Motley Fool Money - The Companies That Sound Most Confident May Be the Ones to Worry About

Episode Date: June 21, 2026

Every time you listen to an earnings call, you're scanning for signs that a company knows where it's going. But what if the most confident-sounding language is actually the biggest red flag? Motley Fool analyst Rachel Warren sits down with Phil LeBrun, former international CIO of McDonald's, and Dr. Jana Werner, executive advisor at AWS — co-authors of The Octopus Organization — to unpack why 70 to 90 percent of corporate transformations never deliver what they promised, what they call watermelon reporting — green on the outside, red on the inside — and the words that reveal whether a company is truly built for the future, or just really good at sounding like one. Host: Rachel Warren Guests: Dr. Jana Werner and Phil Le-Brun Producers: Bart Shannon, Lauren Budabin Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We’re committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

I met a CEO years ago. I read the shareholder report, talked about digital transformation everywhere. I said, you know, what is this digital transformation? He said, well, we haven't started yet, but it's added $5 to the stock price. That was Phil LeBroon, former CIO of McDonald's. He joined me along with Dr. Yanna Werner, AWS executive advisor, to talk about their book, The Octopus Organization. I'm motleyful analyst, Rachel Warren.

Phil and Yanna unpacked why 70 to 90 percent of corporate transformations fail. what those warning signs actually look like buried in an earnings call, and how to tell whether a company's AI strategy is a genuine competitive edge or just a stock price talking point. Enjoy. Hello, everyone, and welcome back to Motleyful Conversations. I'm Motleyful analyst Rachel Warren. Today, I'm excited to welcome Phil Lebrun and Dr. Yanna Werner to the show. They are advisors to Fortune 500 leaders at Amazon Web Services

and co-authors of the brilliant new Harvard Business Review Press book, the Octopus Organization, a guide to thriving in a world of continuous transformation. Dr. Yanna Werner is a global keynote speaker, executive advisor, and business school guest lecturer at world-class institutions like Oxford, London School of Economics. She currently serves as an executive in residence at AWS, advising Fortune 500 executive teams on innovation, AI strategy, and change management. Throughout her career, Yana has led massive digital transformations in financial services, scaled tech startups to successful acquisitions, and and built AWS's enterprise transformation practice across Europe, the Middle East, and Africa.

Phil Lebron is the former international CIO of McDonald's Corporation, global keynote speaker, and university guest lecturer. Phil now leads the global AWS executives and residence team. It's a group of former enterprise and public sector leaders who mentor Fortune 500 companies on cloud technology, generative AI, culture, and organizational agility. Phil, Yana, welcome to the show. Thank you, so, for having a... I'm excited to talk through a lot of the core themes of the book as well today.

But I have to ask why the octopus metaphor. That seems to be a foundational question to ask. Answer the fair question. Well, we got inspired because we didn't want to name a company. No company is this ideal model of what we're talking about. Companies can strive through us to become a bit more adaptive, more iterative, more intelligent at the edges. But even when you do, you might snap back.

And we wanted to pour it into a metaphor that relates to people. And we found we learned that the octopus is absurdly sophisticated in adaptation and in changing and adapting to environments, its skin, its texture, its color. It even can change its RNA. So, for example, if it switches from cold to hot water, it can change its RNA, its chemical makeup within hours. But most importantly, two-thirds of an octopus's intelligence is neurons on its arms. So they can operate sense and react and act in.

independently and quickly and don't always just need to go to the center. And we need more of that in our organizations, less of this traditional centric way of doing things. So there's the octopus. It also can play the piano, but that's a really useless fact. That's not going to help. It's a fascinating point. I think it also really sets us up well for today's discussion. One of the things I wanted to get both your thoughts on, we're in a time where globally enterprises,

companies across industries are pouring billions of dollars into AI, infrastructure. structure migrations, sort of a new wave of digital transformation, if you will. But we know that the data shows that there are a significant number of large-scale transformations that ultimately fail. So I wonder from your respective vantage points, why does corporate change consistently fracture or fail? And what are maybe the hallmarks that that's going to happen rather than, you know, achieve success?

