Data analytics and machine learning have touched almost any other industry around the world, including the aviation industry. The use of big data analytics has been a hit in the airline industry like it has been in other sectors as well. Predictive techniques are being used to argument opportunities that airlines can exploit. This article describes some exciting ways the aviation industry is incorporating analytics.

1. Increasing Revenue

One of the ways through which the aviation industry is using data to increase revenues is by understanding ideal operational procedures that can be used to minimize operational costs and maximize profits. The ratio of targeted sales versus the cost of sales is balanced such that sales are optimized at a lower cost possible. Moreover, airlines are using data to determine and target customers who are interested in personalized offers and willing to pay premium prices.

2. Airport Control

Airport traffic is increasing every day with thousands of passengers using the airport. This is a threat to the security of the airport and passengers as well. Predictive vs prescriptive analytics are being used to understand parameters such as airport capacity, airport security, flight routes, runway bandwidth, and flying patterns of various planes. The analytics aims to optimize the use of the available airspace and airport without compromising the security of the users.

3. Cost Reduction

Cost of operating an airline is an issue of concern with many airlines around the world operating on losses while others depending on cash injections. One of the major costs incurred by the aviation industry is jet fuel cost. With data analytics, an airline understands real-time consumption of fuel while at the same time using analytics in route combination to maximize fuel usage. Other airlines are using data analytics to track baggage on real-time, which has been essential in avoiding loss of luggage, which have to be repaid by the airline.

4. Customer Satisfaction

Customer satisfaction is one of the ultimate goals of any organization. Companies are always trying to please their customers, and so are airline companies. To overcome competition in the aviation industry, a considerable number of airline companies have incorporated sentiment analysis to understand the perception of customers towards their packages. With the data collected, airlines have been able to improve their services such as departure time, elimination of flight delays, and enhancing the overall passenger experience.

5. Smart Maintenance

Besides jet fuel, airplane maintenance is another costly expense that airline companies have to handle. To overcome these challenges, engines, and other vital components of an airplane have been fitted with data recording sensors that help to determine the impacts of humidity, temperature, and air pressure on such components. With predictive analytics, it is easier to determine when a particular component will need replacement or repair. This has significantly reduced maintenance expenses while at the same time improving the safety of the entire industry.

6. Understanding Customer Behavior

Like any other industry, the aviation sector has been using data analytics to understand passenger behavior to formulate different packages that meet the specific needs of the customers. By understanding routes on demand, airline companies are allocating additional flights to meet the increasing demand while at the same time adhering to customer’s real-time schedules.

With an increase in the use of big data and predictive analysis, the aviation industry continues to enhance its operations by lowering operational costs while at the same time maximizing profits. Moreover, services rendered to the customers have also been enhanced with passenger experience and safety being prioritized.