ETL 50: Scott Anthony on ‘Epic Disruptions’ and the Thought Leadership Profession

Transcript: Scott Anthony and Bob Buday

Bob Buday: Hey Scott, welcome to “Everything Thought Leadership.”

Scott Anthony: Wonderful, Bob. It is my pleasure to be here. 

Bob: I want to talk largely about your book, which I as you might be able to notice I’ve been reading here, and I’m mostly through it. I think it’s great. But I’ve been following you and Clayton Christensen, God rest his soul, and disruptive innovation as a concept since his first book. That goes back to the 1990s and the consulting firm I worked at but which is no longer around, and which had a partnership with Michael Hammer. I know that Mike and Clayton knew each other very well back in the day, back in Cambridge.

Your book focuses on historical disruptive innovations that long preceded the ones Clay wrote about, the except for one, the iPhone. The other ones you wrote about long preceded the first sector that Clayton wrote about: the disk drive industry,

You wrote about Henry Ford’s Model T, Julia Child’s TV show on French cooking, McDonald’s and what Ray Kroc did with the McDonald brothers concept in San Bernardino, Calif.

Why did you to focus on these now? 

Scott: A couple things that I would say. First, why a history book in general? I have to admit, the idea of doing a history book was not mine. I had a different book that I proposed to my publisher [Harvard Business Review Press]. 

It was based on a class that I teach at Tuck called “Leading Disruptive Change.” It’s about how you lead through all the uncertainty we’re facing today. The publisher said, “That’s interesting. However, we have a different idea for you.”

They had just named disruptive innovation one of four ideas that changed the world of business, along with emotional intelligence, shareholder value and scientific management. They said, “You have been in this field for 25 years. Who better to go and interrogate the idea through history?”

At first, Bob, I said, “No, that’s not the book I want to write.” But I sat with it and said, “You know, for as much as I’ve thought about the idea of disruption, this is a lens I have never taken. And Clay Christensen always taught you that if take an old problem and look at it through new lenses, you’re going to see something different. 

So I said, “Why not do it?” I’m very thankful I did, because I learned a lot. That’s part one.

Part two was why these 11 [innovations]? Why pick gunpowder and Julia Child and the one that you mentioned? So part of this is I was looking for things that met a definition that Sir Francis Bacon laid out in 1620 in Novum Organum, where he said there have been three things in world history that changed the state and appearance of the entire world. The world’s different before and after. Two of the three that Bacon mentioned are in the book: the printing press and gunpowder. 

The compass isn’t because the history is too amorphous. I was looking for those things where literally you can see the difference between those two. And I’m also trying to tell a good story. Julia Child had her impact in the world. It doesn’t quite rise up to the level of the printing press. I’m not going to argue with that, but it’s a really good story. And through a good story, we can see things we would otherwise miss. 

That’s the biggest thing I take from all this history. As a lens, history can teach us things. It may not repeat, as the saying goes, but it certainly rhymes. And as we deal with all of these things today that feel like they will change the state and appearance of the entire world — well, the past can help show us things we would otherwise miss. 

Changing His Own Perceptions

Bob: Did you have any perceptions before you did your research that turned out to be wrong after writing the book? 

Scott: Boy, I was completely wrong about this aspect of disruptive innovation. You know, there’s two things I would highlight here. The first is an obvious thing. If you look at the previous books I’ve written, they have as their subject companies generally. So it says, “Procter & Gamble did this.” And the obvious thing is, Procter & Gamble doesn’t do anything. Procter & Gamble is an organization that does something. 

Well, people do something. So this idea that it really is individuals who are then working in teams, that are then in departments, that are then working together — that’s what makes innovation happen. I have a story in the book about Pampers. It’s not Procter & Gamble that does Pampers. It’s Vic Mills tapped on the shoulder to explore new areas, asking Bob Duncan to go into the diaper category, getting a team with Harry Tecklenburg and others, and then all the main blah, blah, blah, blah, blah, the stories have heroes, and those heroes, it’s a plural word, not a singular word. 

It’s kind of obvious, but doing the historical research brought that into relief. 

