Have you ever wondered how much data a typical flight generates?
Imagine yourself on a journey from Frankfurt to San Francisco. In a 12-hour flight, a twin-engine aircraft can produce a staggering 844 terabytes of data. And that’s just the beginning. Booking systems, airport operations, marketing campaigns, and social media create a data deluge. This culminates in a journey that generates a mind-boggling petabyte of data. The question arises — is this immense volume of data a challenge, or can we harness it for better decision-making?
“Echo-Delta-Charlie” is a comprehensive plan for airlines to achieve their CXO objectives through an effective data strategy. Technology enables the democratisation of data, giving business users the power to generate, consume, and collaborate on insights.
As the aviation industry experiences a resurgence, with more flights taking off than ever before, it’s clear that the skies are busier than ever. However, the path to recovery hasn’t been without its turbulence. Recent events, such as flight cancellations due to staff shortages in air traffic control, highlight the challenges faced by the industry. Challenges can also bring opportunities. Across various sectors, data isn’t merely a critical enabler for overcoming business hurdles; it is also shaping new business models with data at their core.
Echo: Elevating excellence with the “5 Es”
– Elevate experience
Customer expectations are evolving rapidly. In-flight Wi-Fi, once a luxury, is now considered a critical part of the passenger experience. 77% of passengers now view in-flight Wi-Fi as essential — a 40% increase compared to pre-pandemic levels. Data-driven decisions like seat upgrades and personalised services enhance the passenger experience. For instance, imagine receiving an upgrade to the upper deck of a Boeing 747, all thanks to data-driven loyalty programs run by all major airlines.
– Elevate efficiency
Efficient decision-making is crucial for airlines. Even minor improvements to taxi times can lead to significant fuel savings and emissions reduction. The question is, can the efficiency of experienced pilots and ground crews be democratized across all airline processes and systems through data-driven insights?
– Elevate effectiveness
The art of swift turnarounds — The third “E” is “effectiveness.” Many airports in Europe and North America have overnight closures, typically from 11 PM to 5 AM. This statement underscores the significance of efficient operations. Reducing turnaround times from the typical 90-120 minutes to under 40 minutes requires synergy across systems, processes, and people. Effective data-driven coordination can lead to successful outcomes, as evidenced by the achievement we are witnessing.
– Elevate Environmental, Social, and Governance (ESG)
Sustainability takes flight — The aviation industry increasingly focuses on sustainability, which is the fourth “E,” — ESG. Airlines like the Lufthansa Group are setting ambitious climate protection goals to achieve carbon neutrality by 2050. Data ecosystems are emerging to support sustainability efforts, such as decarbonisation in shipping.
– Elevate economics
Navigating financial skies — The aviation industry’s financial landscape is complex. While profits are expected to improve, CXOs must navigate factors like fuel costs and inflation. In addition, it is essential to tackle supply chain and geopolitical issues in order to ensure financial viability. Investment decisions, cost simulation, pricing based on own data and market intelligence can be crucial in this context.
Delta ─ Data, analytics, and AI strategy to realise 5Es
While data and AI can help achieve CXO goals by embedding data and AI into day-to-day business processes, it all starts with the right data strategy.
Here are six steps that will help you take your data-to-decisions journey to a higher level of success:
– A significant amount of preparatory work must be considered when planning a new route. Similarly, data and AI initiatives must be planned well. Commencing with a use case or a set of use cases is preferable for initiating the design of a data platform. Use cases must be prioritised based on business value outcome, market time, and implementation cost.
– Airlines put a lot of effort into choosing the right aircraft and engine combination. Having a robust, scalable, and functional data platform is key in the world of data and AI.
Three components are of utmost importance:
– The data engine — Preferably built on cloud-native data platforms in the market, the data engine should support volume, velocity, variety, and integration requirements.
– The insights engine — Ease of reporting and dashboard development are essential considerations. Decision intelligence, a search engine for data, data science, AI, and GenAI model development and deployment are key considerations in building the insights engine.
– Improving data trust — The better the quality of data, the better the quality of insights obtained from it. To ensure reliability of data, it is crucial to establish a foundation for measuring and monitoring data quality. However, a human-centric approach with the right data ownership and governance structure is strategic to maintain high-quality standards.
– Monolithic long-duration data and AI initiatives will have little success in the current world. Effective program management and governance are crucial for the successful and timely delivery of use cases through cross-functional teams. This process is similar to pilots monitoring key controls in the cockpit.
– Change management is the most critical aspect of any modern data initiative. Since the data and initiatives are embedded in day-to-day business processes, change management goes beyond the use of an interactive tool. It involves considering how the business processes can be transformed with data and AI.
– Last but not least is the predictive and periodic maintenance of aircraft, the maintenance, repairs, and operations (MRO) process to keep the aircraft in good health. The same is true with the data and analytics ecosystem. Developing line of business (LOB) specific “data observability” for seamless monitoring of data and AI platforms is crucial. Ensuring the health of data pipelines, data quality, and insights consumption has also become pivotal in addition to periodic enhancements and upgrades.
Charlie – Create, consume, and collaborate with insights
The final product aligned with the five CXO objectives and created through six steps of data and AI strategy is a tool for business. Business users can create, utilise, and collaborate on insights within Airline teams and with travel industry ecosystem partners. This model enables self-service and promotes true data democratisation.
In the data-rich skies of the aviation industry, the journey from data to decisions has never been more critical. CXOs and business leaders are on a mission to turn around the industry. They aim to enhance passenger experiences, optimise efficiency, and effectiveness, meet sustainability goals, and drive back to economic stability and long-term success. Data, analytics, and AI can guide aviation professionals in achieving this mission. Setting up the right data strategy is pivotal. Data initiatives shouldn’t be driven as horizontal technology enablers. Instead, they must be embedded in the business strategy and day-to-day business operations. The result will be the right data ecosystem that business teams can leverage to create, consume, and collaborate with actionable insights.
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