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Six Data Takeaways from the Aviation Festival Americas

The best parts about attending a conference are meeting new people and learning about something new. Both were in abundance this year at the Aviation Festival Americas in Miami (May 9-10th, 2017).

The underlying theme present in all conversations was data. How to collect data, how to store data, and most importantly, what to do with that data? This theme was present in almost every track — marketing, passenger experience, airline IT, strategy, and the keynotes. How can marketers gain an edge by leveraging customer data and building a 360-degree view? What insights can be gleaned and actioned to improve the passenger experience? How can data and biometrics improve safety? How can data collected in airports improve the experience and margins realized by airlines? These were some of the questions I heard being asked time and time again.

What became apparent to me is that many airlines and airports are still in their infancy when it comes to advanced analytics, and many don’t know where to start. I kept telling people that they shouldn’t feel bad about this, as almost every other industry is in the same position when adopting data-driven decision making. I focused my energy on addressing the adoption of data-driven decision making when I spoke on the Aviation Festival Americas panel. The topic? Creating Actionable Insights: Learn how to properly extract insights from your raw data.

Here are six takeaways from our session:

1. Start small, but start

So many airlines are facing analysis paralysis as they try to tackle the big problems. Research shows that to be successful in any change management process; one must demonstrate regular, incremental wins or one risks losing future support. Start by tackling the small problems and build a groundswell of support within the organization.

2. Stay focused

It is the scientific method that allows teams to remain focused. One must ask a question, form a hypothesis, test and analyze results, check for alignment with the hypothesis, retest if necessary, and communicate results.

3. Focus on outcomes, not tools

So many are enamored, confused, or simply confounded by phrases like artificial intelligence, neural networks, and machine learning. The use of terms like these when describing what you are trying to accomplish to your colleagues may scare the shit out of them. Instead, focus on what outcome you are seeking to achieve. No one cares that you’re using Natural Language Processing. They care that you can achieve the outcome.

4. Infrastructure needs to be built

There are many things one can do without significant infrastructure expenditures, but eventually, you’ll need to invest. Bringing disparate data sources together can be the key to unlocking a competitive advantage, but most airlines do not have the infrastructure developed to make use of this in a timely fashion. There are many tools available to help accomplish this, but in keeping with point #3 above, I won’t discuss them in this post.

5. Translation is crucial

I spoke to a number of airlines and service providers who suggest that there is a major gap between data analysis and valuable data insights. What good is showing a percentage change if it’s left to the user to interpret it on their own? Translation is needed, which is to say that an expert who can translate the work of the data scientist so as to support an executive in their decision. No one wants more questions; they want answers!

6. Hire experts

Amy Valcik, CMO of Flybe, said she relied heavily on external experts and vendors to support Flybe on their analytics journey. Considering the cost associated with building an internal data science practice, it makes sense that early on firms should simply buy expertise before they consider building it. Be great at what you do – running an airline, and let those who are experts in data science, engineering, and software development be great at what they do.

 


 

If you’re interested in learning more about Lixar, our data practice, and our software development expertise, please contact us. We love meeting new people and sharing ideas!

Contact: data@lixar.com