The data has been pretty consistent over the past few decades. 70 to 90 percent transformations don't see the benefits. that were predicted when they were started. And much of what we found is we apply old ways of thinking to an old organizational model and expect something new to result. So we use the metaphor of a tin man to describe organizations that are still based

on 19th and 20th century norms. So the tin man in Wizard of Oz was heartless, slow moving, creaking, rusting, and if we look at organizations of how they operate today, often there operated like machines. And if you think back to the 19th century with factories, for instance, where people were measured on producing more and more nails or cars or whatever it may be. It's all about compliance and predictability, measuring the task, measuring the individual. It's sort of worked then, but we're in a complex world now where a small change in one area of the business

has this ripple effect, the second, third, fourth, fifth order impact that's really, really hard to predict, if you can even predict them at all. So we are still applying that sort of project planning, five-year plan to try and change an organization to be one that is more adaptive and resilient. And it's like trying to predict the future. It simply doesn't work. We see that with AI, with the rise of AI technology, many of the foundations that we build our organizations on that Phil just described these Tinman foundations are being actually taken and out of our world in which we operate. So, for example, organizations were designed to lower cost

because delivery was very expensive. But now with AI, the cost of delivering change goes towards zero almost. You can now decide, should I build one or another prototype? You just build both. So this cost of execution has gone down, but the speed of change has gone up, and nobody has the answer anymore. So these two fundamental things have changed the basis

on which we build our organizations, and that then creates a lot of dysfunction. So the old ways of putting the power of interpretation in the hands of a few at the top, rather than creating the conditions for emergent solutions to come up and to flourish and the people closest to the problems doesn't work anymore. And that's what we try and help and turn on its head. So you can create organizations that are faster, that operate at speed. The companies that are ahead now are those that learn really fast what works. and what does. And that requires more of an octopus way of being.

Our audience are comprised primarily of individual retail investors. So I wonder, for investors who are listening, who are interested in reading your book and maybe using it as more of a strategic filter for their portfolio, how can we as investors use some of these principles in your book to, for example, audit a company's execution runway? Well, I think at Stalop, the three buckets we created. So we looked at 300 dispunctions of change we board those into 38 what we call anti-patterns, which are conditioned habitual responses. So, for instance, centralizing things in an organization because it feels more efficient even though they've created this massive bottleneck.

And what we found is they fit into three categories, clarity, ownership, curiosity. And as an investor, I would start with clarity. So is it clear what the competitive differentiator for that organization actually is? is it clear to the employees? One study said that 67% of managers thought their employees knew what their company stood for and what the priorities were

and yet 2% of employees actually knew. So if you don't have that clarity in an organization about what does great look like, then everyone's moving in different directions. There's no process to make good decisions because everyone's version of good is different. Even looking at priorities,

many priorities or strategies in an organization are very Dilbertesque. Often there'll be a strategy to be a people-centric organization or a most sustainable organization or a world-leading, world-class organization. They're actually all yoga babble. They don't actually mean anything. And if you take that down to the priorities, what are the top one, two, three priorities that organization has? Because if it's not clear to you as an investor, it's not clear. It's not clear. to the employees. And if it's not clear to the employees, then how do you know you're actually making progress? And often we talk about durable needs when it comes to strategies. So rather than try and be all things to all people, we talk about what are those things which are likely to be true

even in 10 years' time? We're not futurists. We don't believe in futurists. But if you take Amazon, for example, it's pretty fair to say, if you're a customer of Amazon in the future, you won't want less selection, you won't want slower deliveries, you want want higher prices. So they become the durable needs the company's anchored on. So just looking at that clarity across strategy, priorities and the such light gives you a good sense for whether that company's moving in a sustainable direction together. You talked earlier about anti-patterns, which there are many that are focused on within the pages of your book. But I wonder, going back to that topic, Why do anti-patterns matter more than best practices?

