Ruth Muller grew up in a Māori community of about 200 people at the very top of New Zealand. It was a place, she says, where collaboration wasn’t a management concept; it was just how things worked. That upbringing gave her a deep instinct for difference as a positive thing, and a belief that the best thinking happens when people with genuinely different perspectives are in the room together.
She carried that into a 25-year career in corporate R&D. Sixteen of those years were at Unilever, where she moved from bench scientist to global R&D operations based in the Germany, before taking on senior roles at Arnott’s and then Suntory Oceania.
Across those roles, she watched large companies try to build in-house, run up against the limits of that model, and slowly start to look outside. We talked with her about what that shift actually requires, what startups consistently get wrong when they approach corporate R&D, and why she believes the future belongs to companies that are better at orchestrating ecosystems than at owning capabilities.
You spent 16 years at Unilever before moving through Arnott’s and into Suntory Oceania. Looking back, what did those years inside a large global FMCG company teach you about how R&D actually works at scale?
The resources at that scale are amazing; I don’t just mean the dollars for research, or the equipment and labs, but the depth of people. The level of scientific capability in Unilever’s Netherlands R&D centre, or in Tokyo at Suntory — that’s genuinely world class.
But one of the key things I learned was that R&D isn’t just about invention. It’s also about commercial execution. There are always choices and priorities to be made, and a lot of the most successful innovation is actually the incremental rather than the breakthrough. The tension between low-risk incremental projects and high-risk transformational ones is constant.
A useful lens: how new is the consumer proposition versus how novel is the technology? The Tokyo team at Suntory developed sweetness technology that went into an existing product — you wouldn’t even notice it except that it tastes much better. The technology was advanced, but the consumer proposition wasn’t disrupted. That’s an example of creating sustained value in a way that’s actually quite achievable. Whereas something with a genuinely unique proposition and amazing technology might be small and niche for a long time, because you have to change consumer behaviour to get there.
“Breakthrough, real breakthrough, is pretty rare in consumer goods. And often, the most exciting innovation isn’t necessarily going to be the most commercially successful — at least not in the short run.”
Large companies have historically tried to build innovation capability in-house. You’ve lived through different versions of that model. Where does it work, and where does it break down?
Big companies do some things very well — maintaining high quality standards, keeping regulatory compliance in place. That lends itself to incremental innovation and line extensions, where the opportunity is quite straightforward and defined.
But it doesn’t work so well when there’s a need for experimentation and iteration. We’re set up for high throughput, high volumes, and predictability. Not for uncertainty. Big companies aren’t built for risk the way startups are — you’ve got high hurdle rates, high volume requirements. Making small runs and small products is genuinely hard to justify.
If you put something in market and it needs a bit of iteration, there might not be the patience to wait for that. It might be: okay, let’s move on to the next thing. So ideas can get killed too early before they have a chance to prove themselves.
You’ve spent the better part of your career on the receiving end of external pitches. What do startups most commonly misunderstand about how corporate R&D makes decisions?
Startups move so fast, and that’s all they’re thinking about. They’ve got this founder’s view where they’re living the problem night and day. So if they go to a corporate and don’t hear back for three months, they assume there’s no interest. But three months is not that long in corporate land when you’ve got heaps of other priorities. In the startup’s mind, three weeks would already be a long time.
The other thing I see is that in my companies, everything is consumer-centric. It’s about whether the consumer proposition is genuinely compelling. And the level it needs to be isn’t just I like that. It needs to be: would I change my behaviour? Would I incorporate this into my repertoire? There needs to be a genuine pain point being solved. And when you have to create a new habit rather than replace an existing one, that can be really expensive.
Corporate people are also thinking through the commercial lens from the start — feasibility, viability, evidence of demand. Rate of sale in one store can be a more relevant data point than the overall size of the business. It demonstrates the potential without requiring the startup to already be at scale.
“If you’ve got like 20 problems, and a startup is solving number 15 — that might be important, but it’s probably not the first thing I’m going to jump on. Figure out what their number two is. If you go and solve their number two, they might be keen to talk to you about number 15 as well.”
