Data Science in Airline Industry has drastically impacted the industry and overturned many usual practices.

Customers have been the point of focus, besides generating new ideas for expanding the business and improving the existing processes in many industries as Data Science has taken over.

Data science in Airline Industry is no exception!

After all, data is generated not just from the customer bookings but from other sources as well.

Whether the sensors worked fine during a flight or were there some disturbances in the mode of operation; all this and many other factors generate enormous amounts of data.

Why do we need Data Science in Airline Industry?

Data Science in Airline Industry is quickly changing a lot of things about the sector. 

Be it facilitating customer dealing- bookings, cancellations, upgrades, updates, etc.; preventive aircraft maintenance; reduction in costs and automating processes etc., Data Science in Airline Industry has always been productive.

It is a known fact that real-time data is way too crucial and meaningful than historical data.

How does the Aviation Sector benefit from Data Science?

There are several applications of Data Science in Airline Industry that have given wings to the sector. 

Here are 7 of these applications of Data Science in Airline Industry.

1. Airline Safety

A colossal amount of data is generated when a flight is in operation. On an average, a six-hour flight collects around 240 terabytes of data from the aircraft. The aircraft A350 has around 6000 sensors in an aircraft and generates 2.5 terabytes of data every day.

Do you know what will this number be when a newer version of the aircraft starts operations? It will be thrice the amount of data mentioned above.

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The data thus collected can be scrutinized and analyzed to improve flight safety.

Which flight was delayed due to a technical snag? What was the factor that led to the plane crash last month?

Constant innovations with data will help the Aviation sector answer questions like these and collect relevant data.

Data analytics will help identify major risks and the solutions to ensure passenger safety. This will become extremely crucial when air traffic is expected to double in the next 20 years.

2. Smart Maintenance 

Was your luggage mishandled at the airport? Were there issues during check-out or at the conveyor belt? Issues like these are easily addressed on the basis of the data collected through data analytics.

Optimizing the airspace in terms of flight routes, runway bandwidth and types of aircraft, etc. are the issues that creep up with the increase in airport traffic. 

Data analytics is the savior. It not only alerts the authorities to make necessary amendments but also to focus on passengers’ ease and safety.

Did you know that cancellations or delays cost dearer to the airlines? Compensations given to the passengers or expenses on aircraft maintenance shudder the financials.

Predictive analytics will save the day for the Data Science industry as 30% of the complete delay is due to unplanned maintenance.

When the technicians will have access to real-time data, they will easily identify the issues and probable glitch and get it solved or the parts replaced.

The metrics of how, what, when and which of product selling is answered through Data Science in Airline Industry

Revenue management is the key.

It answers how to sell a product to the targeted customer; what is the correct price; when is the right time and which is the right channel to be adopted for this process.

The use of Data Analytics in revenue management is based on a few important factors like income groups, time of purchase, etc.

With the use of Data Science and AI, the revenue specialists regulate prices on the basis of markets, search for productive distribution channels and supervise the seats. 

This is done to make the airline customer-friendly and competitive.

4. Messaging Automation 

A customer should have immediate, proper and effective resolution to all his queries and grievances. Should he/she not get it, the result would be loss of customers.

Picture this scenario…

Allen misplaced his baggage at the time of check-out and was devastated. He immediately walked up to the CSD and informed them. The authorities told him to wait for some time. This wait time seemed to be endless for Allen. Within an hour, the airport authorities searched for his baggage and handed it over to him after completing the formalities.

Now, have a look at this scenario…

Macey also misplaced her baggage at the time of checkout. She rushed to the airport authority and informed what had happened to her. The authorities casually told her to wait. Hours passed by and she reminded them every hour that she is getting late, but to no avail. It was only after four hours that Macey could get her luggage back. She vowed never to fly with the X airline again.

This is exactly what happens in the real world too.

The way customers are dealt with and the steps taken to ensure that their problem is resolved is as important as the time taken for this resolution.

The faster the resolution, increased chances of customer retention. 

All this can happen with the right data collected at the right time and analyzed to be put to the right use.

What’s the result? Chatbot development is the savior here.

5. Customer Satisfaction 

Let’s see some tools that help in the Aviation Industry maintain high levels of customer satisfaction.

Sentiment analysis, predictive analysis and travel journey analysis are the tools that help the Aviation Industry to roll out the right offers to the right customers. What does this mean? Airlines get to know their customers even more with the help of data they collect.

What do their passengers prefer? What is a passenger’s spending behavior?

All these and many other questions are answered and a customized offer is made to the customers.

Data is collected not only during the process of rolling out an offer or resolving a passenger’s grievance, but even after it. 

Did the customer accept the offer? Was the aggrieved customer satisfied with the resolution provided? Even these points make for a strong base to collect data and data thus collected is used to analyze further.

6. Performance Measurements 

Competition prevails in the Aviation Industry like any other industry, on a global as well as domestic level. This calls for the airlines to have a swift and precise enterprise performance measurements.

Did you enjoy your flight? Was your last flight hassle-free? Were the services offered passenger-friendly?

The answers to these passenger-specific questions and some airline-specific ones are crucial.

Why? Even the factors that are seemingly small, also have the potential to drive notable and effective results. It can be a little overwhelming for the airlines to generate, maintain and analyze daily activity reports.

Data analytics proves to be a savior in this case and automates the complete process of daily activity reports– generation, analysis, etc. 

This comes in handy when details related to flight maintenance or daily metrics like the total number of passengers on a flight, the sector/route having more number of passengers and in which specific time slot, distance flown etc. will prove to be useful in bringing out estimated performance measurements. 

Which route generates maximum revenue? Are there any sectors/routes that are slowly bringing down the revenue? All this and many more can be answered and thus daily, weekly, monthly and yearly revenue generation can be assessed. 

7. Cost Reduction 

As per the rule, any damage that a passenger suffers due to baggage loss is compensated by the airlines. This results in increased expenditure for the airlines. Guess what? Data analytics has come forward has the savior in distress.

It has resulted in reduced costs with the introduction of real-time baggage tracking. The data thus collected saves baggage from being lost, damaged or delayed.

Apart from this, the collection and analysis of real-time fuel consumption data will result in efficient fuel consumption. 

Based on several crucial factors like type and weight of aircraft, weather during the flight hours, distance and altitude of the flight, etc., the optimal quantity of fuel required for a flight is calculated.

Real-time access to data has made it easy for the Aviation sector to enhance operational efficiency.

Not just this, several long pending issues like reduction in costs, production-related issues, automating processes, etc. are now possible with the introduction of Data Science in Airline Industry. 

Data science has augmented growth in the Aviation sector. Watch the industry fly high!