The airline industry has undergone a profound transformation over the last several years. With the emergence of technological advancements like AI, airline companies are now taking advantage of revamping traditional systems and optimizing processes to streamline revenue management and other departments.
In this episode of AI.RLINE by Fetcherr, host Omri Hurwitz is joined by Andre Americo, Revenue Manager Director at Azul Airlines, Fetcherr’s first live customer.
Dive into a conversation about how artificial intelligence is not just reshaping Azul but setting a new course for the airline industry.
Omri: Thank you so much for being on the show. To give content to our audience, can you talk about your role in Azul?
Andre: I already have 15 years of experience in the airline industry. I studied economics and got my master’s in econometrics and quantitative methods. That led me to the curiosity of exploring new science and technologies. I have been working in Azul for more than 10 years already, switching roles between revenue and planning, and now I’m in charge of both departments which helps us a lot in synchronizing and taking the best out of both worlds while managing two big teams.
Omri: The aviation industry is going through major innovations right now, especially with AI. For a traditional industry like airlines, what are some of the greatest challenges that it’s currently facing?
Andre: I think many of the systems processes we use are still dated back from the 90s, and we have been trying to push those boundaries a little bit further as we explore new technologies, new ways of doing things, and experimenting with new processes. I think the industry, as a whole, is also evolving in terms of technology. We have been seeing many gains not only in the revenue planning field but also in our operations. We have recently been awarded with the number 1 in OTP in world rank, and that’s also due to new technologies, new ways, and new approaches to old problems. The airline industry is evolving a lot, but there’s a huge legacy and heirloom we have to adapt to why we make those changes and move on to new things.
Omri: How can the adoption of new AI technologies improve the airline industry as a whole, and how did it help Azul?
Andre: It helped us primarily in expanding our approach to the revenue problem. I think every airline in the world has a system to manage their revenue and inventories in an algorithmic, old-fashioned way. The reason we wanted to explore and try new technologies is to learn something different and to learn how these problems could be tackled differently. I think the biggest thing here was not the new kind of management and science being done behind the scenes, but all the learning that we got from this process, like how we can see things from a different angle, including more variables and perspectives in the data and how that leads us to better decisions.
Omri: So what I’m sensing is that the result is better analytics and insights, is that correct?
Andre: Yes, that’s correct. With Fetcherr, for example, we used more variables than the traditional RM system uses, and we are always trying to push new variables into the context of optimization so we can learn new stuff. Of course, many of them are trial and error, and that’s part of the learning process and what actually impacts demand, bookings, and revenue. Being able to adapt to new circumstances is in our DNA from the very beginning, and it’s not different when we approach the revenue optimization problem as well.
Omri: How data-driven are you today compared to how you were 6 or 7 years ago?
Andre: I wouldn’t say that the traditional systems aren’t data-driven, because they ingest thousands of data and they know all the major trends, but I think the big leap here is the current models that are in use is that they are statistically correct, but they cannot have a deep understanding of what’s going on and all the association between different data points and variables. I think that’s where the big gain is, is once we put more context in our analysis, and once we can link more dots among different variables, I think that’s where the real value is.
But the traditional systems got the whole industry to where they are and it has been evolving as well, but we thought a different approach would be adequate right now as we’re looking into expanding our ways of doing analysis – I always mention that because I think it’s really the core and create new understanding on the data that we currently have. All airlines have massive amounts of data, and just like our brains, we don’t use 100% of what we have. And I think the AI and Big Data leap in tech is going to allow us to use and learn more from that same data.
