Why Most Innovation Fails: On Risk, Sponsorship & AI Hype with Dr. Nicola Millard, BT

Why do most innovation projects quietly fail? What actually makes people adopt something new at work? Dr. Nicola Millard, Principal Innovation Partner at BT, has spent 35 years finding out, from building the UK's earliest workplace chatbots to running home-working trials before "hybrid work" was a phrase anyone used.

In this episode of the Innovation Brief podcast, Nicola shares the real reasons innovation succeeds or fails within large organisations, and why technology is almost never the reason.

We cover:

• Why most innovation projects fail, and why that's not always a bad thing
• The one factor that can kill a project overnight: losing your senior sponsor
• Her "useful, usable, used" framework - and why peer pressure decides adoption more than leadership buy-in
• The Inverness Experiment: BT's 1990s home-working pilot, decades before the pandemic made it universal
• Why 82% of UK managers are "accidental managers", and what that means for hybrid work
• AI hype vs. reality: work slop, vibe coding, skill atrophy, and her theory that we're in a "42 moment" with generative AI

Nicola Millard is Principal Innovation Partner at BT, working with corporate and public-sector clients on innovation strategy, and partners with researchers at Cambridge, Bristol, MIT, and Stanford. Connect with her on LinkedIn.

🎧 Subscribe to the Innovation Brief for more conversations on innovation, technology, and the future of work. Available on Spotify, Apple Podcasts and YouTube Podcasts. Also available on Substack.

Contact Us

Thanks for tuning in to the Innovation Brief, the podcast by Metta for the people building, funding, and governing innovation - inside corporates, governments, and ecosystems across the globe. Bi-weekly conversations with the leaders shaping the future.

Find out more:
Website: https://www.innovationbrief.co

Email: hello@innovationbrief.co 

Follow us on social media:
Connect on LinkedIn: www.linkedin.com/company/innovation-brief/

Subscribe on Substack: https://innovationbrief.substack.com/

The Innovation Brief is produced by Metta. Metta focuses on research into innovation & entrepreneurship, programme design and delivery, and ecosystem building for more sustainable and resilient futures.

Learn more about Metta: https://www.metta.partners

Follow us on LinkedIn: https://www.linkedin.com/company/mettatalks/ 

Follow us on Instagram: ht...

Transcript

SPEAKER_01 0:03

Welcome to the Innovation Brief, the podcast where we have real conversations with leaders driving meaningful change across diverse sectors. Each episode, we bring you insights from innovators who are shaping the future through bold ideas, fresh perspectives, and transformative work. Today, we're joined by Dr. Nicola Millard, principal innovation partner at BT, the UK's largest telecoms provider, part of the country's critical national infrastructure, and a company that I know pretty well from a few years that I spent working there towards the beginning of my career. Nicola has been labelled quite appropriately, I think, as human caffeine. She describes herself as half social scientist and half technologist. In her work at BT, she uses techniques from a wide range of disciplines to generate data, provocations, and stories, which create conversations from the boardroom all the way to the front line. Nicola is an award-winning presenter. She's a TEDx Talk veteran, and she has made radio and TV appearances around the world. Whether you're an innovation leader, technologist, or someone trying to make future thinking land inside a large organization, I think you'll find this to be a really interesting and entertaining conversation. So let's dive in. Welcome, Nicola. Really glad to have you here. Thank you, Matt, for that lovely introduction. You're very welcome. By my count, I think you've spent more than 35 years inside BT.

SPEAKER_00 1:27

I've lost count.

SPEAKER_01 1:28

Is that right? Yeah.

SPEAKER_00 1:29

I was only six when I started. I hate the idea.

SPEAKER_01 1:32

Yeah, exactly.

SPEAKER_00 1:33

It's been a while.

SPEAKER_01 1:34

It's obviously one of Britain's largest corporations, a real national institution, I might say. But your title, principal innovation partner, doesn't quite sound like a conventional corporate sounding role. So what does that actually involve? Maybe you could tell us a little bit about it.

