Mintel and Black Swan: A New Era of Predictive Intelligence

In this CEO Series episode, Leonard “Lenny” Murphy sits down with Matt Nelson, CEO of Mintel, and Hugo Amos, Co-Founder of Black Swan, to unpack why their newly joined forces make strategic sense right now.

They discuss how Mintel’s deep consumer and product intelligence pairs with Black Swan’s forecasting strengths to help brands spot whitespace, reduce innovation failure, and turn faster signals into better decisions. The conversation also digs into the AI era’s double edge, separating signal from noise, and why the winning formula remains data + technology + human expertise.

Transcript

Leonard Murphy: Hello everybody. It's Lenny Murphy with another edition of our CEO series. Uh thank you for taking time out of your day to spend it with myself and my guests. And today I am joined by Matt Nelson, the CEO of Mintel and Hugo Amos, co-founder of uh Black Swan. Sorry, Hugo. Let's quick quick a little brain fart there for a second. Um and uh you you guys recently joined forces and we're going to talk about that. Uh, full disclosure, Hugo and I go back a couple years. Uh, did some work with with Black Swan early on. So, I'm looking forward to catching up and finding out about where things are today. But before we get into that, so Matt, why don't you uh kind of tell us your origin story and then Hugo, you can do the same and then we'll get into the fun stuff.

Matt Nelson: Yeah, thanks Lane and thanks for having uh thanks for having us on. Uh my origin story, I've been Mintel's CEO for the last four years. I've been with Mintel for about 15 years. I started my career through India and Asia Pacific selling and growing those businesses. U and then before that I I was an architect and a tour guide. So, I've I've had quite a checkered background to get to this point with lots of different skill sets and lots of different experiences, and it's probably one for a different podcast, but

Leonard Murphy: Okay. Well, all right. We'll have to follow up on that because that's but the first thing that popped my mind is, you know, that kind of makes sense about, you know, if you're a tour guide or an architect, you know how to put things together. Um, which, uh, obviously is something that Mintel does. So, I I could I could see where you get to that path.

Matt Nelson: this that there's a close correlation. I think it's it's it's one of the one of the skills I'd like to think that I could bring to the bring to the role is being able to see things at 10,000 ft and right up close as well.

Leonard Murphy: All right. Excellent. Excellent. So, Hugo, how about you for those who are not familiar with with uh your origin in Black Swan?

Hugo Amos: my origin. Um, well, I've never been a tour guide, so I can't I can't can't go back far, but um I was probably more traditional. I came from a business school and then um started my career client side. So um um a lot of that with PepsiCo um and spent many years kind of learning the ropes on on that side of the fence. And um I suppose the origin um and the bit where it perhaps gets more interesting is um the point where I chose to take the leap and um we were I was kind of working a lot in digital marketing at the time and and digital insight. And it was back in the day when the internet was becoming a bit of a thing and big data first became a buzzword that we could scare everyone with. And that started to open up new opportunities. And the observation being that there was more data than ever being created by consumers and by brands. And we saw myself and Steve co-founder of Bloxon saw some an opportunity to try to harness that data. And the kind of maybe lofty ambition at the time was that if we could get enough of that data together, we could start to see patterns that brands couldn't necessarily see. And so for those that don't know, the origin of the the term black swan was a a 16th century statement of impossibility in England where you you'd say it's as likely as seeing a black swan. And then we sent some English people over to where Matt comes from. Um and there was a ton of black swans over there. And so it proved that actually with the right data you can spot those patterns. And so at the time we thought, well, that will be easy. Um turned out it was a rather larger undertaking than we thought. But I guess the good news is that um we survived. And and now I think with this um kind of merger or acquisition by M2, we're kind of in a I think a really powerful position to realize that original vision actually of being able to get the data together in order to spot those unforeseen events. And so that journey has taken us to where we are today.

Leonard Murphy: Well, you know, when I saw the uh the news, um my first thought was that makes so much sense because here's my my broad take. When I think about Mintel, I think about obviously a company that is amassing tons of information about, you know, purchase behavior and and you know, in store activities and uh etc, etc. And then obviously, you know, Black Swan with more of that forecasting component. Uh, and thought, well, that just makes just perfect sense. Uh, not just have two sides of the coin, so to speak, on and here's what we know is happening. Here's what we think is going to happen, but that the way that that those two data sources uh could be synthesized to unlock even more uh predictive value overall. So, did I read that right? Was that kind of the uh the Reese's Cup scenario that you guys thought of when you started connecting of Yeah, this just kind of makes sense or or was there more to it? Whoever Which one of either one of you come back

Matt Nelson: No, no, I No, I think I I I think you're spot on with it, Lenny. Um, I think we both for a while, you know, I don't want to speak for Hugo, but we both wanted to solve the same problem, which is there's a lot of failure around innovation and and and what goes in front of consumers. And I think, you know, Mintel's always been fantastic at understanding, you know, what consumers want today and what products are in the market, but maybe struggled a little bit with more of that understanding that more more real time analytics of of what's coming. And so, so I think when we first both met, that was a that was a common problem. We were we we discussed and then there was obviously the cultural fit as well. When we met the team from Black Swan initially, we kind of felt like they were Mintel people. Um, you know, the same type of curiosity, the same type of excitement around these problems. And so it it just as he went through the process, it felt like more and more of a natural fit.

