Why data flow is the fuel for aviation operations

After a punishing two years, the aviation industry finds itself within a major period of growth. Despite the good news flowing from a strong return to travel, operational challenges are weighing heavily on organizations’ ability to efficiently manage the recovery phase. With supply chain issues, staff shortages and air traffic control challenges all adding mounting pressure, the odds of emerging stronger seemed stacked against airlines.

No doubt these issues will eventually be resolved, yet airlines are sitting on a treasure trove of data that can help speed a more efficient and informed return to service. The challenge? How to develop the ability to capture, analyze and action data to drive a more successful airline operation.

While data is already central to the way that an aircraft is maintained to assure safe flights and identify issues, data is yet to be fully utilized more widely across aviation operations to streamline workflows and improve decision making. Coming through the next five years with revenue and momentum will rely on this approach of monitoring, analyzing and optimizing operations by integrating data flows for every part of the business. Ultimately, if the industry is to overcome inertia within the system, efficiencies need to reach beyond single defined areas such as fleet management to the passenger experience, baggage, catering, staffing, scheduling and beyond.

Winning the battle with embedded data flows

Financial, reputational and environmental imperatives require performance optimizations to minimize fuel consumption, maximize strained resources and keep airline operations moving on schedule as planned. However, the complex nature of airline operations means that teams often must adapt at a moment’s notice or deal with a series of connected consequences which can range from unexpected weather to staff callouts, air traffic control slowdowns, baggage issues or geopolitical challenges.

Any one of these issues or a combination of factors leads to flight delays, missed connections, disappointing customer experiences and likely risks to the airline’s reputation. Increasingly, their compounding impacts are drawing the attention of regulators, the media, and the traveling public, heaping more pressure on an already complex industry. ?

While no one single “remedy” will solve all problems, airlines should prioritize making use of their monumental amounts of data to help identify areas of improvement and enable more strategic decision making. With a commitment to exposing more operational data, modern airlines can rely on deeply embedded data flows to identify issues, find a strategic course of action, and predict outcomes in real-time. Harnessing machine learning to analyze this information, applying business intelligence, and AI techniques, airlines can create efficiencies to mitigate disruption.

For example, real time data on a late fuel truck can signal a threat to turnaround time by detecting this and recommend ‘parallel boarding’ that enables passengers to board while the aircraft is being refueled. Another case in point is preventing fines associated with regulations that mount up to millions of dollars yearly. Airlines can leverage artificial intelligence, machine learning and predictive analytics to assess aircraft time on the ground and generate actionable insights that prevent them from being at risk of breaching regulations. And rather than just focusing solely on isolated problem resolution, trend analysis taken over time can result in a positive ripple effect when embedded data has the ability to feed into a much greater, powerful impact on operations over time.

Data and the human factor

Aviation staff are at the forefront of the battle to deliver efficient service, yet shortages are leaving many overstretched and fatigued – so much so that it has sparked protests and strike action. Embracing intelligent automation across operations to support their roles and responsibilities can also therefore be a crucial tactic for playing the long game of operational efficiency. Whether it’s harnessed to free staff from manual ID checks, optimize staffing levels, or equip them with the insights to effectively to handle fluctuating passenger numbers and baggage loading demands, data-driven processes not only streamline workflows – they can support frictionless workforce experiences too. The outcome can improve staff engagement, while also contributing to overall passenger satisfaction.

As Glyn Hughes, Director General of The International Air Cargo Association (TIACA), points out, competition for the future workforce will be fierce, so embracing projects that increase productivity, capacity and service levels will be key:?“We must focus on continual staff development to retain a workforce with career-building and value-adding prospects. We must automate and use other tools such as robotics to support physical staff in performing duties with increased productivity and efficiency.”

The imperative of better data-driven operations

As airlines search for long-term strategies to keep improving their operations, massive gains in efficiency and decision making will in no small part be attributable to digitalization. With 84% of US airlines and 81% of airports looking to loosen their purse strings and spend more on automating passenger processing and compliance (SITA), many are starting to recognize the need to bridge the gaps in workflows. Smart CIOs and operations executives will prioritize projects that enable their teams to gain better access to embedded data insights, leverage automation and business intelligence techniques, and optimize business decision making based on real-time and historical trend data to improve operations.

With many airlines and airports operating legacy systems, projects will need to focus on systems modernization techniques to expose embedded data flows. For internal IT teams stretched to the max on day-to-day operations challenges, airlines and operators will look to augment internal teams and address data skills gaps with outside experts with deep institutional experience. Such expertise can be applied to accelerate efforts to gain the insights more quickly from data-oriented initiatives – but the outcome of their efforts lies in how far they can leverage data beyond single touchpoints to reach multiple interacting operations while smoothing airline operations to drive efficiency, growth and profit.