The Consulting Growth Podcast
Joe O'Mahoney is Professor of Consulting at Cardiff University and a growth & exit advisor to boutique consultancies. Joe researches, teaches, publishes and consults about the consulting industry.
In the CONSULTING GROWTH PODCAST he interviews founders that have successfully grown or sold their firms, acquirers who have bought firms, and a host of growth experts to help you avoid the mistakes, and learn the insights of others who have been there and done that.
Find out more at www.joeomahoney.com
The Consulting Growth Podcast
Thought Leadership & AI in Boutique Consultancies – Insights with Athena Peppes
What does great thought leadership look like for boutique consultancies? Join us on the Consulting Growth Podcast as we engage with Athena Peppes, a luminary in thought leadership and artificial intelligence. Drawing from her stellar career at Accenture and her current role as an independent consultant, Athena unveils what makes thought leadership effective.
In this episode, Athena demystifies how boutique firms can leverage AI to distill valuable insights from existing client relationships. Discover strategies to produce impactful annual statement pieces that can strengthen your firm's market position. Athena also explores the transformative power of generative AI in professional services, emphasizing the importance of high-end thought leadership amidst an oversaturated content landscape. She delves into emerging technologies like gen AI and synthetic data, which are making advanced analytics more accessible than ever.
Our conversation doesn’t stop there. We navigate the complex landscape of AI and robotics, reflecting on the multifaceted expectations surrounding AI’s capabilities. Inspired by insights from economist Anton Koronek, we discuss how businesses can better anticipate and adapt to disruptive AI applications. Learn why addressing specific business pain points is crucial for successful AI integration, and hear Athena’s thoughtful analysis on the future challenges and opportunities that AI presents. This episode is packed with invaluable insights for anyone looking to stay ahead in the rapidly evolving world of technology and consultancy.
Athena's website: https://www.athenapeppes.com/
The Thought Leadership-as a Service consultancy: https://www.beaconthoughtleadership.com/
Prof. Joe O'Mahoney helps boutique consultancies scale and exit. Joe's research, writing, speaking and insights can be found at www.joeomahoney.com
Welcome to the Consulting Growth Podcast. I'm Professor Joe O'Mahony, a Professor of Consulting at Cardiff University and an Advisor to Consultancies that Want to Grow. If you'd like to find more out about me and access some free resources to help your consultancy grow, do please visit joeomahonycom. That's J-O-E-O-M-A-H-O-N-E-Ycom E-O-M-A-H-O-N-E-Ycom. Okay, welcome back to the Consulting Growth Podcast. I've got the real pleasure today to be joined by Athena Pepes. We're going to be talking around thought leadership and artificial intelligence, and it's quite rare that you can get someone who can talk on both of those topics fluently. And Athena's had a fantastic career at Accenture and has been involved in thought leadership for quite a few years now, both in terms of research for thought leadership and also being a subject matter expert on the topic. So, athena, I'm over the moon to have you on the podcast. Welcome.
Speaker 2:Thank you, joe, and I'm over the moon to be joining you today, so thank you for the invitation.
Speaker 1:Thank you. Could you tell us a little bit about how you got into thought leadership and also, you know, since leaving Accenture, what you've been doing and you know what your niche is? Please?
Speaker 2:Yes, sure. So, as you can imagine, thought leadership is a niche field in itself. So no one leaves university kind of aiming to go into thought leadership. So, as many others in this space, I ended up in it almost by accident. So I studied economics, that was my training. That was the first phase of my career. I worked as an economist in insurance and then in shipping, so very much kind of demand supply forecasting space. And then the financial crisis hit, the Great Recession, and I started thinking about the value, I guess, of forecasts for business and questioning that a bit more. And then I moved on to Accenture where, as you said, I spent 15 years there working on research, both leadership projects, with the aim of focusing on technology and economic trends and helping organizations think about emerging problems that they might have, that they might not have realized they are coming up. So thought leadership is.
Speaker 2:Maybe we can get into a little bit more about what thought leadership is in a minute, but you know, as you asked, what my niche is.
