#283 Data Storytelling With High ROI: How to Create Great Thought Leadership with Cindy Anderson & Anthony Marshall, CMO and Senior Research Director at IBM

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We know that executives spend somewhere between two and three hours every week actually reading consuming Thought leadership. So you need to know what that sort of aha message is. That real hook before you get started. We believe ROI is going to be the measure of success for thought leadership moving forward. There's a 16 times premium for thought leadership ROI compared to a typical marketing campaign.

The way we think about generative AI is within the context of the value chain for thought leadership. Where can we insert it? At specific places to improve scalability, to improve productivity, to deepen analysis.

Welcome to Data Framed. This is Ritchie Data storytelling is one of my favorite topics on this show. Today we're going to look at one specific type of data story, namely thought leadership. This typically means white papers, but it can be anything where you do some original research, crunch some numbers, and turn the resulting analysis into a business story that helps executives make decisions. One of the great things about thought leadership is that it's a type of data story that can make you, or a least your business money. That means that learning how to make thought leadership is an incredibly valuable skill. I have two guests for you from IBM's Institute for Business Value and they've just written a book together called the ROI of Thought Leadership. This, rather pleasingly, is thought leadership. About Thought Leadership Cindy Anderson is the Chief Marketing Officer and Global Lead for Engagement and Eminence. I must confess, I don't quite understand the second part of that job title, but it does sound cool. She has more than 30 years experience as a marketing executive and she currently runs a team of 30 editors, designers and marketers. On top of this, Cindy founded the Global Thought Leadership Institute at the business productivity nonprofit apqc. Anthony Marshall is Senior Research Director of Thought Leadership where he leads a top rated thought leadership analysis program and runs a team of 60 technology and industry experts, statisticians, economists and analysts. He's been working in thought leadership since 2011, having found his way into this field from Management consultancy. Anthony also works at APQC as the chair. Now, discovering how to make money from data stories is far too exciting. So let's dive straight in.

Hi there, Cindy. Hi, Anthony. Welcome to the show.

Hey there.

Very good to be here. Thank you, Richie.

Brilliant. So I'd like to start with a bit of motivation to begin with. So what is the greatest piece of thought leadership that you've seen?

That's an interesting question. The greatest piece of thought leadership I've ever seen. Anthony, do you have a greatest piece of thought leadership you've ever seen?

It's like saying the best movie, what's your favorite movie in the world? And I said I can give you my top 10. But there is some tremendous thought leadership. And if you think about the really quality stuff that's out there right now, the Edelman Trust Barometer, it sort of comes out regularly. It's coming out right now in sort of January, February timeframe. And that's a really compelling piece of thought leadership that actually influences decision making of a lot of people around the world. I think some of the stuff that McKinsey comes out, McKinsey produces really strong analytical stuff like generative AI will create $4 trillion worth of stuff. That sort of study that McKinsey released a year or so ago, very compelling and had very big press impact and is still talked about. It's of a type we wouldn't write that sort of report. But I think it's a really good example of compelling thought leadership.

And I, Richie, I really love the trends pieces. If I'm thinking about what's super wonderful, it's like I really like the stuff that's forward looking and that uses data to sort of say here's what we think we see coming down the pike and what does that maybe mean for business?

Okay, yeah, I think trends is always a popular topic. It's like wanting to know what's going to happen in the future. Very, very common desire. Now I would say about half the profiles on LinkedIn like, like people claim to be a thought leader. I'm sure you've got strong opinions on this. What counts as thought leadership.

I'll tell you how we define thought leadership and in our book we define it really as quite simply distinctive evidence based intelligence that gives leaders the insights they need to make better business decisions and it gives them the inspiration to act. And that's really important because there are many, many people who confuse thought leadership with other types of marketing content. But getting the definition right really matters because the research that we conducted to write our book shows that the best thought leadership has a measurable and material impact on executives who consume it. So it influences decision making, it drives sales. And in order to do that, it really needs to be bias free and based in that kind of data oriented, trusted, independent kind of environment. And it's got to have actionable results, right? It's got to tell you what you can do as a result of the data that you're bringing forward. But when it's all of those things together, when it's distinctive, when it's evidence based, when it's actionable, it's one of the best and most impactful relationship building investments that an organization can make.

That's very cool. So I like the idea that this is something that is data driven and it's designed to help you make decisions. Some of our favorite topics on this show for sure. So it sounds like these are really just like very cool forms of data stories then. So you mentioned McKinsey and other sort of organizations where creating report is kind of their bread and butter. Who else might want to create their own thought leadership?