Leonard Murphy: Yeah. Hugo, would you add to that?

Hugo Amos: Yeah, I think um very we we I suppose from the startup perspective have always felt that we were on a bit of a mission um and we wanted to find a way to um to achieve that that vision and I think we we realized that it's a tough industry to crack on your own and as a small startup and I think Lenny you probably know better than most there is a large history of kind failed startups in this space. And so I think we were pretty determined to find a way to not only achieve that kind of technical vision of bringing the data together, but also the scale that Mintel brings and I think the opportunity to bring this capability to a much wider audience. And so um I think the other thing that we found was that our customers were doing it already. And so most of our customers were manually putting these data sources together and and so we it was a very common request to say, "Hey, why don't you guys sort this out?" And so I think all those things together kind of made it feel like a an obvious fit. And so far it's um I think that's proving out and and hopefully our customers would say the same that it that it makes sense and that they're excited to see what's coming next.

Leonard Murphy: Yeah. So, and you did this during this AI revolution, right? And when I I think about AI from how it's affecting the industry, it's one obviously you know business workflow and process and the efficiencies around that and uh and that's the kind of less interesting aspect of things from the innovation standpoint. Obviously, Matt, I'm sure you're paying attention to it from a from a productivity and and cost standpoint of like, oh no, that's really interesting. We could we could do a whole lot more. uh but that ability to potentially unlock new uh new thinking around the data, right? To explore hypotheses and uh in ways that we just really couldn't do before because it was so time consuming uh overall. So how has that played into this from a kind of a product planning standpoint? Um obviously you you've brought the data together and there's this whole other now system of tools that can be applied to do even more that potentially than uh you know where it's a 1 plus 1 equals 3 scenario. Um how's that playing out that uh what's your take on that?

Matt Nelson: Yeah, I think you're 100% right. I think for us the exciting part and you mentioned earlier about prediction um you know we we called out 12 18 months ago probably just prior to us meeting black swan for the first time that you know predictive intelligence was somewhere where we needed to play into it was that Mintel's very good at understanding what happened and why did it happen but there's that additional part of what's going to happen and how do I make it happen and you know a lot of the way that Mintel's being built it's very much in silos so product silos across you know new product innovation and consumer understanding and trends AI has given us the ability to sort of go across that more of a horizontal and sort of diagonal point to start start to bring together signals that I think we've always been quite good at predicting but it was quite manual to get to and so you know unlocking that through the use of AI and then having black swan next to it you know straight away the low hanging fruit for us is to really understand you know what are the gaps in the in the innovation market from a CPG perspective and you know Mintel understands what's in the market and what consumers are thinking today and black swan's looking ahead and say, well, what are consumers going to want tomorrow? And obviously the delta right away there is that whites space opportunity that we want to sort of start to push on. And this is what we're hearing from clients is the obvious fit is this as a start. Um, and I think AI is helping us sort of scale up that a bit quicker than what we were previously hoping to get to. And obviously Black Swan coming on board.

Leonard Murphy: Yeah. And Hugo is that this would be one of those things that I mentioned of like, wait, Lenny, don't go there. But um but it just occurred to me, right? They came up the black swan and the way that you leverage social data. Um now AI is double-edged sword, right? does all this stuff but yet we're seeing AI slop so to speak um to you know manifest in social feeds and then we have the recursive problem and etc etc um and we just tie that into the the entire data quality conversation right uh how are you guys really kind of separating out the uh the signal from all the noise um out there that potentially could be a contaminating factor within uh within the social fees that you know are at the core of Black Swan.

Hugo Amos: Yes, good question. Um, I think um, Black Swan's core strength I think if you take everything else away has always been about quality of data. Um, I think has been the reason that we were able to carve out the position in the market we had. um versus kind of the the very noisy um data that exists in social um listening tools if you're use trying to use them for prediction or for for kind of research purposes and I think that's continued and so without giving away secret source I mean we're using AI ourselves to help solve the AI problem to an extent I think you can kind of get into an existential crisis mode about this if you're not careful about where where do you go so I think it's it's a very live thing that we're we're paying attention to but I think it's essentially just helping us on the journey that we've always been on and I think I'll starting

Leonard Murphy: Yeah.

