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The aviation industry is a sector involving high cost and security concerns. Analytics in this sector has huge potential, as varied data can be collected at each touch point showcasing customer interests. Crucial factors such as weather forecast should be critically analyzed using sophisticated tools to ensure passenger safety. A lot of logistics complexity also lies straight from building an aircraft to safe take–off and landing. Also, since customers pay the highest prices in this form of transport, the same level of satisfaction and experience too is demanded by them.

Almost 1% of the world’s GDP is expected to be spent on air transport (nearly US$ 750bn) in 2016. With such humongous money associated with the airline Industry, the difference between a successful airlines and a still struggling to compete airline is just of Data Analytics. Using sophisticated analytical tools airlines try and capture accurate sensor data to optimize the maintenance of aircraft. They use the weather forecasting tools as well to optimize fuel loads on the machine and hence save costs incurred due to weight. They also indentify and collect the unstructured demand information. This helps them to offer higher customer satisfaction and hence differentiate themselves from the rest. Now-a-days airlines are using technologies, such as Hadoop and sophisticated data mining algorithms, to capture such unstructured data.

Leveraging analytics to enhance customer satisfaction:

After all the price wars that goes on between airlines offering almost similar prices. It simply boils down to who ever provides better customer satisfaction and personalized experience that becomes the winners. When a customer buys  a ticket online he is often offered complimentary deals. All this is done using data analytics where analytical tools based on past purchases forms a customer profile which helps in converting customer lead, based on their choices. For every touch point the best service available are thus offered. Personalized offers can be sent through emails, app notification, social media, etc. At a macro level change management should be introduced keeping customer centric approach in all stations like service desk, etc. Not only present but also the future behavioral changes in customer can be predicted giving airlines a bigger advantage in certain type of services.

Security concerns:

Security is of utmost importance at any airport. Any disturbance in the normal operation of security activities triggers could trigger an emergency and cause panic, in addition to loss of money and time. This calls for security features which not only monitor and control crowd at the airport and in the peripheral area, but also systems which can detect potential threats automatically and alert the security personnel. Algorithms are being developed and tested to identify questionable passenger behavior such as isolated movements, movement against the flow of traffic, etc. Such smart systems make security monitoring and enforcement easier.

Weather conditions:

It is the most critical external factor which affects airline operations. This necessitates the availability of systems which can predict the weather accurately and in a timely manner. Such predictions enable airlines and airport authorities to plan out operations for the upcoming time period. Airlines can prevent passenger inconvenience due to last minute delays or cancellations. Accurate time estimation and geo-location of storms and other hostile weather conditions would enable airlines to control accidents and save lives. Weather analytics uses past data and other factors that affect the overall weather.

Airlines industry is a capital intensive one and customers have high expectations when it comes to quality of service. To add to this, increasing competition has made it difficult for players to maintain high margins. All these factors require better understanding of one’s own business in order to control costs, understand customer better, reducing business loss on account of external factors and yet maintain high quality of service and security. Data analytics helps airlines in all these areas and enable players to gain a competitive edge over the other players.

For original post and further reading on role / application of Analytics, click here.   

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Tags: Airline, Analytics, Aviation, Bigdata, DataScience

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