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Is it Possible to be Incorruptible?

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Is it Possible to be Incorruptible?

Exclusive Interview with Eric Ries

This candid, wide-ranging Q&A dives deep into what Eric Ries calls the “physics of organizations” — the hidden structural and financial forces that dictate whether a company thrives or decays over time. Moving past superficial business trends, the conversation tackles the intense psychological toll of entrepreneurship, the systemic flaws of shareholder primacy, and the historical reality of alternative corporate governance.

Over the last two decades, Eric Ries’ ideas about continuous innovation, long-term thinking, governance, and market reform have reshaped company building and management practices. He is the creator of the Lean Startup method, and the author of the New York Times bestseller The Lean Startup; The Leader’s Guide; and The Startup Way.

Eric RiesAs a founder, he has put his own ideas into practice with The Long-Term Stock Exchange (LTSE); Answer.AI, an AI R&D lab; Virgil, a legal services startup; and IMVU. On The Eric Ries Show, he talks with world-class technologists, thought leaders, and executives building for the long-term. He lives in the San Francisco Bay Area with his wife and three children. He is excited to announce his latest book Incorruptible: Why Good Companies Go Bad… and How Great Companies Stay Great.

Ries offers a provocative look at how truly resilient, mission-driven institutions can protect themselves from the gravitational pull of short-term financial systems to prioritize long-term human flourishing.

Below is the text of my interview with Eric and a preview of the kinds of insights you’ll find in Incorruptible presented in a Q&A format:

1. Why do purpose-driven companies create so much value for society?

The evidence shows that purpose driven companies outperform conventional companies financially as well as in almost any other dimension you care to measure, including the social dimension. Intuitively, this makes a lot of sense, because entrepreneurship is very difficult. Everyone says they know this, but I don’t think we really grapple with this fact nearly enough. If you just want to make money, there simply are better, more convenient ways than entrepreneurship. So to get not just the founder, but the early team, the early investors, all these people to take a risk to do this crazy thing generally requires some kind of extra-financial purpose or goal. Sometimes we call that vision, sometimes we call that, in a more demeaning way, strategy. But it’s also fine to call it purpose, which is really what intuitively makes the most sense to people that do this. This is one of those cases where intuition and the evidence agree, yet it is somehow still considered a controversial fact.

2. What were some of the most important lessons you absorbed during your time on the bathroom floor?

As I’ve been going around talking about the book, this is one of the stories that actually gets a very different reaction depending on whether I’m talking to an entrepreneur or somebody else. Entrepreneurs all recognize this moment, where I really thought my company was going to fail and I couldn’t handle it. A lot of non-entrepreneurs don’t get it. They’re like, “Why? It seems like a bit of an overreaction. Okay, you had a business setback. We’ve all had career setbacks — what’s the big deal?” But what you don’t realize until you’re in it is how much, especially if you’re doing something out of a sense of purpose or passion that’s personally meaningful to you, you start to identify with it and start to become inseparable from it. So that story is very important in the book because I learned a lot of important business lessons. I thought the company was going to die, but it didn’t. It survived precisely because of its mission, not in spite of it. I learned, in a very visceral way, about the forces, that prevent reform from coming to fruition in so many areas of our life, not just financial. And of course I learned a personal lesson about the importance of equanimity and the need to tackle the psychological and even spiritual dimensions of entrepreneurship if we’re going to create real change in the world.

3. How much chance is there of us getting companies to more broadly redefine profit to include elements of maximizing human flourishing?

This question reminds me of a of an incredible video of the great Steve Jobs before he died. He’s being interviewed at an industry conference at the time of the launch of the iPhone, when the Blackberry was the dominant smartphone in the world. It had something like 80 or 90% market share. A journalist asks this question something like, “Do you really think realistically you can take share from this dominant player?” And you can tell Steve is irked by this question, and I’m expecting because we all know his famous temper, that he’s going to lash out at the person. But he doesn’t. Instead, he says, “You know, that’s not really up to me. My job, our job at Apple, is to make the best phone we can, the one that we’re proud of. Market share is up to the customer. That’s their decision, their choice. We don’t think about that, we don’t know, and we don’t need to know in order to do our best work.” I’m paraphrasing because I haven’t seen this video in a long time, but that’s how I feel about this, too. I get this question a lot because people want to feel like, if I’m going to jump on the bandwagon, I want to know that it’s going to work. But the truth is none of us know what’s going to work, even those of us who advocate for these ideas. You, who’s reading this, are the only one who gets to decide if this is likely or unlikely. This is not what the economist John Maynard Keyes called a beauty contest. You don’t have to worry about what everyone else is going to do. You only have to decide for yourself if you think this makes sense to you. And if it does, well, like I said — like Steve said — it’s up to you.

4. As America becomes more capitalist and less of a free market economy, what steps can we take to reverse the regulatory capture, lawfare and other methods that degrade competition, purchasing power, class mobility and the American dream? Do we need a pCombinator? (purpose-driven company accelerator)

You’re asking questions about words that we no longer have consensus about what they mean. What is a free market economy? What is capitalism? What is regulatory capture? The very definition of these words is what’s under threat. If you look at the broader media landscape, the political landscape, in many, many pockets of our society now the very idea of a for-profit company is being attacked as inherently exploitative or extractive. The consensus that we used to have that we can be working commercially to improve the world and make it a better place, that used to be seen as quite obvious and now that whole idea is under threat. I don’t blame the people doing the attacking, especially the young people who have, after all, lived their whole lives, under this regime of a very extractive flavor of capitalism that goes by the anodyne-sounding name “shareholder primacy”. This is the simple idea that customers, employees, communities all exist as resources to be mined for the benefit of shareholders. But this question is also loaded with so many other political issues of our time that we are going to have to tackle if we’re going to come out of this darkness, as our grandparents who battled fascism once had to do. So, I don’t think it’s going to be as simple as fixing one thing. But I think that one of the things we have to do, among many, is build a power base, an economic gravity pulling towards the values aligned with human flourishing. And many of the political, economic, and social challenges of our time are downstream of this action in the same way that the catastrophes that we’re currently living through are downstream of what seem like very simple and relatively benign policy changes from the past century.

5. What should purpose-driven companies look for in a CEO as the company outgrows or outlives the founder(s)?

IncorruptibleThis is a really important part of the architecture of institutional longevity. Most companies fail the test of succession. The evidence seems to suggest that people who train and hire from within have a big advantage here. I think that is something we don’t even really teach anymore as a corporate value, but that is actually super valuable. There’s a reason why that old story of the employee that worked their way up from the mail room was such an important legend in the previous century. Now we hardly tell stories like that anymore. We tend to want the big fancy turnaround, the bold new strategy, the external CEO, which for companies that are in crisis makes sense. And since our modern best practices tend to ruin companies, they tend to be in crisis quite a lot. But what we want to do is we want to find a CEO who combines two really important elements. One, they personally, deeply and profoundly reflect the ethos of the company. This is why a company that doesn’t have an ethos can never pass this test because they don’t even know who to pick. But you don’t want someone who, who apes the values of the past, or is slavishly loyal to the specific things that worked in the past. You need someone who is both deeply aligned to the ethos, and who nonetheless is very performance oriented, meaning they see that when the ethos is working, it should generate long-term performance. They can’t get distracted by short-term blips but they have to have the adaptability to realize when sacred cows need to be challenged. Now, it’s commonly said that only a founder can have the moral authority to do this unique combination of things I’m describing, only they can go into founder mode, as it’s called. But I don’t think that is supported by the evidence. When companies have the right structure, they actually can imbue subsequent generations of managers with this moral authority.

6. Why is magnetic alignment so important for purpose-driven organizations and their survival?

I conceived of this book as a look into the physical forces, the underlying forces, that affect organizations. So not the surface level characteristics that we spill so much ink about, org chart, culture, business model strategy, even vision, things we can touch and taste and control. Those things are important, don’t get me wrong. But there is a deeper layer to this, like a physics of organizations. In the book, I explore very dominant force that I call financial gravity. This is the gravity that pulls companies down into mediocrity or worse and is exacerbated by our heavily financialized economy. So to build an organization that is going to endure and is going to maintain its distinctiveness or its sovereignty over time, we have to have a force that is stronger than gravity with which we can power both the alignment that we need of people, and the structural integrity to resist outside pressure. And I call that the force of magnetic alignment. This is the mechanism by which companies gain that most valuable and underrated asset: trustworthiness. And the evidence shows that companies that have this asset, that activate this force, have numerous superpowers that conventional companies simply cannot touch.

7. Is super voting stock the silver bullet for purpose driven companies or are their other possibly better or complementary ways for purpose-driven companies to protect themselves?

It’s funny because the simple answer to your question is no. And yet I advocate for super voting shares all the time. I may be the most negative advocate of super voting shares! To understand, you have to see it this way: Imagine I went to a political science professor, an expert in political philosophy and I said, “I’m thinking of setting up a new city state, a new polis. I want your advice about what kind of governance it should have.” The professor’s going to be really excited. “Oh, great. What are you considering?” And I’ll say, “Well, I’ve only got two options. Option one is a situation in which whoever borrows the most money gets the most votes. Also, the tourists can vote, and you only have to borrow the money or be a tourist on election day, after which you can release your loans or leave the country and your vote is still binding on the whole polity.” The professor’s going to look at me and be like, “That’s pretty terrible. What else you got?” So, I’ll say, “Okay, option two is despotic emperor for life and my heirs and assigns.” The professor is going to say, “That’s all you got? Those are the only two options you can think of, really? You know, in the political science department, we’ve been working on this problem for a couple hundred years. We could maybe suggest a few other things!” That is the state of corporate governance today. It is such a paucity of thinking and originality. It is so bare of our human birthright, which is to imagine different ways that power can be shared amongst people. Human beings have been experimenting with this question since there have been human beings. So, the fact that companies are choosing despotic emperor for life to me should be read not as an endorsement of autocracy, but rather as an indictment of standard governance. Standard governance is so bad that emperor for life looks like an improvement. So yes, I do think it is an improvement. I do think there are times when that’s the best we can do, but we know from the research that it is not really the best long-term solution. We know that having too much power centralized in too few people leads to what psychologists called hubris syndrome, and many other problems besides. On top of being, ultimately not that long-term, since it’s limited by the human lifespan, this also puts a lot of founders into really an untenable and very undesirable psychological situation, where they are basically indentured servants and can never leave, for fear that their creation will be destroyed. So, maybe it’s the least bad of the current available options. But of course, we can think of far better ideas. In the book I argue for what I call “constitutional governance”, which is a set of concepts that take us beyond this false dichotomy.

8. How do you think we escape the big food doom loop? (healthy food company starts, wins customers, seeks an exit to get paid, big food makes it unhealthy and lower quality – i.e. Naked, Ben ‘n’ Jerry’s, Breyer’s, etc.)

