1, June 2026
by: Arreoblue
Matt Robertson didn’t set out to work in data, and that’s part of the point. Now leading Digital & Analytics across EMEA and APAC at CBRE, he sits between business users, data teams, and engineering, making sure the work being built actually helps people do their jobs better. In this episode of the Arreoblue podcast, he spoke about how he ended up in data, why domain knowledge still matters more than most people expect, and why the gap between the business and the data team still shows up more often than it should.
Like a lot of people in the industry, Matt didn’t plan a career in data. He started in real estate, working for a data provider in the sector, and gradually found himself getting pulled further into analytics simply because the problems kept appearing. He kept seeing the same patterns: teams manually pulling data together, rebuilding reports, running into the same issues, and spending more time preparing information than actually using it. Getting involved to fix those problems led to building tools, then building products, and eventually moving fully into the data side of the business.
What kept him there wasn’t the technology on its own. It was the combination of understanding the domain and seeing how better data could change how people worked day to day. That mix ended up shaping most of the roles he’s taken on since, and it’s still the part of the job he finds most interesting.
One of the frustrations he mentioned early on was assuming the data would be there when it was needed. Early in his career, he built models expecting the business to supply the information later, only to find the data either didn’t exist or wasn’t in a usable form. It meant going back to the people who owned the process and asking them to surface something they’d never really had to formalise before.
That experience stuck with him, partly because it still happens now. Data projects often start with the idea that the technical solution will unlock value on its own, but in practice the hard part is getting the right data surfaced, owned, and understood by the people creating it. That’s usually where the gap between the business and the data team shows up, and it’s rarely a tooling problem.
Matt’s view is that the gap doesn’t close by expecting everyone to become an expert in everything. Not every business user is going to become a data engineer, and not every engineer needs deep domain knowledge. What tends to work better is having a small number of people who understand both sides well enough to connect them, people who can talk to the business without losing the technical detail, and talk to the data team without losing the context.
Having domain experts who learn the data properly, and data specialists who take the time to understand the business creates a core group that can translate between the two. From there, the message spreads more naturally across the organisation, because people start to see how the work fits together. He also mentioned that communication style matters more than people think. Being direct helps, but so does being honest about what you don’t understand. Saying “I don’t know, explain it to me” usually gets you further than pretending you do.
The conversation also moved onto control versus access, which is something most teams are still working through. Everyone wants better governed data, but they also want the freedom to explore it, and those two things don’t always sit comfortably together. Putting structure around how data is created can be the hardest part, especially when people have been working in their own ways for years and don’t immediately see the benefit of changing.
Change tends to land better when people can see what they’re working towards. Even without a full proof of concept, showing the end result helps teams understand why the effort is worth it. On the other side, locking everything down too tightly creates a different problem, because business users still need somewhere they can test ideas without affecting the core platform.
Done properly, that kind of sandbox doesn’t weaken governance; it usually makes the platform stronger. As Matt put it, if people are exploring the data, they’re also helping test it.
When the conversation turned to careers in data, Matt came back to something that’s shaped his own path. The people who tend to be most effective are often the ones who understand the business as well as the technology, even if they didn’t start out that way. You don’t have to be an expert in either, but having an interest in the domain makes the work more useful, and usually more interesting as well.
Someone who understands what the business is trying to achieve will ask better questions, and better questions tend to lead to better insight. It also makes the work feel less abstract, which helps more than people expect, especially in large organisations where it’s easy for data to become something that feels disconnected from what people are actually doing.
Later in the discussion, Matt talked about his book; Data on Your Plate, written to help people who don’t see themselves as data specialists understand how they fit into the data lifecycle. The idea behind it is simple. Data isn’t something happening somewhere else; it’s something everyone is part of, whether they realise it or not. People create it, change it, rely on it, question it, and act on it every day, even if they wouldn’t describe themselves as working in data.
The more comfortable people are with that, the easier it is to use data well and to have sensible conversations about how it should be managed. In most organisations, that’s still the part people are working through now, and it’s often where the biggest improvements come from.
If any of this sounds familiar, it’s a conversation we’re having with a lot of teams at the moment. We are always happy to talk through where you are and what the next step looks like.
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