And if we're investors, we're reading annual reports, company filings, one of the red flags that might tell us that a company's mission statement that their messaging is actually more marketing fluff than a substance that's going to drive the growth story forward. Best practices fascinate us because the problem with best practices is they stop you implementing better practices. So often we hear in organizations, people say, well, we're going to be. implemented the best practices. And it just means they've copied someone else and done something,

which may at a point in time, have made a lot of sense. But things move on. So even the words we use actually limit us. I met a CEO years ago. I read the shareholder report, talked about digital transformation everywhere. I said, you know, what is this digital transformation? He said, well, we haven't started yet, but it's added $5 to the stock price. So rather than these abstractions, what Scott Galloway talks about as Yoga Babel, where we talk about wanting to be a platform-based machine learning data-enabled organization that leverages our customer synergies, what does that actually mean? Does it translate into real meaningful priorities grounded in customer needs? And can you see that actually happening in the organization through the actions

it's taken? So getting away from these abstract mission statements to, I mean, I'll take the example of the company we work for today, Amazon. Our purpose statement is, quite simply to be as most customer-centric the company. That's why our jobs exist. Our jobs is to help executives make their own mistakes, not someone else's. It affects everyone's role and how we think about our customers and the organization itself. And yet we find companies, we were dealing with one company recently, which has declared

itself to be an AI-first organization. It's a luxury car manufacturer. It's like saying I'm going to be an electricity first organization. Yes, use the technology, but you're still a luxury car manufacturer. What do you do with that technology to actually capitalize on the fact that that's the business you're in? Well, and something you've talked about, both of you today is warning against the tin man trap of making everything the strategy. So if we, for example, we hear a company leader listing many 10, if you will, different top priority AI initiatives, which is something that is quite common in earning calls nowadays.

How does that dilution of focus destroy long-term economic value, but also how do investors separate the value from the hype in those situations? We find that if everything is a priority, then nothing is. So we talk about you need to guard yourself against this additive culture, the tyranny of end. Tinman organizations try to fill 100% of people's time. But if you do that, they are unable to think. outside the box to rethink in second and third order consequences of what they're doing,

how they can operate in a better way. So it actually makes them less successful and less productive. We find that organizations that are really clever cut down their priorities and that's painful. It's much easier to say yes, to give favors to people that want their things done and their pet projects progress. But the idea of learning what to cut back makes such a difference. One of the things that you've argued is that executive peers must deliver joint value rather than guarding information in siloed kingdoms. And I want to lean into that a bit more. And what are the signs that we can look for to see whether a C-suite is unified or operating as independent personal territories? We talk about are you a team of leaders or a leadership team?

One study showed that about 50% of transformations fail at step number one, which is if you have each of the executive. team write down what the outcome of the transformation is meant to be and who's accountable, how many answers do you get? And we've seen situations where an executive team of 15 people, part of the way through their transformation, had 13 different answers. Because what happens is the boss says, hey, we're going to become a digital organization. And of course, everyone sits around the table and says, that sounds good. And then they leave the room, assuming that the CIO, in this case is going to lead it. And no one puts their hand up and says, hey boss, it sounds good, but what does it mean? Who's going to lead it? How do we know what success looks like? What are we

going to stop? What impact does this have on customers? Have we asked customers? So very, very simple things. All it takes is for one person to ask these questions. Because otherwise, what happens is each of those leaders leaves the room, goes back to their functional silo, and translates it into goals for their silo. So in finance, it may mean cutting costs. In marketing, it may actually mean spending more money, and you've automatically generated this friction in the organization. I love your concept of watermelon reporting, things that look green on the outside, but are bleeding red on the inside of an earnings call. It's a great analogy. Maybe you could dive into that a bit for me. And also, how can everyday investors spot this fundamental mismatch?