Speaker 2:My niche is kind of a focus on technology and economic topics. As you know, as expected, artificial intelligence is hugely important at the moment, and then always approaching that from the angle of thought leadership and also foresight, but foresight is more like a set of tools that can help you develop more creative thought leadership, and right now I work as an independent consultant. I'm the founder of two consultancies. One is strategic foresight consultancy that helps my clients anticipate and reimagine the future and then how they might act differently, and the other is a thought leadership consultancy called beacon thought leadership that I've set up as a partnership with three other co-founders that I've worked with in the past and I think we were talking the other day worked out that between us we have something like nearly 100 years of experience in in the space of thought leadership and so, yeah, very excited we're launching that more formally soon and very excited to be doing that oh great, okay, how good.
Speaker 1:Best of luck. Um, yes, thank you. Let's do what thought leadership is to start, or what good thought leadership is, because I think a lot of people think that their, their blog or their tweets or their linkedin post is is thought leadership thinking about the listeners for this podcast. I, who tend to be boutique leaders, um, I guess, with between 20 and 300 or a thousand people at most, um, what should, should thought leadership be for them and what could it do for them?
Speaker 2:that's an question. So, as you said, thought leadership is probably one of the most misused terms in in business and marketing, or misunderstood. It's really about shaping a narrative around a business problem that's backed by evidence ideally original research or robust research with the aim of persuading and influencing your audience to act in a different way. So the kind of three pillars of good thought leadership are new ideas about a business problem, which you know a lot of the listeners on this podcast will have right. If they're founded a consultancy, it's aimed at solving a problem that that they've identified.
Speaker 2:The second is original research. That can be quant research, qualitative research. So, for example, depends really much, very much, on the kind of problem that you're focused on. But nowadays, with artificial intelligence, there's a lot of new quantitative research that you can do as well. We can come back to that in a minute. And then the third pillar, in addition to new ideas and original research, is persuasion putting that together in a way that is memorable. It tells a story and influences your audience to take action. So not necessarily a TikTok video or a tweet or anything like that, but there is something to be said about using different mediums to get your message out there, so you might have those three components. It might result in a robust kind of lengthy report, but it might also look like an article published in Harvard Business Review or in Forbes or video content, because we know people consume thought leadership in very different ways as well.
Speaker 1:But you know if you've got any high quality asset. You know, thinking about that funnel. You know, if people don't know the company and they're you know scrolling through LinkedIn, what's the thing, what's the message that's going to cause the right people to stop the scroll and then they're not going to. You know, necessarily pick up the 10,000 word paper and read it, it and then thinking about the middle of the funnel and the bottom of the funnel and perhaps even the sales process itself. When you can send bits of thought leadership to people, I think that's a really important point yeah, I agree, because people you know people have different styles.
Speaker 2:Some people are quite analytical. They really do actually want to see in in my experience, the very lengthy you know, 100 page report. They like getting into the details. Or they might come across an interesting kind of hook on social media and then follow up with a lengthy report. Others just want the high level message and an overview of how it's backed up by research and an overview of how it's backed up by research. So that's why you need, I guess, a suite of different outputs from your thought leadership as well.
Speaker 2:And if I can come back to the question you raised before in terms of what can thought leadership do for this audience, what might be the benefits of it? I think one important benefit is kind of it enables new conversations, you know, discussions with potential clients that are perhaps more natural and not necessarily sales focused. You know it's a very it's a very different starting point sharing with someone an article you've written that's focused on a problem that you've identified for their business, and talking to them about the research you've done on the problem and the new perspective you bring on it. And it's very different asking for a sales meeting. So it can enable new conversations, conversations, engagement with new clients.
Speaker 2:The second thing is also trust and enabling companies to find a niche as well, um, or at least to show what that niche is. The big companies, fortune 500. They have an established band, a brand. They've got a lot of you know a big marketing machine around that, um, but a medium-sized consultancy or small size consultancy can establish a lot of brand equity through their thought leadership as well, and it can allow them to own the niche that they've identified and, you know, build around that, as long as their thought leadership is obviously aligned with that as well.
Speaker 1:Yeah, my dad always used to say to me you know, have a perspective, yeah, when you're talking to someone. The trouble with a lot of the AI-generated stuff that we're starting to see coming out is that very often it's pretty bland and in effect, I always tell my students you know, but for a marker you want to see an argument you want to say you know I'm arguing this because of ABC rather than here's a description or here's a list of 20 things that you should think about.
