When airlines are AI-borne, customers take flight
Better data insights help airlines succeed in a competitive, post-COVID world
Successful airlines have always utilized their proprietary data for a competitive advantage. As COVID-19 has upended the world, harnessing such data streams has become more essential than ever. We sat down with Rob Ranieri, global industry offering leader for Travel and Transportation at IBM, to learn how these carriers are channeling their data with AI and virtual services to help manage the challenges and opportunities on the horizon.
How has the current moment pushed carriers to do more with AI?
When Covid-19 hit, it really highlighted the need to look at how airlines connect employees and passengers. Most airlines invested in providing technology to passengers both for cost savings and improved experience.
Employees, however, were generally using 10- to 20-year-old technology. We’ve been focusing on how to make the employee experience better so they can do a better job serving customers, and many airlines have upped their game.
Covid-19 highlighted continuing gaps, though.
Passengers and employees may be digitally connected to the carrier, but the connection between them was still lacking. They’re still physically connected at a boarding gate or in the aircraft, with a whole bunch of interactions and back-and-forth. That wasn’t going to be possible in the new normal.
Why can’t they digitally interact with each other, we asked, and why don’t we recreate digitally those experiences that connect employees and the passengers? That’s something that will deal with the immediate need for physical distancing. Once there’s a vaccine available or once we progress past the pandemic, we may want to ease things up. But that digital connection will continue because it will improve the overall passenger experience.
You envision a long-term shift?
Absolutely. Once we establish a digital connection, it will be much better than standing around a physical gate and lining up to ask the person about, say, an upgrade. That’s going to be a huge leap forward from where we were prior to the pandemic. We’re going to look back and say, “I can’t believe we stood in line at a gate for a seat change request or to standby on that flight!”
We’re looking at creating a digital gate that the customer can carry with him or her that allow them to get updates. Then they can stay where they are comfortable, doing what they want to do prior to boarding, and don’t feel anxious about standing in line next to people who may or may not be wearing masks. This allows for a much more orderly experience.
How else is COVID changing things?
It’s accelerated a lot of existing trends, like planning and scheduling. The old systems were built on a premise that you would change where you flew, or the frequency, on a quarterly or semi-annual basis. Now, it’s all happening in real-time. The only way to manage that effectively is with AI. Your algorithms are looking at the data and doing the tens of thousands of permutations, making hypotheses, testing them and readjusting—all near instantaneously.
Things are going to present themselves as opportunities very quickly—and they may do the opposite very quickly. Behind every decision with a route, you need to consider the ten-plus other decisions that sit behind it: crew allocations, plane allocations, spare parts, etc.—all the things that need to be put in place to support that decision.
The old way of building a test market, putting it out, getting a bunch of reports, having humans look through it and say, “OK, sounds like we can build more capacity if we make these changes.” That doesn’t work when the market is changing as fast as it is today.
Airlines have long been leaders in harnessing data?
And not in the way you’d think: through mileage programs, loyalty programs, credit cards and past purchase history. The airlines have a lot of proprietary data going back many years. They can use it in a unique way that other industries can’t. Not only do they know the customer, but also what’s their propensity to buy, where they like to travel and so on.
That data has significant value, and now airlines are investing in AI to unlock more insights from that data. They need to compete with digital intermediaries that are trying to get in between the airline and their customers.
What are some of the other unique uses?
With all the self-service—which airlines have also been a leader on—whether it’s buying tickets online, checking in at a kiosk or an app… more and more, passengers don’t need to speak to the airline employees. The first person they may encounter is the cabin attendant inside the aircraft. But you still want to deliver a personalized service.
How do you do that, with all these digital tools? The answer is data. Using the data from kiosks, apps and programs, we can actually greet the person by name, understand their experience and understand how to best provide service in the little time we have with them.
What carriers have been standouts in this regard?
Lufthansa was doing a bunch of initiatives in different airlines and pockets within the Lufthansa Group. Really the leap forward that took it to the next level was establishing a competency not only around data but how Lufthansa would execute it in a strategic fashion across the group.
Forever, organizations would say: I’ve got a lot of data but I don’t know what to do with it, or I’m not getting the value out of it. It’s the management system and governance you put around the business, around data and AI, that needs to be raised to a level where it’s not stuck in silos of each part of the organization. One set of data may seem to be part of the commercial business, another part of the maintenance part of the business. The reality is, it’s all interconnected. A maintenance issue can ground a plane that can cancel a flight that can ruin customer experience at the gate.
Lufthansa was one of the first to realize this and to link up all this data. Starting with an IBM Garage design-thinking engagement, Lufthansa and IBM established a governance process around what to do with data and how they should be doing it. They’re looking across the whole enterprise to drive cognitive insights and new intelligent workflows.