The career path to the built environment isn’t always linear, as Head of RLB Digital, Michelle Zompi, explains to Digital Construction Plus.
As well as talking about her career journey, she explains how the management of data is essential today and how she advocates for a no code/low code solutions approach first rather than looking for the latest tech solution.
You began your career in policing. How did that lead you to construction?
I studied law, but realised I wasn’t keen on the advocacy side. What I loved was research and analysis, which led me into intelligence work – at the time, police forces were just beginning to bring in intelligence analysts. That’s where I discovered my passion for data: pulling together information from all sorts of disparate sources and using it not just to respond to crime, but to anticipate it.
And that’s when you moved into the built environment?
One of my first major projects was with Network Rail, helping embed new information methodologies. That led to work with Amec Foster Wheeler on development consent orders. Those processes generate huge amounts of data under tight deadlines, so I helped design an environmental impact assessment process that mapped and connected information to make it accessible and auditable. They liked the approach and asked me to join them – that’s when I became fully immersed in digital construction.
What does RLB Digital offer?
We’re a subsidiary of RLB and we have three core strands. The first is information management – helping clients define their requirements, understand what they need, and set up the right processes to meet those needs.
The second is development, which focuses on low-code and no-code solutions. You don’t always need expensive software to solve your problems – often, it’s about connecting and automating what you already have. Using tools like Microsoft Power Apps or Power BI, we can streamline processes quickly and affordably.
The third is technology strategy – helping clients make informed decisions about their tech stack, especially when transitioning between systems. We encourage them to think beyond specific software brands: understand your information needs first, and let your technology facilitate them. That way, you’re not locked in and can adapt as tech evolves.
We’re doing a lot of work across healthcare, education and increasingly, data centres, where owners are under pressure to improve how they manage and use their asset information.
What kinds of AI applications are emerging?
There’s huge variety. You might build an AI agent that queries an organisation’s internal data – something as simple as an HR assistant that answers policy questions or as complex as analysing asset performance data.
The key is bringing together information that’s currently scattered across multiple platforms – asset databases, FM systems, spreadsheets – and making sense of it.
We’re also seeing organisations wanting to reclaim control of their data. Many are moving away from proprietary software because they don’t want to be dependent on vendors who effectively ‘own’ their information. They want their data stored in their own environment so they can analyse and use it freely.
How big a challenge is interoperability in all this?
It’s a major issue, and one that’s really coming to the fore. A lot of organisations are realising their data is effectively locked inside proprietary software platforms. They want to regain control, to have their information in their own space, where they can ringfence it, interrogate it and use it across different systems.
True interoperability means being able to move data freely as technology evolves, without being tied to a single vendor. To achieve that, my advice is always to start with the fundamentals: understand what information you’ve got, what you actually need, and where it needs to flow to and from. Once you’ve mapped that, you can build processes that allow flexibility and consistency, rather than letting the software dictate how you work.
We also encourage clients to take a low-code or no-code approach wherever possible. Often, the tools they already have can be connected and configured to achieve what’s needed, and when technology inevitably changes, your systems and information can adapt with it.
Are there particular tools or developments making the biggest impact?
It’s less about specific software and more about avoiding overreliance on any one platform. Things change so fast.
Of course, AI language models like ChatGPT have had a massive influence. Even simple uses – like asking an internal AI assistant to summarise all the meetings and emails you missed while on holiday – can save hours of admin. That’s a tangible productivity gain.
Then there’s the rise of AI agents – dedicated digital assistants focused on specific functions such as finance, HR or project management. The next step is ‘agents of agents’, where one master agent connects across domains to provide integrated insights. That’s where we’re heading.
And all of this loops back to fundamentals: if your data and processes aren’t accurate or consistent, your AI will amplify those errors. That’s as true in construction today as it was in policing 20 years ago.
This is an abridged version of an article that first appeared in Digital Construction Plus.
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