Speaker 1:And having that perspective, I think, is something boutiques can do better than the large firms, because they can afford to piss people off because they're not selling to the whole of the market they're selling to the 100 or so that that perhaps chime with them best there are a lot of benefits.
Speaker 2:I agree with that, and I think there are a lot of benefits like being able to be very close to the, to the clients, um, that you serve, getting them involved in the research, uh that you do to. You know, for your thought leadership as well, which you, you know, perhaps larger consultancies might not be able to do they've got different things they can do but, um, I definitely agree with that that there's a having a perspective. Backing that with the evidence as to why you have that perspective as well is important, and not just sharing a laundry list of. Well, here's some stuff I came across and put together in a in a short blog for example.
Speaker 1:I don't think they still do, but I know that Source Global Research used to do awards for thought leadership. But in terms of you know where your work has, or your team's work has, either won awards or really moved the needle on client engagement, what was the uh secret formula? What were the three or four things that you got right? Or is it just difficult to tell?
Speaker 2:yeah, so so still does those rankings as far as I know? Yeah, that's right, and uh, I'm not sure who's top at the moment, but Accenture was number one quite recently, and has been for some time, in terms of the secret formula. I guess the key is to bring original ideas, original perspective innovative research as well. Perspective innovative research as well. So I mentioned before how there are new things that we can do with research that we couldn't before. So, for example, being able to analyze, using natural language processing, analyzing news articles to pick up what's top of mind and how that breaks down across different industries, for instance. Or when business executives talk about a certain topic, what's the sentiment around it, for example, what's the feeling, what are the other topics associated with that issue. So that's kind of some of the new research that can be done.
Speaker 2:So original ideas, ideas, differentiated research and also some call to action, but without it being obviously very sales focused. You want to give a prompt as to? I get your problem. You can think about this differently. Here's how we're thinking about it. Here's a starter for 10 and kind of leave it at that to create a new sales or a new conversation that might then lead to sales. So those would be the different kind of things that go into the recipe.
Speaker 1:Before you move on to the AI and tech side of things, which I know you know, obviously, coming from an Accenture background, you've been quite embedded in that for a long time. But before moving on to that, so I'm interested in the type of research and content that your busy boutique leader could get their hands on to that. Perhaps you know they can't, if they can't afford to do what Accenture or Deloitte could do.
Speaker 2:Yeah, that's a great question. My personal belief is that the kind of time and budget that they might dedicate to thought leadership will obviously differ. But the fundamentals in terms of having a new perspective, creative ways to do research and then, you know, persuasion those you can still develop even with relatively limited resources. I mean, one plug here is obviously that's the kind of thing that we're hoping to help our clients with at Beacon Thought Leadership. Right, we appreciate not everyone can build a whole thought leadership machine in-house, but they recognize the value of thought leadership so we can work with whatever resources they have to help them, you know, craft and shape their own thought leadership or offer thought leadership as a service.
Speaker 2:Now, in terms of what can you, you know, do with what you've got I mentioned before? Right, you've got one-on-one relationships with your clients. There might be ways to, for instance, conduct interviews and then codify those interviews. You know there's so many easy ways nowadays to generate transcripts. You can create new insights from those transcripts, either using generative AI or, you know, with the effort and or the effort of the marketeers or researchers or whoever might be involved in this project as well. You can also partner with others as well.
Speaker 2:I think there's opportunities sometimes to create. You know, if you want to be the owner of a niche, you can create a community around this topic, so you can ask for partners that are also interested in the same business problem and then, you know, share the resources around that. I think that's quite common in thought leadership. So, using new tools, partnering with others that share your kind of passion about the business problem you're looking to solve, thinking more creatively about access to people and insights that you've got in-house, those are some of the things that you do house, um, those are some of the the things that you do.
Speaker 1:It doesn't work for all firms, but I'm quite a fan, with a boutique that is big enough to afford it, of doing a statement piece. One of the keys to success, of growth of of a boutique up to, say, 100 people, is getting that niche really, really tied down and there's nothing like sort of an annual statement piece. You know the state of the union address equivalent.
