No business should make any decision at all, unless you have the data to prove it.
Let me repeat myself. No business should make any decision, at all, unless you have the data to prove it.
Data-driven decision-making is core to any digital business.
And even more so in airlines.
With restrictions around the pandemic easing over the past year, air traffic is bound to increase going forward. This jump in demand, however, is a looming threat to the redundant legacy airport infrastructures that exist in so many regions around the world.
So there’s more need, than ever, to use data and analytics for determining insights from past trends and patterns in order to predict future passenger and operational efficiencies.
And what’s awesome about this modern digital world is the accessibility we have to the necessary tools for capturing, processing, and analysing that data.
Digital Transformation & Data Abundance
No matter what channel you offer, or what engagement approach you take, you are able to track absolutely everything. From the passenger, to the employee, to the partner.
You are able to build up a repository of information around your passengers, their habits and needs. On top of that, you are also able to build a repository of data around your operations and processes.
You’re building up valuable information around how you manage your planes and how you manage your partners.
And digital transformation enables that. It enables an environment where access to data becomes abundant. It enables greater accuracy in every decision-making process.
But the hard part is visualising this data in order to make fast, seamless decisions around the business.
As you get your first taste of this new-found power, you ask very basic questions of your business. Like, “Am I making a loss or not?”.
So the granularity is the first step that you start to notice as a business. You get so much data that you can really deep dive into the fine-grained details of any decision.
Which really helps you be more effective with your questions and decision-making.
Questions evolve and look more like, “Am I making a loss today?”, “Am I making a loss this hour?”, “Am I making a loss this hour, on this airline, on this route, for that particular set of customers?”.
The problem is that this granularity gets increasingly complex as more data floods in, as you digitise further and you ask increasingly complex questions.
The data essentially explodes. There’s so much that it would take years to work through, analyse and produce any disruptive insights.
And This Is Where Machine Learning Steps In
With machine learning, you’re given the power to sift through, categorise and analyse vast amounts of data, allowing you to answer very complex business questions.
A good example of a complex business question is: If I’m making a profit at a particular time of day on a particular route for a particular set of customers, where can I find more of these customers and what other services could I be building that they would find interesting?
It’s a complex question to find a simple solution to.
Traditionally, we would build those products and services, take them to market and measure their success.
And that measurement of success is based on revenue.
Now, with machine learning models, you can get a highly accurate prediction from your data.
And if the data backs the prediction, then you can make the investment.
And when you make the investment, it would be on a minimal viable product. Where you start with a test and you get feedback from customers as quickly as you can.
The secret is that if the feedback is showing the same indicative results of the machine learning model, you’ve got the green light to forge ahead and reap success.
If it doesn’t. Either tweak the model and reconsider your approach, or try to understand what you’re getting wrong around that product or service offering.
Take A Data-Driven Approach
With an effective digital transformation in place, your world of decision-making should be powered by data everywhere. Everything that you do should be tracked by logging it, observing it, and by responding to it in a real-time manner.
It’s a big shift in mindset. But a necessary one.
Traditionally, we’re used to running reports and seeing data that is 30 days old. In this modern world, everything can (and should be) real-time.
Don’t have the compute power? Seem impossible?
With modern toolsets, you have compute on tap and to top it off, you only pay for what you need – and when you need it.
So why not consume vital data points in real-time and at any possible time?
Why not have all the information you’ll ever need at the tips of your fingers across whatever channel is most suited to you?
It’s simple: Become a data-driven, ML-powered business.
The scale of this data is so vast that if you’re not using machine learning to dig for deeper insights, to optimise your environments and to revolutionise the passenger experience, you’re going to find it very difficult.
