CASE STUDY
What we have learned is that if we want to push change in the industry , we need to find consensus . We need to find the common ground where everybody will find their interest because it is very difficult to push a change when only a few parties are really winning . Trying to identify where all the stakes are in order to identify where we have a common interest is what we ' re doing to create a foundation that we foster in order to change .
How is data , or technology more generally , enabling airlines to plan for the year ahead , given the challenges surrounding travel due to COVID-19 ?
We are helping them because we are defining the standards that they can use everywhere in order to implement this technology change . One of the challenges airlines have is that they cannot afford to implement something different in every country they operate in , so this is why they rely on IATA . The work we ' re doing in terms of setting up standards is helping airlines to push the change and to have this change implemented the same way in all the airports worldwide .
This change also has to be accepted by the regulators , because sometimes it will impact the security and safety of operations . We have a lot of regulations that are driving aircraft operation . And when we ' re bringing a change , we have to make sure that the regulator will accept it , and that the risks , brought about by the technology , are well mitigated and accepted by the regulators .
How far will good-quality data allow the industry to respond and survive this crisis ?
Everything is in the quality of the data because whether we use data to do Incident Management or for passenger loyalty , the analysis of the flight data is a critical continuous improvement process in order to assess if the procedure is optimal , to understand the potential impact and to assess the level of safety and the risk .
For aircraft operation , data integrity is key . For passenger data , compliance with data privacy obligations is a must because airlines are handling a huge amount of personal data . Another example is that since the crisis , the capacity forecast that we have is less accurate . Why ? Because the historical data handled by the aircraft is not relevant because of the crisis . An example : when the aircraft are flying , they are sending this data to ground stations and this is helping everybody to build the weather forecast . Since we have less aircraft flying , the accuracy of weather forecast has been reduced .
Our industry is only about data . When a modern aircraft is flying , it can generate 1 Terabyte of sensor data every 24 hours . Of course , older aircraft generation are creating far less . And all this data is used after to verify the safety of the operations and to try to improve operations such as the consumption of fuel .
How do you work with the wider C-suite to ensure technology is given strategic priority within the organisation ?
The good news is that more and more C-suite members are tech-savvy , or they understand the benefits of the technology for their operation . There is also a big concern in the industry about cybersecurity . It is really important and we need to go back to the board members and to the C-level executives also , to make them aware of best practice in terms of cybersecurity . However , it ’ s not just about technology , it ' s about people behaviour and understanding and about educating people , implementing the right process and the right control .
Where are you looking to invest moving forward , and does the current uncertainty have an impact ?
Yes , it does . We currently don ' t have a lot of money because our industry has been largely impacted by the crisis , so all our investment at the moment is going into business intelligence and into predictive analytics , because one of the biggest challenges airlines are facing at the moment is that all their historical data is no longer relevant . And so , they are asking us to come back with new models where we can predict the future with a limited set of historical data . So , with one month of operation , can we predict something ? In the past , you needed five years of operation data in order to build a reliable model . Now , they are asking us to build the models on only the last month of operation , and of course every month , the model has to auto-adapt .
We have to offer airlines visibility because this is the biggest issue they have at the moment . They don ' t have visibility on the operation , they don ' t have visibility on their capacity and it is impacting the operation . This is therefore having an impact on customer satisfaction because there were a lot of cancelled flights . p
FOR AIRCRAFT OPERATION , DATA INTEGRITY IS KEY .
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