Speaker 1:Great thing about this is that piece can evolve year after year to emphasize different areas, but also it becomes part of the furniture of the firm and you know. Then you start to build, you know press releases around it, you start to get into new publications and and that can be such a big asset, especially if a firm you know when a buyer is looking at a firm. All firms say, oh, we've got a great brand. But if you do have this statement piece that's based on consistent research and has been going for a few years and really speaks to your brand and what you do, it's such a powerful asset.
Speaker 2:Absolutely is, and you know that needs the thought leadership. We touched on this before. The thought leadership that you develop needs to build on the brand that you're looking to. You know to create and establish. So there needs to be alignment and definitely consistency. It's kind of it's your own body of thinking that you just build on over time and evolve as your research evolves. So, absolutely agree, it's not like you do it once and that's the end of it. Having that statement piece that you mentioned and then building your thought leadership around, that is a great anchor for the work that you do.
Speaker 1:Yeah, let's move on to AI, and I realize there's quite a bit of overlap, because obviously AI can help us do thought leadership, as you said transcribing things, analyzing things but also you can do a thought leadership about AI. You can do a thought leadership about AI.
Speaker 1:Now I'm obviously specifically interested in AI and professional services. I just got off a call just before this one and it was a guy from who's, based in Ethiopia, American educated, who basically said to me oh Joe, you know, we're looking, I've got this passion and I've got this great idea about transforming business in Africa, but I can't get enough people and can't afford enough people. How do I, you know, use AI to replicate people? And we had a conversation around that, which is, you know, we're a few years off from that at the moment. You know, the way I see it at the moment is you've kind of got task-based AI, which kind of we're now on top of doing the PowerPoint, writing this, analyzing that.
Speaker 1:The steps that we're moving towards is process-based, generative AI, where perhaps it can do the analysis and write the report and sense, check it, and there you might have agents running the tasks. But the third step really is where you have that employee, or would have that employee, who manages and thinks for themselves and ties things up in the organization. We're nowhere near that final step where you can replace people, well, replace professional services with AI, but you can replace tasks with AI. What are you seeing out there, Athena? What's got your interest, both in terms of what you do in terms of producing world-class thought leadership, but also what you're seeing in the professional services space more generally.
Speaker 2:Yeah, the hot topic at the moment, I think. Maybe, for the purposes of what I'm about to say, just to clarify, I think I'll focus on generative AI more specifically, because I think that's the kind of real game changer for professional services. But I would like to touch on a couple of other emerging not necessarily emerging fields, but hot fields like causal AI and synthetic data that are also transforming thought, leadership, supply of leadership, because it's kind of reduced the barriers to entry. You know democratized access to a lot of things that might have before been the remit of the big professional services firms. You know, we talked about something like transcription. Right, it seems relatively low impact, but that can enable you to do multiple interviews that you couldn't before because you would have had to think about the fact that each one would cost you, you know, two hundred dollars to type up or to translate. You know so and then the time involved. So you might have said I'll just do 10 interviews, but now you can perhaps do 50 or more, and then you would have needed, say, two or three researchers to analyze those. Now you don't, you could do that with one. So it can actually even small things like that can have quite a big impact when you look at it across the whole journey of thought leadership. On the other hand, I think it's also increasing the demand for really high-end thought leadership, because in a world where we're flooded with content, you know you need a thought partner even more, someone to help you make sense of what's being talked about out there, so affecting both the kind of demand and supply dynamics of thought leadership. It's also changing the skills required. You know you need to see AI and generative AI more specifically as a co-pilot, someone that can help you.
Speaker 2:As you said, we're a long time, I think, from you know general artificial intelligence, where they can fully replicate exactly what a person does, but we can think about tasks that would be quite laborious, boring. How can they be taken away? Or use generative AI instead so that people can focus on the stuff that's more fun, or collaborating or brainstorming together about new ideas, for example, one of the limitations with B2B research is that a lot of the outcomes is very hard to disentangle. Correlation with causation, right. So a company that has certain innovation capabilities or does well in certain innovation metrics might also have really good profitability, but you don't necessarily know that one leads to the other.
