Over 2010-2018, airlines made profits every year, benefited from a 63% jump in passenger traffic, and increased flight volumes by 37%. Additionally, 2018 marked one of the most fuel-efficient and best on time performance (OTP) year for airlines in the last decade. Time to crack open the bubbly? Actually, not just yet.
The industry continues to encounter some serious turbulence in the form of operational inefficiencies. Last year, the costs of these amounted to a staggering 1.5 times its operating profits. And while airlines recognize the directional value of digital solutions in plugging these operational loopholes, a persistent challenge remains the inability to quantify their impact and value.
A recent whitepaper by Frost & Sullivan, brought out in collaboration with GE Aviation’s Digital Group and Microsoft, is illuminative in this context, revealing the real, measurable economic value that data and analytics could bring to three of the biggest operational challenges currently faced by the global airline industry.
Network Disruptions: Slashing Nearly $10 Billion
At $33.4 billion in 2018, network disruptions represent the most significant inefficiency cost to the aviation industry. Despite gradual improvements and a record OTP of 81.5% in 2018, over 5.6 million flights were delayed and 655 million passengers faced travel disruptions during the year. Flight delays and cancellations remain at unacceptably high levels, for which the industry has been paying in more ways than one. The immediate fall out has, of course, been a fall in profits; while flight delays cost airlines approximately $97 per minute, cancellations ring up to an average of $68,000 per flight. The deeper, more long-term impact has been felt in terms of dwindling brand loyalty and customer satisfaction.
The irony is that two-thirds of all delays and cancellations are within an airline’s control.
Disruption management strategies have sought to minimize the impact of disruptions on customers and operations by supporting a comprehensive and simultaneous recovery of passenger, crew and aircraft schedules. Data and analytics could make strong contributions here. While predictive tools can anticipate and, therefore, avert potential disruptions, recovery tools can improve decision-making capabilities.
In essence then, data and analytics could optimize aircraft and network operations, improve passenger handling, enable real-time customer engagement and enhance situational awareness. Collectively, they could boost OTP – the key operational metric for network operations – by a significant 2 percentage points, and slash network disruption costs by nearly $9.4 billion.
Unplanned Maintenance: Halving The Bill
In 2018, unplanned maintenance cost airlines over $20 billion or approximately 27% of all maintenance expenditure. This had a cascading effect on network operations since nearly 3.8% of all flight delays and cancellations were caused by Aircraft on Ground (AOG) events.
Traditional impact minimization strategies have focused on maintenance and engineering software that target workflow efficiencies and reductions in hangar time. However, these legacy systems have their limitations.
Instead, advanced data and analytics solutions powered by large aircraft datasets—aircraft health monitoring, predictive analytics, and asset performance management software, among them—promise to deliver several crucial benefits. These include reductions in AOG events, overnight technical delays and unplanned engine events, on the one hand, and significant improvements to technician productivity, on the other.
A quantification of these benefits shows that data and analytics could nearly halve unplanned maintenance bills, allowing airlines to whittle associated costs to a more manageable 14% of total maintenance expenditure.
Fuel Overspend: Lopping Off Almost $4 Billion (And Carbon Emissions, For Good Measure)
The success of fuel efficiency programs notwithstanding, fuel overspend—estimated at a hefty $11.3 billion or about 5% of the total fuel bill in 2018—remains one of the most significant operational challenges for airlines. To aggravate matters, airlines emitted over 50 million metric tons of unnecessary carbon dioxide into the atmosphere last year.
Inefficient flight planning and flight profiles, along with lack of aircraft weight optimization, over-fueling and engine overuse have been identified as the main culprits behind fuel overspend.
A combination of existing as well as advanced data and analytics solutions could transform current fuel monitoring, flight planning, and flight optimization practices. Direct, digitalized data feeds and analytics could enable real time decision-making about flight planning and fuel procurement. Advanced analysis of live data streams generated from multiple sources, together with additional digital sensors and predictive tools, could unlock immense value while informing innovative fuel management practices.
The outcome would be $3.6 billion in savings, and a hefty reduction in CO2 emissions of more than 250 kg per flight.
Back on the Runway, Readying for Takeoff
Turbulence, indeed. Operational inefficiencies related to network disruptions, unplanned maintenance and fuel overspend, among other factors, cost airlines nearly $74 billion in 2018. For an industry whose cost per available seat kilometer (CASK) is 8.11 US cents, this represented a massive waste of 0.74 US cents.
And while the industry has used data and analytics to address many pain points, it has really been a case of doing too little, too late.
In 2018, for instance, airlines recorded only 1.5% of the 1,325 petabytes of data they generated. In a data-fueled economy, that’s a clear case of veering off the runway. By 2030, advances in aircraft designs, ubiquitous connectivity, cloud computing, artificial intelligence, and machine learning could result in nearly 25.9% of 5,924 petabytes of generated data being recorded.
Milesh Gogad, CMO, GE Aviation’s Digital Group says, “Data and analytics can drive real, measurable economic value for airline operations. Meaningful use of data-driven insights can power intelligent operations, create sustainable revenue streams, enable cost savings, and drive competitive advantage for airlines.”
There are already several compelling business cases that highlight such themes.
Emirates reduced its unscheduled engine removals by 56% using an analytics-based maintenance approach. AirAsia saved $1.7 million over a single year by optimizing its required navigation procedures. China Eastern Airlines did not see a single safety related incident on its A320 fleet of aircraft, thanks to data scientists who analyzed full flight data. Qantas’ pilots used a data-driven flight analytics tool to achieve a 15% uptick in fuel-saving techniques.
Each of these examples represent tangible, materially significant, measurable outcomes of applying data and analytics, not just directional. A case of getting more for less.
Article was originally published on Forbes.com