Hugo Amos: point is that we've we've got systems processes in place that are designed to achieve the highest quality data in the market quite honestly from a social from an unstructured perspective and so I think it is um something that we we need to pay attention to but um it's I think it opens up the door even more for the value proposition that black black swan has um and I think like I think that I mean probably where you're going ahead in another question is kind of there's two sides of this kind of impact of AI at the moment there's what it can from our capability and some of that the risk represents, but it was also changing the way that we need to talk to customers and the way that we serve serve our customers. And so, um, like it's happening all over the place, right? But there's now, I think, a need for us to be able to think more, um, more kind of entrepreneurally than ever about meeting our customers where they are. And so whether I think that we still see a massive role for human expertise and and consultancy, but we also have to acknowledge that customers are um on their own journeys with how they're implementing agentic kind of workflow solutions themselves or they're using kind of some of the established um kind of um AI solutions that are out there. So we it's on us to make sure that we are able to inter in um interact with those systems in a way that our customers want us to. And I think the focus for for Matt and myself actually is to go back to your original question is to make sure that what we provide is um absolute quality context into those those engines. And I think that ultimately is the unique strength of Mint and Black Swan together. It's that proprietary um intelligence that can give an advantage to those systems.

Leonard Murphy: the M. Would you add anything to that?

Matt Nelson: Oh, I'd line was saying it was again I probably missed it earlier. It was one of the key points around Black Swan is that Mintel's heritage. We're 52 years old. You've got a phenomenal reputation of heritage of quality and trust. And so, you know, we continue to push on that. I'd also jump off the back of what Hugo said. Uh that human part of the story and the equation is critically important. and I think will remain that um whether it's through consultants, experts, analysts, data experts. I think we we've been quite clear that calling out that it's a combination of data, technology, and people, it's going to win the race versus just data versus just the technology or versus just the people. Um and I think one of our missions is to make it as easy and simple as possible for clients. And and we're still on that journey. Granted, it's it's the start of I think a long journey, but really being adaptable to meet clients where they want to be met.

Leonard Murphy: Yeah. So, and Huger, you did tee up a question uh for me. Thank you on that. the so this year we started to hear rumblings um from you know various folks on the uh the push now from buyers from CBG you know especially um to say you have to adapt and integrate into our agentic systems to your point you know they're on that journey as well and they're building out they see the efficiencies all the way from procurement and execution uh but fundamentally it's about now you know integration and in data feeds um uh whether we're talking about you know kind of custom uh or more syndicated licensing you know type of of solutions as well the and I think that's to your point M that's exactly meeting them where they are right that's not going to be a solution for everybody out of the gate but I think it is going to be a solution for everybody in pretty fairly short order um uh over the course of the next few

Matt Nelson: Yeah.

Leonard Murphy: Years because it just makes good business sense to be able to streamline these processes as much as possible. Um and and particularly to leverage data. Uh you know there's there's you know a shift to uh kind of ad hoc uh point in time solutions into something that looks a whole lot more like an always on uh you know data solution uh with AI all in the middle kind of managing that. So to that idea of meeting clients where they are, what are you hearing from a client standpoint on what does that future look like for them? So how are they thinking about this evolution of still wanting the human element but also obviously now having tools to be able to unlock more uh potential uh value creation through kind of data feeds overall.

Hugo Amos: Yeah, I think I mean I I think we um we hear a fi pretty similar story.

Leonard Murphy: Sure.

Hugo Amos: I think it would be fair to say it's not the same for all customers and I think they're at different points in the journey. I think you're probably right that eventually the sea will will go with it. Like I think we see a pattern of a lot of particularly the bigger brands that we work with have um invested pretty heavily in many cases on um exploring generative AI technology usually focused on coms use cases and marketing use cases to to begin with. I think that's for obvious reason that's where a lot of the media spend goes and it's the the biggest kind of opportunity. I think what they've seen is some success with that and not total success but some success and so now you're seeing kind of a trend to say well hey if we can do that there what does that mean for innovation what does that mean for kind of market research side of things and so um obviously without talking about specific instances we can we're seeing a lot of the major brands taking different approaches to that different partners different different solutions and I think it's a journey that they're all on I don't think we've seen many complete it yet or really see kind of the full full story and We we absolutely are part of that solution I think and we're for us it's really important as I'm sure it is for all vendors at the moment to to use the phrase again to meet them where they are. I think Black Swan and Mintel are set up very well to do that and we're we're kind of heavily down the path of making sure that we have the right connectors in place to be able to do that and to be able to make it easy for customers to to to use the use the data. I think it asks some really interesting questions of future commercial models which I don't think either clients or vendors are quite there with yet to be honest. So I think that's going to be the the journey we go on to look at how does this make sure that this kind of works for everybody. Ultimately I think that the winners will be those that have access to the highest quality data and and proprietary data. So I think it's um kind of our strategy is to make sure that we do what we've always done Rich is focus on ensuring that the um the kind of data and insights we're able to provide are are proprietary and are valuable. Um and I think we'll need to go on a journey with our customers to to go with them on on this. I think it will it's going to evolve a lot right like it's going to change I think some will go faster some will go slower some will stay in PowerPoint for years right so it's going to it's going to create challenges for us make kind of evolving that go to market model will keep us all in a job I think for from quite Yeah.