This question is not really about food, so I’m not going to address big food. What does that even mean? Because we have a tendency to want to personalize these dramas, looking for villains. I understand that there are some villains out there. I get it. But this phenomenon that you’re describing, where someone figures out a more enlightened way to create any kind of product — doesn’t matter if it’s a food product or a tech product or a product design to bring a little beauty into people’s lives — it doesn’t matter what it is. The more successful it becomes, the more valuable it is as a target. And the more of a premium someone bigger will pay to acquire it. On this book tour, I have encountered many people who’ve told me their horror stories. They tend to want to tell food stories. That’s why I like this question. They’ll be like, look, private equity took over my favorite restaurant. Now the food is disgusting. Someone said to me a couple of weeks ago about a certain brand, “I hope they’re really successful,” and then they had to amend their statement to “Well, actually, I hope they’re somewhat successful. Successful enough to keep going, but not so successful that they get bought out by private equity.” That’s how much this idea that when things become successful, they get ruined has passed into the mainstream culture. So this is not about food. In the book, I describe this phenomenon, dating back at least two hundred years, and give the mechanics of how it happens and why. Why are we so conditioned to reenact the parable of the killing of the golden goose? And more importantly, what we can do to stop it?

9. Is it time to change the ‘corporations number one duty is to its shareholders’ narrative (aka shareholder primacy)? Is that part of what you’re trying to do with this book?

Yes. I believe that the era of shareholder primacy is actually already over, for two reasons. One is, this is an idea that has proved to be self-defeating. It was originally enacted — not in ancient times, but in the 1980s, at least in Delaware — to be beneficial to shareholders, but that is not how it has proved. We’ve actually metastasized into what I would call “extraction primacy”, in which investors themselves are now locked in a zero sum prisoner’s dilemma struggle where each has to try to squeeze as much out of everything they invest in lest someone else beat them to it. I think even investors are ready for change. The second reason I think it’s already over, and that we’re like the road runner having run off this cliff and haven’t looked down yet, is there’s a massive generational shift underway. As I mentioned before, the younger generation who has lived their whole lives under the hegemony of this idea, increasingly find it absolutely repugnant. They may not know to call it shareholder primacy, they may not realize that this is an idea that, by the way, has never been democratically enacted ever in history and therefore has no democratic legitimacy. But they are hungry for something new. And so I think our energy needs to be spent not on complaining about shareholder privacy anymore. It’s over. The question needs to be, what should the successor idea be? In the book I suggest mission primacy as one alternative.

10. You mention Novo Nordisk and its foundation in the book, which apparently is about to be passed by the OpenAI foundation for the mantle of the largest foundation (much bigger than the Bill & Melinda Gates Foundation) through their 26% ownership of OpenAI shares. Is this a model that we should encourage more startups to embrace from the outset?

I’d be very careful drawing lessons from the OpenAI experience because that company is quite singular and there’s a lot of stuff going on there quite unusual, a lot of big ego people like Elon and Sam. But interestingly, people often claim that the foundation ownership of OpenAI is unusual, and that’s not true. The idea that a for-profit company can be governed by a nonprofit foundation is an old one. The German optics company Zeiss had the structure in the 1880s. And as the question asked, Novo Nordisk has had it since the 1920s. In fact there are so many of these companies in the world that they have been studied and found to be dramatically more stable. Companies that have this structure are simply more likely to invest counter-cyclically. They are more likely to invest more in R&D. They have better financial performance and they are something like five or six times more likely to live to year fifty than conventional companies. Now the key to the structure’s stability is to have a system of checks and balances, which, as far as I understand, OpenAI struggled with for much of its existence. OpenAI had only one board, but what makes companies like Novo Nordisk, Patagonia, and Tony’s Chocolonely distinctive is that they have two entities — a for-profit board of directors who’s held accountable or in some cases even appointed by an outside board of trustees. That checks and balances, two-entity structure seems in the data to the most stable corporate form in the world.

11. As we enter the age of AI and the disruption it is beginning to cause, can the displaced really rely on enlightened capitalism to keep their families from starving?

This is a very grim question, and it presupposes one of the many, many doomsday scenarios about AI that is circulating. In order to think clearly about what it makes sense to do with AI, you have to realize two really interesting facts about this moment. The first is that almost every future scenario about this technology depends on a series of empirical facts that no one on this planet really knows the answer to. And these facts are very strange. Only a few years ago, they would have been considered post-modernist, irrelevant debates in your local philosophy department about questions like, “is there such a thing as reasoning or is it all just language?” And “what is the nature of intelligence and consciousness?” Of course, we as human beings have studied these questions for many generations. But I was on CNBC talking about this the other day — it’s rare that they are of such economic import that stock traders are wondering about them. To give one example, one of the most important questions you have to ask about AI is when or if the scaling laws will ever run out. So far, for quite a number of years,, thanks to pioneering researchers, including many far-sighted ones like my co-founder at Answer.AI Jeremy Howard, have figured out that simply by applying more computation to a very simple learning algorithm, you can create language models that seem quite intelligent, at least at first glance. So far, the more computation we use to train and run these models, the more capable they become. I think most people generally assume that this is some kind of S-curve and that eventually this curve will level off. Some even think that it already has leveled off. Others think we are years, or even decades, away from it leveling off, and of course some people believe it will never level off. This is the law of the universe. Depending on which of those things is true, the future scenarios are almost comically different from each other. A world in which the scaling laws level off next year is almost unimaginably different from one in which we have ten more years of this. And many of the doomsday scenarios, but also many of the utopia scenarios, depend critically on knowing the answer to this fundamental question about the universe that nobody knows. So, back to your question: How do we know what actions to take when the range of possible futures is so wide, so different from each other and so dependent on facts not in evidence. I think there’s only one thing that makes sense, which is to ask ourselves what are actions that would make sense, that you’ll be glad that you did, in a wide variety of potential futures? And I think that takes us out of the job of having to predict the future, which is very difficult, and rather into a more prudence-based mindset of what can be done to prepare for many possible futures. And when you go through that analysis, many of the things that you want to do to protect yourself against future AI scenarios are actually things you probably should be doing anyway. Think about having better mandatory disclosure, hardening our critical infrastructure, making sure that the gains from new technologies are widely distributed, going back to the era of widely shared prosperity. So if people are going to be displaced, should they just sit around and hope that the leaders who do the displacing will wind up being enlightened? Absolutely not. Of course not. In fact, the whole point of this book is to show how unless we make changes, the gravitational field of our financial system will warp and even destroy, turn malignant, any company. But where does the gravitational field come from? I think the most surprising part of the book for many readers is in later chapters when we reveal how the same tools that we’ve been discussing about how to create more resilient companies are also tools that can be wielded by all of us to shape the gravitational field of the future and affect what kinds of companies can and can’t form, how those companies can and cannot behave. And while some of those levers are traditional levers, like policy changes, of course., the book is primarily about the other, more surprising lovers, that I bet most readers have not thought of before.

I hope everyone has enjoyed this peek into the mind of the man behind the insightful new title Incorruptible!

Image credits: Eric Ries, Google Gemini

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What Defines a Good Strategy?

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What Defines a Good Strategy?

GUEST POST from Greg Satell

One of the most frustrating statements I come across is that “we had a good strategy, but just couldn’t execute it.” That’s nonsense. Obviously, if you couldn’t execute, there were some important factors that you didn’t take into account. You miscalculated in some significant way. So how was that a good strategy?

This raises an important question: What makes a strategy good? The concept of strategy gets thrown around so much and so incompetently, few stop to define the term. Strategy often becomes self-referential, a consensus-driven story that no one dares to question, but everyone is duty bound to carry out, for better or worse.

One helpful concept is the German military principle of Schwerpunkt, which roughly translates to “focal point.” You need to pick the battles that will prove decisive, the ones that matter and which you can win. Or, as Richard Rumelt has put it, good strategy puts relative strength against relative weakness. Figuring that out is what makes the difference.

Choosing The Right Battles, Fighting With The Right Weapons

Che Guevara was, in many ways, the prototypical revolutionary. Charismatic and brilliant, he was a master at guerilla warfare, launching revolutions against authoritarian regimes across Africa and South America. Yet although he may have won some battles, he lost the wars and, in the end, was executed for his actions.

That’s not unusual. Violent uprisings almost always fail and studies have shown that nonviolent revolutions do much, much better. In the early 1960s a political scientist named Gene Sharp began to figure out why. Governments have significant advantages in the use of violence. Successful revolutionaires, he found, use alternate weapons rooted in psychology, sociology and economics, where they can build strength and regimes are vulnerable.

In much the same way, innovative firms are often poorly served by trying to identify the largest addressable market for a new product or service. Those are the customers incumbents have been serving for years, where they have vastly superior knowledge, experience and relationships. Competing for that business will inevitably be an uphill battle.

A better strategy is to identify a hair on fire use case — a customer who needs a problem fixed so badly that they are willing to overlook the inevitable glitches in a new product or service. They will help identify shortcomings early and collaborate to correct them. As things get ironed out you can gain traction and compete for bigger markets.

For example, Tesla didn’t try to sell electric cars to everyone, at least not at first. Instead it sold high performance, environmentally friendly roadsters to Silicon Valley millionaires. Rather that compete with the big automakers head on, it pursued a market they couldn’t. A good strategy is specific. It doesn’t apply to everyone, but rather to a particular context.

Undermining Sources Of Power

During the civil rights movement, activists faced an uphill battle in the deep south, where the segregationists enjoyed a monopoly on state power, controlling not only legislatures, but police departments and the courts. Black citizens were terrorized and had absolutely no legal recourse. In many cases, it was the law enforcement officers who were doing the terrorizing.

But what if the activists weren’t poor, black and vulnerable, but elite, white and connected? That was essentially the strategy of the Freedom Summer Project, which recruited students from prestigious schools to spend the summer in Mississippi working to register voters and educate poor black children.

Almost immediately three of the activists disappeared and a national crisis ensued. President Johnson sent an army of FBI agents to investigate and the media descended onto the state. Terrified parents, whose children remained in Mississippi, sent urgent letters to their representatives in Congress. Local media in upscale white communities in the north closely covered events as they unfolded.

Of course, given that blacks were killed and tortured with complete disregard for decades, this sudden torrent of concern only underlined the inherent racism of the system. Yet still, that’s what made the strategy work. Civil rights leaders were able to put the strength of the national media and federal government, as well as the clout of industry, against the relative weakness of what passed for power in Mississippi.

The Freedom Summer’s exposure of Jim Crow would have significant ripple effects throughout the 1960s. It would help lead to the 1965 Voting Rights Act the very next year and many of the activists would go on to lead movements for women’s equality, for workers’ rights and against the Vietnam war. The country would be forever changed.