SPEAKER_00 1:51

I don't think I've ever been conventionally corporate, to be perfectly honest. So uh so my current role is a weird one. So obviously, innovation's in my job title. Largely my job, uh so I work for BT business. So with a bit of BT that works with um with uh largely large corporates and public sector customers, mostly in the UK, but sometimes uh outside as well. So my focus really is to innovate with and for those customers. So um so I'm I'm working with uh across multiple sectors, to be perfectly honest. So whether it's retail or banking or insurance or indeed as a public sector as well. So that's that's fun for a start. I did also used to be a futurologist. That was my official job title, which always came with the same question, which was do you have a crystal ball? The answer to that question was yes, I do, um, because someone very kindly gave me one. Sadly, I saw no future in it, which is why I'm now a principal innovation partner rather than a futurologist. But um, but I mean the role largely is to take a lot of the um obviously BT innovates itself. So we do a lot of innovation internally. We're not very good at talking about it or even recognising that it's innovation sometimes. My role is to scout around and see what's going on innovatively within BT, but also we have a lovely set of university partners as well that we work with. And obviously, I am part academic as well. So um, so whether it's working with Cambridge or Bristol or uh London Business School or MIT, uh Stanford, all those fabulous universities, we're sort of tapping into a lot of the brilliant brains there as well, to try and sort of say, you know, what are the challenges of work at the moment? What are the challenges that our business customers are are addressing? I am also a slightly weird part of the innovation team in that you would imagine, as as with um, it's BT. So there's a lot of people that are very interested in the network, rightly so, because that's our core business. We've got a lot of technologists as well, but I always say I'm half a technologist, and I'm never terribly sure which half, but um, whichever half isn't the technologist, the rest of me is a psychologist. So I always claim I look at the most disruptive part of innovation, which isn't the technology, it's us. Because frankly, if we don't embrace it and use it, it's a tiny bit rubbish, to be perfectly honest. So um, so that's the component that's often overlooked uh because people get very distracted about the shiny new stuff and they forget that people actually have to use some of these things. So I'm there to try and sort of look at that people aspect to make sure that we don't get carried away, that we do need to bring people along with us, because if we don't, innovation isn't is not going to work.

SPEAKER_01 4:23

So, what does that look like in in practice then, this idea of people-centered innovation?

SPEAKER_00 4:27

So, I mean, I learned I'm obviously you you you alluded to the fact I joined BT very, very early uh in my obviously very very early in my life, obviously when I was six, but um, I mean I learned very early on that um you can't innovate without people. My first project actually in BT was um building chatbots for contact centres. So um, so and and that was part of our research division. And we did a trial very early on in the AI excitement of the 90s, because we've had AI excitement before, believe it or not. Um we had a trial up in in Thurso, which is um I always say if people go, Where's Thurzo? I go, keep driving north, and when you fall into the sea, you'll find Thurzo. So a very long way up, we had a contact center up there, and we actually trialled um neural networks up then. And we did a couple of trials, and I think the people aspect came out really strongly in those trials because the first trial we very much involved people. We were doing effectively network diagnostics, but with non-network people. So, what we were trying to do was to get some of the information that were in our engineers' brains into the mouths of the people doing the customer service who who were very good with customers but didn't really, they weren't engineers. So, what we're trying to do was to transfer a lot of the expertise in the engineers' brains, basically, put that on the desktop of the advisors. And we involved both the engineers and the advisors on that because frankly, back in the 90s, we did not have data lakes, everything was uh very manual. So I ended up uh interviewing loads of people about how they did their job effectively, and then we trialed it, and actually it was a very successful trial. The only trouble being was it was very expensive because the data bit was the bit that it worked on and it still does. AI doesn't work by magic, oddly enough. It works by data, and we had to maintain the data, and the maintaining the data costs more than building the system, so you can understand why that first trial worked. We then did another trial off the back of that where we didn't really work with people because we got a lot of information in the first place, and we trialed another another version of it slightly further south. Um, so we we were still in Scotland, but uh we moved down to not quite the edge of the country. But um, we did another trial, we didn't talk to people, and oddly enough, we put it on a desktop and they didn't use it. So instantly it was kind of okay. We do understand that we need to work very carefully with people to do these things because otherwise they won't know what they do, they won't figure out that it will help them to do their job, they don't feel the sense of ownership, they don't trust it. All of those things are the fundamental things that we see now, still in the many, many years of innovation I've done, most of which have failed, and it has to be said, which is one of the things around innovation, but uh it it generally doesn't succeed, but you learn from those things. And I think we learned quite rapidly that if we we wanted a successful implementation of anything, particularly in things like contact centres, which has been a theme across my career, you do need to involve people.