Leonard Murphy: Yeah. Knock on wood, right? the the I was watching videos of some of the the the humanoid robots coming out of China this week. Um and I don't know it's like uh that's a whole other topic. We won't get into all that. Um but but you mentioned that the change in business models and I've been thinking about that a lot and certainly lots of conversations with with CEOs uh of various companies as well especially in kind of more the traditional fullervice ad hoc. I mean I think they're really feeling that potential shift. um uh and the impact when we move from models that are inherently well they just look a whole lot more like subscription I think when all is said and done um you know it's it's uh subscription first and then building off of that to fill in gaps of information I think that's kind of the tier now that we're shifting towards which I would imagine you guys are in a pretty good spot to adapt to that so first Is that your view on the future? Um that we're going to be looking a whole lot more like uh you know subscription data feeds in general um first with then uh you know solutions built on top of that to you know fill in gaps of information or dive in deeper on specific things. Um or is there do do you envision something different? What do you what do you think the future may look like without giving away your strategic plan? Obviously, I'm not not asking for that, but just your sense of where things are. So, Matt

Matt Nelson: Yeah. Um, it's a great question. I I think it's one we wrestle with every day. I I think just to add on to what Hugo was saying, we're certainly taking the attitude at the moment that co-creation is critical with our clients and partners. Um because as Hugo said, they're all on everyone's on such a different part of the journey and different stages. And I think the more that we can get in and work with clients to help them solve the problem. Obviously, it works well, you know, for Mintel and Black Swan, but it also we learn along the way, you know, you become more agile, you take away lessons and and you can sort of you can feed that through. So, I think that's critical. It's it's a great question. It's a hard question. I mean I see a world and I' I've challenged Mintel and our teams here to say well you know it may very well that we be that we don't own websites in the future that you know you don't go to Mintel websites that we're embedded into look whether it's in clients world or whether it's into some of these large language model companies you know the open AIs that we've seen you know that that because really if you're putting clients at the center of it and talking about ease and integration and making it easy for them you know we have clients daily sort of say look we want you to work with different partners your competitors essentially to help us get the information. You know, they they're less worried about where it comes from. They're worried about how it all comes together to help them solve a problem. So, I guess I'm not, you know, not giving away the full source, but we've got heads up, eyes open as to what the potential opportunity is. Integration is a critical part of it. Um, we've also viewed that, you know, traditionally we call analysts, you know, experts looking at categories or trends. You know, the future is also going to be talking about analysts and experts from from data, from algorithms, from machine learning because no one knows Mintel's data and Black Swan's data and taxonomy better than us. And so, you know, the whole plugandplay doesn't necessarily work when you're talking about, you know, different data sets even under an agentic framework. So, the more we can sort of integrate in and help clients understand that how it fits, again, it's just a stronger position for us to partner with clients.

Leonard Murphy: Yeah. So I and I I think that's the right take. Um you know I don't want to go name dropping competitors, right? But but if we did this conversation that just seems rude. But the uh but as I look at the market and see companies that are playing in different aspects of this, it seems as if uh some are going for maybe we'll call it a a systems integrator or aggregator type of play. Um and there's certainly companies that exist already like that that that are I will name them because they're not competitors. Snowflake, data bricks, right? I mean there's these large data clearing houses effectively that perform that function but we're seeing some kind of build in more bespoke uh within insights. Um, and it does beg the question of, well, okay, that's fine, but if we're just integrating different feeds from different companies, there's some value there, right? You're the the marketplace. Okay. But from a business standpoint, you just need to start buying the companies and putting them all together and doing those things. Um, uh, which I got, I hear you. I don't want you to give away secret sauce, but you kind of hit it at those possibilities. I think it it it creates interesting combinations similar to what you and and Black Swan did to think about from a value creation standpoint. Um uh and that's my guess is over the course of the next 18 to 24 months. Um I think there's going to be a lot of interest there. I I would expect to see uh private equity coming back around to the inside space pretty significantly and looking at mid-market rollups and I think those will probably be data aligned and vertically aligned um overall. Uh and that's just going to reshape the entire structure of the industry. Uh, it's my take. What do you What do you think?

Matt Nelson: I I mean I can see Oh, go for it. Here you go.

Hugo Amos: No, I was going to say I I I think um I think you're you're right. I think the I mean Lenny you know a little bit about our background and it kind of came from a VCbacked sort of environment and I think that that was all really driven by a SAS disruption of market research and I think kind of arguably there were very few successes in that space right it's a hard model to crack the adoption for SAS tools in market research is notoriously poor um and so I think what this what we're really looking at I think is the next wave of of disruption but actually one that might kind of I think have a easier user adoption curve with customers and is more likely to kind of succeed I think in disrupting it. I think a big open question for us though is like I I think that large language models tools are going to solve for many many problems and automation will bring a huge amount to it but I think there are likely to always be um or or likely to be a need for that human context as Matt was talking about earlier. So I think the kind of puzzle that will probably a lot of discussion we're having a lot of our clients is what's the right mix of these things right how do you work with customers to get to impact I stood on stage with PepsiCo last week at TMRE and like the big conversation there was about impact so great investing in all these large language tools but still there's this gap to impact and so kind of I

Leonard Murphy: Right.