Creating A Dilemma Instead Of A Conflict

I once had a six-month assignment to restructure the operations of a troubled media company and the sales director was a real stumbling block. She never overtly objected. but was quietly sabotage progress. For example, she promised to hand over the clients she worked directly with to her staff, but never seemed to get around to it.

It was obvious that she intended to slow-walk everything until the six months were over and then return everything back to the way it was. As a longtime senior employee, she had considerable political capital within the organization and, because she was never directly insubordinate, creating a direct confrontation with her would be risky and unwise.

So rather than create a conflict, I designed a dilemma. I arranged with the CEO of a media buying agency for one of the salespeople to meet with a senior buyer and take over the account. The Sales Director had two choices. She could either let the meeting go ahead and lose her grip on the situation or try to derail the meeting. She chose the latter and was fired for cause. Once she was gone, her mismanagement became obvious and sales shot up.

Key to the success of a dilemma action is that it is seen as a constructive act rooted in a shared value. In the case of the Sales Director, she had agreed to give up her accounts and setting up the meeting was aligned with that agreement. That’s what created the dilemma. She had to choose between violating the shared value or giving up her resistance.

When you respond to an attack, you are fighting a battle in a time, place and context that your opposition has chosen. When you design a dilemma, on the other hand, you are setting the parameters, which allows you to bring relative strength to bear against relative weakness.

Mastering Strategic Conflict

We tend to think of change as a journey to bring about some alternative future state, but that’s only half of the story. The truth is that future state is in a strategic conflict with the status quo, which has inertia on its side and never yields its power gracefully. You can never bring about the desired future state until you address the status quo.

The key to doing that is to define the focal point of your efforts—the Schwerpunkt—where you can bring relative strength to bear against relative weakness. However Schwerpunkt is a dynamic, not a static, concept. As your actions impact the context, the focal point will necessarily change, requiring you to adjust with strategic agility.

In How Big Things Get Done, Bent Flyvbjerg argues that any planning big project requires experimentation and testing. You don’t start with answers, but questions. Planning consists of a series of low-cost virtual experiments in which you are exploring possibilities, identifying opportunities and exposing problems. We want to fail in planning, where it’s cheap, so we minimize failure in the real world, where it costs us dearly.

That’s why we need to take a more Bayesian approach to strategy, in which we don’t pretend that we have the “right” strategy, but endeavor to make it less wrong over time. Good strategy isn’t a master plan, but a process of discovery. It is, most of all, an iterative set of choices made about how to address meaningful challenges.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Customer Experience Strategy

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A Complete Framework for Building CX That Drives Revenue

Customer Experience Strategy for Driving Revenue

by Braden Kelley and Art Inteligencia

Most organizations have a customer experience strategy in name. Few have one in practice. The evidence is in the numbers: 80% of organizations claim CX is a top priority, yet Forrester’s CX Index has declined for four consecutive years. The gap between organizational intention and customer reality is not a commitment problem — it is a strategy problem. Organizations are investing in the wrong things, measuring the wrong outcomes, and building programs that produce activity without producing experience improvement.

A customer experience strategy that actually works — one that produces measurable improvement in customer loyalty, retention, and revenue — requires more than a CX team, a VoC program, and a dashboard of satisfaction scores. It requires a clear theory of how experience creates competitive advantage, organizational alignment around that theory, and the capability to diagnose and fix experience failures systematically rather than reactively.

This guide provides a practitioner’s framework for building a customer experience strategy that produces those outcomes.

What is a Customer Experience Strategy?

A customer experience strategy is a deliberate, organization-wide plan for designing, delivering, and continuously improving the experiences customers have with your organization — with the explicit goal of building the loyalty, advocacy, and revenue growth that excellent experience generates.

Three components of this definition deserve emphasis:

Deliberate — Customer experience is not managed by default. Every organization has a customer experience, whether it has a strategy for it or not. The question is whether that experience is the result of deliberate design or accumulated accident. Organizations whose experiences are the result of design consistently outperform those whose experiences are the result of organizational inertia.

Organization-wide — Customer experience is not owned by the customer service team, the CX function, or the Chief Customer Officer alone. Every function that touches the customer journey — product, marketing, sales, operations, technology, and service — contributes to the experience. A CX strategy that operates within a single function produces incremental improvement in that function’s touchpoints while leaving the rest of the experience unchanged.

Continuously improving — Customer experience is not a project with an end state. Customer expectations evolve, competitive standards rise, and the experience that was excellent last year becomes merely adequate this year. A CX strategy that treats experience improvement as a one-time initiative rather than an ongoing management discipline will fall behind the organizations that are constantly raising the standard.

The Business Case for Customer Experience Strategy

The financial return on customer experience investment is among the best-documented in business strategy:

  • CX leaders generate 6x the revenue growth of bottom-quartile peers, and the typical CX investment returns 3x within 24 months, per Forrester CX Index 2026
  • 86% of buyers are willing to pay more for a better customer experience — meaning experience quality directly affects price realization, not just retention
  • 41% of customer-obsessed companies achieved at least 10% revenue growth in their last fiscal year, compared to just 10% of less mature companies
  • A 5% improvement in retention drives 25–95% profit growth — the retention economics of excellent experience consistently outperform acquisition investment on lifetime ROI
  • Brands that align customer experience and brand experience unlock up to 3.5x revenue growth compared to those that manage them separately, per Forrester’s Total Experience Score research

The organizations generating these returns are not doing so through better survey scores. They are doing so by building genuine organizational capability to understand what customers actually experience, identify where that experience is falling short, and fix the specific failures driving churn, suppressing expansion, and preventing advocacy.

The Five Components of an Effective CX Strategy

1. A Clear CX Vision and Promise

An effective CX strategy begins with a clear, specific definition of the experience you are trying to deliver — not the generic “we put customers first” aspiration that appears in every annual report, but a specific commitment that describes what customers should feel, think, and be able to do at the end of every interaction with your organization.

The best CX visions are simultaneously aspirational and actionable. They are aspirational because they describe a standard that the current experience doesn’t fully meet — creating the tension that motivates investment and improvement. They are actionable because they are specific enough to guide decisions: when a product team is debating whether to add a feature or simplify the onboarding flow, the CX vision should make the right answer clear.

A strong CX vision has three characteristics: it is grounded in genuine customer insight (not internal assumptions), it is differentiated from what competitors are promising, and it is achievable within the organization’s strategic and operational capabilities.

2. Deep Customer Understanding

A CX strategy built on assumptions about what customers experience is a strategy built on sand. The organizations with the most effective CX strategies invest continuously in understanding what customers actually experience — not just what they say they experience, but what they do, what they feel, and what they compare you to.

This understanding is built through four complementary sources:

  • Voice of Customer programs — systematic collection and analysis of direct, indirect, and inferred customer feedback across the full journey
  • Customer journey mapping — visual documentation of the customer experience from the customer’s perspective, validated against real customer research rather than internal assumptions
  • Direct experience walking — actually going through your own experience as a customer, and your competitors’ experiences, to build firsthand understanding of the gaps
  • Periodic experience audits — systematic, holistic assessment of the full experience landscape that supplements continuous VoC monitoring with deep diagnostic capability

The organizations that consistently outperform on customer experience are those that treat customer understanding as a continuous investment rather than a periodic research project.

3. Cross-Functional Alignment and Governance

The most common reason CX strategies fail to produce results is not insufficient investment — it is insufficient alignment. When product, marketing, sales, operations, and service teams are each optimizing for their own metrics without a shared understanding of the customer journey they are collectively creating, the result is a fragmented experience that frustrates customers and produces avoidable service contacts, churn, and missed expansion opportunities.

Effective CX governance requires three things:

Shared metrics — Every function should have CX-related metrics in their performance management framework, not just the CX team. When only the CX team is measured on customer outcomes, only the CX team is accountable for them.

Cross-functional journey ownership — Each major stage of the customer journey should have a named executive owner who is accountable for the experience at that stage, with the authority to coordinate across functions to improve it.

Regular cross-functional experience reviews — Leadership teams should review the state of the customer experience on a regular cadence — not just quarterly satisfaction scores, but a genuine assessment of where the experience is improving, where it is declining, and what is driving the changes.

4. Prioritized Experience Improvement Roadmap

A CX strategy without a prioritized improvement roadmap is a set of principles without a plan. Experience improvement requires the same discipline as any other organizational investment: clear priorities, defined owners, specific timelines, and success metrics that connect improvements to business outcomes.

Prioritization should be driven by two dimensions: impact on customer loyalty and revenue (which improvements will most move the needle on the outcomes you care about?) and feasibility (which improvements can be made with available resources and within acceptable timeframes?). The highest-value CX investments are almost always the ones that address high-frequency friction points — the experiences that affect large numbers of customers and generate avoidable contacts, churn, and negative word of mouth.

A rigorous prioritization process requires two things that most organizations lack: a complete, evidence-based understanding of where the experience is falling short, and a financial model that connects experience gaps to revenue impact. Without both, prioritization is driven by advocacy and politics rather than customer and business value.

5. Measurement and Accountability Infrastructure

You cannot manage what you cannot measure — but the more important principle for CX strategy is that you cannot improve what you are measuring incorrectly. Most CX measurement infrastructure is designed to report on experience quality rather than to drive improvement. The organizations that generate the strongest financial returns from CX investment have measurement systems designed around a different purpose: connecting experience quality to business outcomes in a way that guides investment decisions.

Effective CX measurement has four layers:

Relationship metrics — NPS, customer lifetime value, churn rate, and share of wallet track the overall health of the customer relationship and connect experience quality to revenue outcomes.

Journey metrics — Experience quality measures at key journey stages (onboarding completion rates, first value realization timelines, renewal conversation sentiment) track whether the experience is building or eroding loyalty at the moments that matter most.

Touchpoint metrics — CSAT, CES, and FCR at specific interactions identify where particular touchpoints are falling below acceptable performance thresholds.

Leading indicators — Behavioral signals (product usage patterns, support contact rates, engagement trends) that predict future loyalty outcomes before they show up in lagging metrics like churn.

Organizations that demonstrate how customer satisfaction is associated with growth, margin, and profitability are 29% more likely to secure more CX budgets — meaning measurement that connects experience to financial outcomes is not just analytically valuable, it is organizationally necessary for sustained CX investment.

Common CX Strategy Mistakes

Starting with technology rather than understanding
The most expensive CX strategy mistake is investing in CX technology — journey analytics platforms, AI-powered personalization engines, omnichannel service infrastructure — before understanding what the customer experience actually is and where the highest-value improvement opportunities lie. Technology amplifies existing experience design; it does not substitute for it. Organizations that deploy sophisticated CX technology on top of a poorly designed experience produce a more sophisticated version of the same bad experience.

