I recently had the opportunity to be a part of a panel discussion focused on the use of analytics and data in the aviation and travel industries. The conversation revolved around the benefits that the aggregation and analysis of data could have on increasing efficiency and operations. But the conversation eventually shifted to the challenges that are holding decision-makers and senior executives back from fully embracing data and analytics for their organizations.
There are many examples that highlight the shared benefits of data analysis, as well as the impact of using data to improve airline and airport operations. For example, how predictive maintenance – utilizing historical and manufacturer’s parts data to repair or replace things before they fail – can significantly reduce aircraft downtime and delays. Or how data could be used to calculate flight paths to optimize travel time and reduce fuel consumption.
Data and analytics solutions are doing the same exact processes – they’re just doing them in a more automated and efficient way.
With so many benefits, so much optimization, and so much money saved, it would seem like virtually every organization would be racing to deploy solutions that can leverage data and analytics. But there are some organizations that have yet to do so and – according to the panelists that joined me – they have a valid reason: trust.
Can you trust something predictive?
If I were to tell you – with incredibly high certainty – that the brakes on your car would fail at 50K miles, you would probably head over to your mechanic when the car reached 49K miles and have them replaced. After all, why would you take a chance with something so essential and important to the safe operation of your automobile?
But there might be some skepticism about that prediction. How certain is it that it will happen? How much uncertainty is there in its accuracy? And that’s understandable.
Airline and airport decision-makers might be reticent to purchase data and analytics solutions if those systems will only cost them more money in unnecessary repairs and part replacements in the future. And they might be concerned that there’s no way to truly test – and therefore trust – that the predictive analytics they’re receiving from their data is truly correct and accurate.
But there are reasons why airlines and airports can trust these solutions.
Pair technology with industry expertise
It’s true that an airline knows its aircraft well. But they probably don’t know it as well as the manufacturer, and probably don’t have the depth of knowledge that some analytics solution providers offer.
While an airline or airport may have wide operational experience and knowledge of a part or product by virtue of using it, the manufacturer is privy to data from across its entire customer base. The manufacturer can also work with its Maintenance, Repair, and Operations (MRO) shops to test its products and parts against the predictions its analytics solutions are making.
The understanding of the parts…these providers have – coupled with their access to historical and current flight data – enables them to demonstrate that the predictive analytics solutions that they’re offering can increase airline and airport efficiency.
Analytics solutions offered by companies with a long history and deep knowledge of the aviation industry also benefit from that industry-wide perspective and insights. But what about analytics tools that do things like flight optimization? How can organizations test those?
This is where industry domain data and expertise come into play.
Many organizations designing solutions like flight path optimization tools understand the aviation industry. They can not only generate flight paths that are more efficient but also useable in the real world. After all, what good is an optimized flight path if it doesn’t recommend a viable route? Also, these providers have a large installed base of solutions that allows them to do significant A/B testing to validate that the suggested flight paths from analytics tools are better than the alternatives.
The understanding of the parts, products, and solutions these providers have – coupled with their access to historical and current flight data – enables them to demonstrate that the predictive analytics solutions that they’re offering can increase airline and airport efficiency.
But even working hand-in-hand with these solution providers to implement and test an analytics solution might not be enough to convince some decision-makers. In those cases, a different perspective could be beneficial.
Everything you’re doing already – just automated
The average airline is already looking at weather patterns and using that information to create optimized flight paths. They’re internally tracking the amount of time or number of flights that they get out of their routable components (i.e., wheels & brakes). But, in most instances, they’re doing these things themselves, and they’re doing them manually.
Analytics solutions offered by companies with a long history and deep knowledge of the aviation industry also benefit from that industry-wide perspective and insights.
Data and analytics solutions are doing the same exact processes – they’re just doing them in a more automated and efficient way.
Instead of manually looking at weather patterns and trying to estimate their impact on passenger comfort, flight duration, and safety, these solutions analyze the weather automatically. They compare weather information against the historical impact of similar patterns, and dynamically update proposed flight paths as the weather changes, providing the airline with real-time analysis into which flight path is better.
So, can airlines and airports trust analytics? The answer is “yes” and as we look to the future, I believe that analytics tools will become even more fundamental to their operations.
