Data Science in Airlines: Industry Applications and Benefits

Data Science on Airlines provides great opportunities to the Airlines Industry. The airplanes flying high in the skies are generating a trove of data on engine systems, fuel utility, weather, passenger information, etc. With more advanced aircraft, fitted with sensors and other data-collecting tools, getting adopted in the industry, there will be more data generated. This data, if leveraged properly, can open new opportunities for the industry. Opportunities in process optimization, people management, and disruptive innovation.

Still, at an early stage, we’re witnessing increased adoption of data science technologies in the aviation industry. Let’s look at some of the applications of data science in the airlines’ industry-

The prominence of Data Sciences in Airlines:

1. Ticket Pricing- Airline pricing is driven by demand and supply. There are lots of factors that influence pricing- weekends, holidays, routes, etc. It also depends on the timing of flights. Evening and early morning flights have different pricing than afternoon and late-night flights. However, the pricing needs to be competitive all the time so as to attract customers. Analytics-driven pricing can help airlines automate the pricing mechanism and help them boost their revenues with optimal capacity utilization.

2. Personalized Selling- Airlines also sell a lot of comfort services like lounge services, extra baggage, seat upgrades, food, etc. A data-driven recommendation engine can analyze a customer’s past history and suggest ancillary services at the time of ticket booking. It can also recommend personalized services based on the customer’s economic profile.

3. Customer Feedback- In the current digital world, customer feedback comes from multiple sources- tweets, pictures, calls, videos, and so on. Data Science has the capability to process both structured and unstructured data in real time and help the customer support team to listen to the customers and quickly respond to their needs.

4. Fleet Maintenance- Every cancellation hurts the revenue and the brand image. Unplanned maintenance also causes delays. With airlines trying to boost revenues through optimal fleet optimization, predictive maintenance can help airlines in keeping their fleet up and running. Collecting and analyzing aircraft data in real time can help the maintenance staff be proactive in avoiding tech glitches and planning their maintenance schedule.

5. Crew Management- There are so many things that go into crew management. Work hours, days off, member licensing, language skills, etc. Data Science can not only help in automating crew schedules but can also bring a lot of insights to solve challenges in personnel management, crew fitness, and regulatory compliance.

6. Fuel Efficiency- The fuel bill of the global airline industry was estimated to be $180 billion (accounting for around 23.5% of operating expenses) in 2018. Data science technologies like AI and machine learning can help airlines get fuel-burn, weather, navigation, and operations data to deliver actionable insights to optimize fuel utilization and reduce operational costs.

These are some of the common applications of data science in the airline industry. As adoption widens, we will see a deeper application of data in the industry. A technology-driven and customer-facing industry like airlines need to optimally leverage data to disrupt and innovate. That’s what will give a competitive edge in the future.

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