There's an organization, Source Global, that actually does ratings of thought leadership, identifies excellent thought leadership. And Source has been doing this for something like 15 years or so. In their terms, they assess about, I don't know, 20, 25 organizations against four criteria. One is differentiation. How different is a piece of thought leadership appeal? Does it incent you to sort of read on? There's resilience in terms of how trustworthy does it have the proprietary data that you're talking about and prompting action, you know, how practical is it? But in those rankings it is really the big consultancies, the big technology firms. But all sorts of organizations are and can produce thought leadership. And I think Cindy and I are sort of seeing this groundswell of interest in round thought leadership and in the conversations that we're having. Real estate companies, architecture companies, law firms, the engineering organization, staffing and talent talk and the list goes on. And thought leadership, based on sort of the definition that Cindy was putting forward, that it is seen as being very valuable and really as a determining factor of influencing clients, influencing customers.

I would just add to that Richie, that the organizations that are the most successful at producing thought leadership are the ones who really look at it as a long term investment. They look at it as a way to build loyalty, as a way to build their brand, as a way to really deepen their client relationships. Because thought leadership isn't a marketing campaign, it's not an ad, It's Very different approach to building your business and to building client loyalty and a really strong brand for the long term.

Okay, so it just sounds like there can be some pretty strong benefits for anyone who, like, if you need to influence executives, then it's probably a good idea to consider this as part of your marketing strategy.

So.

So I'd like to get into the storytelling aspect of this a bit more. So you mentioned that executives tend to be the target audience for this. How do you go about deciding who you should target, and how might you change your thought leadership to appeal to that audience?

I think the way that you would consider who you target is really looking at your. If you're creating thought leadership as part of an enterprise, you're working in a thought leadership unit there, you would really want to connect your thought leadership to your business strategy. And in most cases, you're going to know who your target audience is at the executive level, and you really want to be careful about targeting your thought leadership to take advantage of that link to your business strategy. So in our case, the audience that we most often want to reach is the C suite executives. So when we create our surveys, our research surveys, we think about those executives that we want to reach, and we're very targeted toward making sure that the parameters of our research actually apply to the audience that we want to reach. And if you are working as a sole proprietor, let's say you're an architecture firm, and the people who are making decisions about your product or your service are COOs, let's say, or their supply chain folks, you would want to be very strategic about how you pick that audience and then craft your survey to assess what their needs are. And that's how you would look at that.

All right, so, Cindy, it seems like any organization really ought to know exactly what their executives want. So I like the idea that you need to think about, like, what are the business problems that those executives are trying to solve and then tell your story towards that. So a lot of the time in storytelling, we talk about, like, you know, you've got things like the hero's journey and sort of standard story types. Are there any equivalents of those for thought leadership?

There are actually. The story types that we talk about most. There are four basic story types in thought leadership, and they start with explainer pieces. So an explainer is something that would take a complex or an emerging topic and really unpack it, really get into it and kind of pull. Pull it apart and explore it and analyze it. And you see a lot of that right now, thought Leadership around that, with especially around generative AI. So it's the hot new technology, right? We're in the hype cycle. And there's a lot of explainers about generative AI and how that's going to work. We're going to start to see a lot more of that on quantum in terms of the next big technology. So explainer pieces is kind of the first story type. The second story type, you know, something that's related to maybe diversity, sustainability, something that might be a societal or a business issue that really needs to be looked at. The third type of thought leadership story is really a how to. So that's more about helping business leaders figure out the best way to solve a problem or to look at case studies. That's where you see a lot of cases from organizations that have done this before. So that kind of, here's what other organizations have done, here's what you might consider to solve your problem. And then the fourth story type is really around persuasive pieces. So that's the kind of thought leadership that you would see. You mentioned earlier, people who consider themselves thought leaders. That's the kind of story that usually someone who's considered a thought leader would want to use and they would bring their perspective, their unique perspective forward. And, you know, here's why you should be thinking about this topic right now. Here's why you really need to spend the time to investigate this at this moment in time. So explainers, issue pieces, how tos and persuasive are the four story types for thought leadership, largely?

What's your process for creating thought leadership? Where do you begin?