SPEAKER_01 7:09

So perhaps you could tell us a bit more about some of those blockers that you have come up against as an innovation leader inside a large organization. Maybe there's some lessons you could share with us uh about how you've overcome some of those hurdles.

SPEAKER_00 7:23

Yeah, there are many. I mean, obviously, I I mentioned the fact that we fail quite a lot in innovation. And to be honest, failure in most organisations would be something that's punished, you know. It's kind of, oh my god, that's really bad. You failed, or no, right? We'll sack you, or you know, we'll give you a terrible appraisal. But actually, in innovation, it's weird because actually failure is something that's it's not good. I mean, you never want to fail, but you do want to learn. So I think um that the first thing is that obviously leaders typically are fairly uncomfortable when you go, this is probably gonna fail, but we're gonna try it anyway, but we're gonna learn a lot. Um instantly, they're kind of backing off and going, oh, we're not sure about this. So I think that whole capacity for risk and that that possibility of failure is always there with innovation. Now, obviously, I keep saying you don't tend to innovate on things that are inherently risky in the first place. So you don't want to do brand new innovation on something that's safety critical, for example. Um, you definitely want to be testing something before it goes into a safety critical area. But um, but that that sort of appetite for risk and the you know the possibility not to punish failure is is big. The other thing I think, and I was lucky, most of the initiatives internally I've worked with in BT, because obviously I do most external, uh most things externally now, but internally with MBT, the the key was actually having a senior champion. So I mean, particularly if you want to involve people and contact centre people, especially because even my PhD was on contact centres, I'm very obsessed with them. They're brilliant places, to be honest, because they're very human, but there's lots of technology involved. But um, but if you want to interview someone in a contact center, you have to build a business case to take them off the contacts because you know that's what they're employed to do. And and you can see pounds, shillings, and pence uh actually associated with that. So you need senior buy-in to even get permission to talk to people. So um, so you know, you need a senior sponsor. The risk then is if you're part way through the innovation and the senior sponsor then leaves, um, which we has happened on so many occasions, you get someone new coming in who's going, What's what's going on? And you you then have to kind of start again. So I think senior sponsorship and buy-in is is absolutely critical to get things right. And then, of course, I did run a culture change team for a while, and that seems a bit bizarre, but I kind of realised that innovation is more about culture change than sometimes the the technology. So a lot of it's around, as I said, you know, getting people's hearts and minds on board, actually telling them about you know what this innovation is and how it might help them. And actually in my PhD, I did a whole framework around the psychology of innovation, of course, of change and motivation. I took motivation as the key principle because I thought, oh, well, if we can motivate people better, and not using the traditional ways of motivation, which is usually carrot and stick, but actually the real motivation, intrinsic motivation. How do we actually sort of embed technology and intrinsic motivation together? And we came up with a framework that was very complicated, but we boiled it down to three U's, effectively. So you have to ask three questions. Is it useful? Now, most technology is, to be perfectly honest. It it does what it says on the tin, but it's the perception that it's useful that's the important thing. So, how do you actually convince people that this is something that will actually you know change the way they do their job? But often people are very comfortable in the way that they do their job. So changing the way they do their job is instantly, oh, I don't know if I want to do that. So you have to kind of work with them to say, actually, is this genuinely gonna change the way you do your job in useful ways, not making the job harder? Then, of course, the second you is usability. Um, use is it usable? I mean, I was in human factors and our usability division for probably about 10 years in BT. So all of those principles are far easier because they're well documented. You know, just make sure that you design it well is the bottom line there. So don't design it to make it hard or complicated. Uh try and make it as easy as possible for users. And obviously, as consumers, we're used to that because you know, we pick up technology and we expect it to be instantly uh intuitive to use, but often in businesses we don't think about that so much. But useful and usable technologies are not always used, and that's where the really interesting psychology comes in. I I it's sort of the evil psychology. I would do an evil laugh at this point. I won't. It's kind of um who else is using it? So there's a lot of behavioural economics sort of embedded in this. So it's a lot to do with peer pressure, and it's more likely that you're going to be using a technology if people that you think are like you are using it. And I guess social media is a very good example of that because a social network of one would be terrible. And you the reason you're on a certain platform is that other people like you are on that platform, and that works across the board, whether you're a customer, whether you're an employee, you kind of have to recognize and realize that it it is often about peer pressure with adoption. And for internal innovation, that's again not just getting the leaders on board, but also the key influencers. And those key influencers are not always obvious because they're not always the people that are in charge. It was quite interesting in in one project in the contact center that we were working on. I was just looking at whoever who was everyone going to if they had a problem? Who were they asking? And you could see those people, and they were usually very experienced people, but they were providing the answers. And they're the people you have to get on side because actually they'll probably be the most resistant as well, because effectively you're taking all those questions away from them. So work with them to kind of get the system in place and work with them as champions for the system because they are the key influencers. So, yeah, there's all of that kind of invisible people stuff for innovation that that really needs to be in place. But that's the bit that often people forget.

