As the aviation industry races toward the ambitious goal of net-zero emissions by 2050, airlines are actively seeking solutions to reduce carbon emissions and enhance operational efficiency. The key to achieving these goals lies in the ability to aggregate vast amounts of data, conduct in-depth analyses, and transform raw information into actionable insights that drive real change.
In this interview, Captain Deha Demir, Operational Efficiency Pilot at Pegasus Airlines, shares their experience with the implementation of SkyBreathe® Analytics.
What problems were you trying to solve with SkyBreathe® Analytics?
We address multiple challenges with the implementation of SkyBreathe® Analytics. Our primary goal is to significantly improve our operational efficiency and reduce our carbon emissions.
By analyzing flight data, we aim to identify areas for improvement in our operations and implement best practices that will help us reduce emissions and meet our goal for net-zero carbon emissions by 2050.
Why did you choose SkyBreathe® Analytics?
We chose SkyBreathe® Analytics to enhance our capabilities and track our data.
We want to measure the areas where we can improve in our operations.
The platform’s ability to process large amounts of data, combined with the Query Editor, allows us to explore countless possibilities. Our imagination is the only limit, and I hope it will help us reach our goals.
Can you describe your overall experience with the SkyBreathe® platform?
Our experiences with the implementation process is very positive.
The platform has enabled us to run deeper analyses, leading to a significant reduction in carbon emissions and improving operational efficiency
It was seamlessly integrated with our existing systems. This integration capability is one of the reasons we chose SkyBreathe®.
Can you provide examples of how the OpenAirlines team has helped you in your work?
The OpenAirlines team has supported us in being successful, from the very beginning of the implementation and after.
Our Customer Success Manager provided comprehensive online training sessions, ensuring that everyone was well-prepared to use the Analytics platform.Ongoing support has also been invaluable. OpenAirlines helped us track our progress and access insights on what we’ve achieved and what we can expect in the near future.
One notable example is their help in analysing the complex dataset and dealing with specific areas for our environment. With the assistance of the platform and our Customer Success Manager, we’ve optimized our operations, and we’re hopeful this will result in measurable reductions in our emissions, helping us move closer to our goals.
What has motivated you to attend OpenDay?
The main motivation for attending OpenDay is being part of the OpenAirlines community. As far as I know, there are around 67 members, though I haven’t caught the latest numbers—it’s a growing community. It’s a great opportunity for networking, especially since the other companies are using the same platform as we are and face similar challenges and goals.
It’s a good opportunity to share thoughts about it. Meeting face-to-face is far more efficient than virtual networking through Teams or Zoom!
Another motivation is the focus on AI. We’re eager to learn more about the new developments OpenAirlines has been working on.
What are you most looking forward to experiencing or learning at OpenDay?
At OpenDay, we’re focused on redefining our goals, beeing challenged with our peers. There’s so much to learn from both our colleagues and OpenAirlines’ expertise. We’re here just for that.
LEARN MORE
Watch our webinar "How Pegasus Airlines quickly implemented a fuel efficiency solution to transform its flight operations", featuring Pegasus Airlines sharing their inspiring journey to implement a new fuel efficiency management system.
Learn how it's transformed their flight operations and how it resulted in improved operational efficiency and a reduction of their environmental impact within a short timeframe.
📆Original broadcast date: December 12, 2024
⌛ Duration: 1 hour
