Five Ways Data Can Power the Airline Industry Reboot in Pandemic Times

Article
By
Ranjith Kumar
November 24, 2020 8 minute read

The revenue loss for the aviation industry, worldwide, due to the pandemic outbreak is estimated to be at 314 Billion USD [1]. The economic implications of the COVID-19 pandemic, therefore, are far-reaching, to say the very least.

The airlines industry has been one of the worst affected sectors where businesses came to a screeching halt as the pandemic’s fear and social distancing norms discouraged people from making travel plans. In September 2020, The International Air Transport Association wrote that it expected overall traffic in the year 2020 to be “down 66% compared to 2019. The previous estimate was for a 63% decline.”

Governments started offering stimulus packages and relaxed travel restrictions to motivate industries into resuming operations to fill the lacuna in the global economy caused by operational shutdown. Under the CARES (Coronavirus Aid, Relief, and Economic Security) Act, the US government reportedly rolled out “$25 billion for loans and loan guarantees to passenger airlines; $25 billion for wages, salaries and benefits of airline employees; and $10 billion for aid to airports.”[2]  This offered some solace to the airline industry as companies explored the viability of getting back to business in limited financial reserve and an uncertain market demand.

While grounded flights have been wheeled off the hangar, the overall airline industry’s business outlook will take a while to make a complete comeback. Experts say that it will take at least 2 more years for the demand in the airline industry to match the demand in 2019.[3] This uncertain scenario highlights different areas and functions wherein the airline industry can benefit from accelerated adoption of analytics:

1. Predicting demand:

An accurate prediction of demand holds immense value for airline companies who are aggressively optimizing their routes and carefully planning seat bookings to prevent revenue leakage. Despite bookings, the uncertain social environment created by the pandemic is making accurate demand forecasting challenging. Relying heavily on historical data alone would not suffice in the current scenario.

Employing demand intelligence analytics can help stakeholders identify specific factors influencing sudden demand oscillations. Enterprises must tap into multiple data sources to provide insights on factors like flight status and schedule of other air carriers, search trends on booking sites, and impact of day to day world events to gain a holistic picture of the demand scenario. Innovative methods such as forward-looking forecasting can help improve forecast accuracy by utilizing information gathered from news articles, sourced from multiple reliable sources to attribute a potential impact value to upcoming events and help improve forecast reliability as airlines start to operate at scale.

2. Cutting on unwanted fuel expenses:

A dip in passenger volume has forced major airline companies to ground a part of their fleet. However, deciding which plane to ground is a tricky riddle to solve when downsizing. While there are aging aircrafts that have ferried passengers with minimal or no operational downtimes, there are also new-age aircrafts with no illustrative flying history.

With a view to retain aircrafts that can run cost-efficient operations, fuel efficiency must be considered as a defining parameter. Flight telemetry data is analyzed by fuel dashboards to examine the fuel efficiency of an aircraft. Robust analytics algorithms can map fuel usage and propose measures to optimize the usage accordingly. As is, fuel remains one of the most significant costs for airlines companies – “The global airline industry’s fuel bill is estimated to have totaled $188 billion in 2019 (accounting for around 23.7% of operating expenses)” and in an economically challenging time, the onus is on making judicious use of available resources at optimum cost.

Unplanned fuel expenses prove costly for companies. Setting up robust analytical frameworks can help identify and regulate unplanned excess fuel consumption, by utilizing notes from pilots and leveraging other pertinent information to plan their routes and enable them with guidelines for effective fuel management.

Furthermore, analyzing data on airport traffic trends such as length of runways, types of aircraft landing on runways, among others, will also help to identify optimal flight paths near runways. This will allow pilots choose the shortest in-air route that can be taxied by an aircraft even with single engine, thereby saving fuel significantly.

