#118: "AI tools help stimulate creativity, humans think beyond" - Stuart Whayman, President of Corporate Markets at Elsevier

0:00I think AI tools and other tools can help stimulate creativity, but in the end they're always very much grounded in what has happened before, what the model has been trained on. And I think humans do have a propensity to be able to think beyond and think differently. On the other hand, AI tools can help that happen more quickly. So as you rightly say, it's a partnership between the tool and the human.

0:31Relics Group is a quietly powerful force in the world of information analytics and scientific discovery With a presence across legal, medical, technical, and even events, the organization sits at a unique crossroads where data meets decision-making and where artificial intelligence is beginning to fundamentally reshape research and development. Today's guest is Stuart Wayman, president of Corporate Markets at Elsevier, a part of Relics Group. An Oxbridge maths graduate, Stuart has spent much of his career helping to steer the company through its transformation from a print-heavy publisher into a data-rich AI-led business powered by some of the most advanced research institutions and enterprises on the planet.

1:19We discuss Stuart's personal journey, the lessons he's carried forward from academia into the consultancy world and then into industry, and how AI is quietly but profoundly shifting the way R &D is carried out, particularly in the domains of pharmaceuticals, scientific discovery, and beyond. We also explore how Relics Group, which includes LexisNexis, builds trust into its AI products, tackling thorny issues like hallucination, bias, and also model drift, challenges that many businesses are only just beginning to grapple with. This conversation is an illuminating look inside a company that often operates behind the scenes, but whose tools and data shape critical decisions around the world.

2:05This is Stuart Wayman.

2:12So Stuart, thank you so much for coming on the Tech Leaders podcast. I've been really excited to talk to you. I know Relics, Reid Elzevira reasonably well as an organization. Very exciting time for you guys. So much to dip into. But let's start with the eternal opening question on the Tech Leaders podcast. What does good leadership mean to you, Stuart? Good leadership. I mean, there's a lot of different qualities that come into it. Clarity, vision, good judgment, all of those pieces. But I think the thing that is most important for me and the thing I've experienced from great leaders I've worked for, but that I've always tried to sort of live out in some respect is some level of what I call serving leadership.

2:55So recognizing that in the end, as a leader, you're serving customers and you're serving teams and a wider organization. Early on in my career as a manager, you sort of think when you go into management, you become the boss, right? And people are going to do what you say. But that's actually not what it's all about. And I remember going on a training course quite early on as a young manager. And I think we saw a video of a squadron leader of the Red Arrows. He's got a team of people who are flying these amazing planes at high speed, incredibly dangerous, but very, very talented. And I was very struck by the fact that as a squadron leader, you're thinking, well, he's the big dog, right?

3:36He's the one. And actually, he basically put himself down and said, no, actually, what I am, I'm the enabler. I'm the one who removes all the barriers so that my talented team can be the best that they can be. And I think as a leader, in the end, that's what you want out of your organization, to make them be the best that they can be. Yeah, absolutely. Well, you've nailed it. That's exactly what leadership is, isn't it? Well, that's just getting the best out of others, obviously, the cliche, but ultimately that's a lot easier said than done. Red Arrows is a great example. Do you know what? It's funny you should say that, Stuart.

4:08I watched them on the weekend. It was the Wales Air Show in Swansea. We went down and watched them on the beach. And I'm just always in awe of them. It's just they never fail to impress. I've probably seen them 50 times and it just never gets boring. It's just phenomenal. But that's certainly an environment where good leadership is necessary, isn't it? No, that's a really good answer. So look, a couple of the listeners may be aware of Red Elsevier, but may not be aware of yourself. So could you maybe give us a little bit of an overview of your backstory, maybe starting with why you chose to pursue the career path that you did and how that sort of played out?

4:43So an overview of education days up to joining Read Elsevier. Yeah, it's been quite a journey. So I'm a maths graduate in terms of academic background. Probably when I was starting out way back when, I didn't imagine that I'd be in the environment and the world that I am in now. When I was really young, I thought I might like to be a sports journalist. That was my dream job. I love sports and I love talking. and I thought that would be a great thing to do, paid to watch sport and all of that stuff. And then I realized that through education, I was probably better with numbers than I was with words.

5:21So I ended up studying maths. And then as I was sort of developing and thinking, what do I want to do with the rest of my life? I was also thinking the thing that kept coming back was working in business. And there were a couple of things that sort of took me down that route. One was my dad. So my dad was a leader of a local regional building society. And I was always really struck by the way he always believed that there was a really positive impact that his organization could have on the local community and on people. And that sort of vision for the positive impact that an organization can have.