Optimizing components rather than journeys
Experience improvement programs that focus on individual touchpoints — improving the support chat experience, redesigning the onboarding email sequence, upgrading the checkout flow — often produce local improvements that don’t translate to loyalty gains. Customers experience your organization as a journey, not a collection of touchpoints. A touchpoint that is individually excellent but that follows a frustrating prior stage in the journey will not produce the loyalty improvement the touchpoint quality alone would suggest.

Treating CX as a department rather than an organizational capability
When “customer experience” is the name of a team rather than a description of organizational behavior, the CX team becomes responsible for improving experiences that other functions are simultaneously degrading. Product decisions that generate avoidable support contacts, sales promises that onboarding cannot fulfill, billing processes that require customers to call to understand their invoices — none of these are the CX team’s problem to fix, and none of them will be fixed as long as the functions causing them have no accountability for the experience they produce.

Measuring satisfaction rather than loyalty drivers
Satisfaction is a lagging indicator of an experience that has already occurred. Loyalty is a forward-looking outcome that determines future revenue. CX strategies that optimize for satisfaction scores may produce organizations that customers find acceptable but don’t actively choose — behaviorally retained but not genuinely loyal. The most important CX measurement question is not “are customers satisfied?” but “are customers building the trust and emotional connection that will make them loyal and advocate for us?”

Treating the experience audit as a one-time project
A customer experience audit conducted once and never repeated produces a snapshot of the experience at a point in time. Customer expectations evolve, competitive standards rise, and new experience failures emerge continuously. Organizations that treat experience diagnosis as a periodic investment — auditing the experience regularly rather than annually at best — consistently outperform those that conduct a one-time audit and consider the diagnostic work done.

Building Your CX Strategy: A Starting Point

If you are starting from scratch or rebuilding a CX strategy that hasn’t been producing results, begin with three foundational activities before investing in any specific improvement initiatives or technology:

1. Audit the actual experience
Before deciding what to improve, understand what the experience actually is. This means walking your own customer journey — from first search to onboarding to service to renewal — with genuinely fresh eyes, and comparing it against the experiences your customers can get from alternatives. The gap between what you think the experience is and what it actually is almost always contains the most important strategic insight.

2. Quantify the revenue impact of experience gaps
Translate the experience gaps you identify into revenue language — churn contribution, expansion revenue foregone, acquisition cost elevated by poor NPS, price premium sacrificed because the experience doesn’t justify it. This translation is what connects CX strategy to business strategy and secures the organizational commitment and investment that experience improvement requires.

3. Build cross-functional alignment before building programs
No CX program produces sustainable results without cross-functional alignment. Before launching improvement initiatives, build a shared understanding of the customer journey across product, marketing, sales, operations, and service — and establish the governance structure that assigns accountability for experience quality at each stage of that journey.

A customer experience audit is the most direct way to accomplish all three simultaneously — providing an accurate picture of the actual experience, a prioritized assessment of where the gaps are most costly, and the shared organizational language needed to align functions around a common understanding of what needs to improve.

CX Strategy in 2026: The Emerging Imperatives

The CX landscape is evolving rapidly, and the strategies that were leading-edge in 2022 are table stakes in 2026. Three imperatives are reshaping what effective CX strategy requires:

Proactive over reactive
By 2026, 40% of customer service organizations will adopt proactive strategies, enabling them to anticipate needs, resolve issues before they escalate, and contribute directly to revenue growth. The organizations capturing the most CX value are not those with the best reactive service — they are those that design experiences to prevent problems from occurring, and intervene proactively at the moments of highest risk before customers need to reach out.

AI-augmented human experience
By 2030, 67% of customer engagements via digital devices will be managed by intelligent machines rather than human agents. The strategic question for every organization is not whether to use AI in the customer experience, but how to use it in ways that enhance rather than degrade the human elements of the experience that drive genuine loyalty. Organizations that deploy AI to reduce cost without considering its impact on trust and emotional connection will save money while eroding the loyalty they have built.

Personalization as foundation, not feature
65% of consumers expect tailored experiences, and 80% are more likely to make purchases from brands that deliver personalized interactions. Personalization has moved from a competitive differentiator to a baseline expectation. Organizations that are not systematically using the data they have about customers to deliver more relevant, contextualized experiences are falling behind the standard customers now expect.

Frequently Asked Questions About Customer Experience Strategy

What is a customer experience strategy?

A customer experience strategy is a deliberate, organization-wide plan for designing, delivering, and continuously improving the experiences customers have with your organization — with the explicit goal of building the loyalty, advocacy, and revenue growth that excellent experience generates. An effective CX strategy has five components: a clear CX vision and promise; deep customer understanding built through VoC programs, journey mapping, and direct experience research; cross-functional alignment and governance; a prioritized experience improvement roadmap; and measurement and accountability infrastructure that connects experience quality to business outcomes.

What is the ROI of a customer experience strategy?

The financial return on customer experience investment is well-documented and substantial. CX leaders generate 6x the revenue growth of bottom-quartile peers, with typical CX investments returning 3x within 24 months. A 5% improvement in retention drives 25–95% profit growth. 86% of buyers are willing to pay more for better experience, meaning CX quality directly affects price realization. 41% of customer-obsessed companies achieved at least 10% revenue growth in their last fiscal year, compared to just 10% of less mature companies. The organizations generating these returns are building genuine organizational capability to understand and improve the actual customer experience — not just reporting on satisfaction scores.

Who owns customer experience strategy in an organization?

Customer experience strategy should be owned at the CEO level and executed cross-functionally — not delegated to a single team. In practice, accountability is typically assigned to a Chief Customer Officer, Chief Experience Officer, or Chief Marketing Officer, with cross-functional governance ensuring that product, operations, technology, and service teams are aligned around shared experience standards. The most common CX strategy failure is treating experience as a department responsibility rather than an organizational capability — holding the CX team accountable for outcomes produced by decisions made across the entire organization.

What is the difference between customer experience strategy and customer service strategy?

Customer experience strategy addresses the full customer relationship across every touchpoint — from first awareness through advocacy — and is owned by the entire organization. Customer service strategy addresses the specific moments when customers seek assistance and is owned primarily by the service or support function. Customer service is one component of customer experience. A customer service strategy that produces excellent support interactions cannot compensate for poor product design, broken onboarding, or friction-laden processes elsewhere in the journey. Organizations that conflate the two consistently underinvest in the upstream experience design that determines whether service is needed at all.

How do you measure the success of a customer experience strategy?

Effective CX strategy measurement operates across four layers: relationship metrics (NPS, customer lifetime value, churn rate, share of wallet) that track the overall health of the customer relationship; journey metrics that measure experience quality at key stages (onboarding, first value realization, renewal); touchpoint metrics (CSAT, CES, FCR) that identify where specific interactions are underperforming; and leading indicators (product usage patterns, support contact rates, engagement trends) that predict future loyalty outcomes before they show up in lagging metrics. The most important principle is connecting experience metrics to business outcomes — organizations that demonstrate how CX improvement drives revenue, retention, and profitability are 29% more likely to secure sustained CX investment.

How does a customer experience audit support CX strategy?

A customer experience audit provides the diagnostic foundation that effective CX strategy requires — an accurate, evidence-based picture of what customers actually experience, where the experience is falling short of competitive standards, and which gaps are generating the most significant revenue impact. Without this foundation, CX strategy investment is driven by assumptions, advocacy, and the loudest recent customer complaints rather than by a systematic understanding of where experience improvement will generate the greatest return. An experience audit is particularly valuable at three moments: when building a new CX strategy from scratch, when an existing strategy isn’t producing the expected results, and when competitive pressure or declining metrics signal that the experience may have fallen behind the market standard found via competitive experience benchmarking.

Ready to build a customer experience strategy on a foundation of genuine understanding? Start with an Experience Audit →

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude and Google Gemini to clean up the article, add images and create infographics.

Image credits: Google Gemini

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Sources:
— https://www.digitalapplied.com/blog/customer-experience-statistics-2026-cx-data-points
— https://www.superoffice.com/blog/customer-experience-statistics/
— https://porchgroupmedia.com/blog/how-to-drive-customer-engagement/
— https://searchlab.nl/en/statistics/customer-experience-statistics-2026
— https://www.forrester.com/about-us/forrester-timeline/
— https://cxm.world/customer-experience/perception-is-profit-forresters-total-experience-score-reveals-all/

Ideas Are Validated Forwards Not Backwards

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Ideas Are Validated Forwards Not Backwards

GUEST POST from Greg Satell

In 2007, our media company in Ukraine completed its IPO and would soon be valued at $100 million. For a rough and tumble organization that, just a few years before, was a relatively small business, it was exhilarating. We had big plans and were eager to execute them. It was a “damn the torpedoes, full speed ahead” moment.

We also had an innovative strategy that we thought was a clear winner — a bet on Ukrainian language media. Although the Russian language was dominant at the time, we thoroughly researched the idea and found that a large part of the market said they preferred Ukrainian. To grab the opportunity, we launched three major brands in a year.

It was a disaster. Although the first launch was cause for concern, we were moving so fast the other two were too far along to stop. Then the 2008 global financial crisis hit and we were soon struggling to stave off bankruptcy. It was a brutal lesson. You can research an idea, but you never really know what you have until you’ve actually tested it in the marketplace.

The Rule Following Paradox

The Philosopher Ludwig Wittgenstein famously wrote, “no course of action could be determined by a rule, because every course of action can be made out to accord with the rule.” He meant that every rule is subject to some interpretation and, given varying contexts, interpretations are bound to vary.

That’s essentially what happened to us. We did our research and combed through all the evidence. Television and advertising was, by law, in Ukrainian and not Russian. Consumer surveys consistently showed that a significant portion of the Ukrainian public preferred Ukrainian language media. There were plenty of signs that we were on to something.

Given that analysis, our course seemed clear. We should not only launch Ukrainian language products, we should proceed at a rapid pace so that we could move out ahead of the pack. Surely, once competitors saw how big the opportunity was, they would pounce and our opportunity would be squandered.

Except that there was no opportunity. We weren’t acting on facts, but our interpretation of them and that interpretation was horribly, drastically wrong. To make matters worse, all this was happening as the Ukrainian media market was hitting its peak and the world was about to head off a cliff into the worst financial crisis since the Great Depression.

Survivorship Bias

Business school professors and consultants gain fame—not to mention large fees—when they are able to define a novel concept or success factor. If you are able to isolate one thing that organizations should do differently, you have a powerful product to sell. A single powerful insight can make an entire career, which is probably why so many cut corners.