3. Route Optimization:

It is safe to presume that regions less affected by the pandemic are likely to exhibit higher passenger volumes. However, in these precarious times, guesswork can only herald more risks for the airline industry. A digital data dashboard that offers real-time COVID-19 updates on geographies will allow insights into economic recovery on a global as well as regional scale. This will help in identifying regions that may exhibit signs of the fastest economic recovery. Airline companies can tap into the consumer behavior data derived from their websites and apps exclusive for those identified regions to get a hint on consumer demand for flights.

4. Customer Experience:

As air traffic gradually increases, airlines would look to attract customers that have not travelled in a while, given the health concerns brought about by the pandemic. Airline companies can harness historical flight and accommodation data for cues on individual preferences and offer personalized services based on customer preferences. Furthermore, offering services like seamless, hassle-free check ins, and cross-sell suitable services with higher propensity, WIFI package offers, etc. In addition to these, recommending ideal destinations based on preferences, cookies and prior travel history will motivate customers to plan vacations they had put in the back burner for a while.

Access to passenger health data will allow airline enterprises to recommend meals and seating arrangements suited to passenger comfort, and most importantly address their health concerns. Information on passenger health records will also equip in-flight crews with necessary medical aid in case of mid-air emergencies. Maintaining an updated database on infection rates exhibited by regions will allow airline companies to issue timely warnings to passengers on their destination regions’ health risks.

5. Data Partnerships:

Prudent partnerships with sectors, such as the healthcare sector to transact data relevant to both partners, will have an overarching impact on airline operations such as customer service, passenger safety, among others. For instance, a bilateral partnership for data transactions between healthcare and airline industries can help both parties address concerns in this critical time. Apart from enabling customized in-flight and emergency services, analysis of a patient travel history will allow healthcare authorities to identify and segregate passengers from high-risk zones. Upon identification, airline enterprises can impose flight restrictions on passengers suspected of being asymptomatic transmitters of the virus. Researchers fused case data such as reported infection rates from John Hopkins University and air travel data provided by International Air Transport Association (IATA) in a tool to map the route of COVID-19 transmission.[4] This tool’s findings are expected to guide policymakers to impose travel restrictions in regions that exhibit the highest risk of contagion.

Setting up data partnerships between airlines, hotels, tourism companies, etc., can also help bolster connected services like accommodations, safe shuttle services last mile logistics, etc. Within the firm, referencing miles or loyalty data points can help to generate insight about the consumer profile based on the preferences they choose.

Will the pandemic-induced dynamism intensify the data clout in the airlines industry?

There is no doubt that the pandemic has exposed the lack of preparedness of the aviation industry in the face of unprecedented situations. This statement finds more ground in the USD 84.3 billion loss through 2020, projected by Alexandre de Juniac, the Director General and CEO of IATA. However, the eventual opening of regional borders has stimulated demand in the airline industry as individuals have resumed business and leisure travels at slow paces. During a virtual meet named Flightplan that discussed the future of the airline industry, Joe Leader, CEO of Airline Passenger Experience Association (APEX) observed, “The United States has returned to stronger levels of air travel despite increasing COVID-19, this is because air travel remains the safest transport link, aside from one’s own personal vehicle.” [5]

Therefore, while the aviation industry seems to be on the path to recovery with more borders reopening and travel restrictions easing out, the data collated during these difficult times can provide valuable insights. When leveraged efficiently, these datasets can help train neural networks to guard against and be better prepared in the face of future risk events. The need of the hour is to build robust, resilient systems that can better withstand any disruptions or risk events in the years to come.

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Leader
Ranjith Kumar
Delivery Unit Head

Ranjith Kumar is a pioneering data practitioner with over 15 years of experience spanning industries such as retail, CPG, and more. He has built capabilities across RGM, workforce management, and forecasting and is an expert in building custom business applications. At MathCo, he spearheads innovation and platform development to create capabilities across the analytics value chain. He has also planned and executed multiple enterprise-level initiatives that delivered tremendous outcomes for leading Fortune 100 enterprises.