The aviation aftermarket has a wealth of data to draw upon to optimize aircraft maintenance. However, in practice, many industry stakeholders are struggling with how to effectively leverage this data—particularly when facing challenges in implementing new technology processes.
“We’re seeing that [the industry has] mountains of data, and now we’re piling more data on,” says Jeff Wheless, global research lead for aerospace and defense at Accenture. “We’re reaching a tipping point now in terms of how to get a handle on that.”
During a panel at the World Aviation Festival in London in early December, airline executives from British Airways, EasyJet and Virgin Atlantic estimated that only 10% of their data is being used—a problem that is being exacerbated by aging technology systems.
According to Accenture’s recent global survey of aircraft service executives, 60% are having problems using and sharing the data to which they have access. “A lot of that is because they’re attempting to do it with core legacy systems that are out of date and that, frankly, are in some cases taking approaches to integration and getting access to this data that are more attuned to the period of time when those systems were initially conceived,” says Craig Gottlieb, managing director for aerospace and defense at Accenture.
To accelerate access to data and improve the end experience without expensive, time-consuming investments in new infrastructure, Gottlieb says companies will need to focus on data integration as a competency. Aftermarket staff, he argues, should be able to access and understand which data elements are critical, even within legacy systems. “We see a lot of the thinking moving there, particularly as folks are considering the role of cloud-based approaches to their overall business,” Gottlieb says.
In other cases, new technology systems may be necessary to truly make the most of available data. At Aviation Week’s Aerospace Incubator event in November, panelists from MROs and technology companies cautioned that this type of shift will require collaboration and buy-in across every level of an organization.
“A lot of my clients have what I call ‘random acts of digital,’ where you get a lot of different organizations trying to do something in the smart factory or Industry 4.0 space,” says Michael Schlotterbeck, smart factory asset integration leader at Deloitte Consulting. He adds that different departments in an organization need to approach these types of technical implementations with a cohesive strategy rather than through separate, disparate efforts.
“It’s very important for companies to get all of the relevant players together in the beginning to try to get a vision together,” he says. “Because if you don’t get to that first step, then when you get to the training and adoption piece, you will hear, over and over again, ‘Well, you never asked me’ as one of the main reasons for not adopting the change.”
The instinct at many companies is to start by getting executive-level buy-in for new technology adoption.
“Every company is different, but I think that you should start with the top down,” says Anna Paugh, senior director of engine material at TrueAero. “You need to have the executive team support to bring the new system in and make sure that they are willing to invest not just money but the time it’s going to take to implement the new system and train the employees.”
Paugh says the next step is communicating with employees to understand which areas challenge them and see how new technology systems can help. However, some panelists noted that a top-down approach to technology implementation can result in blind spots.
“There are a lot of things that people who are at the top of an organization don’t see that people who are at the bottom, figuratively speaking, have to deal with every day,” says Andy Hakes, founder and CEO of AireXpert. “We’re not just trying to onboard and get people to sign up to a system; we’re trying to get them to be actually engaged with that system and have a consistent level of involvement and investment.”
Hakes argues that not prioritizing the user experience can be the nail in the coffin for companies trying to implement new technology processes. He notes that technicians and engineers have a high level of autonomy, so if they perceive that a new system will be difficult or time-consuming to implement and learn, they may reject it because they believe it was designed by people without a real understanding of how they do their jobs.
“Designers need to understand the environment the system is going to be used in. You have to spend time on the ‘why’ to get users to accept it,” Hakes says. “Most technicians and engineers will never set foot in a maintenance control center, a network operations center or a system operations center and thus [believe] the people on the other end of the phone are the enemy and only exist to make life difficult. Spend time talking about the ‘whys’ and you’ll get a much better response.”
Peter White, associate director of maintenance engineering at Tsunami Tsolutions, points out that it is helpful to bring in user groups to define requirements of a new technology system, but this should also extend to the data itself. “Often where projects fail is that they don’t bring users in to go through the same level of effort with their data,” he says.
White suggests that companies develop user working groups early on to define all the needed data sources, challenge areas, expected outcomes and mitigation plans. “One of the biggest areas of deficiency for airlines is repair shop data on other components,” he says. “It’s typically not digitized, but if you don’t have it, you can’t do a true failure analysis to really understand what’s going on with either the components or the systems on the aircraft.”
White notes that companies should have subject matter experts to work with data architects so the people processing, loading and transforming data can understand how it is being used. Finally, he says, companies need to document everything and work with the established IT and data governance plan to maintain the quality of data being put into the system.
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