Yeah, we see this a lot and we have delivered large-scale projects that were done in traditional waterfall ways and there were maybe not, it wasn't a safe environment where you could talk about what was going wrong. There was so much pressure once a project was signed off and all these resources were being put together and they're proceeding and it's like the tanker has left the harbor and you just need to deliver. And there's no room for someone to say, I'm sorry, we are not on track. Or it's even dangerous. I even had cases where someone who realized that something dangerous was happening

from a compliance point of view was unable to speak up. And that's why we're talking about sometimes you have this reporting where people give their weekly status report green, green, green, but on the inside it's red. because it's too scary. The culture or the setup or the mechanisms in the organization don't allow you to be honest because companies place big bets and then just hope for the best. I want to talk about a couple specific, any patterns from your book, specifically culture of fear versus true transformation. We've talked about how companies are spending millions on AI and cloud tools but still fail to change how they work. And I'd like to talk about more about what's going

wrong there, but also importantly, what are the indicators that show up when the transformation is working when that growth story is going the right way? The culture of fears interesting because we've known for probably decades that the foundation for innovation and transformation is intellectual honesty. It's the ability to say things aren't working, please help me, as opposed to this theater of innovation that often happens and these status updates like the Watermelon Reporting, which shows that everything's fine. Hopefully it will be fine in the end, but for now I'm going to tell people it's good because I don't want to face a difficult conversation. So it's the ability to have the tough

conversations. One of the things I find fascinating in organizations is often these transformations start at a high level in the organization. There's a group off to the side that's developing a solution that can be deployed to the entire organization. And yet we know that a typical manager only knows about 40% if that of the work that their employees do, their direct reports effectively. So if we're not engaging the people at the front line of the organization and the transformation, that's probably an indicator of things are going wrong. If people are using fluffy words and avoiding some of those hard conversations, that's another sign. If employees are speaking at the front line the organization about management making decisions and there's that sign of disempowerment.

That's another sign that something's wrong in the organization as well. We've talked a lot about this idea of digital transformation. If we hear a company announce an AI transformation, digital transformation, should our reaction as investors be to naturally be skeptical? What is your thought process on that? I think it's never wrong to be skeptical. I think it's important that organizations are starting to adopt AI. The best time to adopt and start working with and experimenting with AI was two years ago. The second best time is now ASAP. So I think it's positive if companies are doing that. But to Phil's point earlier, if you have a luxury car manufacturer saying we are now an AI organization, then I would

get skeptical. So the point needs to be, how does adoption work? What is the outcome they apply this to? How does it weave naturally and intelligently into their strategies. Ask why it's being adopted. What's the adoption approach? How do you bring their people on the journey? How do you see a path to value and to cost out? Those are the questions that I would ask. How is success measured?

How do they understand there is value in it? How do they learn fast? How do they unlearn these tin men habits? That's really, really important right now. So I think it's a positive. It's almost a must. I personally don't think you'll survive as an organization if you don't start adopting AI. But the how, I think there are different, different ways.

We see bottom up focus on individual productivity. That's great for learning, but there's a lot of duplication. The organizations that do this well, don't just duplicate and automate tasks that shouldn't be there anymore. They take a value stream and they reimagine this value stream with technology. That also cuts them through all these tinman things. like silos, like leaders doing different things in their silos, dependencies hand-off. So looking at how this is done and to what purpose.

Is it a separate strategy or is it bolted on or intrinsically linked to how the organization is making value now and wants to create future value? How curious are they to experiment with big new ways of changing things? That's what would get me excited as an investor. This spring, Denham gets a lot. softer, lighter update. Introducing Old Navy's drapey denim wide leg, a new fit that moves with you. It's everything you want denim to feel like for summer.

Easy, breathable, and effortlessly cool. With a fit that creates natural movement and a wide leg that feels modern, not overwhelming. Plus, that signature, wait, for this price, moment. Old Navy's drapey denim wide leg. Wall Street loves linear, predictable five-year plans, but your book argues. that high-performing companies have to think probabilistically. So I wonder what specific language tells us that a management team is managing risk realistically rather than just selling a manufactured fantasy.

