With more than 20 years’ experience across data, insight and consulting, Tim has spent his career helping businesses make the most of one of their greatest assets: data.

Having recently joined us as Chief Data Officer, Tim shares his career journey, the importance of strengthening a data-driven culture, how AI is changing the way businesses think about data, and what has stood out to him during his first few months at THG.

Can you share a bit about your career journey up until now and how you got into the industry?

Before recently joining THG, I started my career at Dunnhumby, the company behind Tesco Clubcard. I’d say I fell into it as a graduate and accidentally discovered that I really enjoyed the core principle of the business, which was essentially - how do you use data to deliver a better experience for customers?

It took me a while to figure that out fully, but I ended up really believing in it. I spent eleven years there and worked across Europe - helping set up the business in the Czech Republic, running the business in Hungary and then in Poland. What it made me realise was that I really enjoyed being close to the doing - owning decisions, facing into difficult questions and being part of the business itself rather than sitting outside of it. 

My wife’s job brought us to Manchester and the opportunity at Co-op came up at the right time, and I ended up leading data and insight across the group. After that, I moved into consulting for a while. It was brilliant in a lot of ways - great people and culture, interesting work, but I realised it wasn’t for me because I missed the ownership.  

Then this opportunity at THG came up and it felt like the kind of role that would get me back into owning something I really cared about.

What are some of the key practices needed to embed a stronger data-driven culture across an organisation?

It’s very easy to get excited about AI and all the things it could potentially do. But none of it works properly unless the foundations underneath it is right.

For example, we can get excited about using AI to recommend products to customers, but if the product data isn’t labelled properly, if ingredients are wrong, products are named inconsistently or categorised badly - then it won’t work properly.

One of THG’s greatest strengths is that everybody wants to use data. There’s a real enthusiasm for it across the business and people genuinely want to create value from it. But that can also become a weakness because lots of people can end up trying to solve the same problem in different ways. You can end up with different versions of the same metric or different interpretations of the same thing. Then you spend more time debating which version is right rather than focusing on what the data is actually telling you.

So, the challenge is finding the right balance, encouraging innovation and creativity while also building the right foundations and consistency underneath it. That said, THG is already advanced when it comes to people’s access to data and willingness to use AI and large language models. There’s a lot of good here already.

How difficult is it to keep pace with changing customer expectations?

It’s about investing at the right time. You can move too early and build something customers aren’t ready for yet. Or you can move too slowly and fall behind. The real question is deciding where you want to be ahead of the curve and where you don’t necessarily need to be first.

And that’s where foundations become really important. If your foundations are shaky, it becomes much harder to move quickly. 

How is AI changing the way businesses should think about data?

Data is basically the fuel for AI systems. If your data is poorly labelled or badly structured, then your AI won’t work properly. It’s the same as putting bad fuel into a car. The reason large language models have evolved so quickly is because there’s a huge amount of structured language data available for them to learn from.

For businesses, the companies that will succeed with AI are the ones with strong, well-structured data foundations. If your data is organised well, labelled properly and understood clearly, then AI becomes much more powerful.

What excites you most about AI?

 The pace of change it enables. Throughout my career, a lot of progress has been driven by advances in hardware and infrastructure. What’s exciting about AI is how quickly it can accelerate software development and iteration as well. The fun part is getting something into market and seeing how it performs. If AI helps reduce the time it takes to get from idea to reality, that’s incredibly exciting. Instead of taking nine months to build something, maybe you can test and learn within weeks.

What have been your biggest takeaways from your first few months at THG?

Culturally, the business is fascinating. It genuinely feels very outcome-focused and not particularly hierarchical. If you’ve got something valuable to add, people want to hear it. There’s also a huge enthusiasm for data across the business, which is great for someone in my role because people genuinely want the data function to succeed. 

The business is also very comfortable with change. Change feels normal at THG, which is a real strength. There’s a huge amount of opportunity here. Everywhere I look, I can see things where relatively small changes could make a big difference.