by Sejuti Das

Predictive analytics propels Indian airline industry to great heights

Dec 08, 2016
AnalyticsBig DataBusiness

Indian airliners embrace big data and predictive analytics for granular insights that can help them enhance customer experience and gain greater business efficiencies.

With constantly changing market behavior, increasing customer demands and preferences, big data and predictive analytics has proven to be very useful for the airline industry. 

Aviation is a high-cost industry with huge fleet sizes, high operating costs, fuel costs, landing charges and various taxes. In order to optimally utilize its resources and to deliver sustainable business performance, airliners need granular insights into their operations as well as customers.

The explosive growth of data and the availability big data in the public domain have prompted airlines to take advantage of predictive analytics to bring in new efficiencies and tap new opportunities.

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As Sudipta Ghosh, Partner & Leader – Data and Analytics at PwC India observes, taking business decisions is getting increasingly complex, and therefore to stay ahead of the game in this competitive environment, airliners need to depend on analytics-enabled decision-making process.

“Big data analytics plays a significant role in unlocking the value of data by generating patterns and insights. However, airliners in India need to invest in creating the right structure, strategies, and processes to make this happen,” says Ghosh.

Over the time, a few renowned names in the Indian airline industry have deployed analytics to change the way they do business. The best example is Indigo. With 100 aircraft and more than 600 flights a day, the company has over 30 percent share of the domestic market. A key factor contributing to Indigo’s success is the way the airliner uses technology. It uses big data analytics to enhance fuel efficiency on ground, and reduce other costs to improve business performance.

India’s Jet Airways is not far behind. It maps the data and integrates it with advanced analytics to accurately track and report emission levels by individual aircraft. Even the customer loyalty program by Jet Airways has been a model for others to follow, as they use data management and analytics to provide their customers with personalized offers.

SpiceJet has also started taking baby steps towards adopting big data analytics in their business operations to understand its customer behavior. “As an organization, we are not behind,” says Glory Nelson, Senior Vice President – IT at SpiceJet. “We have already started integrating social media analytics to understand travel patterns, passenger preferences, the ability to pay, and many other facets of airline travel to decide what can be done best for our customers.”

Also Read: Indian oil and gas industry embraces predictive analytics

Big data analytics is not only limited to transactional data but is increasingly being used by airlines to analyze social media feeds, according to  Ehtisham Zaidi, Sr. Research Analyst, Gartner. He says, “Most airlines take their social media analytics extremely seriously, as it can make or break their business, in terms of customer sentiment, which is increasingly important in a heavily commoditized industry.”

Today’s travelers expect a customized and personalized experience while traveling, and the airline companies must know all about engaging them at the right time, through the right channel. Ravinder Pal Singh, CIO at Air Vistara also believes that predictive engineering is the key to the future of Indian airline industry.

According to Shanmugam Nagarajan, Co-founder & Chief People Officer at [24]7 Inc, a company that provides customer engagement solutions, the competition among the Indian airline companies has reached an unprecedented level. “Understanding the influence of analytics and big data is indispensable for an airline company to survive in this competitive marketplace,” says Nagarajan.

“With advances in analytics, airlines now have the opportunity to introduce smart, low-cost channels such as virtual agents and digital chat agents, which can be far more effective with the underlying layers of big data and predictive analytics,” concludes Nagarajan.