Hugo Amos: Think I think that journey is still a long one to go on I think the gap between data providers inside providers and actual business impact is embarrassingly big still so so and I don't I think a large language model tool will solve that on its own. Um, and so I I think it's going to again it's it's the competitive landscape is definitely going to shift.

Leonard Murphy: Yep.

Hugo Amos: You're absolutely right on that and we hopefully are positioned in a place to to capitalize on that and you you've hit the nail on the head in terms of kind of the the opportunity with the data assets that we have to to be in a strong position there. But um I think that being agile in this space and working with customers is going to be key to to getting them.

Leonard Murphy: Yeah, Matt.

Matt Nelson: I I mean I again I'll just push on there's a human expertise side that I think quite often in today's day and age and the pace at which AI and large language models are moving it's critical to keep that top of mind that there is value to understanding the human condition how people evolve how people feel um it look it sounds soft and fluffy but I mean this this adds the context text on top because at

Leonard Murphy: Mhm.

Matt Nelson: The end of the day, you know, you can talk about agentic systems buying products for people, but people are still consuming them. So, so there's that understanding that's critical. Um, I I do think there's going to be there are there's a lot of noise in this space at the moment, you know, with, you know, new AI companies in insights and market research. Look, some of it quality, some of it's not, you know, is is is just riding the fad. I think there is going to be a coming together and a consolidation a little bit more, but how that looks over the coming 18 months, I think is is still a little bit up in the air.

Leonard Murphy: Yep.

Matt Nelson: Um, and and as Hugo hit on pricing models and and the way that customers and clients interact with insights and research, I think is going is going to change. Um, but again, I think it's that working with customers, talking to them, being open, bring them into co-creation, and really riding that wave with them. Because at the end of the day, I I'll I'll go back to what I said at the moment where we're trying to position certainly Black Swan and Mintel is helping to solve the innovation problem and 90% of innovation fails. That is a lot of money, a lot of time and a lot of resource that's that's not well spent. Um how can we help clients solve that together is is critical for us. So,

Leonard Murphy: Yeah. Well, even my own uh experience, I probably a year ago, I was reluctant to utilize a lot of these these tools um because I thought it would devalue me. uh because I'm fundamentally exult how I you know make my living the and that's changed dramatically um because and this pertinent to your point that the synthesis of you know human the uh even last night I was I'm I'm was working on doing a strategic plan for a client and leveraging all of the unique data assets that I have grit etc etc And you know the AI will only go so far. It it's glaringly apparent that even leveraging those tools requires human expertise to unlock the real value. Um uh whether we think about as creativity, intuition um uh to an extent certainly experience uh and that kind of collaborative process that's what I see emerging and I think that's actually very hopeful for the industry as a whole. Uh that we could think through. Look, I generated a 40page document in four hours. I can't argue about the efficiency of doing that, right? And it wasn't AI slop. It was directed and driven by my perspective like, well, let's let's look at this, let's look at that, what about this, you know, etc., oh, nope, that's not right. Let's pull that together. So, I think it's there's a process taking shape for us. uh and I expect that's happening on the brand side as well as on you know the supplier side to to find this synthesis between the two. This starts with good quality data. Got to have the data first obviously. Um but human expertise to say but what the hell does it really mean? Um and then the efficiency obviously to put all that together and generate something quick. Uh that isn't a doesn't for my perspective isn't a detractor. Um I view it as a superpower now. So right I can do more than as a sole practitioner consultant than I ever could before. Is that part of what you guys are finding as well? is this journey of collaboration with your your clients is that same type of thinking of you know look we're going to we're going to find the best of both worlds here to create more value overall to solve these problems around innovation. These tools just turbocharge us. Just make it easier in a variety of ways.

Matt Nelson: Yeah, I I mean speak they'll help they take away some of the repetitive tasks and provide more time to to solve you know what I think are the the real problems um and the real value for clients. I think as you were talking Lenny one thing that triggered with me one of the great strengths of you know AI large language models aantic systems is the is the allowance for hyperpersonalization and it's interesting for Mintel because you know we've always provided quite syndicated reports one to many um and products but I've I've learned over the last you know 24 months of using these tools just how much they know about me and you know so
 
Leonard Murphy: Yeah. Yep.

Matt Nelson: When you think about embedding that into the way the clients are receiving this information you could have you know, a pretty generic view of, well, not generic, but a pretty specific view of how consumers behave in a certain market, but the large language model is actually very good at adapting that to what the end user current situation is. And and I think that's a phenomenal opportunity. And so, you know, that then sort of frees up the time that people may have done to may have spent on you doing that to do other other pieces of work that maybe are more high value.