SPEAKER_01 12:54

I guess potentially a lot of our listeners at the moment are dealing with this challenge of technology adoption within our organizations when it comes to AI. I think a lot of senior leaders have decided to spend vast sums on AI tools, and now they're kind of questioning are we getting the productivity benefits from this that we expected? I'm interested in your take on that. I know you said you've kind of been working with AI since the 90s, but this current cycle, how do you see things going and how are BT implementing AI tools?

SPEAKER_00 13:24

Yeah, I mean, I'm talking about AI a lot at the moment, uh, oddly enough, and there's a lot of hype about it. I actually was a recent uh piece, uh recent survey, I can't remember who did it, but um they surveyed bosses and employees about their attitudes to AI, and it was very clear that the bosses were very excited about it and the employees were all mired in work slop and weren't always appreciating it. I mean, I've always said that sometimes new technologies intensify work, and AI is one of those ones where the promise is it takes work away, but actually the reality is it often doesn't, mainly because particularly, I mean, every there are so many different flavours of AI. We talk about it as if it's one technology and one methodology, and it's not. Obviously, it's large language models and generative AI that are getting most of the press at the moment, and indeed most of the visibility. And there are some inherent flaws in those models, in that obviously they hallucinate, which is one of the big problems. I keep saying they're very convincingly wrong. So we've kind of automated mansplaining, haven't we? So um, so it's basically um a lot of it's around it generates some really good stuff, but then you spend almost the same amount of time that it spent generating it, yeah. Well, more time than than you it spent generating it, checking it, um, because it's often very wrong. And that that certainly for things like programming, where it's become, you know, very uh vibe coding has become a thing, hasn't it? Um, and that's in one sense very good because I don't need to know a programming language anymore to vibe code. I just need to be able to speak and tell it something that I want and it will code it for me. And obviously that's great. Uh it makes things much more accessible to people. But if you're not a coder, you don't spot where the code is wrong. And even though it might execute well, it might not scale, and it certainly might have some security flaws. So the expert programmers are now, rather than programming, actually, their job is about overseeing the code rather than coding. So, and that's strange because again, you take some human control away. I have some anxieties about some of this, certainly around things like independent thinking and strategic thinking and and and also just keeping those basic skills because the really disturbing things about our brains is our brains are brilliant, but they're also quite lazy. So skills that we acquire over, you know, years and years of friction and learning and failure and all of that can be forgotten very fast. Uh, there's evidence that it actually there was a paper that was very disturbing that I actually put out on my socials recently saying um that it only takes 10 to 15 minutes on some tasks for us to forget how to do them. And if we never learnt those tasks in the first place, but AI was handholding us, we don't know how to do them. It's the Google Maps effect, isn't it? Um none of us know how to read a map anymore. Well, certainly any anyone under under 35 probably never got taught how to read a map. I was always rubbish at maps anyway, but you know, we don't know how to read them now. We don't know how we got from A to B, we just know we did. So if if we if we can't use our sat navs or or Google Maps or whatever, we get lost if we don't have them. So because we don't know where we are, we don't know where we've been. So all of those things really make me slightly anxious around. I think this has to be much more about augmentation than than automation. I mean, I think we're in that mode where we went through it before in the 90s where there was a boom and a bust. I'm not sure whether it's going to be quite as big a bust because we went through a 10 to 15 years of completely forgetting about AI. That's not entirely true, but it wasn't part of the conversation for quite a long time. And now obviously it's very much part of that conversation, but it's not meeting the hype. As with a lot of technologies, it hasn't improved productivity to the extent that some of the analysts were predicting. So, yeah, it's all sorts of things that I think we're trying to look at at the moment strategically, as well as what the technology potentially could do for us. I also think, again, from a human center's perspective, I love science fiction. So I think that the most prescient predictor of AI in the science fiction world was Douglas Adams in the Hitchhiker's Guide to the Galaxy. Um, and obviously he created some incredible AI some from Marvin the Paranoid Android, the uh the android that was so, so intelligent that he felt, you know, all of his trivial interactions with humans were very boring and he moaned about them all the time. To lifts that got tired of going up and down and started to experiment going sideways. And of course, the new traumatic drinks for the Spencer, which um analysed all your taste buds and came up with something that was almost but not entirely unlike tea, I believe was the uh the phrase. But of course, his most famous thing was 42, the answer to life, the universe, and everything. And I think that we're in a 42 moment in AI at the moment, because of course 42 was the answer to life, the universe, and everything, but we'd asked a supercomputer to think deeply about this, and it took 4.2 million years, I think, to come up with the answer, and the answer was 42, but by then we'd forgotten what the question was. And I think sometimes with AI, we've forgotten what the question is. So we've created something where there's not a huge amount of purpose to it, and then we introduce it to people, and they do start to use it in weird ways sometimes, and and that's the beauty of people that uh sometimes they embrace these technologies in ways that you don't realize they're gonna embrace them, and that's innovation. But you've also kind of got to work out well, why are they there? What are they doing? What's their purpose? What are they actually trying to achieve? And in some cases, I'm not going to say all, but in some cases, um, I think we've we've kind of come up with the answer 42 without remembering what the question was in the first place, or even knowing that we had a question in the first place.