So you need to know what that sort of aha message is, that real hook before you get started. Otherwise you really risk backing into something that tends to be watered down or like it's a rehashed message. And it's not unique, it's not interesting. And we know that executives spend somewhere between two and three hours every week actually reading Consuming Thought Leadership. The way that we like to have our teams think about the assessment of the AHA is say, why would an executive spend part of their two to three hours that they're dedicating to Consuming thought Leadership on this topic right now.

Yeah. So if you think about the thought leadership value chain, you know, it goes from sort of idea conception through to what do I need or what data or intelligence do I need in order to analyze, in order to think through what, what narratives do I want to create? Then it's the storyboarding, it's creating hypotheses it's, you know, whatever you do in order to create that right through to analysis, putting together the report and then providing the report. And this is a sort of thought process. When we think about something like generative AI and the application of generative AI to the thought leadership value chain, this is how we sort of decompose that value chain. How would we intersect a technology like generative AI in slotting into these various things? So I think there is a value chain. It might be very different from one organization to another. It might be different types of data interviews might, might be used as opposed to what we would call panel data, for example. It could be any number of inputs to validate the hypothesis that you're creating as you sort of work through that flow.

So you mentioned the idea of a data interview. Can you just tell me more about what that involves?

We use several different approaches in terms of the data inputs that we have. Traditional data, everyone would be familiar with you. You go out and you'd craft a survey. You work with a survey vendor, or you deploy the survey yourself and you're getting data, you analyze the data, or you're actually conducting deep interviews with whomever you're interested in. From our perspective, it's typically business executives, but it could be anyone, depending on who your target audience is, and then you sort of having those interviews. We also have a pretty big benchmarking capability. So if that's a sort of a benchmarking conversation, much of the discussion there really is about understanding the data that's captured within an organization so that we can sort of quantify that. There are case studies, you know, there's any number of ways that you could obtain the data, attain the insight and the intelligence that you're going to analyze.

Okay. Survey analysis seems pretty standard. It seems like slightly more of a challenge, I guess, if you're interviewing lots of people than trying to turn that into some sort of quantifiable result.

Although there are mechanisms to do analysis of language and certainly some of the technologies, generative AI technology, are starting to catch up. So we're starting to have the ability really at the infancy at this stage, but really look at time series to do those. Language is one of the early applications of GENAI to do that sort of analysis at scale that would have otherwise been not possible before that. So I think there's all sorts of interesting opportunities in addition to what people are sort of used to right now.

Yeah, that sounds quite cool. Like I guess you guess the. You get the transcript of all your interviews, summarize each one. Like pull out like four of the spicy bits and then somehow compile those into. Into statistics.

Yeah, I get inferences from it. Yeah, exactly. Yeah.

Nice. Okay, cool. So do you have any tips on how you might go out, like communicating the results of these analyses? I guess you're taking. Yeah. A load of statistics. You got to turn them into some sort of report. Talk me through. How do you explain things?

Well, yeah, I think that's similar to the story building approach and the value chain that Anthony mentioned. You know, there's a specific sort of process and operation within thought leadership. So you'd start with your sort of, aha, your kind of your thesis, your hypothesis, and then craft your survey. Get your results of your survey. You've got your results, you do your analysis. You know, your hypothesis is either supported or not. And then you pick your story type, which you probably already know when you go into it. And then what you do is think about from an editorial perspective. You know, go back to your audience, who is your audience? What's the best way to tell a story to that audience? And then one of the things we talk about a lot is if you're writing for a big audience, then start small. Assume that you're writing to one person, you're having a conversation about the topic that the research is related to, and write your story as if you're talking to that one person. Forget that you're trying to reach 300,000 CEOs in technology companies around the world. You'd craft that story for an audience of one, knowing that it's going to go to a much larger audience. And that's a little bit how we keep it personal. And if you're in an organization that has generative AI capability, hyper personalization is one of those things that generative AI is really good at. So you get your story written to your audience of 300,000 CEOs, CIOs, and then you can actually hyper personalize to one or two or three or one client or a particular industry or a particular geography based on what you know about that group. By using generative AI, you do the hard work upfront, right? The humans do the hard work of analyzing the surveys and coming up with the hypotheses and figuring out what the story is. But then you use generative AI tools to help you create those derivatives that hyper personalize and that extends or expands audiences with content that's specifically relevant to what their needs are.

Okay, so since we had ROI in the title of this episode, let's talk about how you get value from these things. So what constitutes a successful piece of thought leadership? Like, how do you track it? Like, what sort of metrics should you be looking for?