Leonard Murphy: Yeah.

Matt Nelson: So, I think there's something fascinating in that that's going to continue to evolve.

Leonard Murphy: Yeah, agreed. I've been using my current favorite is Perplexity. Um the uh and it it really has adapted now that it it anticipates what I'm looking for uh to a surprising degree.

Matt Nelson: Yep.

Leonard Murphy: So it's I don't know if I'd call it training but I know that is what's happening. It is certainly adapting to my use and my style and the data set right the memories uh you know there to be predictive of even my own needs which just adds more value.

Matt Nelson: Yeah. Yeah.

Leonard Murphy: Now I don't know if we want I don't think I want a Lenny bot out there in the world. That's actually kind of a scary thing, but I see certainly the value of a, you know, a a lesser Lenny pot existing in my own usage to your point and and it's a good thing.

Matt Nelson: Yeah.

Leonard Murphy: That is a good theme of customization standpoint. Hugo, uh, anything you would add to our little excursion into uh, the world of of uh, AI replicas and and value for us?
hugo amos: No, I think I think you guys have have hit it on the head. I mean, I think we I mean, we've all been in the industry a long time, right? And I think you can see the massive opportunity for for kind of efficiency. I think like the but it I think there's a lot of what goes on which those human beings can be doing much more useful things as you've said.

Hugo Amos: So, yeah. And like this is moving fast, but I think we're barely out the starting blocks on it, right? Like and I think there's a lots of lots of hype out there. But um but and it's not to say that it isn't going to happen, but it's far from reality today. So I think there like I think it's just an exciting opportunity kind of on all sides, but it's it's going to be going to be a balance to navigate. Um and and I think that we often kind of I think kind of uh a lot of our time I think as CEOs is about kind of what does this mean for our teams as well?

Leonard Murphy: Mhm.

Hugo Amos: And so like not only our clients but then also how our team's jobs are changing and evolving and making sure that's positive for their career development and and so yeah it's it's um a complicated um multi-sided opportunity I

Leonard Murphy: Yeah, absolutely. Well, I want to be conscious of uh of your time as well as uh as our listeners. Um uh is there anything else that you wanted to add or touch on before we kind of move into the final uh more uh more wisdom distillation aspect of the conversation? No, I mean this you get brag now, right?

Hugo Amos: I think we're good.

Matt Nelson: No, I think I think we look I think from Mintel's perspective um we've we're known for many things across the market research market intelligence

Hugo Amos: I don't know how

Leonard Murphy: I mean you get this is when you know you get to say well Mintel is doing all these amazing things. So if there's now's the time Here

Matt Nelson: Industry, but I think there's definitely a accelerated push into innovation and helping to solve that problem. Um, you know, and I think it's an exciting journey and I'm, you know, incredibly excited that Black Swan can become a part of it and sort of that that for us is that sort of shining light is how we help to solve that problem going forward.

Leonard Murphy: You go. Any uh any last uh last chest dumping for you?
 
Hugo Amos: Um I I guess just how like I mean I guess if any of our clients do listen to this kind of thank you for going on the journey with us and like hopefully we are um investing in building something which is going to help all of us and so this is not a by accident um situation. We we we touched on it in today's um discussion, but like we think it's a huge opportunity for these data sets ultimately to provide some extremely exciting proprietary metrics which I think will however you choose to consume them through an language model or a PowerPoint are going to make um kind of the the challenge of innovation a lot easier and a lot more precise. And I think that's the conversation we're having a lot with customers now about the need for precision in this. And so like growth is hard to come by for most of our customers at the moment. And so being able to be more precise and bring more scale to fewer opportunities, I think is the the narrative of of many of our customers at the moment. And so I think what we're building will enable that. And we're really excited to go on that journey with our with our customers. So

Leonard Murphy: Okay, very cool.

Matt Nelson: I I will add just on Hugo's point, it's a it's a great point. I would encourage customers and brands to keep pushing us because we've we've found some great innovation and unlocks through co-creation and and through our customers and and just you know companies coming up to us saying you should do this or this isn't where it should be. So I would encourage that because I think this industry grows and I think insights grows as an industry and research through you know that that collaboration from both sides and that real pushing to sort of create that friction and creativity and um you know really try and explore new grounds. I think there's a massive opportunity there and it's not going to just happen through Mintel and Black Swan alone. Um it's going to be everyone pushing each other.

Leonard Murphy: Yeah, that's that's a great point, right? There was a time where uh there was kind of an Illuminati in the inside space, right? um the uh of the largest the heads research heads of some of the largest companies that met regularly. I I I know for a fact they they met at least twice a year and they then would say all right here's what we want to put out uh into the industry to get folks to do that. Uh now I don't know if that official proceeding still happens anymore but the point I think it's just wonderful Matt is that it does need to be a dialogue uh that's happening. So uh the the final point of these conversations always about your journey as a CEO and uh obviously I think from your introductions there's two very different ones right Hugo you were on the you know the startup VC backed ride Matt you've grown into this role in an established company um so I'd like to just get your takeaways on wisdom that you would impart to other CEOs uh that you've learned and Hugo why don't we start with you uh since you've been on that that ride, right? That founders ride. Uh lessons learned that you'd want to pass on to other folks.