For example, in their study of 108 companies, distinguished INSEAD professors W. Chan Kim and Renée Mauborgne found that “blue ocean” products, those in new categories without competition, far outperform those in the more competitive “red ocean” markets. Their book, Blue Ocean Strategy, was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ book, Profit from the Core, boasted even more extensive research encompassing 200 case studies, a database of 1,854 companies, 100 interviews of senior executives and an “extensive review” of existing literature. They found that firms that focused on their ”core” far outperformed those who strayed.

It doesn’t take too much thinking to start seeing problems. How can you both “focus on your core” and seek out “blue oceans”? It betrays logic that both strategies could outperform one another. Also, how do you define “core?” Core markets? Core capabilities? Core customers? While it’s true that “blue ocean” markets lack competitors, they don’t have any customers either. Who do you sell to?

Yet there is an even bigger, more insidious problem called survivorship bias. Notice how “research” doesn’t include firms that went out of business because there were no customers in those “blue oceans” or because they failed to diversify outside of their “core.” The data only pertains to those that survived.

The Problem With Case Studies

The gold standard for research is randomized, double blind trials in which some of the subjects receive some sort of intervention, a control group gets a placebo and no one, not even those conducting the study, know which subjects are in which group. This design minimizes the chance of bias affecting results.

Yet this type of design is impractical for studying real businesses that are competing in the marketplace. So researchers largely depend on case studies in which participants are interviewed after the fact. These can be helpful in that they offer first-person perspectives of events and their context, but have obvious problems.

First, much like in Wittgenstein’s rule-following paradox, a lot is left up to interpretation. There are rarely more than a half-dozen people interviewed and they tend to be insiders. We almost never hear from competitors, customers or lower level employees. Then the researchers themselves bring their own biases to what they see and hear.

There are also issues with survivorship bias. Clearly, key players will be much more forthcoming about successes than failures. So we tend to hear about strategies that worked when, for all we know, those same strategies may have failed in other organizations and other contexts. There’s simply no real way for us to know.

Incidentally, researchers did a series of case studies on our company and I was struck by how much they depended on who was interviewed. While there wasn’t anything factually wrong, a different sample of perspectives would have led to very different interpretations.

Adopting A Bayesian Strategy

Traditionally, strategy has been seen as a game of chess. Wise leaders survey the board of play, plan their moves carefully and execute flawlessly. That’s always been a fantasy, but it was close enough to reality to be helpful. Organizations could build up sustainable competitive advantage by painstakingly building up bargaining power within the value chain.

Yet as Mike Tyson pointed out, “everybody has a plan until they get hit.” We can research and plan all we want, but the real world is a messy place. The facts, as we see them, are really just interpretations of the data we have available to us. Invariably, there are other data we’re not seeing and, even that which we have in front of us, can be interpreted in multiple ways.

That’s why we need to take a more Bayesian approach to strategy, in which we don’t pretend that we have the “right strategy,” but endeavor to make it less wrong over time. As Rita Gunther McGrath has put it, it’s no longer as important to “learn to plan” as it is to “plan to learn.” We need to be more iterative, see what works and change course as needed.

Today, instead of thinking about strategy as a game of chess, we’d do better to envision an online role-playing game, in which you bring certain capabilities and assets and connect with others to go on quests and discover new things along the way. Unlike chess, where everyone knows that their objective is to capture the opponent’s king, we need to expect the rules to change over time and adapt accordingly.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

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Unlocking Trapped Value from the Technology Adoption Lifecycle

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Unlocking Trapped Value from the Technology Adoption Lifecycle

GUEST POST from Geoffrey A. Moore

For some time now I have been making the case that investment decisions, be they made by customers engaging with a new product and vendor or private equity firms backing a new technology and entrepreneur, should begin with finding the intersection between the innovation at hand and a pool of trapped value it can release, thereby creating the return on investment. That said, one of the core principles of investing is called risk-adjusted returns, meaning that the greater the risk you take, the higher the return needs to be. My expertise is in the risks related to technology adoption, where the risk factors change over the course of a new technology’s deployment. With that thought in mind, here is how the trapped value thesis needs to risk-adjust to adapt:

  • Early Market: very high technology adoption risk. The prize here has to be quite large indeed. Typically it will come in one of two forms. For B2B investments, it will be like an oil reservoir that, if tapped correctly, will produce a gusher. Regulated industries have pockets of trapped value all over the place that fit the bill. Also, industries like automotive and real estate, which are restructuring their relationships with dealers and agents, would qualify. By contrast, B2C investments tap into trapped value that looks more like shale oil—no deep pockets, but incredibly broad presence. Media, transportation, and hospitality have funded extraordinary returns for Netflix, Uber, and Airbnb, not because the trapped value was severe but because it was so pervasive. The point is, early-stage venture investing needs to target home-run bets to warrant the risks it takes. Same goes for visionary customers in B2B markets who are the early adopters of these technologies. They are taking on significant risk so they need to be targeting outstanding rewards.
  • Crossing the Chasm: high technology adoption risk, but readily mitigated. The challenge here is that the technology has great potential for any number of use cases but needs some additional support in every case to achieve the desired end result. The chasm-crossing playbook focuses on a single use case in a single industry and geography in order to create a killer “whole product” that nails the use case and to build a coalition of customer references and partner successes that will keep the market growing even as the technology vendor expands into other segments. Here the trapped value should be intense but narrowly confined, designed to meet three critical success factors:
    1. Big enough to matter (it should be able to generate 10X your current year’s billings target)
    2. Small enough to lead (if you crush your plans, you should get 50% segment share)
    3. Good fit with your crown jewels (if you win, nobody is going to displace you).

    As you can see, there is risk here, but it is manageable through market focus and disciplined execution, the key risk reduction factor being how compelling is the customer’s reason to buy.

  • Bowling Alley: modest adoption risk. The challenge here is to expand beyond your first “beachhead” vertical into adjacent use cases with the same segment as well as adjacent segments with the same use case. Part of the source of reduced risk is that you have a working playbook from the first vertical. Much of the source, however, comes from the emergence of local ecosystems of partners who complete the whole product solutions for each use case. These partners make their living supplementing the technology vendor’s product or platform, and their extra talent, domain expertise, and segment focus represent a major risk reduction. As a result, the trapped value rewards have a lower hurdle to clear to garner investor interest and customer buy-in.
  • Tornado: low adoption risk. The risk here is the opposite—getting left behind as the world embraces the shift to a new normal. The trapped value that drives a tornado is released by “killer apps.” These apps may not release the most trapped value, but they represent a sure winner to start with, making the buying decision a no-brainer. The point is, if you want to get any traction in the tornado, you have to lead with a killer app, a no-regrets offering that delivers simple-to-consume rewards and gets everyone onto the new platform. That means the trapped value must be easy to target and the value of releasing it must be obvious to all, especially to the end users who will be the prime beneficiaries.
  • Main Street: very low adoption risk. The primary adoption challenge here is converting conservative end users who simply do not want to switch to yet another new technology. The trapped value now exists in nuisances, little bits of inefficiency that have workarounds but are annoying. From the point of view of productivity, the cost savings from eliminating them are minimal. But in terms of the user experience, as well as customer satisfaction, the impact can be substantial. B2C enterprises spend most of their R&D here focused either on eliminating “hygiene” issues or innovating with new “delighters,” both of which can increase demand, the cornerstone for volume operations success. B2B enterprises use six-sigma analytics to scout their value chains for bottlenecks that increase latency, something that adds risk without adding value, and frustrates even their most loyal customers.

The key takeaway is that there are different kinds of trapped value, each occupying a different sweet spot in the Technology Adoption Life Cycle. As a vendor and potential leader of a go-to-market ecosystem, you must be crystal clear about the kind of trapped value you are targeting, the kind of risk-taking it warrants, and the kinds of solutions that will get the most traction.

That’s what I think. What do you think?

Image Credit: Unsplash

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Neo-Feudalism and Innovation Impact

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A System Designed to Concentrate Power – or Accelerate Breakthroughs?

LAST UPDATED: March 27, 2026 at 4:55 PM

Neo-Feudalism and Innovation Impact

by Braden Kelley and Art Inteligencia

The Return of Lords and Serfs — But This Time It’s Digital

For decades, we’ve told ourselves a reassuring story about progress. Markets would open. Technology would democratize opportunity. Innovation would decentralize power. The barriers to entry would fall, and with them, the dominance of entrenched elites.

And yet, as we step back and observe the system we’ve actually built, a different pattern begins to emerge. Power is concentrating, not dispersing. A small number of platforms, institutions, and individuals exert outsized influence over how value is created, distributed, and captured. Access — whether to customers, capital, data, or opportunity — is increasingly mediated by gatekeepers.

We may not call them lords. We may not call ourselves serfs. But the structural similarities are becoming difficult to ignore.

This is the uncomfortable premise at the heart of the growing conversation around neo-feudalism: that despite the language of free markets and open innovation, we are drifting toward a system defined less by competition and more by control — less by ownership and more by dependency.

At the same time, we are living through one of the most explosive periods of innovation in human history. Artificial intelligence, biotechnology, climate tech, and digital platforms are reshaping industries at a pace that would have been unimaginable even a generation ago. The capacity to innovate has never been greater.

How can we be experiencing both unprecedented innovation and unprecedented concentration of power at the same time?

Is this concentration a temporary distortion — something the system will eventually correct? Or is it an emergent feature of how innovation now scales in a digital, platform-driven world?

What does this mean for the future of innovation itself?

Because innovation is never neutral. It does not exist in a vacuum. It is shaped — constrained or accelerated — by the systems in which it operates. If those systems are evolving toward something that resembles a modern form of feudalism, then the implications extend far beyond markets and technology. They touch how we work, how we live, how we build wealth, and how we relate to one another.

Before we can assess whether neo-feudalism is helping or hindering innovation, we must first understand what it actually is — and what it is not.

What Is Neo-Feudalism? A Clear, Modern Definition

Neo-feudalism is a term increasingly used to describe a modern socio-economic system that echoes the structural dynamics of medieval feudalism, but in a contemporary, often digital, context. While not a perfect one-to-one comparison, the analogy is powerful because it highlights a shift away from open, competitive markets toward systems defined by concentrated power, controlled access, and growing dependency relationships.

At its core, neo-feudalism describes a world in which a relatively small number of dominant entities — whether corporations, platforms, or institutions — exercise outsized influence over how value is created and distributed. Individuals and smaller organizations, in turn, become increasingly dependent on these entities for access to customers, income, infrastructure, and opportunity.

Several key characteristics define this emerging pattern:

Concentration of Power: Economic and technological power is increasingly concentrated in the hands of a few dominant players, creating asymmetries that are difficult for others to overcome.

Control of Access: Instead of owning “land” in the traditional sense, modern power centers control platforms, ecosystems, and infrastructure — effectively determining who gets access to markets and audiences.