The second thing is I believe in the power of disruption. I believe it makes the world a better place. I believe it drives progress. The research showed me very clearly that while that is true, disruption also casts a shadow, and part of that shadow we get intuitively when a disruptive innovation changes dynamics in a market.

There are winners and there are losers. But it’s deeper than that when a big disruptive change happens, like Henry Ford’s Model T, society has to deal with change. In the 1920s, there’s chaos and carnage on the streets of cities because they were built not for cars, but for people and for horses. And it takes time to go through that. 

Individually, we all suffer from the status quo bias. We would like things, all else being equal, to stay exactly the same. When something like ChatGPT shows up in your hand, and you’re a teacher or you’re a parent, you all of a sudden have this new thing to deal with, and it’s really hard. 

That shadow is something that was drawn into very sharp contrast through the research and writing. Those are the two things I learned. 

Can Big Companies Handle Internal Innovators?

Bob: On your first point – about innovation about being the result of several people, not just one, sometimes these people have to leave an employer to pursue their innovation. Ross Perot was a pioneer of outsourcing IT.

Ross Perot was working at IBM, and he tried to sell IBM on outsourcing. And so, I guess he didn’t get very far. And so he left and he founded EDS. 

Same with thing with the founder of the payroll service, Paychex: Tom Golisano tried to sell a midmarket payroll service firm on providing payroll services for small businesses. Everybody, including ADP, were focused on large and midsized business. So Tom couldn’t convince management of the payroll processing company he worked for that they should go after the local shoe store. And so he left and he did it. 

So sometimes these individuals work in big companies. Sometimes those big companies don’t listen to them, and they leave, and they create an innovation that changes a lot of things so and historically. 

Scott: Your stories are great because historically, the big companies wouldn’t listen, particularly if it was something that was a true disruption that took things that were complicated and expensive and made them simple and affordable, reaching new market segments, changing dynamics driving explosive growth. Clay Christensen’s research showed very clearly that the large, established organization would discount and underinvest in these things, so people would have to eject out and do it. 

Now the thing that has really changed is large organizations now understand the phenomena. They don’t always manage it perfectly. But you go back 20 years ago, Microsoft would have been dead. It would not have gotten the cloud. It would not have gotten AI. Facebook would not have acquired WhatsApp. It would not have acquired Instagram. Sometimes for better, sometimes for worse, the large companies are figuring this out. 

Bob: It is materially different now. Entrepreneurship has thrived in some places. A brother of mine was chief marketing officer at Nestle for many years, until about three years ago, and he used to tell me about the Nespresso, which has been a huge hit. It was created by people at Nestle. Nestle is an $80 billion a year multinational company, and I think Nespresso is their most profitable division. 

That’s an example of intrapreneurship that has thrived. We typically hear of the failures of intrapreneurship, or the intrapreneur who had to leave in order to, you know, launch the big business with help of others. 

Paying Attention to History

Bob: So looking at your book, what do you think were the biggest lessons? What are the biggest lessons and who needs to heed them the most? 

Scott: Well, I will say, with the bias of an author, that I think everybody needs to heed them. But in particular, if you’re leading a large enterprise, you need to pay attention to the lessons of history about disruption. If you are tapped on the shoulder and asked to go and create something anywhere, you need to heed these lessons. 

I argue that if you’re living life in 2025-26, you need to heed these lessons, because we’re in a world where disruption is just coming fast and furiously. There are three primary lessons. Number one, disruption changes the world for better and sometimes for worse. We have to understand that when a disruption like artificial intelligence or robotics or some of the new things emerging in healthcare, as they play out, the world will look materially different. There will be good things. There will be bad things. 

Number two, disruption isn’t done by superheroes. Julia Child is an example of that.

We’ve talked about she wasn’t born a great chef. The first time that she took the final exam at Le Cordon Bleu, she failed. It the first meal that she made for her husband Paul was brain simmered in red wine sauce. Why she picked that? Who knows? But it was a disaster. She learned. She experimented. She was curious. She persevered. 

That’s innovation. Great innovators are not superheroes. They follow these kinds of behaviors. They’re curious, they’re collaborative, they experiment and so on. 