Hugo Amos: Yeah, I think um I suppose with a focus on maybe people on a similar sort of um growth journey and maybe a smaller kind of startup space, I think that the biggest lessons we learned were really about um adapt adaptability and change. Um, and maybe it's an obvious thing to say, but like as you go through the different periods of growth in a in a scaleup company, it's was always remarkable to us how much you had to be able to change. And we we literally kind of saw sort of people that had sort of different DNA at different stages of that growth. And I think people some some people can go the whole way, some people can't. And I think the big lesson we had was being being kind of prepared to disrupt yourself over and over and over again. Um, and I think that probably still was true for for Mintel and in a different way and at a different scale, but like it is that kind of um that that constant change being the norm, I think, and and sort of psychologically being comfortable with doing that. And sometimes in in a startup world, that can literally mean letting go of someone that might be your friend. Um, that just isn't right for that next stage of the journey. And I think that was the probably the biggest and hardest lesson we learned was the importance of knowing when and how to do that um in order to grow. Um and I think that probably carries through um into into challenges for bigger organizations as well. But it was it was probably the thing that um has stuck with us having done that journey.

Leonard Murphy: And let me echo that my own experience. I am I am a gleefully recovering CEO. Um and because I'm not very good at it, you know, I'm a I'm a great founder starter. You know, I'm a great idea guy. I suck at running and scaling businesses. I really do. So, so I hear you right. I think that's part of the the knowledge of understanding in that that world. We do different people fill different roles at the time. So, and I'm, you know, you mentioned failed startups earlier. I mean, yeah, right. Right there. I've got a couple under my belt um because I'm not very good at that scaling piece. So, uh so good wisdom. Uh thank you for for sharing that, Matt. Now you've you're guiding the ship on uh an established company. Um what's that journey been like? What wisdom have you learned as a CEO?

Matt Nelson: Well, I think you were very kind saying I've grown into the role. I'd say I'm growing continually. It's never it's never a completed journey. It certainly doesn't feel like a completed journey. Um I think for me, I I inherited a company that was ultra successful and had been run incredibly well for a long time. Um, but you know, with the with the era that we're in at the moment, whether it's AI, competitive spaces, it faces it cha it's it's facing challenge and I think it's disrupting it from the inside. I think the there's a couple lessons that I've learned. One is more companywide and one is more personal. Um, the companywide one is just the challenge of bringing everyone along on a journey. Um, you know, Mintel plays into so many different places, countries, regions, you know, sectors. It's it's how you bring everyone along on that journey and then that is an ongoing thing and I think I probably took that for granted a little bit at the beginning and thought that well as as CEO it's my responsibility to work this out. It's my responsibility to have the answers and I think over my tenure the last four years the more I've sort of let go and bring others into that uh the more successful it's been.

Leonard Murphy: Yeah.

Matt Nelson: Um and and just obvious look it goes without saying this is common sense but just overcommunicating being out the front whether it's you know in front of the company individually small teams um and then the vulnerability and transparency that goes goes through with that I think that's something that I've bought into the role for myself is I I do believe in being quite open and honest and vulnerable and um you know I I I think that

Leonard Murphy: Heat.

Matt Nelson: That the more and more you do that the more and more people can sort of see you as being a a person not a quote unquote CEO.

Leonard Murphy: That's wonderful wisdom and I I agree. I I don't I don't know any other way to be than authentic, right? Um and I think I like to think that's one of my that's one of my charms. uh you know uh but fundamentally it's also it just it it does make things work better for people. So I agree. And how many how how big is Menel from an employee standpoint? Matt, how many how many people do you need?

Matt Nelson: About 12, 1200. 1,200 people.

Leonard Murphy: See, that's that's a Yeah.

Matt Nelson: Yeah, it's it's a it's a huge it's a you know it's a big business. It it really is it's a big business and that that's a there's a lot of power in having everyone going in that same direction. 1,200 people is a lot of good energy and a lot of good thinking. And the thing that I've loved about Mintel is just it's and it should be because it is a research company. It's it's diverse in its thinking and you know it's it's we've made it critically important to make sure that we've got people that you know without getting into it believe left right up and down because you know really you're trying to talk about how people behave and people don't come from from the single mold. So you know there's there's great power in having that diverse thinking that that you know those different perspectives and uniting that going in one direction.

Leonard Murphy: Uh-huh.

Matt Nelson: I really believe it can move move mountains and change change industries and and that's kind of why we're in this game a little bit is to to shake things up and see what we can do with it.

Leonard Murphy: Yep.

