Barcelona, May 5th 2026
Digitalisation has become one of the defining themes in logistics and international trade. But beyond platforms and tools, a more fundamental question is emerging: how do professionals actually learn to operate in increasingly complex, data-driven environments? We spoke with Orlando Reveco, Digital Products Manager, about the role of simulation in bridging the gap between knowledge and decision-making.
Q: Digitalisation is everywhere in logistics right now. From your perspective, what is still missing?
I think we’ve made significant progress in terms of access to tools.
Many organisations now have platforms, dashboards, and digital workflows that simply didn’t exist a few years ago. But having access to tools doesn’t necessarily mean that people feel confident using them to make decisions. That’s where I see the gap.
A lot of professionals understand the components of logistics — transport, documentation, costs, compliance — but they haven’t always had the opportunity to work with these elements as part of a single, interconnected system. And that’s what real operations look like.
Q: Why is that so difficult to replicate in a learning environment?
Because complexity is hard to teach in isolation.
Traditional training tends to break things down into manageable pieces, which makes sense from a pedagogical point of view. But in doing so, it often removes the very thing that makes logistics challenging — the interdependencies. In reality, decisions don’t happen in a vacuum. A change in one part of the operation affects everything else: timelines, costs, responsibilities, even risk exposure. If you don’t experience those connections directly, it’s difficult to fully grasp them.
Q: So where does simulation come into play?
Simulation allows you to reintroduce that complexity, but in a controlled way. Instead of talking about an export process, for example, you actually execute it.
You manage documentation, you make decisions about transport, you see how those decisions affect the flow of the operation.What’s interesting is that participants quickly realise that even simple operations are not that simple. There are layers — operational, financial, regulatory — and they all interact.
In a digital environment, especially one that integrates operational workflows with ERP logic and data, those interactions become visible. You’re not just learning what should happen; you’re seeing what does happen when you make a decision.
Q: Does that change how people relate to data?
Very much so.In many organisations, data is available, but it’s not always actionable.
People see dashboards, but they don’t necessarily connect them to the decisions they’re making. In a simulation, data becomes part of the decision process. You’re analysing performance, costs, risks — not in theory, but in relation to what you’ve just done. That creates a different kind of learning. It’s not just about understanding indicators, but about using them to guide your actions.
Q: What tends to surprise participants the most?
Usually, the level of interconnectedness.
Someone might make a decision thinking it’s purely operational — for example, choosing a transport option — and then realise it has implications for cost allocation, timing, or even sustainability metrics. These ripple effects are difficult to appreciate until you see them in context. And once you do, your perspective changes. You start thinking less in terms of isolated tasks and more in terms of systems.
Q: You mentioned sustainability. How does that fit into this kind of environment?
It becomes part of the same decision-making framework.
When you analyse operations digitally, you can incorporate indicators like CO₂ emissions or external costs alongside more traditional metrics. That allows professionals to see sustainability not as a separate objective, but as another dimension of operational performance. Again, the key is that it’s integrated. You’re making decisions and immediately seeing their broader impact.
Q: What does this mean for how we should think about professional development in logistics?
I think we’re moving from a model based on knowledge acquisition to one focused on capability.
It’s no longer enough to understand how a process works in theory. Professionals need to be able to operate within systems that are dynamic, data-driven, and interconnected. Simulation is one way to accelerate that transition, because it creates a space where decisions can be tested, analysed, and refined.
Q: For someone who hasn’t experienced this before, how would you describe the difference?
It’s subtle, but important.
It’s the difference between recognising a process and being able to manage it. Between knowing what should happen and understanding what actually happens when multiple variables interact. Once you’ve worked in that kind of environment, you start to approach problems differently. You ask different questions.
Q: You’ll be exploring this in an upcoming session. What can participants expect?
The idea is to make this approach more tangible.
We’ll walk through how a digital simulation of a logistics operation is structured, how decisions are made within that environment, and how data is used to analyse outcomes. It’s not about presenting a perfect solution, but about giving participants a clearer sense of what it means to operate a supply chain digitally.
Q: And for those who want to go further?
There are structured programmes that build on this methodology in a more comprehensive way — combining simulation, teamwork, and analysis across different types of operations. But I think the first step is simply to experience it. Once you see how these environments work, it becomes much easier to understand their value.