And number three, innovation rewards people who are patient and have perseverance. You have to learn how to be comfortable being uncomfortable. There are no overnight success stories. The last chapter in the book is the Apple iPhone. I sometimes will ask groups, how old is the iPhone? And people are like, well, it launched in 2007 so that makes it about 20. I say way back. They say, people were probably working on it for a couple years. You can talk about Apple’s failed effort with the Apple Newton in the mid-1990s.

Way back, you can go to the 1950s where a failed science experiment done by Corning, ultimately, 55, years later, led to the Gorilla Glass on the iPhone screen. So it’s not overnight successes. You have to be, in Jeff Bezos’ words, willing to be misunderstood for long periods of time and learn how to be comfortable with the discomfort that comes with that. 

The Late-Blooming Innovator

Bob: Some of these innovations you write about in your book, like Ray Kroc’s, came later in his life. He was in his 50s when he saw what the McDonald brothers were doing in San Bernardino, all the people who were lining up outside their, you know, burger chains or fast food, and said, Something’s going on here. As you said in your book, Ray was selling milkshake machines. 

Scott: The reason I’m smiling is the things that are in plain sight that you miss. I was talking to the PR company that helped me with the book launch, and they’re trying to think about story angles. They said, “What about going after AARP? Because the people who are members actually are very avid book readers. I said, “Well, I just turned 50 this year, so I’m now an AARP member.” 

They said, “Are there any stories in the book with people older than 50?” I’m like, probably, but I hadn’t thought about it. And then every single chapter, it’s not that Ray Kroc is an anomaly, because he’s the plus 50 or 52 whatever, when the stories start, protagonists, every chapter has a critical role, even the printing press in Gutenberg, when the Gutenberg Bible came out, he was 54 years old, and this is in the 15th century. 

I think there’s something interesting. If you study intelligence, there are two types. There’s fluid intelligence, how quickly we learn things, etc. And there’s crystal intelligence, which essentially is accumulated wisdom. Fluid goes down over time. It peaks around 20 and begins to decline. But crystal intelligence goes up for a very long period of time. 

You could argue that the crystal intelligence that someone like Ray Kroc had, who had been around the block, who had seen many things, who knew a good idea when he saw it — that’s really important for innovation. Maybe this is a self-serving argument now that I’ve turned 50, but I think disruption begins at 50. 

Bob: Don’t you wonder, though, whether Ray had walked into Kleiner Perkins or any other venture capital firm on Sand Hill Road, at age 50 whether they would have listened to his pitch? 

Scott: No way. You never say absolutes. But I think the only hope Ray would have had such a meeting is if he found some kind of 19-year-old to go with him, and Ray would be the guy in the corner, and the 19-year-old would be the puppet, in this case, pitching the story. 

Look, there’s a clear bias among venture capitalists that disruption comes from the youth, and the bias is not fully supported by data. Of course, lots of great things have been done by young people that there is data to suggest that. But there’s a role to play for wisdom and intelligence and accumulated experience as well. 

The things I really wonder about, which we will never know, is something I talk about in the book about how Kodak was this close to being the leader in social media because it bought Ofoto Inc., the photo sharing site, in 2004 — years before Mark Zuckerberg and team begin to code and you just do the thought experiment. What would happen if a company that was run by smart, thoughtful people, that would carefully consider upsides and downsides to the approaches that they followed, actually owned social media? Would our world be drowning in disinformation and polarization? Would it be a different world? You can’t argue the counterfactual. But I think maybe it would actually be a better world. Who knows? 

How the Book Unfolded

Bob: I agree with that 100%. Let’s talk about how you did the research. Was it Kevin Evers at Harvard Business Review Press who said, “Hey, Scott, we like your idea, but we have another idea”?

Scott: Yes.

Bob: When he said that, how did you embark on the research? 

Scott: I just started reading a bunch. I first started looking at “The Innovator’s Solution,” Clay’s second book, along with Michael Raynor, his coauthor. In the first chapter, there was appendix that said, over the past 100 years, there are a bunch of disruptive innovations. I said, “Okay, Henry Ford, Model T — that looks pretty good. McDonald’s, that looks pretty good. There’s steel mini-mills, which is a classic.” You got to include that if you’ve got a book on Clay Christensen.