Matt Nelson: And you know it's great to have Hugo and the Black Swan team as part of that now.

Leonard Murphy: Yeah. So, so I said that was going to be the last question, but it's not. This just occurred to me. One more thing. My take is that we are in an era of one long black swan event, right? I mean it just seems like it is just a continual process of of change that affects consumers people at the individual level and that's what kind of triggered this thinking about your team um and there so things that drive our behaviors change our priorities our values uh and continue to evolve and I don't see a place where where that we reach some stasis right so the uh I think it continually is going keeps shifting um which is obviously why you guys exist because brands need to well yep things are changing we need to understand that we need you know we need data uh to understand changing behaviors and preferences for consumers but I hadn't thought about it from the standpoint as a CEO of managing that within an organization of that size as well so one both of you and this could be the final do you agree that we're in this process of change constantly um uh and that helps underline the value of the business and does that also create interesting opportunities for you as leaders in the business in adapting even internally um to this weirdness that we the world seems to be now uh Hugo why don't you uh uh just chime in and Matt we'll wrap up with you Yeah, I don't know about we can't we can see that it's coming.
 
Hugo Amos: I think technically it's not a black swan event because we can kind of see it coming, can't we? But um so I uh true.

Leonard Murphy: I don't know if we can always make out what it is though,

Hugo Amos: Um yeah, I think yeah, we've kind of touched on it, haven't we? I mean, I think it is a it is going to be a period of of massive change and constant change. And I think that is both opportunity and challenge I think in and and Matt has much more experience than me, but I'm getting getting up to speed quite quickly with what it's like to run be in a company of 1200 people and that it is um it is challenging to to change quite a large organization and change the DNA and bring bring people on that journey of change and that will be I think as critical to future success as it is making sure we have the right proposition for customers and we do the right thing for that. So it is it is absolutely about the opportunity but also the challenge on on doing that on both sides.

Leonard Murphy: Right.

Hugo Amos: So um so I I suppose the short answer yes I completely agree and I think that's um that really is I guess going to define the role of leaders in this space for for the foreseeable

Leonard Murphy: Matt, final word on that.

Matt Nelson: Uh I I no I think you're right. Um so there's massive opportunity. You know we've seen it in Mntel because we've been trying to push some some real change over the last 18 24 months. You know you do get fatigue pe people get sort of ti you know it's not tired it's not unmotivated or it's just okay we're going in this direction. I think for us there's that underlying tenant of well what's the purpose of this because that shouldn't shift the purpose should be that sort of guiding light and you know that's basic that goes for anything not just business. Yeah. Knowing that there's going to be forces that are going to knock you left right and center and it could be new competitors could be a quick advancement in technology but it's how do you have that sort of underlying purpose but then understanding that people are going to move at different paces and how are you sort of bringing people along acknowledging that not not everyone's going to be a part of that journey. Um some are are just going to choose not to be a part of it. Some are going to want to lead it. Um and so I think it's being able to adapt to people and understanding that everyone's human. Um and doing your very best to sort of bring that across as a some with something clear underneath it.

Leonard Murphy: I it's a great place to uh excuse me to wrap this up. Plus, I get a frog in my throat at the very end. Um that was very touching, Matt. You uh gentlemen, really appreciate it. Uh thank you so much.

Matt Nelson: Thanks, Lenny.

Leonard Murphy: Where can people find you? It's a good way to reach out to you.

Matt Nelson: Sorry, this sounds silly.

Leonard Murphy: Yeah.

Matt Nelson: As in uh Oh, yeah.

Leonard Murphy: No, you where can people find you? How can people You said we want to collaborate. So, how can somebody saying, "Oh, wait. I

Matt Nelson: Yeah, right. Uh, sorry.

Leonard Murphy: Have an idea. I want to reach Matt." Sorry. Go ahead.

Matt Nelson: Yeah. Um, grab me on LinkedIn. That's the best way to find me. Emails at the moment. I am trying to work out how to deal with them. They are massively overflowing. Sorry, Lenny. I thought you meant And if you need to find me in person, I'm in Chicago.

Leonard Murphy: All that too. Uh, all right. But I wasn't trying to direct people to you uh specifically at your, you know, you're at 122. Never mind. Anyway, uh, yeah, we don't want to give that out.

Matt Nelson: Yeah, I picked I I did pick that up, but it took a while.

Leonard Murphy: Anyway, uh Hugo is LinkedIn or Okay, good.

Hugo Amos: LinkedIn or hello blackswan.com works as well. We uh we actually look at that email address so that one always works. But yeah, LinkedIn is also good. And thank you Lenny. It's been a pleasure.

Matt Nelson: Yeah. Thank you, Lenny. It's been great.

Leonard Murphy: Thanks, guys. I appreciate it. Uh and thank you to our audience. Thank you to our sponsors and our producers. And that is it for this edition of the CEO series. We'll be we'll be back again soon with another one. Bye-bye.