We believe ROI is going to be the measure of success for thought leadership moving forward. But like many activities that are oriented around building relationships, marketing in particular, it's been very difficult to calculate a return on investment of that kind of activity. And as much as it helps executives make smarter business decisions, it really also helps organizations get to that point where they can supercharge those client relationships. And we know that because this research that we did that led us to calculating the value of the ROI of thought leadership proves that it is really immensely valuable. Previous efforts at ROI calculation have really been based on assumptions or estimates or expectations or things, things that have been done before. But what we did is with this research, we were actually able to take the data that we had collected. We crafted a survey specifically to collect this data and get the results of the survey that would allow us to calculate thought leadership based on the experience of the executives who actually use thought leaders. So we surveyed 4,000 business leaders around the world. And Richie, the magnitude of the impact of thought leadership on executives and their decision making and their purchase decision making in particular, is really astounding. We were stunned by it and in fact, almost speechless. For people who, you know, use words as a living, we really almost didn't know what to say because what we found when we looked at the data and did the calculation was that thought leadership investment returns 156% versus a typical marketing campaign, which over time, as I mentioned, has been really difficult to measure, but returns nine. So there's a 16 times premium for thought leadership ROI compared to a typical marketing campaign. We think that means that thought leadership has really earned its place as the platform that marketing leaders should really use to build the rest of their campaigns. You know, we kind of call it the eighth P of marketing. Many marketers are familiar with the P structure, and we think that thought leadership is really the eighth p, which is the platform. And if marketers use thought leadership as that platform, they can. It's kind of like the missing piece, honestly. They can use that as the anchor for their brand building and really deliver a strong return for their organizations. And that's new, that's different, that hasn't been validated before. So we're really excited by that and kind of giving people that do what we do, giving CMOs really that evidence that thought leadership really is a valuable part of that marketing mix.

Okay, that's very cool. Like you said that you got surprised that it was sort of 16 times more valuable than other marketing channels or other marketing approaches. So that's, that's very, very cool stuff. I also like that it gets a bit meta because you're doing thought leadership about the value of thought leadership as well.

Nice.

Okay, so you mentioned it being the 8th P of marketing. Now I'm sure when I learned this in school there were like four P's. It was price, product, place and promotion. What are the other ones that I've missed in the last three decades?

There's people, process and physical evidence. So it's usually four or seven. We're going to be either the fifth or the eighth.

So.

Yeah, all right. Yeah, seems like a nice add on to the existing marketing attributes. All right, nice. So I'd like to talk a little bit about the use of generative AI as well. So it seems like these days you can use generative AI to create almost any kind of content pretty quickly and cheaply. So talk me through. How can generative AI be used for creating thought leadership?

I think it can be used well or badly. Right? So badly is you use the generative AI to create the content. Now, generative AI by its nature is a backward looking tool and thought leadership is supposed to be something that's forward looking. And so already just at that very basic level, you start seeing some of the challenges of creating creative, visionary thought leadership if you're just relying on generative AI. So I think even though it's very easy to produce more content, we know from our surveying that an executive and Cindy mentioned that executives spend between two and three hours a week consuming thought leadership. At this stage, it's more on the three hour side. It was really two hours during COVID and it's been increasing since COVID so it's around three hours. But they only consume thought leadership from an average of 5 organizations. So even though the amount of generative AI oriented or created content has been expanding and probably will continue to expand dramatically, it's not all being consumed, it's just noise. And so the way we think about generative AI is within the context of the value chain for thought leadership. Where can we insert it? At specific places to improve scalability, to improve productivity, to deepen analysis. It's really augmenting, supplementing human capability because it can be immensely valuable at improving productivity. But you still need people, visionary people, visionary experts. You still need data, proprietary data to formulate and create the story and actually come with the inspiration. Generative AI is really good at doing specific things and really bad at doing some other things. And so I think that's the tension that we have with generative AI right now.

So you're not going to get novel ideas from generative AI, at least without an awful lot of work. So basically it might be able to help you out with your data analysis, might be able to help you out with your story crafting, but you're going to need some humans in the process there at least to get the uniqueness and generate good quality content, I think. Okay, wonderful. So in terms of actually going about creating this stuff, are there any sort of interesting analytical techniques that you might be using? But beyond just like it's survey analysis or is there anything more exciting going on there?