So I had those three. I thought the iPhone would be a good ending story. I had four. Then Kevin suggested gunpowder and the printing press. I thought the printing press seems like something you got to have. I had a backbone of six. Then I got a bunch of books that talked about the history of each of them, and started reading. 

As I started doing that, ideas for other things came in. In one book I read, the meaning of the word innovation has gone through lots of changes. In the 16th century, it was a derogatory word as opposed to a positive word. So I decided to talk about what allowed that word to be reclaimed as scientific revolution. That’s a disruptive idea. 

I started doing that and got more ideas there. But it really is just a lot of reading and then trying to make sense of it.

Then December of 2023 was a very pivotal moment. I had done enough research and was ready to start writing. But my soul was not ready to start writing. I had a random webinar that came up with a company. I said, “I’m going to use this to do a low-resolution prototype of the book. I’m just going to say I know enough to talk for five to 10 minutes about any of the stories in the book. I’m going to try and use it as a way to teach general innovation principles.” 

I told myself it might not work, but I’ll learn something in the process. It helped me begin to see, all right — these are foreground, these are background. These are things I want to highlight. These are things I don’t want to highlight, etc. That was the basic approach I followed: read, then talk, then write. Then repeat, repeat, repeat. 

Bob: Was there any aspect of that was more difficult for you than others? Is the writing the hardest part, or is it the thinking – i.e., “What am I going to say?” I mean, was it figuring out the narrative, the argument you were trying to make? 

Scott: It’s great question. I’m looking to the ceiling, hoping that the heavens provide me an answer. You know, this is the way I think about it. My daughter is 17. She is taking a creative writing class at her high school, and she’s reading the book “On Writing,” by Stephen King. I was excited she’s reading that because I read that book and really liked it. The way Stephen King described his writing process, he said that Version 1 [is with] with the door closed; Version 2 [is with] with the door open. So door closed, you’re with yourself and your words, and you’re trying to come up with something, and you do the best you can. Then you open the door and begin to get lots of feedback. 

Getting Version 1 done is never a super hard thing for me. I might not be the best writer, but I’m a pretty quick writer — obviously, not as fast as ChatGPT. But whatever this was, [it was] 100% written by humans. [Then after] Version 1, [I was] then trying to figure out what’s really going to make it a great book. That’s hard. 

So you open the door for Version 2, and [HBR Press] gives input. Friends give input. You’re talking about it with people. I’m sharing stories with my kids and [getting] two people who give completely contradictory feedback. Who do I listen to? Et cetera. There’s no formula for that. That’s just trying a bunch of things out and continuing to push until you get it right. 

I remember just one example of this. I had lunch with Melinda Marino, who is Kevin’s boss at Harvard Business Review Press. And she said something that I just didn’t anticipate. I called the first version of the book “Magic Methods and a Bit of Madness: How Disruptive Innovators Change the World.” She said, “I like the idea, but the methods part — just take it out.” I tried to cram in tools, frameworks, checklists. She said, “You said you’ve done that before. You’ve got books. People could find it. I just want the stories because they’re so rich and interesting, a little bit of light takeaways. But this is not meant to be a tool book. Take them out.”

And you know, Harvard does “tool” books and “framework” books. So to have the top editor say that, I said, “Huh, didn’t see that one coming.” But I listened to her, and again, I’m glad I did. 

Bob: It’s a great read. My wife, Cathy, will love the book. She loves the personal stories, and she’s a foodie, so she’ll love the Julia Child story, just as she loved the movie “Julie and Julia.” 

Disruptive Innovation in Thought Leadership

Bob: Let’s look at disruptive innovation and this profession that I and others call “thought leadership.” It’s a profession that includes people like you who are well recognized for ideas. But it also includes the people who help people like you bring your ideas to market. They could be ghostwriters, editors, data visualization people, speaker presentation coaches, event organizers. In fact, there’s a woman in Europe who’s a specialist in marketing events. She writes passionately about how this growing field  — of running a marketing event with thought leaders speaking — has become a discipline.

