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Application of Data Science in the Airline industry

  1. D A T A S C I E N C E I N A I R L I N E I N D U S T R Y
  3. O B J E C T I V E S To understand the problems faced by the airline industry and its consequent impact. Application of data science tools to overcome the problems faced by the airline industry. Develop an understanding of data science and how it derives valuable insights to make smarter data-driven decisions.
  4. I N T R O D U C T I O N T O T H E A I R L I N E I N D U S T R Y The airline industry refers to companies that offer air transport services to customers and carry cargo for commercial purposes. They operate services regionally, domestically and nationally. The industry has become the enabler of global business. It provides the rapid worldwide transportation network, generates economic growth, creates jobs, and facilitates international trade and tourism.
  5. As of 2019, aircrafts are taking off around the world at a rate of over 400 departures per hour! I N T E R E S T I N G F A C T S ! Every day, airplanes transport over 10 million passengers and around USD 18 billion worth of goods. Aviation represents 3.5 per cent of the gross domestic product (GDP) worldwide The demand for air transport will increase by an average of 4.3% per annum over the next 20 years.
  6. C H A L L E N G E S F A C E D B Y T H E I N D U S T R Y : Running an airline business is extremely costly. Majority of the costs include - fuel , lease & rent, airport charges, salary etc, out of which only a few can be regulated/controlled by the company. Therefore the cost pressures, government intervention, and world factors immediately affect their revenue and margins. Therefore carriers must analyze data while considering thousands of parameters to do this. Doing so with outdated systems may mean losing passengers to the competitors. Under such situations, operating flights with unreserved seats may add to the burden of increasing costs.
  7. H O W D O E S D A T A S C I E N C E H E L P R E D U C E T H E L O S S ? S O L U T I O N : REVENUE MANAGEMENT SYSTEMS: Revenue management (RM) is the use of data and analytics to define how to sell a product to those who need it at the right price, at the right time, and through the right channel. Revenue management specialists use artificial intelligence to define destinations and adjust prices for specific markets, find efficient distribution channels, and manage seats to keep the airline competitive while also being customer-friendly. To capitalise on rising demand, revenue teams may use event data to raise fares for specific routes and dates. Some events, such as festivals, conferences, or expos, cause temporary increases in demand. Predict H.Q.'s, a software specialising in event forecasting, aviation rankings employ ranking algorithms that compare past flight reservations with event data to demonstrate how much a particular event may impact traveller demand.
  8. C H A L L E N G E S F A C E D B Y T H E I N D U S T R Y : As per studies, by mid-2030s no fewer than 200,000 flights per day are expected to take off and land all over the world. Predictions also estimate that demand for air transport will increase by an average of 4.3% per annum over the next 20 years. Often, large manual check-in queues disrupt efficient operations, burden staff and cause delays. Airports need to become larger and more efficient to handle the increasing demands.
  9. To accomodate more passengers in a shorter span of time, biometric technology is used by airlines. The technology compares images from border control agency databases to facial scans of travellers. These images could be from a passport, a visa, or other travel documentation. With the help of this technology, smoother, faster, and safer travel is possible. This also helps in reducing contact with other people, which proves to be extremely helpful especially in the post pandemic world. S O L U T I O N : Delta airlines has been using biometric technology in few of their terminals in United states.
  10. C H A L L E N G E S F A C E D B Y T H E I N D U S T R Y : Airlines have to spend nearly 30% of their income to buy Aviation Turbine Fuel (ATF). Optimising the amount of fuel used may help reduce cost and divert those funds to achieve greater efficiency. Over the previous five years, carbon emissions rose by 32%. Airlines and aircraft manufacturers are therefore looking for ways to increase fuel economy
  11. In order to become more fuel-efficient, an airline must precisely forecast how much gasoline it will require for each scheduled flight. Airlines use AI systems with built-in machine learning algorithms to collect and analyse flight data about each route's distance and altitudes, aircraft type and weight, weather, and other factors. Southwest Airlines worked on such a solution in its fuel consumption project. The team developed 8 predictive models that included time series algorithms and neural networks the system could produce 9600 fuel consumption forecasts for each month. S O L U T I O N :
  12. C H A L L E N G E S F A C E D B Y T H E I N D U S T R Y : Airline employees have to assign crews to each of the thousands of flights operated every day. This could be a tedious task, if done manually. Various factors such as flight route, crew member licensing and qualification, aircraft type and fuel usage, work regulations, vacations and days off to approve conflict-free schedules for pilots and flight attendants
  13. To overcome this, eployees rely on software that integrates data from various sources, allowing them to get a full picture of daily operations. Using uncovered insights, they are able to make an optimal schedule in terms of working time, crew qualification, aircraft utilization, and expenses. Such models integrate predictive models with the airline systems. cAdditionally, few crew management solutions allow addressing fatigue risk that pilots are in danger of due to a constant change of time zones, long duty days, scheduling changes, S O L U T I O N :
  14. Delta : In early 2021, Delta launched the facial recognition technology to identify passengers at the airport touchpoints. It also uses AI-driven system that supports operational decisions in critical conditions like bad weather and predictive management systems. A I R L I N E S T H A T U S E D A T A S C I E N C E T O O L S : Air France implemented the specialized Sky Breath software, an AI platform collects data from the flight, performs in-depth analytics, and helps identify fuel-saving opportunities and increase efficiency. Alaska Airlines uses Flyways AI platform, a flight monitoring and routing tool that assists dispatchers in making informed decisions and planning new, efficient routes. The system creates data-based predictions and provides recommendations on flight operations and routing.
  15. C O N C L U S I O N The airline industry can use data science to optimize its operations. It helps with increasing consumer satisfaction, improving effeciency by cutting costs and reducing time. Data science is prevalant in nearly all industries today and companies that do not leverage it may lose out to their competition. Data science is now more important than ever. The reason for this is data transformation. We require sophisticated analytical methods that can handle vast volumes of heterogeneous data are needed for this data.
  16. T H A N K Y O U Esha D Nair Christ University, Bangalore