It's evolving pretty dramatically, certainly. And in thinking through, Sydney and I work for a relatively large producer of thought leadership. We have an analytics team that is, you know, of about 10 people that are capable of doing really deep analysis, different types of analysis, certainly regression, beyond regression analysis. But not every producer of thought leadership is able to do that. So there's basic frequency is still a very useful way of describing data. Right. So there is absolutely nothing wrong with looking at data from a very linear perspective. And that's a statistician joke, you know, and so very simple perspective and sort of presenting that data. There's nothing wrong with that being said, in addition to the sort of analytical techniques that are out there that advance beyond regression to some more complex stuff, that generative AI is starting to catch up. Generative AI originally was around language and wasn't really quantitative. That being said, there's all sorts of possibilities with synthetic data with generative AI that are creating some really interesting opportunities. And that is in terms of really around the scale of data serving, doing surveying is really expensive. And so a big survey of 10,000 executives or employees or whomever really amounts between half a million and a million dollars and people just don't have that sort of budget available to them. But using synthetic data, you could do a survey that's substantially smaller and use some of the emerging techniques around generative AI to apply it to that. And some of the analysis that our team is doing about whether that is creating accurate forecasts of data are very positive. And the opportunity that is that a 400N count survey could turn into a 14,000 NCount survey. And what that allows you to do is some of the data cuts the sub areas, whether it's by industry or region or by gender or however you want to cut the data which starts to fall apart at low, very low numbers, it just loses its statistical significance. You can't infer observations around a population from that sample. Using synthetic data allows you to do so with great accuracy. And so it sort of gives the scale of a McKinsey or a BCG or of an EY or a KPMG to organizations that can only afford a 400 ncount survey. And it really can be extraordinarily powerful of allowing people to scale up their capabilities in a very robust and responsible way.

I do like the idea of just being able to do a lot more with less data because data is expensive to acquire. Yeah. Certainly once you if getting executives time, that's an incredibly valuable thing. So yeah, I can certainly imagine how like half a million dollars for a survey is, is going to happen. Okay. So yeah, synthetic data and I guess bootstrapping techniques just to kind of fill out the blanks in the survey. Nice. And it seems like because we talked about generative AI being able to create almost anything, you need to make sure that you've got high quality research. So it seems like there's going to be some sort of trust issues with the audience on is this really going to be high quality research? So first of all, I guess, what best practices are there for research? And then also how do you persuade the audience that your research is trustworthy?

Well, our research actually indicated five distinct value levers. So the research is one part of, it's the basis of the thought leadership. But in total, the thought leadership program really needs to build that trust for the organization. Right. So if there are five sort of distinct levers that define what good thought leadership looks like, and those are quality, uniqueness, reach, independence, and trust. So the first three, quality, uniqueness and reach, are really controlled by the producing organization. Right. And each of those five levers has very different definitions or attributes that will drive toward trust. So quality is really about the answers that your thought leadership gives, and you get those answers through the research. Right. So you pull all your data together, you do your analysis and you create a hypothesis, you create your point of view, you create your thesis, and that's really what delivers the quality. Is it the right topic? Is it the right time? Does it give the consumers, the readers, the users of the thought leadership, the answers that they want? If you look at uniqueness, uniqueness is really about the questions. So that goes back to your point of how do you define the research? So you're not going to get uniqueness in your thought leadership if your questions don't allow for that kind of analysis. So you need to craft questions that are going to allow an interesting insight. And it's very rare that a piece of thought leadership will be a completely on a completely new topic. What's much more common is that thought leadership will look at a topic that's been analyzed or assessed before in a new way. And that's how you get to the uniqueness aspect through the research that you craft. And then reach is really about getting your thought leadership in front of the right people. And from a research perspective, a survey perspective, that doesn't apply to the reach parameter as much. And reach is about getting into the right organizations, the right people in the right organizations at the time that they need the insight that you're delivering. Anthony mentioned that most users of thought leadership only consume it from one of five organizations at a time. Right. So you want to be one of those five top organizations that an executive looks to for that trusted thought leadership, and you get it through that quality, uniqueness, and reach.

Okay, so I like the idea that you can have high quality research, but maybe like, you can't distribute to hundreds of thousands of people. Or it might be the other way around, or it might just be, yeah, asking the same questions as everyone else. There's gonna be a bit more competition there. And you need those three, the quality, uniqueness, and range in order to be successful. Okay, so I guess in terms of the figuring out how do you build after thought leadership program, what should your strategy be like? How do you get to success?