Speaker 2:So the promise of causal AI is that it can ask what-if scenarios and it can actually help you get around those research gaps, and there are a lot of companies out there that can help you do that. You know data the kind of cornerstone of all AI that can also be a limiting factor. We talked before about how can you make the most of what you've got Before you'd have to, for instance, survey thousands of executives, for instance, that can generate data sources for you that have the properties of the data that you need, without you going out and carrying out expensive field work. So, again, I think that's a good example of how access to different types of research is being democratised.
Speaker 1:So I have a very good friend in the NHS who uses synthetic data to mirror. This is the confidentiality issues.
Speaker 1:obviously he's sitting on top of all of the data that anyone's ever used, you know, being captured in the NHS. Now there's obviously remarkable insights that can come from that. So he's building, in effect, a synthetic layer on top of that data that allows him to, or allows third parties even to, do quite sophisticated interrogation without accessing the real data of the people behind it. If I wanted to use synthetic data to help me understand that, do you have any idea how I would go about that?
Speaker 2:So I'm asking from a position of complete ignorance here, perhaps actually quite interested in looking into it from a research perspective yeah, I think, um, the kind of two uh examples where synthetic data can be quite powerful is a kind of creating a larger sample size. So it could be that, um, if you can create a small database of some of the insights that you have, then you can use synthetic data to create a larger sample size that enables you to have more, bigger insights.
Speaker 2:So that might be one way that it could apply to your situation. And then the other is the NHS example that you mentioned, where, for confidentiality purposes or in other cases where you need to protect the data of the companies and the people being surveyed, then you would, for instance, on issues around, say, inclusion and diversity or sensitive topics that it might be difficult to survey your employees on, for example, and you might use synthetic data to do that In terms of like, how exactly you would get started and all of that stuff.
Speaker 2:I think that's where sure you know, a synthetic data experts company would come in how?
Speaker 1:prepared do business owners need to be for rapid development and adoption of ai technology? Um, and also, I guess, how disruptive do you think it will be, especially to professional services?
Speaker 2:The way I like to think about the future of AI is actually inspired by one of the economists I've been following on this called Anton Koronek, and he talks about the fact that the challenge is we simultaneously overestimate and underestimate what AI can do. So we overestimate what it can do and therefore we expect it to be further along than it is and, of course, it is improving super fast. But you know, I'm sure every one of your listeners will have had this experience of using just a basic chatbot on a. You know, I use mine, I think, on bookingcom recently, and it just gives you completely random uh results and you think, oh, but I expect today I to be more sophisticated and advanced in this.
Speaker 2:So you know, I think what we hear in the, in the kind of media and the hype that's kind of around it and, of course, a lot of investment going into the space, there's a gap with kind of our everyday reality. Still, on the other hand, you have people that underestimate what it can do and kind of dismiss it and again, that's not beneficial because, for the same reason, it is advancing incredibly fast. There's a lot of research, a lot of R&D behind it. I think the artificial intelligence field will only accelerate. One of my kind of interests is also in humanoid robotics. Robotics, um, I think that so far robotics has been very much about it being used in industrial settings. Uh, because they perform very well in rigid, fixed environments. But there's a lot of researchers now um embedding llms large language into robotics.
Speaker 2:So you've got companies like Figure AI and Sanctuary AI, that are really kind of breaking the limits of what was possible with robotics and, as a result, we're going to start seeing them in more everyday settings. In terms of how prepared organizations are, I would say there's like a real huge gap between the top performers, the ones that are, like you know, paying a lot of attention to this, really investing into it, and then the rest yeah um, and maybe this is kind of inspired by from my economist perspective here as well, but we know from past experience that it does take a long time for technology to become commonplace across the whole economy.
Speaker 2:right, a lot of what we hear is from large organizations, but small and medium-sized enterprises are still trying to make sense of what it means for them. What are the proofs of concept? How can they use it? About a month ago, I was chairing a conference on the impact of generative AI on knowledge management and insights professionals, and the key theme that came up there was that there is a kind of huge expectations gap, because people expect that they have to be doing something on AI and therefore they just look for well, what can I use AI? But really what they should be doing is thinking what are my problems, what are my pain points, and where would AI be a good fit for that problem? Rather than well, we must just use AI because that's the hot topic of the moment.
