Flying into Quantum – a Game Changer for Airlines?

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Flying into Quantum – a Game Changer for Airlines?

Quantum is exponentially leading its pass into client conversations and conference sessions.

So, I took some time to dig deeper into the potential benefits for our airline customers based on the excellent WhitePaper “Exploring quantum computing use cases for airlines” published by IBM Institute of Business Value. On top, I was seeking the exchange with our IBM DACH Quantum Ambassador and my Account CTO – Dr. Jan-Rainer Lahmann.

Quantum Technology is a rapidly evolving technology that will cause disruption to the way we use IT and technology today and lead to new chances for enterprises and industries.

Many enterprises start to explore the business benefits for their future quantum advantage. Given the nature of quantum technology, use cases that require a lot of compute power and may not even be possible today due to today’s compute power limits will be in focus – look out for them in the fields of planning, simulations & optimization.

Quantum advantages can be leveraged when a quantum computation is either:

– Hundreds or thousands of times faster than a classical computation

– Needs a smaller fraction of the memory required by a classical computer, or

– Makes something possible that simply isn’t possible now with a classical computer.

For transportation companies, the Quantum days are still early, but some of them already embarked to build the needed know how while exploring the potential use cases and benefits.

So, what’s in Quantum for airlines, then?

Let us have a look in 3 key airline topics where IBM’s Institute of Business Value provides insightful considerations:

  1. Irregular Operations
  2. Personalization
  3. Network Planning & Scheduling

1. Irregular Operations

Imagine you could simulate service disruptions and recover more quickly from Irregular Operations.

Weather, operational issues, technical problems, and other issues such as the coronavirus pandemic can challenge airline schedules and staffing. Recovering from these disruptions is one of the most difficult problems that airlines manage. Current solutions are fragmented and primarily focused on operational information with less consideration given to inventory, profit maximization, or even the impact on customer service and satisfaction.

Due to the limitations of current computers, each specific element, such as crew, slots, and equipment, is managed in a sequential and siloed manner. System-wide recovery can take a week or more, threatening passenger satisfaction. Second-order effects on other flights and airports can cost an airline up to USD 500 million annually.

Due to the massive scope of IROPs and the resulting complexity of its underlying global mathematical optimization problem, solving a single operational disruption on today’s computers could take years—or even centuries. But, with quantum algorithms, airlines may be able to:

– Improve the accuracy and speed of scenario simulations that quantify the impact of potential solutions on future flights and passengers. And do it in time to respond quickly to a disruption.

– Deliver advisory tools to customer service agents and automated customer care systems using quantum machine learning to advise on best approaches to IROPS resolution. For example, a quantum computing algorithm could advise agents on how to best compensate each specific customer whose travels have been disrupted based on their personal preferences for cash, accommodations, upgrades, or other amenities.

2. Personalization

The “segment-of-one” is a personalization strategy most airlines strive for, but for which scalability is probably the biggest challenge. When quantum advantage is achieved, it could help unlock the promise of contextual and dynamic personalization.

For airlines, it’s key to differentiate services, improve customer experience, and drive incremental revenue though individualized offerings. Today’s personalized offering systems often fall short of living up to their promise, mainly because of limitations in the customer segmentation step. Current segmentation methods often rely on basic customer features such as demographic and sales data, but do not include contextual data, reducing the pertinence of the recommended offer. Current systems also lack multi-dimensional segmentation to effectively capture contextual differences in preferences, intent, and behavior of travelers. One of the reasons for the absence of contextual features is insufficient computing capacity and scale to handle the high number of data elements required to build complex segmentation models.

Quantum computing may solve these problems, enhancing the personalization process by:

– Supporting richer customer segmentation. Incorporating more complex customer features for multi-dimensional passenger segmentation, and allowing for higher specificity in contextual profiling to improve personalized offerings

– Improving the accuracy of machine learning models that deliver insights and interpretability of results to help marketers or customer service agents better understand
the causality links between customer data and delighted passengers

– Enabling the identification of a dramatically greater number of finely-tuned customer segments that is unmanageable for classical computers.

3. Network Planning & Scheduling

Running parallel optimization strings to accelerate Airline Planning will become a crucial competitive factor. Airlines will need to quickly adapt to changing demand and evolving crisis situations, e.g., in geographical markets.

Network optimization, starting from flight planning and fleet allocation to crew scheduling, is at the heart of airline operations, significantly impacting the operations costs of any airline. But, despite substantial efforts dedicated to streamlining this process, there are still important limitations—mainly linked to a step-by-step approach that leads to local optimization of the sub-processes deployed with isolated decision support tools. These tools generate sub-optimal, local, and uncoordinated solutions.

For example, aircraft route planning often does not incorporate crew scheduling; similarly, crew scheduling does not include block times; and block time planning does not factor in fuel planning, often with detrimental consequences. Additionally, network planning typically does not coordinate its solution optimization with revenue management (RM) and pricing. This results in two major processes happening daily with the same objective—profit optimization—but with separate models and parameters.

This out-of-sync approach leads to inferior solutions in terms of total cost, profit, and adapting to change. It also causes confusion during key operational updates, such as the introduction of new types of aircraft or the opening of new routes. While RM or pricing is optimizing offers based on schedule, capacity, and aircraft configuration, network planning may be inadvertently changing these parameters based on profit optimization. The main reason for airlines taking this distributed solution path is the complexity required to solve a global network optimization problem in a single step. It is practically impossible to solve with current classical computers.

In the future, quantum computers should enable an airline network to co-optimize fleet, schedule, block/ gates, crew, and fuel, while dynamically coordinating with RM, pricing, cost targets, sales, and customer relationship management (CRM) because quantum optimization algorithms could allow more efficient exploration of the potential solutions of such type of large size problem with complex constraints and business objectives.

In order to make the best use of future quantum capabilities, airlines will need to change the way they manage network operations, with more centralized operating models and tighter data integration.

On top: the Sustainability Challenge

On top of these 3 topics, Imed Othmani also expects an opportunity for Quantum within the sustainability challenge for airlines:

“I am excited about all the possibilities quantum computing will enable, and all the applications and the use cases that we have not thought about yet. And it’s up to us to start to learn this technology, so we can accelerate all these discoveries and try to solve all these problems that are impossible to solve right now. For example, climate change and sustainability for the travel and transportation industry will be some of the biggest challenges that will need to be solved in the future. I am hoping that quantum will help us address these critical challenges.”

Imed Othmani – IBM Quantum Industry Partner

So, last question to tackle is – How to start?

Airlines should embark the Quantum Journey today to identify challenges and opportunities. They need to set out their strategy for embracing this major technology shift and building capabilities within their organizations.

You want to discuss how to start – please reach out:

For more information on how to engage, check out this link:

Technology Managing Director Account Lufthansa, IBM Deutschland GmbH

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