5:58And I was quite struck by that. And I was also struck as a teenager by there was a TV series. I don't know if you remember it. A guy called John Harvey Jones. So he's the old chairman of ICI. And he had a TV show, end of 80s, beginning of 90s, called Troubleshooter. And he went into lots of different businesses looking at how they were doing. And obviously, they were probably underperforming businesses. And they'd go in no nonsense and tell them what they needed to do. But what I was always struck with, my takeaway, and I'm sure there were lots of other messages from the show, but my biggest takeaway was always, are you really serving your customers?

6:30Are you really where the market should be? Actually, if you do, you can have a real impact. And so this idea of having an impact, doing something good that customers really want, is something I thought, well, that's something I'd like to be involved in, in some shape or form. So being numerate and having that kind of motivation, I went into training with KPMG to get into accounting, just because I thought, well, that might be a nice route into business. So I did training with KPMG out in the regions, saw lots of little different businesses, pig farms, breweries, you name it. And at the end of my training, I was very focused on how do I make sure that I see something different to what I've just trained in.

7:13So these are small businesses, but I hadn't seen a large multinational global, and I wanted to get into industry, into business. So I started looking at different businesses in different industries to see what might be interesting. And to be perfectly honest, the first organization that offered for me was Reed Elsevier as it was then, RelX Group as it is today. And it was very interesting. I joined in the financial planning and analysis team just as an analyst. I was struck by the information focus. Information is something that I have an affinity for. I like books, I like data, I like information.

7:51And so there was something there that I liked, but I still, I joined and I thought, well, I'll be there three years. and then I'll do something else and I'll explore something else. And 27 years later, here I am. So yeah, I probably should go on to the rest of the journey, but that's probably where it all started out. That's fascinating. Can I rewind you back a little bit? Obviously, I know you studied maths at Oxford University. Can you talk us through, obviously, a very prestigious course in a very prestigious institution? What lessons did you learn from studying at Oxford, do you think? or what value did you take from that experience which has stood you in good stead through your career?

8:30It's definitely not the maths. I had the depressing moment of finding my books in my parents' attic a few years ago, not being able to understand a word that I'd written with my own handwriting. I mean, the maths was interesting, but it was pure mathematics largely. And I'm quite an applied and practical person. I did it because it was a great course to do and it was great to stretch the brain. My biggest takeaway, I think, was having confidence to tackle hard problems, to apply myself to hard problems, and to have different strategies for solving them in different creative ways. I came from a state school.

9:06I didn't come from a private background. And so going to Oxford, I think, gave me quite a bit of confidence that I could play at that stage, if that makes sense. But it also taught me that lesson. And I love solving problems now. And yeah, it gave me that confidence to do that. So do you think being amongst very mathematical peers, top of the food chain in terms of the British mathematical community, if you like, obviously the maths course in Oxford is obviously renowned. Are you saying that being in that presence, having those peers, that's what gives you more of a determination to solve complex problems?

9:42Is that what you're saying? I think it's a bit of that. I mean, I think I learned a lot from other people. I think you also learn a lot of humility and learning from people who've got brains that are 10 times the size of your own is one of the things you learn very quickly, which is there are problems you can't solve, but there are people who can solve it and you can work with them on those difficult problems. So I think learning to work with others is what is one of the lessons. A bit of confidence of being able to stretch your brain to apply yourself to those difficult things. Those would be the key lessons.

10:16Yeah, sure. So you're obviously a numbers guy then, Stuart. Do you have that mentality these days as well? You said information, you're interested in information. I'm assuming you're interested in data. Can you talk me through how that's manifested through your career and how that's benefited you being a numbers guy in a business leadership role? Yeah, so I think from a numbers perspective, yeah, numbers are something that interests me. I feel very at home looking at numbers. I think probably what stood me in good stead is the ability to quickly spot patterns in numbers. So you can quickly analyze and digest and be able to make good judgments around them.

10:55But I like to think that I'm more than numbers. I mean, I do enjoy words. Back to where I started, I wanted to be a sports journalist. I actually enjoy reading an awful lot. And I actually think one of the things that I like to try and do is be quite broad in both my interests and my approaches to different problems and with my teams and with the business. So numbers are definitely, there's an analytical core to me probably, but I'd like to think to continue to learn and teach myself to go beyond that. Maybe should I sort of take a little bit of the journey of having joined Ralex as sort of some of the, a couple of the steps along the route after that.