SPEAKER_01 18:53

It's an interesting time. It does scare me slightly how quickly I now kind of instinctively think to reach for an AI tool when I need to complete a task. And that's kind of happened in a very short period of time. And yeah, I think I also share your concerns about, I guess, especially for sort of people that are entering the workforce that are coming into this world and perhaps haven't had that experience of working in a non-AI way in the past. If everything is handed to them by AI, then are they able to develop those skills that other people would have done in the past? I guess in some ways, there's kind of a bit of a parallel with this technology shift and this shift in the way of working with this big shift that we saw maybe five or so years ago during the COVID pandemic. And I know that was really a challenging time for a lot of people, but um I found it really interesting. I think that was when I first came across your work, actually, Nicola, when we were colleagues at BT. And I remember we were all kind of trying to figure out what would this new way of working look like? How was everything going to function? And you already had some interesting theories about that. And I'd be kind of quite keen to hear sort of how your thinking around remote working has progressed as we're kind of like five years down the line. A lot of companies have pulled people back into the offices. We perhaps had a shift that we thought was going to be something that would stay with us and everyone would go and everyone would work remotely for the rest of our lives. That hasn't really happened for a lot of people. A lot of people are back in the office. So I'd be keen to hear a bit about your thinking about that and how that's developed.

SPEAKER_00 20:24

Yeah, well, again, my second job after building chatbots in BT was uh was uh helping out on our first homeworking trial. So that was um again, early 90s. So we've been thinking about homeworking for a long time. So when the pandemic hit, pandemic was a very good example of of crisis innovation because we had to innovate. Um, we were in weird times, and crisis is always a really good accelerator where innovation is concerned. It's not a pleasant accelerator, it has to be said, but um, but when you are under pressure to do things, you do end up doing things quite fast. And that was a prime example, the whole pandemic shift almost overnight of people uh going from office base to home-based. But we knew home-based working worked. That trial in the 90s again was with contact centres. Um, and again in Scotland, we did a lot of trials in Scotland and Northern Ireland actually as well. But um, we did a trial that was called the Inverness Experiment, oddly enough, because it was an experiment and it was in Inverness, so we were that original. But that was a year's pilot back in the early 90s where we worked people from home for a year who were volunteers, so slightly different to the pandemic. But we were slightly worried, it was a tech trial effectively, but we were also slightly worried that they might go insane. Um, because you know, 12 months at home could be quite challenging, as a lot of us found during the pandemic. And there were a lot of echoes of that trial that came out during the pandemic. The tech trial was interesting as well, because actually, if we'd had a pandemic in the 90s, we would have really struggled because we literally had to bulldoze people's front gardens in the 90s to get a big pipe into their house because we didn't have Wi Fi, we didn't have 4G or 5G, you know, the home hard. Had not been invented. So uh indeed the smartphone wasn't there either. So, you know, um we literally had to dig people's gardens up, and so that cost around I think it was about 11,000 pounds a seat to do that. So you can understand why homeworking was hard in the 90s, but actually, from a did it work perspective, partially it did. Obviously, the expense killed it because we knew that we couldn't do it with 11,000 pounds of seats, but we proved it worked, and actually we also proved that people could work from home for 12 months without any particular psychological damage. We also put in tons of things, so we put in video conferencing to make sure that they didn't feel lonely. Now that might sound, oh well, we do that every day now, but um video conferencing at the time was, I mean, the the unit itself was the size of a small fridge and the quality was terrible. And oddly enough, they didn't use it because all of those things, but it's there, and we proved that that kind of technology uh again, once you've got the infrastructure to handle it, that worked. That got us through the pandemic. I kind of thought, well, okay, so we've now proved homeworking will work. Everyone is going to start to have a policy around homeworking, and that did happen for a little while. And as you said, then we've got