One of the contrarian signs is the five-year plan. I would love to have known some of the issues in the past were coming because surely they would have been in someone's plan. Of course they're not. You can't predict everything. So I think the language they use actually matters a lot. Things like, hey, we believe our hypothesis is, our experiment yielded, our learning was, we failed here and this is what we've learned and this is how we're pivoting. So they're not signs of uncertainty or poor leadership.

They're actually signs of great leadership because what they're saying is we may be stubborn on this vision. We know where we want to get to, we think. But we don't necessarily know how to get there. because there's so many moving parts and complexity that were prepared to experiment and take risk. We spoke to Annie Duke, who's one of the top female poker players in the world. She's got $4 million in the bank. She's also a doctor of decision science,

and she talks about using language which infers that certainty isn't complete. For instance, I am 70% certain that what we're doing here is correct. And why that's important psychologically is it gives people permission to say, I'm 70% sure, but it wasn't right. As opposed to most leaders go out as if there isn't a bet on the future, that a decision is of absolute, that they're absolutely certain. And they set that decision as soon as they do that and they imply they're right, it's really hard to backtrack. It almost hurts the ego. It's, you know, the idea of making a poor decision feels shameful. So they'll defend the decision rather than saying actually it was a wrong decision.

I'd also add a perspective on risks that many of us have forgotten. I've worked in a highly regulated financial services industry. And risk was all about mitigation and being safe and being low risk. What we've completely forgotten is that risk is also intrinsically linked to opportunity. So as an investor, I would like to see where are companies brave and courageous enough, especially now with the tech, with the volatility in the world, where you really don't have answers anymore. Where can they see risks as opportunities? Where can they take those opportunities? But at the same time, build the long-term basis to manage when these opportunities don't work out

or when a risk turns into an issue and you have the backup plans, the underlying infrastructure, the underlying capabilities to handle that. Because without this ability to positively take risks, An organization will stagnate and is unable to grow. If a retail investor wants to find a tomorrow ready octopus right now, what are a few trends or indicators that they should look for to track this evolution in companies that we own? Firstly, let's be clear, there's no such thing as an octopus organization, which may sound bizarre given we wrote a book on it.

What we mean by that is as soon as an organization declares themselves fully octopus, then they're going to go backwards because, hey, success achieved. And that's what we don't want. This is a continual fight to become a better version of yourself every day and every level of the organization. I'd look for curiosity and experimentation. Again, it goes back to some of the language used in shareholder reports. What experiments are being run? Is all of the conversation about improved productivity or are investments being made around true innovation and experiment?

And we see this a lot with organizations today. There's almost this two-tier economy forming. You've got the large enterprises that are predominantly talking about doing more with less people, so become inefficient. And you've got the startups talking about delivering better product, better services, reimagining what they can do for customers. If I had to place a bet, I know where I put my bet. You can't cut your way to success.

You can reimagine your way to deliver outside. understanding customer value. Look at practical things like where do you have organizations with flatter structures? Where do you have organizations that have technology savvy leaders on their board and in their executive team or even just technology curious leaders? Where is failure cultures? The companies that do this well, even now large-scale companies in Europe, we see that are experimenting with AI, they publicly fail and they have failures with AI initiatives.

If you can't fail, you can't learn. So hiding this is difficulty. So those are indicators you can look at that will tell you if a company is more likely on an octopus path or not. Wonderful. Well, thank you so much, Phil and Yana for your time today. I really, really appreciate it. Thank you, Ruth. Thank you for having us.

As always, people on the program may have interests in the stocks they talk about, and the Motley Fool may have formal recommendations for or against. So don't buy ourselves stocks based solely on what you hear. personal finance content follows Motley Fool editorial standards and is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. For the Motley Fool Hidden Gems Investing team, I'm Rachel Warren. Thanks for listening. We'll see you next time.