In this second of a series of pieces for ABN on digital transformation Oleksandr Plyska, Vice President at Sigma Software Group, turns his sights on how aviation is using data to improve operations
In our first article, we looked at how digital transformation is enhancing the passenger journey.
Now, we turn to the operational side — where AI, IoT [Internet of Things]and smart data practices are driving real impact behind the scenes.
From predictive maintenance to fuel efficiency and automated ground handling, these tools are already here. The challenge is making the most of them.
AI, data science, machine learning, and IoT are no longer future buzzwords in aviation — they are the engine driving a new era of safety, efficiency, and sustainability.
And while these technologies are transforming operations across the board, their true value comes when they’re paired with a data-first, data-sharing mindset. Technology alone won’t fix inefficiencies; better data will.
According to SITA’s 2024 report, 97% of airlines have already adopted AI in some form. Yet, despite this impressive uptake, about 60% of AI projects still fail, mostly due to poor data quality or siloed data infrastructure.
The message is clear: you can’t have smart systems without smart data practices.
That said, some standout examples show what’s possible when analytics, AI, and IoT are implemented the right way — solutions that benefit not just airlines and airports, but also passengers and the environment.
Take Lufthansa, for example. Using data science, they now accurately predict how much water each flight needs, minimizing excess weight and reducing waste — good for both sustainability and cost.
Similarly, easyJet once stocked the same amount of food on every flight. After implementing demand prediction models pre-2018, they began supplying only what was needed. The result? Lower costs, less waste, and a lighter carbon footprint.
Fuel optimisation is another area where advanced analytics pays off. Before 2022, jet fuel made up about 24% of airline operational costs.
Southwest Airlines tackled this head-on with a predictive model that uses time series algorithms and neural networks.
Their new tool produces 9,600 fuel consumption forecasts per month — in just five minutes.
Previously, analysts generated only 1,200 forecasts, and each one took three days. The time and resource savings here are massive.
Perhaps the most impactful use case is predictive maintenance. Instead of grounding flights after issues arise, airlines are using AI and IoT sensors to detect problems before they happen.
Delta Airlines, for instance, has used AI-driven systems to reduce unscheduled maintenance by more than 15%, improving both reliability and cost efficiency.
At Sigma Software, we built a similar system for Scandinavian Airlines that continues to generate major cost savings each year.
We’ve also invested in a solution aimed at improving airport operations. It automates ground handling with fully automatic roster calculations, dramatically reducing planning time and optimising staff allocation.
It’s cloud-agnostic, modular, and designed for usability – just one example of how smart tech can reshape backend operations.
The tools are already here. The question is: are airlines and airports ready to use them to their full potential?
Digital transformation in aviation isn’t just about new tech. It’s about rethinking how organisations collect, share, and act on data.
And while the path isn’t easy, it’s encouraging to see so many in the industry finally taking off in the right direction.
In our next article, we’ll explore why legacy technology still holds aviation back – and what the industry can do to break free. Stay tuned.
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