The airline industry benefits significantly from data science technology. Aircraft flying overhead generate a wealth of data about engine systems, fuel efficiency, weather, passenger information, and more. More data will be generated as more advanced aircraft equipped with sensors, and other data gathering tools are introduced into the industry. This article sheds light on the most prominent implications of data science in aviation.
Applications Of Data Science In Aviation
Ticket Pricing
Supply and demand determine airline prices. Weekends, holidays, routes, and other factors all affect prices. It also determines flight timings. Evening and early morning flights are priced differently than afternoon and night flights. However, the price should always be competitive to attract customers. Analytics-driven pricing helps airlines automate pricing mechanisms and increase revenue through optimal capacity utilization.
Revenue Management
Revenue Management (RM) uses data and analytics to define how products are sold to the people who need them, at the right price, at the right time, and through the right channel. This is because customers perceive the value of a product in different ways, and the price they are willing to pay varies depending on their target group and time of purchase.
Fleet Maintenance
Cancellations lead to lost sales and a bad brand image. Unplanned maintenance activities also cause delays. As airlines aim to increase revenue through optimal fleet optimization, predictive maintenance helps airlines maintain fleet operations. Real-time data collection and analysis help maintenance personnel proactively avoid technical failures and plan maintenance schedules.
Personalized Selling
Airlines also sell a variety of conveniences such as lounge access, extra baggage, seat upgrades, and meals. A data-driven recommendation engine can analyze a customer's history and recommend additional services when purchasing a ticket. We can also recommend customized services based on the client's financial situation.
Customer Feedback
In today's digital world, customer feedback comes from various sources, including tweets, photos, phone calls, and videos. Data science can process structured and unstructured data in real-time, so customer support teams can listen and respond quickly to customers. To their needs.
Crew Management
Crew management has many facets. Working hours, vacation days, member licenses, language skills, etc. Data science helps with crew scheduling and provides valuable insights into workforce management, crew fitness, and regulatory compliance.
Fuel Efficiency
In 2018, the fuel cost of the global aviation industry was estimated at US$180 billion (equivalent to about 23.5% of operating costs). AI and machine learning are data science technologies that help airlines capture fuel economy, weather, navigation, and operational data to provide actionable insights to optimize fuel use and reduce operating costs. Helpful.
Bottom Line
These are some of the most popular data science applications in the aviation industry. As adoption increases, the use of data in the industry will increase. Data Science developers can assist Airlines to make the most of their data to disrupt and innovate as a technology-driven and customer-centric industry. This is the competitive advantage of the future.