Do you think disruptive innovation, especially — and I guess I’m kind of leading the witness here, things like generative AI — are going to change this profession of thought leadership, which you and I have been part of for a few decades? 

Scott: I think the short answer is absolutely, and the longer answer [as well]. 

I had a first career about 25 years as a management consultant. I learned a lot and liked it a lot. But management consulting is a very fatiguing profession. Every day you’re fighting a battle against something. It might be the project, it might be the client, it might be the world, it might be your own team — every day. In 2020 ,and then in 2022, I said, “This has been fun. I’m going to make a career pivot. I’m going to go from consulting to teaching, because being in an academic institution doesn’t change that much. It’s nice and slow moving. Not that much happens.”

I joined the faculty [of Dartmouth’s Tuck School of Business] in July 2022. Four months later, ChatGPT comes out and – boom — we are right in the maelstrom of a disruptive change. And you then echo from education out to thought leadership. And when you have a technology that took things that were complicated and expensive and makes them simple and affordable, it’s a very clear sign that there’s going to be a lot of disruptive change. 

The question for those who are in “the business of thought” is this: Is [generative AI] good or bad? In my view, as always, it comes down to the choices people make. The challenge you have now is, all of a sudden, anyone’s a thought leader because anyone can use ChatGPT, or can use Claude or whatever to come up with things that look really good and are slick. 

Now, whether they have depth or it is internet “slop” or whatever, reasonable people can disagree. But you have many more people who are able to slice, dice, and recreate content in new ways. I was talking to the speaker’s bureau that represents me, and they said, “You know, we’re going to do different language versions of you so that you can speak in Portuguese and Russia, whatever, whatever language you want to speak in.” 

Now you have this ability to do some really different things. I think that means all of us have to do what you have to do when disruption happens: you have to keep learning; you have to keep experimenting; you have to keep playing. But what exactly the world will look like on the other side? I have no way of knowing that. 

But I know fortune favors those who dive right in and play along with it. But I think there’s no doubt you’re going to see big changes in the space of everything related to the creation, distribution, packaging, etc., of thought leadership. My view on all of these things always is optimism because history shows disruption makes things more widely accessible. It allows people to reach broader audiences. It creates powerful growth. The winners and losers are to be determined, though.

Disrupting the Consulting Industry

Bob: Let’s put thought leadership to the side. What about the consulting industry itself — the business of advising companies being brought in, sizing up a situation with a team or an individual and telling a company you need to do this, or you need to do that, or you need to stop doing this. 

Scott: Now we get to the fun part. I started teaching a class a couple years ago called “Gen AI and Consultative Decision-Making.” It’s a mouthful. But half of our graduates go into consulting. So I said, “Let’s create a sandbox where we can be consultants now, fully armed with AI and see what happens.”

The first version of that class imagines that I’m in the business of doing what I would call “arm-waving consulting,” where you’re like, “Yeah, I know enough to give you some advice. But you know, I don’t have super-rich depth.” There’s no way I would create a [consulting] business that looked like a pyramid today. I would create a business that was an inverse pyramid, where I got a bunch of experts and somebody who’s really good at getting quick insight, using AI to make you sound pretty smart.

That’s one type of consulting – arm-waving consulting — the type of work where you align a group behind something and deal with very intricate processes that are complex and individualistic to a specific corporate market that I think exists forever, because I think it’s really hard and intricate, and hard to turn over to technology. 

But I think there are big portions of the advice-giving world that are going to change in very material ways. I wonder whether McKinsey and Accenture be the equivalent of the Catholic Church in the 15th century. 

What do I mean by that? If you go back to Gutenberg and his printing press, the first customer of any scale, not surprisingly, is the church. It’s got real problems to solve. It wants to standardize service. It wants to make sure bibles don’t take three years to produce. So at first, the printing press looks awesome because it can do this much faster. 