You mentioned that the future of R&D is really about building an ecosystem rather than an internal capability. What does that actually look like in practice?
I think the future of R&D is more about orchestration rather than ownership. It starts with: what are the outputs the business needs? The strategic stuff — understanding where to play, what the consumer needs are — that needs to be defined internally. But once you’ve figured out where to play, you ask: what’s the best source for each of the capabilities we need? Is it internal teams? Startups? Universities? Consultants? Fractional experts? Ultimately it’s going to be a combination.
I think the strategy and consumer understanding need to stay in-house. You need people with the instincts to say yes, that’s right, that doesn’t fit our consumer. But then you access external partners for specialist technologies or capabilities, and you build a flexible capability rather than fixed internal headcount. The success of that model depends on openness and integration rather than hierarchy — and it requires R&D leaders to genuinely increase their speed and risk tolerance, which for many organisations is the harder shift.
The Hive in the Netherlands is a good example of what this looks like in practice. They’re right in the middle of the ecosystem: universities, startups, open buildings where people can come in and work. If a startup is using your lab space and your office, you’re learning from their presence and they’re learning from yours. The mindsets rub off on each other.
Can you think of a specific collaboration that worked the way it should? What made it work?
A clear shared purpose, everyone aligned on what problem you’re solving. Clarity on the deliverables and decision rights. And a low-ego working environment where people have the psychological safety to surface ideas without being judged, because sometimes the idea that sounds stupid is the one that gets taken to a completely different level — somewhere neither party would have gone alone.
We had a situation once, an internal collaboration with a global team and a supplier, where we couldn’t get the commercial side to work. So we just locked ourselves in their lab for two or three days and kept going at it. And they figured it out. They never would have conceived of solving it that way if they hadn’t been in the room together. Having the commercial and technical thinking in the room together, right from the start, made all the difference.
Where do you see corporate R&D heading in the next five years?
First, I think it’s really important to get sharp on what the commercial focus is, and then pair that with increased operational discipline. Not process for its own sake, but the discipline of deciding what you don’t do. Looking at the outputs you need to deliver and asking: is there a way of rethinking how we do this with an ecosystem mindset and digital tools, rather than just incrementally improving the current approach?
Using AI a lot more for prediction, modeling, and decision-making. I think often when people think of AI in R&D, they immediately jump to: let’s get AI to develop the product. But that’s probably the last thing we should be thinking about. If you have a human with really good technical knowledge, consumer knowledge, taste knowledge — and you put them in a lab for an afternoon to do some prototyping — it’s going to be a real long time before any kind of agent comes close to that.
So it’s really about looking at what humans do well and what digital tools do well, and how they work together. The combination of human cognitive diversity, having different thinkers in the room challenging each other, and the computational power of AI behind that, working together in an ecosystem. It all comes back to ecosystem. That’s the number one word for me right now.
“The people that win will be the ones that are really clear on what they want and understand what should be internal and where they should find the rest.”
What outside of R&D has most shaped how you lead?
I grew up in a Maori village,where if someone dies and there is a funeral – the whole community comes together on the marae and they bring whatever they have. I think that informed who I am. It’s very much about community – what do you have to bring – to benefit the greater good, which is collaboration, basically.
And my parents believed that difference was a positive thing. Making space for difference. That could be cultural differences or different ways of thinking. I’ve always just been really positive about differences. I get excited about learning from other people.
Finding out I was dyslexic and had ADHD at 42 was a bit of a shock, but it explained everything. I talk about it a lot because I think there’s still a lot of stigma in the world. The world needs different thinkers working together, being compassionate and empathetic about how other people function. It’s not about judging each other. It’s about how do we work together. And creativity required different thinking.
But honestly, I’m a learner. I’m always reading, always doing something in that space. I love complexity and ambiguity and pace; I get inspired by founders and people with huge ambition and huge problems to solve. It’s ironic, I suppose. I technically have a learning disability. But I think I’m the biggest learner of all.
“I technically have a learning disability. But I think I’m the biggest learner of all.”
