are collecting, however, the best they can do is understand historical trends using estimates.
Here’s a scary fact: airports do not know the exact number of passengers going through their terminals.
They have no idea how many customers visited their shops, restaurants, lounges, toilets, etc at any given time.”
Why not?
“Because of the way the data is collected and (not) shared. Hardly any data is analysed in real-time, as the passengers move through the facilities. Security cameras are not designed to take count of the people movements and there are no other sensors installed to handle the task.
Certain areas, like passport control, will know the exact number of passports processed, but that data misses domestic travel. Security screening does not count the flow of people. Check-in information is hard to reconcile from online, kiosk and desk data, recorded at different times.
What the airports need is an ability to measure the flow of people as they move through the terminals in real-time. This live data needs to be dynamically “triangulated” with the secondary sources such as security screening, passport control, boarding gates, shops, etc. – everywhere where a physical measurement can be taken.”
What benefits does this granularity bring?
“The airports can do much more accurate capacity planning once they better understand the flows by season, month, day of week, time of day, even by the second.
Where do people congregate more and why? And for how long? Is it related to a particular flight / gate location, specific facility (e.g. restaurant or bar) or some other reason?
If there are delays with a risk of multiple flights unloading passengers in the same terminal space all at once, the airport can dynamically re-direct some of the flights to lesser congested parts and reduce the strain.
Using travel apps, the airports could provide precise location services to the passengers, such as directing them to their “meet and greet” points, private taxis, even family members. Baggage tags can be scanned as they are loaded on the belt, and the data streamed to the app, thus reducing crowding at the baggage collection or help determine if a bag is missing faster.
The airports will be able to apply predictive analytics capabilities on this data and redeploy resources better to manage and alleviate pinch points before they develop. With such data granularity and instant availability, Large Language Models can create new and enhance existing passenger experiences.
How do operational analytics help?
Operational analytics relies heavily on real-time, production-grade data to offer instant decisioning. It lets you flow information automatically from sensors, systems, DW, etc. to relevant people, systems, tools and apps.
OA’s purpose is to improve business efficiency through the streamlining of operations, enabling fast decisioning, lowering costs (heavy automation), increasing revenue (dynamic packaging/pricing, up-sales), and promoting better collaboration through live data sharing.
Airports stand to gain significantly from real-time technologies, live data integration and dynamic analytics.
IOblend acts as the OA bridge between the disparate systems and sensors of all sorts. It’s the horizontal layer that works across all infra and systems and it’s our bread and butter.”
For more information, to contact or collaborate…
Get in touch with Val on Yocova via his personal profile
Author: Team Yocova
Published: 23 January 2024
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