Then, people like Martin Luther use the same technology to say, “Hey, the dominant doctrine need not be the only doctrine.” The church splinters. They’re not feeling so great about spurring and sponsoring the technology. So right now, it is boom time for the big consulting companies because they’re helping people implement, they’re helping people change decision-making and so on. But what genie are they letting out of the bottle? Does a client get sophisticated enough that it doesn’t need to hire a consultant? Do they obviate a lot of their work by helping clients develop these skills? Again, no one knows for sure. But history says it’s at least a question worth asking. 

Bob: Are you in touch with a lot of former clients of yours at Innosight? And if so, have they told you that they were thinking of using McKinsey or Bain or Accenture, but that they then just typed into ChatGPT a strategic question, and that output was useful? And that they then decided, “Maybe we don’t need one of these firms”?

Scott: Yeah, I’ve heard everything. People will say, “We are experimenting with [generative AI], and there are circumstances where it looks like we’re getting output that’s pretty commensurate with big consulting companies, and yet we’re still hiring them.”

That’s because the job to be done isn’t always “the answer.” Sometimes the job to be done is “I need a third party to give me that answer.” Or sometimes the job to be done is “I need my board to listen when the person says the answer.” Or the job to be done is, “I have to get my group aligned behind something, and it’s hard to do that inside.”

Sometimes you need an outsider to do it. You see some pretty clear signs, and the data supports, of a lot of use [of generative AI], but not change in the purchasing [of consulting services] yet. I think that will change over time as the models get better. People will figure out how to use them. 

Now, of course, the good thing for McKinsey, Accenture, BCG, Innosight, and a range of others is that they’ve got tools that can allow them also to push further. And you go and take the data that you have internally, all the great client work you’ve done, and so on, and you use tools in the right sort of way. You continue to push the frontier as well. 

I suspect that [generative AI] this will not be an extinction event for the [consulting] industry. But my suspicion is it will be a separation event where you will have those that really pick up the technology, use it, refashion their business and get stronger, and those that begin to really fall pretty far behind. Time will tell. 

Leaders and Followers

Bob: What will characterize the ones who fall behind? What will these firms not be doing or be doing that that results in them trailing?

Scott: It really comes back to rigidity and the metabolism of learning. So what is the degree to which they’re continuing to learn and push the envelope? It’s interesting. I was just with a big professional services company this week whose name I will not name because I don’t want to get in trouble. They said, “We’re going to use technology to disrupt ourselves.” I said, “That’s really hard. You don’t actually want to do that. You want to use technology to reach clients you couldn’t reach, to go and compete differently against competitors you want to disrupt the market, and if that leads to you disrupting yourself, great. But if you frame it internally from day one, that’s going to feel incredibly threatening to your people. All sorts of defense mechanisms are going to kick in.”

You’re going to get defensive and rigid if you have it as something where it’s an opportunity, you’re expansive in how you approach it. This is what Clark Gilbert, a long-term colleague and co-author of mine from Innosight, found in his doctoral research that went in the newspaper industry. He said, “You have to perceive the threat, allocate resources, but view it as an opportunity to realize the potential.”

I don’t think enough people have internalized that finding. They get that they need to do something. But they’re too defensive in their response. That’s what I think will separate the winners and losers — the ones who see the possibility, the opportunity, and can adapt and view it as a good thing. Not as “a thing we have to do or do defensively.”

Bob: So are you saying in part, that if you approach it right, in this case, AI and consulting, you might see new opportunities that your consulting firm doesn’t even think are there? 

Scott: I cut my teeth at McKinsey, so I understand that business. I spent 20 plus years at Innosight. I understand that business. There’s a finite set of customers, because you gravitate toward serving people who are in very tall towers, who have lots of money. And that works really well, but that’s a minority of the businesses in the world. 

So if you go and figure out a different model,the world’s open to you. Here’s a product example. When Apple launched the iPhone in 2007, it would have been easy for Apple to say, “Hey, we shouldn’t do this. We’ve got a personal computer line that this could go after. So this is the iPod that brought Apple back from the brink. The iPhone destroyed this business. But of course, Apple’s very happy. It destroyed that business because of all of the net growth that happened. This is what happens when you get disruption. It changes the model, but drives explosive growth. 

