Angela Bishop
CEO UK & Partner
Few environments depend on coordination quite like a major port or airport. On any given day, hundreds of decisions shape whether a vessel berths on schedule, a flight turns around on time, and fuel is ready when it’s needed. Each decision may sit with a different organisation. Yet together, they determine how well the whole operation performs.
That creates an interesting challenge for transport leaders. The industry has invested significantly in digital platforms, data, and AI, with the promise of greater visibility, better decisions, and more efficient operations. But technology alone can’t create that visibility. The reason is simple: transport operates as an ecosystem, while its data often does not.
A major port coordinates terminals, towage operators, shipping agents, pilotage services, and vessel traffic management, to name just a few. An airport brings together airlines, ground handlers, border agencies, fuel suppliers, and dozens of other partners. Each organisation has its own responsibilities, systems, and view of the operation. To optimise the whole, those individual views need to become a shared one.
That means knowing not only what is happening now, but what is likely to happen next, from vessel arrival times and berth availability to resource capacity, delays, and weather. And it means cooperatively exchanging information early enough for organisations to act on it.
How small information gaps become operational problems
The impact of getting this wrong can appear surprisingly mundane. A vessel is ready, but the tug crew isn’t available. It looks like a resourcing problem. But the crew had been on standby and as plans shifted throughout the day, the crew reached their statutory working hours and had to stand down.
Pinpointing what led to that moment: a late update, a berth change, or a decision elsewhere, can be difficult without a shared record of how plans changed across the operation.
What locally looks like poor tug scheduling is actually an information problem spanning several organisations. Multiply situations like this across hundreds of movements and resources and the operational consequences become significant.
The consequences can become strategic too.
If poor coordination affects turnaround times and demurrage, a port becomes less competitive when cargoes and contracts are placed. For a major energy port, that is a commercial risk with implications that can extend beyond the harbour to national energy security.
This is why improving transport operations means looking beyond individual organisations, technologies, and data systems.
A lesson from the Port of Milford Haven
Working with the Port of Milford Haven, the UK’s leading energy port, we looked at how operational information moved across the organisations involved in a vessel's port call.
Coordination worked because people made it work. The Vessel Traffic Service played a central role, relaying information by phone and radio, while terminals, agents, towage, and pilots coordinated directly where needed. The challenge was that much of this information was only visible to those involved in each exchange, making it difficult to build a shared view across the port.
The data existed. The challenge was creating the conditions to use it collectively; agreeing what should be shared, when and in what format, who owned it, who was responsible for its quality, and who could receive it.
These are not simply questions about data. They are questions about trust, incentives, accountability, and governance.
The Port's CFO described the outcome of the work:
“Zühlke helped us take a fresh, independent look at how operational data is used across the Port of Milford Haven and how we could unlock more value from it. Working with multiple stakeholders, the team identified opportunities to better connect data around vessel movements, berth operations, and resource availability, creating a more trusted, shared view of operations.”
That idea of a trusted shared view, commonly held among many organisations, matters.
Trust can sound like a soft outcome in a technology programme. In a transport ecosystem, trust is the currency you need when building infrastructure that your peers will engage in and use. Without trust, organisations are less likely to contribute the information shared systems depend on. And without reliable shared information, even sophisticated technology has only a partial picture to work with.
The same lesson from Zurich Airport
We saw the same principle at Zurich Airport, where operational data sat across a complex network of partner organisations and the existing Airport Operating System faced increasing pressure during peak periods.
Creating a better operational picture meant agreeing shared definitions, responsibilities and expectations around data as well as replacing the technology. That governance work laid the foundation for a platform that now serves more than 7,200 users across multiple partner organisations.
A port and an airport are very different environments, but they reveal the same principle. You cannot optimise an ecosystem if every participant works from a different version of reality.
Start with the ecosystem, not the platform
The instinct in a digital programme is often to start with the platform. In complex transport environments, the more important work happens earlier. Bringing participants together, understanding what each needs and can contribute, and agreeing ownership, standards, and incentives.
That last point is significant as the costs and benefits of shared operational data are rarely distributed equally, so the commercial model needs to be part of the design. Participants need a clear reason to contribute, trust, and use what is being created.
Cross-border rail shows how this works in practice. Once European operators had agreed a shared standard for short-notice train path requests, we could help SBB replace phone and email coordination across several infrastructure providers with a single digital workflow, delivered within weeks.
AI won’t fix fragmented data
There is considerable potential to use AI to anticipate disruption, optimise schedules and allocate resources dynamically. Over time, we are likely to see more operational decisions move from manual, operator-driven processes towards systems for which people supervise increasingly sophisticated automation.
But an AI system can only optimise using the information it is given.
If operational data is fragmented across organisations, inconsistently defined, or arrives too late, adding AI does not remove the underlying constraint. It risks automating poor decisions on top of it.
The organisations best placed to benefit from AI will be those that first make their data accurate, timely, and trusted across the ecosystem.
Transport’s next gains lie between organisations
Ports and airports have spent decades optimising individual assets, processes, and organisations. Digital technology creates an opportunity to optimise at a different level: the ecosystem itself.
The technology largely exists. The harder work is creating the trust, governance, and a shared operational picture that allows the whole ecosystem to work better together.
Ready to turn shared data into better operations?
Our work with the Port of Milford Haven started with a short, AI-accelerated Discovery to define a proof-of-concept for a port-wide data platform. By combining data strategy and governance with deep engineering expertise, we help transport organisations move from ambition to something they can build, test, and scale.
