Data Science plays key role in Route planning and Revenue Management of the industry. Understanding traveler demand for specific city pairs and pricing flights are among the main problems airlines solve to survive. Data science allows for more sophisticated ways to accomplish demand analysis. Airlines can use traveler behavioral data, abandon searches on the online travel agents, and meta search sites or social media chatter can help define leisure demand.
It also helps Airlines in In-Flight sales and food supply. EasyJet CEO John Lundgren tossed the data science team to analyze the demand for food items. Depending on a route the team learned that demand for items on a 6:00 a.m. flight to Edinburgh is very different from that of a Friday night flight to Ibiza. So, the jet was throwing three fresh food items in the trash after each flight or nearly 800,000 euros annually. John Lundgren noted that such a mistake cost the carrier millions of pounds.
Data Science has also helped airlines industry in fuel consumption and optimization. Carbon emissions increased by 32% over the past five years. That’s why aircraft manufacturers and airlines are looking for ways to improve their fuel efficiency. In 2018 airlines spent 23.5% of total expenses on jet fuel. to become more fuel-efficient an airline must accurately predict how much fuel it needs for every scheduled flight to supply a plane the best scenario is to have a single analytical tool.
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. It generates forecasts for a 12-month horizon and considers such influencing factors as fuel price, number of trips, and time to make predictions much more accurate.
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