Bob: I have to tell you about the Paychex example. Tom Golisano started that company around 1970, and I had done some research with Deloitte in 2002 and spoke to Golisano. Paychex at that time was a multibillion-dollar company, publicly held and its profit margins doing payroll services for small companies, with an average of about 12 employees or something like that. Its profit margins after tax were higher than Microsoft’s in 2002 – something like 30% net after tax. Wow, that’s available for small businesses. And so he found a way, obviously, to meet that that market in a very profitable way. 

Advice From Seinfeld

Bob:  You worked with Clay [Christensen] early in his research at Harvard. Imagine you’re a thought leadership professional today, especially a researcher, and you are working with the next Clay Christensen, or you’re working at a consulting firm with a bunch of really smart people. What does that thought leadership researcher have to keep in mind, if he or she wants to keep their job and not be eliminated by generative AI?

Scott: I’d say a couple things, and this comes straight out of the class that I taught some of the reflections from it. One of the key things to being a great consumer of AI is to have wisdom. Wisdom allows you to ask great questions. Wisdom allows you to separate, when you get results [from a generative AI tool], what is actual insight versus what is politely a hallucination and politely bullshit. 

Wisdom helps you do that. Wisdom helps you then put something into context and connect it to other things. Where does wisdom come from? Wisdom comes from accumulated experience. Wisdom comes from struggling. Wisdom comes from learning. 

I tell this to my students: There’s an interview with Jerry Seinfeld in the Harvard Business Review about a decade ago talking about his show. He famously micromanaged every single detail of his show. That led to a lot of burnout. The interviewer asked him, “Would it have been better if you hired someone like McKinsey to make it more efficient?” And Seinfeld said, “Who’s McKinsey?” The interviewer said, they’re a consulting company, and Seinfeld said, “Are they funny?” And the interviewer said, “No, they’re not funny.”

Again, having cut my teeth at McKinsey, I can attest to that. And Seinfeld said, “Then there would be no use for them, because the right way is the hard way. The goal is not to make it more efficient. We have to go through all of that to get to great output.”

For the 22-year-old researcher, there would be temptation to say, “Let me just turn everything over to AI and I’m going to get great output.” You will never develop the wisdom that enables you to truly be a great researcher and then thought leader if you do that. My advice would be, “Yes, lean in. Learn and use the tools and go through the struggle. Because the struggle is how you learn where wisdom comes from. It’s what allows you to really come up with breakthrough insights.”

The analogy I tell my students is, this: Do you want to develop your muscles. You go to the gym, you lift weights. You can bring a forklift there and lift any amount of weight that you want, but that’s not the point. Your arms don’t get stronger. If you do that, you’re basically saying, roll up your sleeves, get in the middle of this generative AI stuff.

I love dearly the colleagues that I work with at Innosight, and I miss them. However, with the tools I have now, I can do research like this that’s really powerful and interesting. As an example, I had a hypothesis. I wrote this book, “Dual Transformation,” in 2017 about companies that had successfully transformed. The hypothesis was some companies that we identified in our research had done great since then. Some companies hadn’t. And there was a difference between the two populations. In the old days, I’d have a team of multiple people going and beating that up over months. In a day, I had a 70% answer to that question, not 100%.

I use both ChatGPT and Anthropic. I said, number one, I need to assemble a database of the 100 companies that are in this book and three research reports that Innosight issued. First step: Identify who has outperformed and who hasn’t since then. So that’s a little bit of light coding to be able to do that. And God, again, not perfect, but a good enough answer. And then I need patterns. I need to say the ones that made it — like Schneider Electric, DBS Bank, Microsoft — are companies that have thrived. A few others are ones that have not they hit it once, and then they decline. What’s different between them? And I said, here’s some things that you might think about. And I had both things going simultaneously. 

I crossed the two streams over and said, “Critique the research you see out of here, and come up with three answers.” One was that CEO longevity really matters because, longer term, CEOs have the ability to continue to push. Number two, it really comes down to culture, the ability to say, “We’re going to not have transformation be a one-shot deal, but be something that really is continual.” And number three, sometimes in life bad things happen, and you can’t control everything. 