11:35Well, yeah, I did. That was my next question. I was wondering, just to maybe reframe that a little bit, Stuart, if you could tell me about the type of organization you joined, okay, and compared to the organization you are today. That's a fascinating question. Back then, I would say it was relatively, well, at the time, it was a dual-listed organization, which had its own challenges from a management structure perspective. Read El Cervere as it was. It was dual-listed UK-Netherlands with two boards. As an organization, it was incredibly print-heavy from a product perspective. So when I joined back in 1998, digital meant CD-ROM to a certain extent, which is quite scary.

12:18Yeah, I remember that. And of course, the internet was out, but actually making money from the internet was still another stage away. And there's been just so much change in the information sector since then that it's been a fascinating journey to be on. So we obviously did the jump from print to online, online through Web 2.0 to data and analytics to tools. And now, of course, we've got generative AI. And the changes that come from that are quite profound. They happen over a period of time. They don't happen immediately overnight, but over time, as an organization, you become more technology focused, you become and have to be more agile and speed focused, and frankly, more customer focused as well as the customer's needs are changing more quickly over time as well.

13:12So there's a lot of things that have changed from something that was probably relatively slow moving and quite stayed back in the late 90s to something that is really quite innovative and agile environment today. So when you joined, it was still in the stage that there was remnants of the old print world there then? More than remnants. That was inherently still a hardware business then, essentially, then, yeah? And you've seen that digital transformation and that shift over to software. Can you talk us through that journey? How painful or how successful has that journey been for the organization, Stuart?

13:49There's been lots of different stages of it. I think it's always been a focus on not just chasing the new technology, but working out what can it do for our customers? How does it actually change the value proposition for our customers? And how do we use technology to improve the outcome for our customers? So actually, in some respects, the change has been relatively gradual over that 27 years. There's not been many, if I can call it, real big bumps in the road. It's been sort of change. It's been a step here, a step there, an acquisition here, a new product there, but keeping with the curve and sometimes ahead of the curve to make sure that we're meeting the needs of the customer.

14:33So it hasn't necessarily always required big, systematic, if I can call it restructuring and complete pivots. Probably the one piece that I was involved with where there was more fundamental change, I was at Rebusiness Information back in the late 2000s. So late 2000s, of course, synonymous with the financial crash. and read business information at the time was a business that was it had a mix of products that were serving vertical b2b markets with information products but those products included print magazines so things like computer weekly farmers weekly but they also had data products we had data products in chemistry in banking in other places and actually we were put up for sale by read Elsevier as it was then in 2008, because it was a business that probably underperformed, but it was also very heavy in terms of advertising revenue.

15:32And Relics recognized that actually, if you were really providing value and information to the customers, they're going to be willing to pay you for that content. It's not going to be sponsored by advertising. And of course, it's going to be much more reliable and recurring in that sense. And so we were put up for sale as a business that was much more heavily advertising driven. And I lived through that process. I was very involved in it. And actually, it was a failed process. So I spent an entire year working on a sale process. It was probably a year I put in more hours than any other year. And I got to the end of the year and the plug was pulled on the disposal because the financial crash had happened.

16:15Our advertising revenue was going down. There probably wasn't the money in the market for a deal like this. And there we were, having worked incredibly hard to be disposed of, now part of an organization that wasn't sure if it really wanted us or not. And then the next few years was all about transforming ourselves more organically. And it was quite a formative time for me in lots of different ways. I ended up being promoted to the global CFO role after a couple of management change rounds in 2010. And we then went on a process with the chief executive of actually selling off those advertising magazines and really investing in the data services and making acquisitions in that space.

16:57And that was slightly more transformative, probably not at a Relics level, but certainly at a business level. It was a much more active step change in the business model and the focus on technology and data. Okay, so I want to move it on then because I'm just keen to talk about the evolution of data. So how have you seen the role of data sort of evolve as like a byproduct of operations to a strategic asset in enterprise decision making? Do you know what I mean? Can you talk us through the evolution of data becoming information for companies to base decisions on? Yeah, so data is incredibly valuable to organizations.

17:34I think that almost goes without saying today. And it's almost amazing to think how organizations were run if you go back 20, 30 years and how little data was available or how late that data was available. And now we take it for granted that data is available immediately. We can have data on customers, on products, on ecosystems that help us to be able to make good decisions. And so we started out as an information business. So at Elsevier, our heritage 140 years ago and since has been around peer-reviewed scientific content. But over the years, we've added data sets on top of that that enable our users and our customers to be able to make better decisions.

18:23So it's not just about reading information and being able to take information and then make judgments around that. It's giving them data points that actually enable them to put measures on that and make sure much harder, objective decision making. In terms of, obviously, the companies that generate data, but they don't extract meaningful, actionable information from it, do you know what I mean? And the ones who do, what kind of separates companies who basically act upon the data and companies who don't? Is it because of technology, Stuart? Is it because of just decision-making at a business level?