Reduced Mobility: Upward mobility becomes more constrained as success is tied to proximity to, or permission from, these dominant entities.

Dependency Relationships: Workers, creators, and even companies become reliant on platforms and systems they do not control, trading autonomy for access and stability.

This dynamic shows up clearly in today’s economy. Digital platforms function as gatekeepers to visibility and revenue. The gig economy often shifts risk downward while concentrating rewards upward. Ownership — whether of assets, data, or distribution channels — is increasingly replaced by access-based models.

It is important to note that neo-feudalism is not a universally accepted or precisely defined concept. Variations of the idea have emerged to describe different aspects of the same shift.

Techno-feudalism emphasizes the role of large technology platforms in exerting control over digital markets and behaviors. Corporate neo-feudalism highlights the growing influence of multinational corporations as quasi-governing entities. Neo-medievalism points to a broader fragmentation of authority, where power is distributed across states, corporations, and networks rather than centralized in traditional nation-states.

Whether one views neo-feudalism as a precise diagnosis or simply a provocative metaphor, it serves an important purpose: it forces us to examine how power, access, and opportunity are actually structured in the modern economy — not how we assume they function.

And that distinction matters, because the way we define the system ultimately shapes how we understand its impact on innovation.

Evolution of Economics Systems Infographic

What Thought Leaders Are Saying (Pro and Con)

As the idea of neo-feudalism has gained traction, it has sparked a vigorous debate among economists, technologists, and social theorists. Some argue that we are witnessing a fundamental shift in the structure of the economy. Others contend that the term is more metaphor than reality. Understanding this debate is essential, because how we interpret the system shapes how we respond to it.

The “Yes, This Is Neo-Feudalism” Camp

Proponents of the concept argue that capitalism has evolved into something meaningfully different. In their view, markets are no longer truly open. Instead, they are increasingly controlled by dominant platforms that act as gatekeepers, setting the rules of participation and extracting value from those who depend on them.

This perspective suggests that we are moving toward a system where economic power resembles sovereignty. A small number of organizations exert control not just over markets, but over infrastructure, data flows, and even the terms of social interaction. In this view, individuals and businesses operate less as independent actors and more as participants within controlled ecosystems.

Some thought leaders have gone so far as to label this shift “techno-feudalism,” arguing that the owners of digital platforms function much like modern-day lords — owning the “land” on which economic activity takes place and collecting rents from those who operate within it.

The “No, This Is Still Capitalism” Camp

Critics of the neo-feudalism framing argue that while inequality and concentration have increased, the underlying system remains capitalism. Markets still exist, competition still occurs, and individuals are not bound to specific employers or platforms in the way serfs were bound to land.

From this perspective, the term “neo-feudalism” risks overstating the case and obscuring more practical diagnoses such as monopoly power, regulatory failure, or the natural dynamics of late-stage capitalism. These critics argue that using an imprecise metaphor may make the problem feel more dramatic, but less actionable.

They also point out that technological disruption continues to create new entrants and new forms of competition, even in industries that appear highly concentrated.

The Middle Ground: A Useful Lens, Not a Literal System

Between these two poles lies a more nuanced view. In this framing, neo-feudalism is not a literal description of the current system, but a lens that helps illuminate important structural shifts—particularly around power, access, and dependency.

This perspective acknowledges that while we are not returning to medieval conditions, we are seeing the emergence of dynamics that echo them in meaningful ways. The language of neo-feudalism, therefore, becomes a way to surface risks that might otherwise remain hidden behind the more familiar vocabulary of markets and competition.

Ultimately, the debate itself is revealing. The lack of consensus reflects the reality that we are in a transitional moment. The system is evolving faster than our ability to define it, and the labels we use are struggling to keep up.

But regardless of what we call it, the underlying question remains the same: how do these structural shifts influence the way innovation is created, scaled, and distributed?

The Case FOR Neo-Feudalism as a Positive Force for Innovation

At first glance, the idea that neo-feudalism could have a positive impact on innovation feels counterintuitive. After all, concentration of power and dependency relationships seem fundamentally at odds with the open, exploratory nature of innovation. But history — and the present moment — suggest a more complicated reality.

Under certain conditions, the very structures that concentrate power can also accelerate innovation in ways that more distributed systems struggle to match.

Stability Enables Long-Term Investment

One of the defining advantages of concentrated power is the ability to think and act long term. Large, dominant organizations have the resources and stability to invest in high-risk, high-reward initiatives that smaller players simply cannot afford. From artificial intelligence to space exploration to advanced biotechnology, many of today’s most ambitious innovations are being funded and scaled by entities with near-sovereign levels of capital and control.

Platforms as Innovation Ecosystems

Modern platforms function as structured environments where innovation can occur rapidly. By providing standardized tools, infrastructure, and access to large user bases, they reduce friction for developers, entrepreneurs, and creators. In this sense, innovation happens “inside the castle walls,” where the rules are clear, the tools are accessible, and the pathways to scale are well established.

Talent Aggregation and Network Effects

Concentrated systems tend to attract concentrated talent. The best engineers, designers, and thinkers often cluster around leading organizations and ecosystems, creating dense networks of expertise. These environments increase the likelihood of idea collisions, accelerate learning cycles, and amplify the pace of innovation.

Reduced Coordination Costs

In highly decentralized systems, innovation can stall due to fragmentation, misalignment, and slow decision-making. Centralized structures, by contrast, can move quickly. Decisions are made faster, resources are allocated more efficiently, and large-scale initiatives can be executed without the same level of negotiation or compromise.

This speed can be a decisive advantage in domains where timing matters, from technology development to market entry.

The Rise of Patronage 2.0

In many ways, today’s innovation economy mirrors a modern form of patronage. Venture capital firms, large platforms, and corporate innovation arms provide funding, infrastructure, and distribution in exchange for equity, data, or dependence. While this relationship is not without tradeoffs, it enables individuals and startups to pursue ideas that might otherwise never get off the ground.

For many innovators, aligning with a powerful “patron” is the fastest — and sometimes only — path to scale.

Seen through this lens, neo-feudal dynamics do not simply constrain innovation. They can also create the conditions for rapid advancement, particularly at the frontier of technology.

The question, then, is not whether these structures can produce innovation. Clearly, they can. The more important question is what kinds of innovation they produce — and who ultimately benefits from them.

Neo-Feudal Stack Infographic

The Case AGAINST Neo-Feudalism as a Constraint on Innovation

While concentrated power can accelerate certain kinds of innovation, it can just as easily suppress others. From a human-centered perspective, neo-feudal dynamics introduce structural constraints that limit who gets to innovate, what gets built, and how value is ultimately distributed.

In many cases, the same forces that enable scale at the top create friction, dependency, and invisibility at the edges.

Innovation Becomes Permission-Based

In a neo-feudal system, access is controlled. Platforms, investors, and dominant institutions act as gatekeepers, determining which ideas receive funding, visibility, and distribution. This shifts innovation from an open exploration to a permission-based system, where success depends as much on alignment with gatekeepers as it does on the quality of the idea itself.

The risk is clear: truly disruptive ideas — especially those that threaten existing power structures — may never see the light of day.

Decreased Diversity of Thought

When influence is concentrated within a relatively small group, so too are perspectives. Innovation thrives on diverse viewpoints, lived experiences, and unconventional thinking. But tightly connected elite networks can become echo chambers, reinforcing shared assumptions and filtering out ideas that fall outside the dominant narrative.

The result is a narrowing of the innovation pipeline at precisely the moment when broader input is most needed.

Talent Trapped in Dependency Loops

For many workers, creators, and entrepreneurs, participation in the modern economy requires dependence on platforms they do not control. Income, visibility, and growth are tied to algorithms, policies, and business models that can change without warning.

This uncertainty discourages risk-taking. When livelihoods are fragile, people optimize for stability rather than exploration — reducing the willingness to pursue bold or unconventional ideas.

Extraction Over Creation

As platforms mature, their incentives often shift from enabling value creation to maximizing value capture. Business models become optimized for rent extraction — taking a percentage of transactions, attention, or data — rather than expanding the overall pool of value.

This can distort innovation priorities, encouraging incremental improvements that increase engagement or monetization rather than breakthroughs that create entirely new value.

Hidden Fragility Behind Scale

Highly centralized systems can appear robust due to their size and reach, but they often lack resilience. When innovation is concentrated within a few dominant entities, failures can have outsized consequences. At the same time, alternative approaches and redundant systems are less likely to emerge, reducing the overall adaptability of the ecosystem.

Erosion of the Innovation Commons

Perhaps the most significant long-term risk is the erosion of shared spaces for experimentation and collaboration. As knowledge, tools, and data become increasingly proprietary, the “commons” that historically fueled innovation begin to shrink.

What was once open becomes gated. What was once shared becomes owned. And what was once a collective engine for progress becomes fragmented across competing silos.

From this perspective, neo-feudalism does not just shape innovation — it constrains its potential. It limits participation, narrows possibility, and shifts the balance from exploration to control.

Which raises a deeper question: even if innovation continues, is it the kind of innovation we actually need?

Centralized vs. Decentralized Innovation

Editorial Perspective: Beyond Innovation — Impacts on People, Society, and the Future

Innovation is only one dimension of neo-feudalism’s impact. To understand the full picture, we must examine how these dynamics affect personal finance, customer experience, employee experience, societal cohesion, and the broader trajectory of humanity.

Personal Finance: Ownership vs. Access

Neo-feudal structures often shift value from ownership to access. Individuals increasingly rent rather than own assets — from housing to software, from transportation to digital goods. This reduces opportunities for wealth accumulation and long-term financial security, creating dependency on centralized platforms and institutions.

Customer Experience: Convenience vs. Control

Platforms often deliver seamless, integrated experiences that delight customers. Yet this convenience comes at a cost: reduced choice, limited transparency, and dependence on a small number of dominant providers. What feels like freedom can also become subtle control.

Employee Experience: Flexibility vs. Precarity

The rise of gig work and contract-based employment provides flexibility, but often at the expense of security, benefits, and long-term stability. Workers may gain autonomy but lose agency over income, career trajectory, and participation in the value they create.

Societal Cohesion: Fragmentation vs. Stability

Neo-feudal structures create “walled gardens” — both digital and physical — that fragment communities and weaken shared social identity. The focus shifts from collective well-being to alignment with the dominant gatekeepers, eroding trust and social cohesion over time.

Innovation Paradox

The same structures that accelerate innovation at the top can suppress it at the edges. While resources and talent are concentrated in elite hubs, the diversity, experimentation, and autonomy that fuel broader innovation ecosystems may diminish, limiting society’s overall creative potential.

Ultimately, the question is not whether neo-feudalism can produce innovation —it can. The critical questions are: what kinds of innovation, who benefits from it, and what broader costs are being imposed on society?