Speaker 1:Compared to your standard automation, because AI has progressed so fast, very often its application could be quite surprising.
Speaker 1:And so I always think, when you get genuinely, genuinely transformative technology, the person who knows the business isn't necessarily going to be capable, shouldn't even be capable of knowing where they could be disrupted most. And it reminds me of the business process, re-engineering, transformation where, you know I think it was kod they did the traditional business strategy approach of saying, well, how can we make film cameras despite having invented digital cameras? They did the traditional approach of, well, how can we make film cameras better, faster, cheaper, instead of going, oh, actually that model is dead in the water and I just wonder if there's companies out there that can't. And I guess this is where you can help them. You know, struggle to think out of the box. To that extent, you know, I think project management might be a sort of low level project management. Program. Program office stuff could be an example of that where perhaps in three years time, that doesn't exist as a consulting service, because AI develops the point that it can do it and I just don't know if it's like the frog in boiling water.
Speaker 1:I don't know if owners of firms or the bosses of firms who have been through that traditional process are necessarily best placed to think about what it can do for them. I don't know.
Speaker 2:Yeah, and I think I get the point around whether they're the ones best placed to kind of imagine the possibilities. I would add two things that I mentioned just now about the conference and that one of the key top um kind of themes that came out was this let's not just use ai for the sake of it, let's think about the pain points. What's interesting is that that was very much. You know that the audience for that was professionals, business execs, drawn from different fields, so law, private equity, consulting, banking. Just yesterday I came across a report by the Rand Corporation.
Speaker 2:And what they did was they interviewed 65 experts on artificial intelligence and machine learning. So they took the other approach of. We hear this from business executives. We want to know what the AI experts are saying that have been involved in AI project implementation. What have they seen as the key challenges and barriers and what success factors are coming from this? And it was a key theme in that report as well.
Speaker 2:I'll share it with you if it's if it's of interest yeah, great, thank you so that was a key theme there as well that you know when you just kind of are looking to to plug it in anywhere, then you haven't really properly thought about what kind of impact are you looking for? Is that that the right fit? And then the risk is that the project fails, so to speak. It doesn't get the outcomes that you want. And then you become disillusioned with AI because you think, well, I tried it and it didn't work, so there's no potential. Where, in fact, there is a lot of potential, you just didn't apply it to the right you know context for your organization, the right use case for your organization. So I think that's the point around making sure that you focus it on solving problems. Now, in terms of innovation and thinking outside the box, that's where foresight, strategic foresight tools can help, because they try and get um, you know individuals, teams, organizations to not only be thinking about how do I innovate for today, but how do I innovate or create business products for five years, ten, 10 years? Well, 10 years, who knows? But you know three to five years from now, because the mindset that you need is very different and it's really hard for all of us to break out of that you know what's happening today, of today's bubble, and really think more creatively about what's coming. I mean, three years ago would we be sitting here talking about synthetic and causal AI and how it's transforming thought leadership? It was an emerging trend. I just think sometimes people underestimate what is coming and it's hard to participate in those things.
Speaker 2:Just one more thing to add on AI, which is that it's a lot easier to think about how we can change existing processes rather than help reimagine. You know all of what you can do. I talked about this in the context of research before. Right, that we can think about how we can save time on things that we do already, like the interviews, for instance. We've been doing interviews for a long time. It's very easy to think about how we can save you time and effort on interviews, but there's also a bit around. Well, what kind of data sets do I have or do I have access to not necessarily my own that are becoming publicly available, that I could analyze using different types of chat, different types of GPTs, to have new insights? That is a lot harder, so, and that is, I think, where a lot more investment will, an effort um will go into. Uh, as AI progresses.
Speaker 1:That's the next yes, yeah, and of course, the thing you know this is what papa said the thing is about. The future is that it's impossible, you know it's impossible to know because we're dependent. Knowledge depends on new technology being invented and some predictable consequences. So interesting times ahead, absolutely. Yeah, athena, thanks so much for your time, really really appreciate your, your expertise. We'll put a a couple of links, um in the in the show notes to your uh, your company's beacon and your personal website, and hope to keep in touch with you thank you very much, joe, pleasure to join you today thank you.
