We’re back! This is your monthly tune into our Behind the Brand series, blog style. Your chance to learn more about our TROers behind the magic, their own stories and passions and what’s on their radar.
We spoke to Andrew Creasey, Senior Systems & Data Analyst. He’s been a part of our team for 13 years.
My role at TRO is pretty varied, which is one of the things I enjoy most about it. While my focus is now very much on systems and data, working in experiential means no two days are ever quite the same. I spend a lot of time building and maintaining business‑critical systems and creating dashboards that help teams and clients understand what’s really going on, rather than just looking at raw data.
That said, the role isn’t limited to analytics. Depending on the project, it can range from setting up and supporting equipment like tablets, iPads and laptops, all the way through to building or “vibe‑coding” a small interactive game for a live event. Having worked my way up from first‑line support over the years, I’ve got a broad understanding of how everything fits together, which really helps when problems need solving quickly and practically.
Outside of work, I like doing things that get me away from a screen. I’m generally up for a challenge and enjoy anything that breaks routine. Last year I took part in Tough Mudder, which was a good way to switch off and focus on something completely different.
That balance helps at work more than anything else. Experiential can be demanding, so having interests outside of tech makes it easier to stay level‑headed when things get busy. It’s probably why I tend to favour straightforward, practical solutions in my role. When I’m working with data or systems, the aim is always to keep things simple, useful and easy for others to work with, especially when time or pressure is involved.
I don’t really have a set list of people I follow. I tend to get more value from broader data, BI and systems communities where people share practical ideas and real‑world examples of what they’re working on. Seeing how others approach similar problems, especially around reporting and system reliability, is usually more useful than keeping up with trends for the sake of it.
I’m particularly interested in content that focuses on making data clearer and easier to use, and systems that are simple, robust and easy to maintain. That kind of thinking strongly influences how I approach my own work, especially when building dashboards or tools that need to be understood quickly and used day‑to‑day.
With an unlimited budget, I’d be most interested in technology that becomes almost invisible to the end user. Not futuristic for the sake of it, but systems that quietly do something smart in the background while the experience itself stays simple and reliable.
That might mean platforms that respond seamlessly to what’s happening in real time without needing constant intervention, or systems that anticipate issues before they become a problem. For me, the most successful experiences are the ones where the technology just works and doesn’t draw attention to itself. When everything feels smooth and intuitive, that’s usually because there’s a well‑thought‑out system underneath doing its job properly.
I’m quite pragmatic when it comes to AI. It can be incredibly useful if it’s applied in the right situations, but it’s not something you can rely on blindly, especially when issues like hallucinations or inaccurate outputs can creep in. For me, it works best as a support tool rather than a replacement for proper understanding or oversight.
One area I’ve found particularly useful is vibe coding, which has made it much quicker to prototype systems or ideas at pace. It’s a practical way to explore concepts, test workflows, or stand something up quickly without overengineering early on. Used sensibly, AI can help speed things up and remove friction, while still keeping systems simple, reliable and easy to work with, which is what really matters in live environments.
The variety. No two projects are the same, and the tech is always being used in different ways. One project might be heavily focused on data or systems, while another involves building tools or platforms that support teams and clients in very different ways.
That mix means you’re constantly solving different problems and thinking about how systems can be used in practical, real‑world ways. It keeps things interesting without feeling repetitive.