Understanding these trade-offs is essential for leaders, policymakers, and innovators seeking to design systems that are not only efficient but also equitable, resilient, and human-centered.

Three Neo-Feudalism Future Scenarios

What Comes Next? The Future of Humanity in a Neo-Feudal Trajectory

Looking ahead, the trajectory of neo-feudalism raises profound questions about the future of innovation, society, and humanity itself. While the current system exhibits both benefits and constraints, the ultimate outcome is not predetermined. Several potential futures are emerging.

1. Entrenched Neo-Feudalism

In this scenario, the concentration of power solidifies. Large platforms, corporations, and institutions become the primary arbiters of opportunity, innovation, and wealth. Innovation continues to occur, but primarily within the bounds set by dominant entities, reinforcing dependency and inequality.

2. Decentralized Rebellion

Technologies such as blockchain, decentralized autonomous organizations (DAOs), and open-source platforms could empower new models of governance and collaboration. Power becomes more distributed, enabling innovation and value creation outside centralized structures. Communities reclaim ownership, autonomy, and agency over their economic and creative lives.

3. Hybrid Renaissance (Most Likely)

A middle path may emerge in which concentrated power is balanced by decentralizing forces. Platforms and institutions retain some influence but are complemented by regulatory frameworks, public oversight, and decentralized networks. This hybrid system could preserve the benefits of scale and stability while expanding participation and opportunity for a wider range of innovators.

Each of these scenarios carries implications for innovation, wealth distribution, social cohesion, and human potential. Leaders and policymakers face the challenge of shaping a system that maximizes innovation while mitigating dependency, inequality, and fragility.

The critical question is this: will humanity design a future where innovation serves the many, or will it remain confined to the few who control the gates?

EDITOR’S NOTE: Stay tuned for future articles examining the impact on innovation of planned obsolescence, right to repair, CONTACT ME WITH OTHER SUGGESTIONS, etc.

Image credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from ChatGPT to clean up the article and add citations.

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Stereotypes – Are They Useful and Should We Use Them? 

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Stereotypes - Are They Useful and Should We Use Them? 

GUEST POST from Pete Foley

I recently got a call from an ex colleague looking to staff up a technology innovation organization.  She was looking for suggestions for potential candidates, and when I asked her for a bit more more information, her first criteria was that she was looking for a ‘Gen Z’. This triggered an interesting conversation around how useful generational and other stereotypes are.

At one level, they are almost invaluable.  We use stereotypes, categorization and other grouping strategies all of the time, both consciously and unconsciously.   Grouping things together is a pragmatic part of how we as humans deal with large numbers of anything, whether it’s people, tasks, objects or pretty much anything, and are often a key tool in prediction. They are not always accurate or precise, but they are often a first step in how we distill large amounts of data or choices down to more manageable numbers, and/or how we begin to understand something unfamiliar. If a stranger were to point an unfamiliar gun at us at a stop sign, we can quickly determine that they are probably dangerous, likely a criminal, and that the gun is likely deadly. That kind of categorization and stereotyping might be the difference between life and death.

But these grouping strategies can also mislead us, especially if we don’t use them effectively.   For example, in the case of generational stereotypes, when dealing with large numbers of people, it can be useful to break them down into generational groups. A targeted marketing campaign may benefit from knowing that people over a certain age are more likely to use different social media platforms than people under 20.  Or a physician and patient may benefit from knowing certain age groups are more likely to face certain health issues and need screening for certain diseases.  Stereotypes can also address fundamental differences in life experiences between generations.  For example, Gen Z grew up immersed in a digital world, whereas earlier generations grew up acquiring digital skills, perhaps changing how we design interfaces for Medicare versus home schooling?. 

But the key lies in the phrase ‘large groups of people’.  There are times when its really useful and beneficial to make approximations on when dealing with large groups. But as tempting as it can be when having to make a quick judgement, or to quickly filter a large number of people, as in my friends original question, applying them to individuals is often misleading, and risks throwing the baby out with the bathwater. 

No matter what grouping strategy we apply, we need to be really careful about applying them at an individual level. And there are of course many different ways to group things, whether it’s categorization, archetypes, stereotypes, sensory cues or many others, depending upon context and goals.  I’ve deliberately blurred the lines between these, because in reality, people tap into different ones depending upon goals, contexts, personal experience or personal knowledge.  And to a large degree, similar principles apply to all of them.  That leads to a couple of concepts, which while pretty obvious, I think are worth sharing or reiterating:  

1. Stereotypes can be useful when applied to large groups of people, but judging an individual through that lens is disingenuous in both directions. Take gender as an example. There are distinct, scientifically measured differences between men and women if we look at them at the large group level. These differences can be physical, behavioral or both.  Perhaps the least controversial is that ON AVERAGE, men are taller and stronger than women. But importantly there is also massive overlap between genders, and there are many, many individual women who are taller and stronger than individual men. We intuitively get that, and nobody would recruit for a job that requires hard physical labor by ruling out women. But conversely, if we are designing a clothing line, we’d be foolish to ignore those average differences when developing sizing options and inventory. Gender differences are potentially useful when dealing with large numbers, but potentially highly misleading on an individual basis

Similarly, using generational stereotypes to target ‘digital natives’ for a tech job may superficially sound reasonable, as it did to my friend.  But it risks ignoring strong candidates who may reside outside of that category.  Even if Gen Z as a whole may arguably have a more intuitive understanding of tech, there are many individual Millennials, X’ers and Boomers who are more technically savvy than individual Z’ers.  Designing software targeted at large groups of specific age groups may benefit from group categorization, but choosing who to write it on that basis is a lot less effective, if at all.  

2. Grouping is how we often manage complex decisions. Faced with more than a few individual choices, pragmatically, we often have to find some way to narrow choice to manageable numbers. For example, in Las Vegas we have 2,500 restaurants. When deciding where to eat, we cannot consider each one individually. We instead use grouping filters like location, cost, cuisine, familiarity or ratings. It’s not perfect, it’s often not a conscious strategy, and we may miss a great restaurant, but it beats the alternative of starving while we cross reference 2500 individual options. Recruitment these days is similar. Most job openings get multiple candidates that we must narrow to manageable numbers. But we need to be careful that we carefully select criteria that benefit us and candidates. Those may vary by context. But especially as we defer screening and decision making to AI and automation, it’s so important that we really understand what those criteria are, and how they benefit our search. I’d argue that generational stereotypes are a particularly ineffective filter in narrowing our choices for many things, especially for recruiting or career management.

3.  Not all stereotypes or categories are accurate.  Even if they feel intuitively right, they may be neither accurate or predictive.  In part this is because they are often based on (superficial) correlation, instead of causation. For example, historically a common stereotype was that women were considered less able at math and science than men.  It was true that for a long time men were better represented in these fields.  But the stereotype that men were were more skilled was fundamentally inaccurate.  We now know there is no gender difference in that innate ability.  But a mixture of social factors, and a feedback loop created by a self fulfilling stereotype created an illusion of meaningful difference.  Conversely, men were considered less empathic than women.  The actual science is far less clear on this, and there may be some small innate gender differences.  But if they exist, they are sufficiently small that it’s hard to separate whether this is due to self reporting biases, socialization, or meaningful differences in biology. But certainly the difference is too small to preclude men from careers that require a high level of empathy, a stereotype that existed for quite some time in, for example, fields such as nursing, which were long dominated by women. 

Even today, only 13% of registered nurses in the US are male, and only 31% of engineers are women  Self fulfilling stereotypes can be particularly hard to see through, let alone break, because they reinforce their own illusion. 

But all of this said, some stereotypes can still be useful.  Take the stereotype that the Swiss are punctual, organized and ‘on time’.  If you are planning on catching a train for an important flight, nearly 95% of trains in Switzerland arrived on time in 2025. In Italy, the number was less than 75%.  That of course doesn’t guarantee than the Swiss train will be on time, or the Italian one won’t. But it does make it prudent to add a bit more padding into an Italian travel itinerary, or at least research back up options!

And then there are examples like the tomato.  No matter how you pronounce it, the tomato is technically a fruit.  But it is commonly used as a vegetable.  So is it more practically useful to categorize it as a fruit or vegetable? I’d argue vegetable.  

In conclusion, stereotype, categories, grouping and similar mechanisms are a fundamental part of the way we as humans deal with large amounts of data.  And at least at one level, as the amount of data we are exposed to explodes, we are going to need those filters more than ever.  But they can also be highly misleading, especially when applied to individuals, so we need to understand when and how to use them, and treat them with a lot of caution.  

Image credits: Google Gemini

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Allocating Resources to Solve Horizon 2

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Another Tough Challenge

Allocating Resources to Solve Horizon 2

GUEST POST from Geoffrey A. Moore

We’ve known about this problem forever—how do you find a principled way to allocate budget across three different horizons of ROI.

  • Horizon 1 pays off in the current year and equates to the funding needed for you to make your operating plan and meet or beat investor guidance.
  • Horizon 3 pays off downstream, typically by making a speculative bet on an emerging category or market that would come to fruition in the out years. Since it is still early days, these bets are relatively small and can be measured by and managed to venture milestones.
  • Horizon 2 is the troublemaker. It calls for a material investment in gaining power in the near term in order to compete effectively in the mid-term. That investment will come out of Horizon 1, either from the Performance Zone trying to make the number or from the Productivity Zone trying to supply the needed support to do so, and most likely both.

In short, both internally and externally, Horizon 2 investments are not popular, even though everyone recognizes that they are critical to long-term success. So what is the process by which one can do right by them?

The key is to recognize that the ROI from Horizon 2 is measured in units of power, whereas that from Horizon 1 is measured in units of performance, and that the two must not be mixed. Now, to be clear, performance creates the funding for power, and power creates the foundation for performance, so they are deeply intertwined. But each has its own metrics of success, and the time lag between them says they cannot be blended.

Power always precedes performance. To underfund power is to jeopardize your future performance, the ultimate result being the liquidation of your franchise. To underfund performance, on the other hand, is to jeopardize the cash flow that you need to fund power, putting your market cap at risk, the ultimate result being to attract an activist investor who will oversee the liquidation of your franchise. There is no safe path to take, only a precarious middle way to traverse.

Now, again to be fair, in good times when your category is enjoying secular growth, you get to have your cake and eat it too. That is, you produce amazing cash flow, have a fabulous market cap, and have resources aplenty to invest as you choose. My colleagues still refer to the period leading up to the first tech bubble as “ the time of the great happiness.” Be that as it may, for most of us in 2024 (our friends in GenAI being a notable exception), this is not such a year. We have to make tough choices, and we have to make them now.

So, back to process — and CFOs, take note because you’re likely the one to be leading it.