the return to office mandates, and I think it's weird because for me, I've kind of got a little bit fed up talking about hybrid work up to this point because I've been talking about it a lot. I just think it's work. I mean, we get so hung up on where we do the work, and actually that's not the important bit. It's kind of what work are we doing and how are we doing it, and how is it being managed? And then if you can figure out what the work is and and the extent to which you need to collaborate, for example, you know, how you're managed, then you figure out do I need to be actually with people or not? And we do know that. I mean, again, our brains are brilliant, but they are wired from from the caveman era that you know, we do tend to trust people and when we see them on a regular basis, actually physically. So you can understand that actually that human bonding is really important for work. But do we need to be in five days a week? Probably not. And it doesn't suit everyone. And of course, the way we work that now was designed largely coming out of the industrial era, so you know, things like Monday to Friday, nine to five, or constructed in an era where there was a rapid industrialization, where the railways were coming into use and people started the commutes and things like that, but they couldn't work anywhere else. In fact, previous to that, people did work at home, obviously, because there wasn't an office to go to. But um, but you know, that that whole concept of of nine to five, Monday to Friday starts to break when you start to think about the digital office because I don't need to be in physical proximity to other people to do a very large portion of my work. So, do I need to be in an office night five, Monday to Friday? Probably not. In fact, even if I am, I'm probably not working nine to five because I've got things that reattached me to my work wherever and whenever I am. Uh, so it's more a case of how do we work, and that's again culture. I mean, culture literally is defined that uh around the sort of the ways that we work. So, I mean, I think it's a challenge for management. Certainly the test of a manager during uh lockdowns was how do you manage and motivate a team when you don't actually can't be in physical proximity to them. And we don't teach managers very well how to manage. I think there was some very disturbing research about two years ago showing that I think it was 81% of UK managers were accidental managers. In other words, they've been promoted because they were doing a good job, but it wasn't the same job as management. And then they weren't given any management training. And that includes face-to-face management as well as hybrid management, which is far, far harder. So managing by working, walking around doesn't work in a hybrid situation. And we learnt again back in those you know homeworking trials that the first people you had to teach how to manage remotely were the managers, and so you need to make sure that you include people in your communications all the time, that wherever they are, they they feel included and that they're part of the communication. And that makes management hard. So you can understand why you know senior managers are often going, well, it's far easier if I just see everybody. But then that can potentially cut the accessibility of work out for certain people who maybe can't commute. Um, so people with disabilities, people on the neurodivergent scale, carers. It tends to penalise women, unfortunately, who still but bear the brunt of caring. So, you know, all of those things were designed in an industrial era where we kind of assumed that everyone was going to be going to an office. And I in the digital era, it shouldn't be about that. It should be about what work am I doing, how do I get the work done? AI is going to further disrupt this because actually we're increasingly collaborating with AIs rather than our colleagues. So um, I I keep saying brainstorming is quite interesting from an innovation perspective. That's obviously, you know, that's the way we used to do stuff. But brainstorming, and there's there's been some lovely studies, notably by MIT, on this, that people often brainstorm better initially with the idea, ideation piece on their own and increasingly with AI. So they're tossing ideas around and refining them using the AI before they then present them to their colleagues. And actually, you get better ideas because people aren't forming a judgment of your ideas when you're actually ideating. Obviously, you do then need to get together to prioritize those ideas and and figure out which ones you're going to take forward. And that is a collaborative process that you need to do with other people. But actually, that whole ideation piece is starting to get very disrupted by the fact that I'm actually chucking weird and wonderful ideas at AI and going, what do you think?

