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Aegean Airlines has been a rapid iterator when it comes to deploying new technologies to improve operations and traveler experience. Aegean is known for partnering with innovative technology companies that focus on the customer experience, most recently, ParkCloud and Mozio. To learn more about the airline's approach, the Sabre Insights team connected with Roland Jaggi, Aegean's Director of Sales, Revenue Management, Pricing, and Distribution.

Looking progressively forward over the next five years, what new approaches or prospective innovations that could influence the way you do business in the future excites you the most?

I'm excited by the amount of already available, but unused, data, combined with additional data available in the future. Everybody talks about airlines to becoming retailers and that technology is now ready for first implementations. There is more to come in the future. I believe we're at the beginning of a period with many new exciting developments in our industry. Personalization and digitalization are gaining a momentum and will change the passenger experience from shopping to booking to traveling.

When it comes to technology, how do you approach choosing a technology partner? And how do your partnerships support your airline's growth strategies?

Innovation and adaptability, strive for improved customer experiences and improvements in our business process are some of the key success factors of Aegean Airlines. So to say: this is written into our DNA. When we are looking for technology partners, we not only look for partners with the latest technology. We're also looking for partners that share and prioritize these values.

Speaking of airline growth, what are the challenges you face today when it comes to growing your airline? And more specifically, with revenue management?

The global uncertainties related to war, terrorist attacks, natural disasters and political unrest is influencing the travel behavior all over the world. While this is impacting all airlines, we're getting an extra portion of volatility and changed travel behavior: our home base is Greece, where we are just finishing 7 years of recession in a row.

These challenges are also some of the main challenges in revenue management. Booking patterns are changing constantly, airlines shift capacities frequently, the value of historic data is diminishing and forecasting becomes increasingly more challenging. Revenue Management including ancillary revenues is another challenge yet to address and then next is to optimize flights and O&Ds on a very granular base, taking advantage of 'big data' and the growing personalization and digitalization.

What value do you expect to get from a Revenue Management System?

First things first: demand forecasting and optimization of my 'core' ticket revenues, this is what I expect from a RMS. We have run several studies in cooperation with Sabre, measuring the impact of a RMS and the impact of RM analysts. In a nutshell, these studies have confirmed my expectations: Users can add value in situations they either know the result in advance (for example: peak flights) or they know something the system does not know (moving public holidays, changes in own/competition capacities).

In the situations which are 'grey zone' and it is not very predictable what the outcome of a flight will be, the RMS is adding a lot of value to airlines. As we have many such situations, my basic expectations to the RMS are solid forecasting and optimization on a network level (as we are using OD Advantage). This is the basic, combined with a good user experience to use the system and its capabilities in an intuitive way to perform their business processes.

In addition to that, I expect from a RMS not only to be continuously improved, but also to be enhanced, taking new developments from the scientists into production as much as taking advantage of new technology.

Today, we are increasingly hearing more about companies taking a total revenue optimization (TRO) approach, is this something your airline is focused on and if so, how do you see this ideology changing the future of revenue management?

At Aegean, we are increasing our focus on TRO. It will further increase the importance of RM, as not only ticket sales revenue streams will be managed by RM, but also all the new revenue streams. Complexity will increase for analysts as much as for systems.

Total Revenue Optimization is the evolution of revenue management. In order to achieve TRO, what role do you see technology playing? And how must it be different from solutions of the past?

As complexity will be increasing, many more data will be available to take optimization decisions, technology obviously is going to play a key role. Humans cannot possibly analyze and process so many data without technology. In terms of capability to handle data, I see the biggest difference in future solutions. As in the past, technology will be here to prepare data for

s in the past, technology will be here to prepare data for analysts, to review system recommendations, to interact/override system recommendations, to support decisions, to support to implement decisions. I'm a strong believer in the combination of 'man and machine'. This will remain.

Aegean has multiple revenue optimization solutions provided by Sabre, including the most recent partnership with Revenue Optimizer, Sabre's next-generation revenue management solution. What is most appealing to you about your decision to choose Sabre and deploy Revenue Optimizer? It is many things! As I mentioned before it's the combination of 'man and machine' that makes us successful. For

For example, I like the key 'machine' improvements in the forecasting area, the introduction of customer choice models. And the idea of optimizing more than just ticket revenues. But my clear favorite is the big step in the user-friendliness of the GUI. This is a great development that will make our key asset, the Revenue Management Analysts, more efficient and it will help them improve the quality of their daily decisions.

Sabre Corporation published this content on 23 January 2017 and is solely responsible for the information contained herein.
Distributed by Public, unedited and unaltered, on 23 January 2017 22:20:02 UTC.

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