  1. Separate strategic planning from annual budgeting by at least one quarter.
  2. Charge each business unit to pitch a strategic plan that would create returns substantially above and beyond their current operating model. Included in this plan is a ballpark estimate of the funding that would be required to implement it.
  3. Facilitate an Executive Leadership Team review of the overall portfolio of opportunities, culminating in a rank-ordered list.
  4. Consult with the CEO to determine how much of next year’s operating budget can be allocated to strategic investments, and in that context, which investments should be prioritized for funding. This funding will be allocated in advance of the operational budgeting and ring-fenced to ensure it is spent as intended.
  5. Most strategic investments will be funded as nested incubations, meaning they will be managed within an existing business unit, and are funded as part of their operating budget. However, you must insist that these efforts be isolated, measured, and accounted for separately from the core business, as they are intended to deliver power outcomes, not performance outcomes, and need to be held accountable to different success metrics. (If you do not do this, their operating budget funds will drift away to supplement Horizon efforts to make the number, and the strategic initiative will falter for lack of sufficient investment.)
  6. Truly disruptive incubations, on the other hand, need to be funded outboard of the current business unit structure, in a corporate Incubation Zone, governed by an Incubation Zone board managing a ring-fenced Incubation Zone fund, following the operating model of venture capital. This is covered in detail in Zone to Win.
  7. At this point budgeting can turn its attention to Horizon 1 and how best to allocate funding to hit the current year’s financial targets.

This process solves for two perennial missteps in annual budgeting. The first we might call “the leftovers approach.” First, you allocate all the resources needed to make your Horizon 1 commitments, and then you look to what’s left to fund strategic initiatives. There will be some resources in the kitty, but not as much as there could be since Horizon 1 managers want to reserve some contingency funding. The result is a bias toward modest investing in incremental innovations that do not create future power but rather extend the current footprint.

The second misstep we can call “the variable approach.” Here you allocate half the resources at the beginning of the year and make the second half allocation contingent upon meeting the Horizon 1 plan for that period. The problem here is that strategic initiatives require sustained investment throughout their time in the J-curve. If you flinch and pull back at any point, you lose momentum, never to be regained. This is a big advantage venture-backed companies have over in-house efforts and one of the reasons why VCs love to invest in a downturn.

That’s what I think. What do you think?

Image Credit: Unsplash

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Why a Customer Experience Audit is Non-Negotiable in 2026

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An Analysis of ROI, Retention, and Brand Resilience

Why a Customer Experience Audit is Non-Negotiable in 2026

LAST UPDATED: May 29, 2026 at 8:20PM

by Braden Kelley and Art Inteligencia

In the current business landscape, the traditional boundaries of competition have dissolved. Pricing is transparent, product features are rapidly emulated, and global logistics have leveled the playing field for distribution. What remains as the final, most defensible frontier is Customer Experience (CX). However, many organizations operate on assumptions rather than evidence, relying on outdated journey maps that don’t account for the rise of generative AI, omnichannel complexity, and the heightened emotional expectations of the modern consumer.

A Customer Experience Audit is not merely a “health check”; it is a rigorous diagnostic process designed to uncover the “silent killers” of conversion and loyalty. It bridges the gap between how a company thinks it is performing and how the customer actually feels at every touchpoint. By systematically evaluating the friction, flow, and emotional resonance of the brand journey, organizations can transform from being reactive service providers to proactive experience leaders. Below, we explore the ten most compelling reasons to initiate this audit, backed by the latest industry data.

Top 10 Reasons to Conduct a CX Audit

1. Identify and Eliminate Friction Points

An audit maps the real-world customer journey to find where users drop off. Small changes to these “micro-moments” can yield massive returns.

  • The Statistic: Simplifying a complex sign-up form can increase successful registrations by 20% (Reform).
  • The Insight: 53% of consumers say being kept on hold alone is reason enough to stop doing business with a brand (Webex/Futurum Group).

2. Improve Customer Retention and Reduce Churn

Acquiring a new customer is significantly more expensive than keeping an existing one. Audits identify the specific negative experiences that drive customers to competitors.

  • The Statistic: Resolving CX issues can reduce churn by 85% (Esteban Kolsky).
  • The Insight: 60% of customers will leave a brand after just one or two negative experiences (Zoom, 2025).

3. Maximize Revenue and Upsell Opportunities

Satisfied customers aren’t just loyal; they are less price-sensitive and more open to higher-value offers.

  • The Statistic: Companies that excel at CX see an average 80% increase in revenue (Zippia/Zendesk).
  • The Insight: 61% of customers will spend at least 5% more with a brand they know provides a good experience (Emplifi).

4. Optimize the Onboarding Experience

The first post-purchase interaction sets the tone for the entire relationship. Audits ensure your onboarding isn’t frustrating or confusing.

  • The Statistic: Effective onboarding makes customers 92% more likely to renew their subscriptions (TSIA/OnRamp).
  • The Insight: Interactive and engaging onboarding content can boost early product usage by 55% (Wyzowl).

5. Validate AI and Automation Strategy

Many companies layer AI over broken processes. An audit ensures your bots are actually helping rather than “getting stuck in loops.”

  • The Statistic: AI adoption can increase the number of issues resolved per hour by 15% (Quarterly Journal of Economics, 2025).
  • The Insight: 80% of customers expect bots to escalate to a human when needed, but only 38% say this actually happens (Zoom, 2025).

6. Align Internal Silos

Audits reveal when different departments (Sales, Marketing, Support) are providing conflicting information, which destroys customer trust.

  • The Statistic: 90% of customers expect consistent interactions across all channels (SDL/Renascence).
  • The Insight: 54% of organizations cite “fragmented or siloed data” as their biggest barrier to leveraging customer insights (Zendesk).

7. Benchmark Against Competitors

In 2026, CX is the primary differentiator as products and pricing become easier to replicate.

  • The Statistic: 89% of businesses are expected to compete primarily on CX this year (Gartner/OnRamp).
  • The Insight: Customer-centric brands are 60% more profitable than those that do not focus on CX (Deloitte).

8. Personalize with Purpose

Generic “Dear [Name]” emails no longer count as personalization. Audits help you use data to anticipate needs and determine the most authentic places to personalize customer interactions and experiences.

  • The Statistic: Brands with mature personalization are 71% more likely to report high customer loyalty (Deloitte).
  • The Insight: 80% of consumers are more likely to purchase from a brand that offers tailored experiences (Epsilon).

9. Enhance Employee Satisfaction

When customers are frustrated, frontline employees bear the brunt of that anger. Fixing the CX reduces agent burnout.

  • The Statistic: 62% of respondents identified a defined relationship between Ex and Cx, stating that the impact was “large” or “significant” and measurable. (Workstep).
  • The Insight: Companies with strong CX leadership are 2x more likely to have engaged employees (Temkin Group).

10. Turn Feedback into Action

Most companies collect feedback, but few act on it. An audit creates a structured roadmap for implementation.

  • The Statistic: Acting on customer feedback can lead to a 25% reduction in churn (Forrester/Renascence).
  • The Insight: 77% of customers view a brand more favorably if they proactively invite and act on feedback (Microsoft).

Summary Table of Audit Benefits

Benefit Impact Metric Source
Revenue Growth 80% increase Zippia/Zendesk
Retention 25-30% improvement Martin Newman
Profitability 60% higher than peers Deloitte
Operational Efficiency 10-15% cost savings Martin Newman

Conclusion: From Insight to Transformation

A Customer Experience Audit is the bridge between organizational intention and customer reality. In an era defined by rapid technological shifts and declining brand loyalty, the ability to see your business through the eyes of the consumer is your greatest competitive advantage. The statistics provided throughout this analysis make a clear case: companies that invest in understanding and optimizing their journey are not just surviving—they are significantly outperforming their peers in revenue, retention, and employee engagement.

However, an audit is only as valuable as the actions that follow (for more see Customer Experience Audit 101). The true power of this process lies in its ability to align internal silos, validate high-stakes investments in AI, and foster a culture of continuous improvement. As we move further into 2026, the question for leadership is no longer whether you can afford to conduct a CX audit (aka Customer Experience Risk and Revenue Leakage Diagnostic), but whether you can afford to continue operating without the clarity one provides. By prioritizing the human-centered elements of your business, you secure not just a transaction, but a long-term piece of your customer’s future.

Customer Experience Audit ROI Flipbook
Download the ‘Top 10 Reasons to Conduct a CX Audit’ flipbook PDF

Looking for someone to conduct an independent customer, partner or employee experience audit? Braden Kelley specializes in conducting these kinds of audits, mapping the relevant journeys and benchmarking your performance against select competitors.

Book Your Experience Audit Today

Image credits: ChatGPT

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article and add citations.

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Humans Don’t Have to Perform Every Task

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Humans Don't Have to Perform Every Task

GUEST POST from Shep Hyken

There seems to be a lot of controversy and questions surrounding artificial intelligence (AI) being used to support customers. The customer experience can be enhanced with AI, but it can also derail and cause customers to head to the competition.

Last week, I wrote an article titled Just Because You Can Use AI, Doesn’t Mean You Should. The gist of the article was that while AI has impressive capabilities, there are situations in which human-to-human interaction is still preferred, even necessary, especially for complex, sensitive or emotionally charged customer issues.

However, there is a flip side. Sometimes AI is the smart thing to use, and eliminating human-to-human interaction actually creates a better customer experience. The point is that just because a human could handle a task doesn’t mean they should. 

Before we go further, keep in mind that even if AI should handle an issue, my customer service and customer experience (CX) research finds almost seven out of 10 customers (68%) prefer the phone. So, there are some customers who, regardless of how good AI is, will only talk to a live human being.

Here’s a reality: When a customer simply wants to check their account balance, reset a password, track a package or any other routine, simple task or request, they don’t need to talk to someone. What they really want, even if they don’t realize it, is fast, accurate information and a convenient experience.

The key is recognizing when customers value efficiency over engagement. Even with 68% of customers preferring the phone, they also want convenience and speed. And sometimes, the most convenient experience is one that eliminates unnecessary human interaction.

Smart companies are learning to use both strategically. They are finding a balance. They’re using AI for routine, transactional interactions while making live agents available for situations requiring judgement, creativity or empathy.

The goal isn’t to replace humans with AI. It’s to use each where they excel most. That sometimes means letting technology do what it can do best, even if a human could technically do the job. The customer experience improves when you match the right resource to the customers’ specific need.

That’s why I advocate pushing the digital, AI-infused experience for the right reasons but always – and I emphasize the word always – giving the customer an easy way to connect to a human and continue the conversation.

In the end, most customers don’t care whether their problem is solved by a human or AI. They just want it solved well.

Image credits: Google Gemini, Shep Hyken

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