So in terms of building a program, it really, you know, it depends on who you are, it depends on who your audience is, it depends how big you are. But we take very much a portfolio approach. For some organizations, building a portfolio program is actually creating one piece of thought leadership. And that's great as long as it's high quality, you're true to the data, you're true to the client or customer, and you advance that piece of thought leadership in a very professional and rigorous way because it needs to be trustworthy. People need to be confident that what you're saying is true and the analysis is accurate from a larger organization. We really think about it as a portfolio and having different types. So Cindy talked about the different types of content, and that really maps to your portfolio. So for a large organization, what are the subjects, the topics that you want to cover? And sort of thinking about those. Some of them could be quite visionary. Some of them could be this big picture stuff. Like what is the. Like McKinsey did when we talked about this study at the beginning. What is generative AI? What's the impact of generative AI going to be over the next 10, 20 years? So very visionary. How is it going to transform industry? Or it can be very tactical, and it can be something about a specific business function or a business activity or a particular segment that. And going into. Into some deep detail, leveraging, benchmarking data potentially, and sort of doing an analysis there. Each of them are going to have their own market, their own targets, and each of them is going to be deeply satisfying within the context of what it produces. But I think sort of thinking, what is your strategy? What are you trying to achieve as an organization? What's your scale? And then thinking, what is my portfolio of content that is going to yield the biggest value to my customers? Because if I yield the value to my customers, I will yield it for myself.

Okay, I've said that's quite reassuring. So, Cindy, when you were saying quite often executives will only consume thought leadership from just one of five organizations. So it sounds like you've got to have some sort of extensive program to be one of those five organizations. But Anthony is saying that basically you can just produce one piece. And as long as it hits your target audience. That makes sense because at Data Camp, we have one piece of thought leadership. We do an annual report on the state of data and AI literacy. So that's good. One piece. That sounds fine. All right, so simple program, I guess. How do you get started on this? Like, what's the first step in terms of getting your first piece of thought leadership out there?

You should never produce a piece of thought leadership that doesn't align with your organizational strategy. And once it does, then your topic areas are pretty much unlimited. Right. Which can be a real challenge for some organizations because they want to produce content on a lot of different topics. So in our book, we outline a business model or an operational model for a thought leadership function. And one of the most key aspects of that is to get a strategy team together to really define the topics that you want to cover. And so if that strategy group can help determine what is that kind of one anchor piece of thought leadership, the thing you're going to place your big bet on as a thought leadership producer and that's aligned to your strategy, and you start there and you're successful with that piece, then you can build derivatives from that piece and expand into other areas. But we would always suggest starting with that one big sort of marquee piece of thought leadership that includes the data that includes the analysis that includes all of the expertise, the SME perspectives that are important for thought leadership. That's how you're going to build the trust. So get your strategy group together, align it to your corporate objectives, pick your big topic, and then build it according to the quality, uniqueness and reach attributes.

Okay, so I like that. Just think about what is the most important sort of area of your business and just go with that. All right, nice. I think you've convinced me that thought leadership is incredibly important and valuable stuff. Just to wrap up, what are you most excited about in the world of thought leadership?

Well, I think Cindy and I are really excited about the new Global Thought Leadership. Well, apart from our new book, very excited about that. So that's very exciting. Hopefully for you as well. Very exciting for us, but certainly more seriously, the Global Thought Leadership Institute, of which Cindy and I are both on the board with Accenture and McKinsey and EY and KPMG and Academia, It's a nonprofit organization that is designed to build standards and certifications across the thought leadership domain. And so it is within the auspices of APQC, which has been around for 40 years, is the global leader in productivity measurement and performance measurement. And the Global Thought Leadership Institute is a new organization that only was performed six months ago. But I think it promises to be for thought leadership what the Project Management Institute has been for project management over the last 50 years. And then that is something that helps build the community in a very inclusive way, whether people are individual producers of thought leadership or small organizations or specific organization or you've got your McKinseys there, you've got your KPMGs and EY's there. And so I think that's enormously exciting for the entire community. Cindy, anything you want to add to that? Being on the board of the new.

Gtli, I agree with Anthony. I mean, it's incredibly exciting to see the practice of thought leadership advance and really mature into a place where we're influential enough to be able to support a professional association like this. So. And I can't wait to see where we go with that over the course of the next several years.

Yeah, that sounds very cool. The idea that there's going to be standards around this and best practices are going to be shared amongst everyone. Educating people on how to create great content, that's what I like.

Brilliant.

So that was a great talk. Thank you so much for your time. Anthony and Cindy, thank you.

Great to be here. Thank you, Richie.

Thanks.