SPEAKER_01 27:35

Yeah, I mean, I definitely find it helps me to be able to brainstorm a bit with an AI tool rather than just chucking my totally half-baked ideas to my colleagues in the first instance. So, yeah, definitely some advantages in those areas. I guess kind of zooming out a bit from the technologies, if we if we think about these kind of these big shifts that we've seen in the way that we work, kind of at a top level, what kind of lessons can innovation leaders take from these shifts and kind of how they implement change within their organizations? How do they make sure that innovation is a positive rather than a negative for their employees and the people in their organization?

SPEAKER_00 28:14

I mean, I think I go back to that useful usable use. Think about this. Who are your users? I work with a lot of engineers, and instantly you go, have you talked to anyone about this? Oh no, why would I do that? Well, it's a great idea. I love the idea, but just talk to somebody about it that might actually want to use this. And that can be very uncomfortable for people who aren't people people, basically. Um, so you know, I I think uh it is around think about who your users are because they're not you. We're all individuals. That's the challenge of design. That design process is really, really hard. I use a lot of persona-based design as well to try and just knock people out of just think about who these people are and what their ideas are and what their motivations are and what they want to do. And if we can actually generate genuine personas, not just completely made-up ones that are based on real people, that's a really good tool to get these incredible technologists to start to think about who might be using this tech and how do we need to design it better for them and not just the average. I would say the average never gets you anywhere because I this is why seats, chairs never fit me, because I'm quite short. And apparently the average chair is designed for someone. I think I forget my ergonomics course, but I seem to remember it was something like five foot seven and I'm five foot four. So, you know, that's why no furniture ever fits me. So yeah, that that's the problem. Designing for the average, no one is average, it's really difficult. So I think trying to sort of jolt people out and thinking, you know, what's this technology for? Who's it for? And can I actually figure out who they are and and what they might like and then go and test it with them? And when I I back in the days we used to do paper prototypes, now you can build, you know, really, really convincing looking things with AI in seconds often that you can then go and just talk to people about and show them and see how it would work. And they can then give you feedback. And you can even use AI to simulate your users, although I don't uh I'm less convinced about that. But um, but you know, um, but uh there's nothing better than talking to humans if humans actually have to use the systems, frankly. But you know, you can test things out very rapidly now and do very rapid prototyping and testing before trying to sort of then put it out. Then the challenge is scaling, which is always uh where often innovation again fails because uh you then get into okay, how do we do this? Does it actually is it resilient? Who's gonna champion it? Who's gonna support it is a very big one as well. So yeah, there are lots of things that innovation leaders need to think about apart from the tech. I've always said, you know, get out there with the users and actually try and sort of figure out where where this tech, what problems is it solving and how do how do we actually solve them? Using probably a combination of tech and people, to be honest. But yeah, the people bit is the is very important and very difficult to get right.

SPEAKER_01 31:01

Absolutely. Nicola, thank you very much. It's been a really entertaining conversation. For anyone who's been listening along to this, where's the best place for them to find out more or hear more from you?

SPEAKER_00 31:11

Oh, crikey. Well, I mean, I I'm all over socials, so um, I've got LinkedIn profile, probably the the first place to go. So I try and post interesting and weird stuff on a fairly regular basis. So yeah, come follow me on LinkedIn. I'm Dr. Nicola Millard.

SPEAKER_01 31:27

Excellent. We'll stick the link in the show description. Thank you very much, Nicola. Um, that is a wrap on this episode of the Innovation Brief. Thank you very much for joining us today. Some really interesting insights into the future of work, life and technology. So hopefully one that our listeners really enjoyed. If you did enjoy this conversation, please make sure to uh share this episode, subscribe to the innovation brief, and leave us a review. It helps other innovation leaders and curious minds to find the show. We'll be back soon with another great conversation. This has been The Innovation Brief, and I've been Matt Briggs. Thanks for listening.