So you know, Orsted had the downside of people looking at wind turbines, and in some countries, thinking it’s a very bad thing. You can’t do too much about that if you’re a single-product company, diversification really, really helps. Is that perfect research? No, I haven’t published it anywhere. I haven’t sought to publish it anywhere. But is it enough that when I’m having a conversation with business leader, I’ve got some good things in my back pocket to talk to them about? For sure. And again, that was a day of work.

Pushing the Frontier

Bob: Have you ever thought about if Clayton was starting his research now, if he was still here, and you were working for him, and you’re 22-year-old, and Clayton’s 40 whatever, and you’re starting to do the case research that led to the big idea — how generative AI would have, impacted the research and the concept?

Scott: One of the things that Clay would always say is a part of doing research, when you’re trying to really pioneer, push the frontier, it’s anomaly-seeking research. You’re looking for the things that you don’t expect. You have to do what he called “dumpster diving,” which is just sorting  through the trash and go and see where’s the scrap that you can find and for him. 

And this is before I was working with him. This is his original research. He assembled a proprietary data set of every disk drive innovation that has ever existed by combing through [a publication called]  “Disk/Trend Report.” Now, had that been [in a] digital [form], and had you had ChatGPT, you could have assembled that a lot faster? I think the dumpster diving could have been expedited with a technology tool. 

Then being able to say, “I’m going to look at this through the lens of Joe Bower research and Robert Bergman’s research on resource allocation and the Pfeffer salonic research on resource dependency. I don’t know what large language model will tell you that, because no one had thought about that before. So that requires a human just having done all the work to say, “Huh, there’s something that doesn’t fit in either of these. Let’s take two very different lenses and look at it.”

Bob: You’re saying he would have collected the dots faster, but he might not have connected the dots. 

Scott: Yeah, I think that’s very well put. I’m thinking, “People can connect the dots a lot faster through this technology.”

Probably, like you, I follow Ethan Mollick. I love all of his writing about the wonders of AI. He talks frequently about how it’s really pushing the ability to generate new knowledge. I have not seen anything that has come out from him that I say, “Huh, that’s an interesting new idea I haven’t seen.”

So to me, it looks like it is improving the ability to develop papers faster, but it is not yet demonstrated that it leads to that “dot connection” where I say, “Ah, a new insight that I hadn’t seen before,” faster. We’re in year three, so I mean, this is still pretty early days. And the thing that I tell students and executives is that the way that you stay in the frontier is by staying on the frontier. So don’t be like, “Oh, I tried that and it didn’t work. So that’s done.”

The technology is improving by the second. Keep pushing, keep playing, keep practicing, keep learning. I’ve got two new, fun little AI tools that I built for my class that I’m teaching next term.  I’ve They’re not the world’s greatest thing, but one lets you experience the innovator’s dilemma through a very short game. One is a virtual shark tank or dragon stand where you can pick nine different personas, and it’s programmed to give you feedback on an idea. You know, just fun ways to engage students in different forms of learning. So, you know, that’s what I do to try and stay current. I’m using AI a couple times a week, and sometimes that’s it. And then there’s some weeks where that’s my life. It’s like watching Tiktok, or threads on threads on Facebook, where it’s addicting, right? It is totally addicting. 

Bob: Last question: You retired early from consulting. You were less than 50. Do you miss consulting? 

Scott: No, I still get a chance to do it individually. It’s more coaching than consulting now. I was thinking about this the other day. Somebody said, “Wasn’t it really jarring to make the career switch that you did?” Actually, not at all. At my core, the way I describe myself is I’m a consummate optimist who is passionate about spreading ideas. Consulting is one way to do that, and teaching is another way to do it. 

I’ve had to learn some new skills. My students will tell you that I’m really good at some of them but have lots of room for improvement in other ones. But [teaching] at its core is ideas and playing with ideas and shaping ideas and sharing ideas. 

The thing I miss are my colleagues. I miss the time that I would spend with them. The thing I cherish is the new colleagues I have. And you know, academics are different than consultants, and you know, for better or for worse. But I found it is really fun and energizing to go on to a new S curve and learn a lot of new things all over again.