Meet the team behind the tech: Tim Norman

Welcome to the first of our new series where we will be showcasing the team behind Synergy technology. First up we have our Head of Product, Tim Norman so let’s get started!

What does your role entail in a nutshell?

My job is to make sure Synergy has the functionality our customers need to handle claims exceptionally well. A big part of that is listening – to customer feedback, market research, workshops, our own teams and what’s happening across the wider industry – and turning all of that into a product roadmap that keeps us moving forward.

From there, I’m involved in designing features and working closely with our development team to get them ready for release. Once something is live, the job doesn’t stop there either. I work with our Client Success team to make sure customers understand what’s available and, more importantly, how to get the most value from it. So, in short: understand the problems, work out what we should build, turn that into something the development team can deliver, then make sure it actually creates the value we intended.

What does a normal work day look like for you?

It’s a cliché, but no two days are really the same.

I do tend to start every morning in exactly the same way through: with a nice, well-defined list of everything I’m going to get done that day. I then normally finish the day having completed about 50% of it, because the other half has been taken up helping customers or members of the team with whatever has cropped up!

On any given day I could be designing and specifying new features, answering questions from developers about how something should work, signing off new functionality, or speaking to clients about their initiatives and how Synergy can support them. Then there are the things that sit around the edges of the product but are just as important – onboarding, proposals, and working with third parties on integrations that can make the platform stronger. More recently, a lot of my time has also gone into AI – both looking at how it can benefit our customers and thinking about how we can use it to improve our own ways of working.

What’s something about claims you understand differently now than when you started?

I think I naively assumed insurance would work like a lot of other industries: you define a process in fairly black-and-white terms, account for a few exceptions, and then automate it. Claims – particularly household claims – quickly taught me otherwise. They come in all different shapes and sizes, and there are so many variables that purely deterministic, rules-based automation will only get you so far. That’s one of the reasons I find the development of AI agents so interesting. Rather than needing every possible scenario defined in advance, they give us a way of responding to more of that variation and uncertainty. For us, that feels like an important part of getting closer to genuine straight-through processing.

What’s a piece of software you think is brilliantly designed, and why?

Google Maps.

There’s an enormous amount of messy, live information sitting behind something that feels incredibly simple to use. Traffic levels, road closures, historic journey data and countless other variables all get distilled down into: follow this route.

I particularly like the predictive side of it. You can ask, “If I leave at 8am tomorrow, how long will this journey take?” and get a useful answer based on patterns and probabilities rather than a simple fixed rule.

That idea really resonates with me from a product perspective. The technology underneath can be incredibly sophisticated, but the user shouldn’t have to experience that complexity. They should just get a clear answer that helps them make a better decision.

What were you doing before this job/company, and what brought you here?

My background was originally in business process improvement and change management, but with every passing year that became more and more intertwined with technology. Over time I found myself gravitating towards the technology side. I’d seen how much more effectively you could solve problems when the people who understood the process and the people building the technology worked directly together.

I’ve also always been a fan of the “fail fast, learn fast” mentality. I’d much rather get something into people’s hands that solves 80% of a problem, learn from how it’s actually used, and then improve the final 20%, rather than spend endless hours in workshops trying to predict every possible requirement upfront.

Synergy itself actually started as technology we were building internally for our parent company. Covid, combined with a great opportunity to work with the AA, gave us the chance to branch out and become a software vendor in our own right.That was really exciting to me. Suddenly we had the opportunity to get our technology in front of more organisations, learn about different parts of the insurance industry and evolve the platform around a much broader range of needs.

It helps that we’ve also got an exceptional team. Everyone takes genuine ownership of what they do, and there’s a huge amount of trust that people will give 100% and support each other when it matters.

What’s the hardest problem you’ve cracked this year, and how did you get there?

One of the hardest problems we’ve been working through hasn’t actually been building AI into the platform – it’s been helping customers feel confident enough to use it. There’s understandably a lot of nervousness around AI in insurance. After all, this is an industry built around understanding and managing risk. Two of the biggest concerns we hear are accuracy and making sure customers continue to be treated fairly. Because of that, our thinking has shifted from simply asking, “Where can we add AI?” to, “How can we help customers introduce AI with the lowest possible risk?”

One way we’ve approached that is through what we call “Draft Actions“.

The AI can identify what it thinks needs to happen next and prepare the relevant action, but instead of immediately carrying it out, it presents it as a draft for someone in the claims team to review. That gives teams the opportunity to validate the AI’s decisions while we collect confidence scores in the background and monitor the changes people make before an action is approved.

Over time, if the data shows that the AI is consistently making the right decisions, customers can progressively move those actions towards full automation. For me, that’s the important bit. Successful AI adoption isn’t necessarily about jumping from manual processing straight to full autonomy. It’s about giving people a safe way to build trust in the technology first.

What is the one thing you wish people knew when looking for claims software?

I think too much focus can go into the “day one” implementation. Obviously it matters that your new platform can deliver what you need when you launch, but the best organisations I see are constantly reviewing their processes and customer experiences and looking for ways to improve them. So I think an equally important question is: how easy will this be to change on day 100, day 500 or three years from now?

If every process improvement requires a development request, a project plan and a place in an external supplier’s roadmap, you can very quickly become constrained by the technology you’ve bought. That’s something I’m particularly proud of with Synergy. We’ve put a lot of effort into self-service configuration tools that allow workflows to be remodelled and refined without needing traditional software development. Our automation engine, for example, lets users build their own workflows, plug in business rules and define the actions they want the platform to take. Some clients upskill their own teams to make those improvements themselves; others ask us to do it for them. Either way, the important thing is that your platform can evolve at the same pace as your operation.

What are you reading, listening to or watching at the moment?

Between work and family life, I don’t get nearly as much time for this as I’d like! Saying that, I did recently re-watch the Alien films. Rewatching Alien 3 and seeing how some of the CGI has aged is probably a useful warning for anyone working with emerging technology: today’s cutting-edge can become tomorrow’s “what were they thinking?” Hopefully nobody is saying the same thing about our implementation of AI in 20 years!

Where would we be most likely to find you on a weekend?

On the side of a football pitch, coaching my son’s team. Although “coaching” can sometimes feel like a generous description – a fair amount of it is trying to convince a group of seven and eight-year-olds that they can’t all be the striker.