Airline operations look orderly from the outside. An aircraft departs, an aircraft arrives. But inside an airline Operations Control Center (OCC), controllers are managing a system where every decision touches dozens of others simultaneously – aircraft rotations, crew schedules, passenger connections, maintenance windows, airport slots, all interacting in real time.
Most people assume the expensive part is the disruption itself. The storm, the technical failure, the crew shortage, the propagated delays. The data tells a different story.
At network carrier scale, poorly planned aircraft rotations – the daily scheduling decisions made before anything goes wrong – can account for a substantial portion of total operational costs. Not because planners aren't skilled. But because the underlying task is genuinely too complex for manual evaluation to handle well.
When you optimize purely for fuel efficiency, for instance, you tend to pack some aircraft schedules tightly with respect to turnaround time. That looks ideal on paper. In practice, it creates fragile rotations: the moment one flight runs 30 minutes late, the delay possibly branches across every subsequent flight on that aircraft, and to every crew member who transfers off it.
Disruptions don't create that fragility. They just make it visible.
This is one of the questions that occupied us when working closely with airline operations teams. The optimization technology isn't entirely new. Disruption management solvers have existed for years. And yet, when we spoke to controllers across multiple carriers, a consistent picture emerged: "everyone wants it, nobody uses it."
Three reasons came up again and again.
The first is speed. Operational decisions – especially in disruption scenarios – must often be made in minutes, sometimes even seconds. If a software takes 20 minutes to compute a recovery plan, the operational window may already be gone. Controllers return to manual judgement not because they distrust the technology in principle, but because they can't afford to wait for it in practice.
The second is transparency. When a system recommends the cancellation of a profitable flight, or proposes a sequence of aircraft swaps that isn't immediately intuitive, controllers need to understand the reasoning. An optimal answer that nobody trusts gets overridden. And every manual override compounds the problem – the more controllers bypass the tool, the less value it provides, and the less it gets used.
The third is onboarding. These tools are often used infrequently, by controllers who rotate shifts and have varying levels of familiarity with the system. Every time can feel like the first time. Adoption isn't a launch event – it's a continuous process that requires investment in training, support, and feedback loops.
These aren't technology problems. They're adoption problems. And understanding them is part of what building Orbit involved.
Orbit is M2P's Decision Support Platform for airline operations, covering two core areas: Disruption Management and Tail Optimization.
On the Tail Optimization side, Orbit helps operations teams build more robust aircraft rotations by evaluating trade-offs across fuel efficiency, schedule stability, crew constraints, maintenance requirements, and passenger impact – simultaneously, in a single optimization run. For a continental fleet with more than 100 aircraft and up to 1500 flights across a certain operating window, this typically runs in under 15 minutes. The result isn't just faster than manual evaluation, it considers dimensions that manual evaluation simply can't hold in view at the same time.
On the Disruption Management side, Orbit includes a feature called the Cancel Assistant, which supports a proactive rather than purely reactive approach. Before a disruption occurs – when a weather event is forecast, or slot restrictions are announced at a major hub – controllers can use the Cancel Assistant to pre-identify viable cancellation options, ranked by impact on passengers, crew, and schedule stability. Each scenario computes in seconds. When the disruption actually happens, the decision is already substantially prepared. Controllers are not starting from zero under maximum time pressure, they're executing against a plan they've already had time to understand and trust.
That last point, trust, is the one we return to most often. Orbit is built on Gurobi's mathematical optimization engine, which processes complex scheduling problems across hundreds of thousands of variables, possibly millions. But the interface is designed for controllers who are not IT experts. Solutions are presented transparently, with clear explanations of which constraints drove each recommendation. Users can adjust parameters, apply their airline's specific business rules, and see how different priorities change the outcome.
M2P Consulting has worked alongside airline operations teams for decades – not just advising from the outside, but sitting in the room with the decision makers, learning the workflows, and understanding what it actually feels like to manage a six-figure decision under time pressure with incomplete information.
That background shaped how Orbit was built. The optimization logic reflects the business rules that controllers actually work with. The onboarding process is structured around the knowledge that adoption requires sustained support, not a one-time training session. And the team that builds and maintains Orbit is the same team that holds the training sessions and answers the operational questions – which means product decisions are constantly informed by real usage.
This is what distinguishes Orbit from a pure technology product. It's a tool built by consultants who understand the problem from the inside.
Orbit is now available for airlines worldwide. The team offers proof-of-concept projects and live demos tailored to your fleet size, OCC setup, and specific operational challenges.
Get in touch with our expert team to explore how we can help your organization become fit for the future.