Mm

... um, generating cash, obviously, in excess of our requirements.

So it's, uh, a deliberation with the board every year with regards to what we do with the surplus, and, you know, one of the preferred routes, of course, is to return to shareholders, and we've done again, uh, this year.

Obviously, a bit more conservative in light of, of the difficult trading conditions but, you know, in all honesty, not really something that's new.

Yeah.

We try and create an aspirational basket for our customers.

We have brands that are trusted, you know, so that attracts customers, too.

And yes, they shop down, but we also, given our spread across the market and even within stores with our price layering, we are able to cater for customers that are just perhaps a bit more price sensitive and cannot buy up.

Even with these breakthroughs, connecting the worlds of science and industry requires more than technical knowledge.

I think it does take a special part of the brain to be able to bridge that fundamental and applied.

The expertise is really critical, and that expertise isn't just the ability to run simulations, it's the ability to translate real problems into simulation language.

That is the hardest problem, is the complexity of real-world operation in industrial environments.

They're messy, they're dynamic, they're unpredictable.

This is not the way we run laboratories.

But it's the way industry operates, so we have to bridge that gap.

To manage that complexity, the program follows a clear step-by-step process to turn intricate industrial challenges into solvable simulations.