19:01What advice do you typically give to companies to basically store and basically make data core to what the decisions they're making at board level? Is it a technology conversation generally you're having, or is it more of a cultural thing? I think it's a bit of both. So people's ability to get to important information, certainly their own information, can sometimes be limited by technology and their own data flows. But of course, then there are providers like ourselves who can provide data sort of off the shelf, if you will. And then it is sometimes about helping customers to understand the value of that, that actually a small investment in a data or information tool can help them have a really large return in terms of the improvement in their own processes and outcomes.

19:53So the part of Elsevier that I lead supports corporates who are doing research and development. So the tools that we're supplying to them and the data that we're supplying to them are going to help them be more successful in their research and development, have more chance of success. They're going to help them to get there faster, and they're going to help their researchers to be more efficient. And I think companies that are able to recognize those benefits are more willing then to invest in data solutions, in data products, and not just see it as an interesting piece of information that's a cost.

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21:30So tell us how AI is going to change how you guys operate then and the value you can offer your customers. I understand you're working on a few new products and services at the moment. Can you tell us a little bit about that? Yeah, absolutely. Let me take a step back and maybe just give a little bit of a picture of the sort of things our customers do today and then how AI will help them and our products will help them. So for those people who are working in research and development, a researcher, our tools today support them across the whole research and development lifecycle, all the way from ideation, idea generation, where shall I invest my time in terms of new research, all the way through to post-launch monitoring of maybe it's drugs, safety, and sort of things that they need to monitor post-launch.

22:21But if I take the first bit, the idea generation, that is an enormous amount of time that is spent on that. And it's an incredibly valuable step, actually both in academia, but also in corporate, because no researcher sort of science doesn't stand on its own a piece of scientific research doesn't stand on its own i think it was isaac newton who said that scientists stand on the shoulders of giants everything is built on the research that came before it and so for a researcher before they start looking at where am i going to go they need to know what research has already been done so there's a lot of work that goes into scanning the scientific literature peer-reviewed literature to identify what has been done in a particular field, what hasn't been done, what experiments have already been done, what's worked, what hasn't worked.

23:11And researchers will spend an enormous amount of time scanning that literature. And that literature base is growing significantly each year. So each year, there are millions of new scientific articles that are published. And so researchers work in this sort of sea of information, trying to sift through it to find a sweet spot for where they're going to invest their time to make a new discovery. So that's a, today, we can sell them databases and content sets, but they're still having to do that search and discovery. What we've been investing in is applying AI to those content sets to really speed up the work of the researcher.

23:51So let me make that real. Instead of a normal search, if I can call it that, of the literature and getting a long list of hundreds of articles. We're able to do that with natural language search to find a much more finely tuned set of articles that actually answer the question, not just the topic name or what have you, answer the question, summarize those articles, and then to do some really cool stuff like take those articles and actually provide a comparison of the experiments that are actually documented in those articles, which is actually a piece of work talking to researchers. They can spend weeks and months doing themselves by hands today.

24:30And actually, we can get that done for them in a matter of minutes. So that's a tool called Science Direct AI. And we believe that's going to make a real difference to scientists, both in academia, but in corporate in terms of making them a lot more efficient and speeding them up. Because for corporates, they've got incredible valuable resource there with researchers with enormous brains, enormous capability, but they want them to be doing that brain work and not just busy work. And today, research is doing a lot of that busy work. Yeah, absolutely. So today, ScienceDirect is our database of all of our content articles, scientific articles, and ScienceDirect AI is now the newly powered AI product.

25:12And we've similarly taken each of our products today and added AI functionality to them over the last year and launched them. So we have a product called Scopus AI, which scans not just our articles, but the whole world of science. And then we have specialist tools in life sciences, where we've recently released a tool called Embase AI, which is more specifically focused on literature in the life sciences domain, which is quite pertinent for pharma companies in corporate world. Yeah, sure. So these products then, are they based on your own large language model that you've trained then? Or are they plugged into models like Claude or whatever?

25:54Or have you built it all yourself? No, we're not a builder of large language models. So we're very clear. We license the large language models. But what we do do is build the technology of how to apply the large language model to our content to get a better answer. Because today, a large language model standing alone is what it is. It's a language model. It's not necessarily a truth model. And actually, we believe that the level of trust that someone can put in a product and a service goes up a lot more if they understand the content set that it's being applied to. So we're using our own technology, applying, combining the language model, our existing databases, our content to be able to provide these results for the researchers.