Author Archives: Geoffrey Moore

About Geoffrey Moore

Geoffrey A. Moore is an author, speaker and business advisor to many of the leading companies in the high-tech sector, including Cisco, Cognizant, Compuware, HP, Microsoft, SAP, and Yahoo! Best known for Crossing the Chasm and Zone to Win with the latest book being The Infinite Staircase. Partner at Wildcat Venture Partners. Chairman Emeritus Chasm Group & Chasm Institute

Compelling Narratives

Compelling Narratives

GUEST POST from Geoffrey Moore

As human beings we cling to two misconceptions of life. The first is that life is fragile. That is not quite right. Living things are certainly fragile — we are all subject to injury and will eventually die. Even whole species can go extinct. But life itself is anything but fragile. It originated some 3.5 billion years ago and has subsequently taken over the entire planet — land, water, sky, even deep within the earth — and shows no signs of loosening its grip. Life per se, in other words, may be the most powerful force we can experience.

Our second misconception is that, when it comes to our own lives, we are the ones in charge. There is some truth in this, but there is also truth in the notion that life is in charge of us. That is, life per se has an agenda that is independent of us, an agenda in which we are inexorably embedded, one that is grounded in the two universal functions that have enabled it to withstand the test of time — metabolism and reproduction.

We know a lot about these two functions from our study of the microbiology of the cell. Both entail a mindboggling number of chemical reactions chained together by a myriad of cascading pathways that are in turn governed by a byzantine array of positive and negative feedback loops. What is truly astounding is that, working in tandem, they have, from their very inception, been both dynamic — ever-changing—and persistent — continuity-maintaining. Life per se, in other words, is characterized by sustained dynamic equilibrium.

To be sure, life has evolved enormously since its cellular inception. After about 2 billion years of single-celled organisms only, cells began to collaborate with one another, leading to the emergence of additional layers of complexity. Over the 1.5 billion years since, they have generated all the variety of living things we see today, as well as a huge variety of species that have passed out of existence. But amidst all that change, over that entire immensity of time, at the level of the cell itself, this absurdly complex concatenation of cascading processes has never ever stopped. Based on this history, I think we must conclude that living things are compelled to live, and that includes us.

Yes, we can end our lives through suicidal interventions, but we cannot will our hearts to stop beating or our lungs to stop breathing. We can’t stop sleeping, and we can’t stop waking up. In short, we are embedded in something that is much larger and more powerful than our conscious selves, and we need to appreciate how this shapes our lived experience.

It turns out there is a whole tradition in philosophy called phenomenology that takes this premise as its starting point. It is organized around the work of Edmund Husserl and Martin Heidegger, but not in a way I am happy with. Like most philosophers, Husserl and Heidegger anchor their work in analytics and then search for narratives to illustrate their concepts. This runs counter to the fundamental premise of The Infinite Staircase, namely that the stairstep of Narrative precedes the stairstep of Analytics, both in evolutionary time and in order of priority when establishing meaning. That is, you need to get your narratives in focus first and then apply analytics to them, not the other way around.

The reason this is so important is that lived experience expresses itself in narratives, not analytics. Analytics abstract from narratives underlying principles which can be used to refine our strategy for living. This is an incredibly important function, one that underlies virtually all the amelioration of the human condition that we have accomplished over the past several centuries. But analytics cannot substitute for narratives. They cannot capture the immediacy of experience nor engage our sensibility with anything like the power of narratives. We are story-telling creatures, first and foremost. That’s how and where we develop our understanding of cause and effect.

Now, if we take the notion that we are compelled to live and we add it to the notion that narrative is our primary mode for processing lived experience, we can reasonably surmise that we are compelled to tell stories. What might that mean?

Well, for those of us in business, this is not a big surprise. We spend the bulk of our time engaged in storytelling and listening. What are you working on? How is it going? What’s the plan? How did the call go? Did you find that bug? What did Harry want? You get the idea. Stories are our lived experience, even more so if we are working remotely.

More formal occasions call for more formal storytelling, be that a proposal, a report, an analysis, an earnings call, or an annual plan. The point is, in all those situations, we are compelled to tell a story. Now, to be sure, our story may well be challenged–that is the function of analytics—but it is not OK not to tell one. The reason is that all our future actions will ultimately be grounded in a story that we agree to accept. Even the most routine bureaucratic approval cycles involve storytelling at some point in the process. We cannot act without a storyline to guide us. Thus, we are compelled to tell stories.

This is even more the case in the realm of politics. Today we are awash in political storytelling, much of which is being labeled misinformation. But the term is misleading. It implies that the teller has got their facts wrong. But that is not what is happening. Instead, they are telling a story that they believe will generate the political response they are seeking, be that to get themselves elected, or to prevent someone else from being elected, or to get legislation passed, or to block legislation from being passed. Our job as responsible citizens is to apply our analytics to their narratives to detect the ones we endorse and those we repudiate.

In both business and politics, pressure-testing the narratives we are presented with requires both judgment and experience. We normally do not have access to an irrefutable body of facts. Instead, we have to assess the character of the storyteller based on how they come across to us, how self-serving their story might be, how plausible it is, and the like, and we often draw on the opinions of professional commentators whom we have found to be trustworthy. There is no guarantee we are going to get things right, but the more due diligence we do, the more likely we will get close.

But what about all the lies? What about all the blatant liars that are just getting away with it? Why aren’t they being held to account? Why do their supporters believe them? The answer, in my view, is because they want to. People are not stupid. They know when other people are lying. The reason they accede to such lies and bully each other into accepting them is because the story being told validates their lived experience. You or I might repudiate the narrative, but we cannot repudiate their lived experience. That is theirs, not ours.

What we can do is share lived experiences with each other with the goal of finding common values. This requires a level of civility that we see openly mocked and that mockery is perhaps the most dangerous current in our present circumstances. It is not the narratives that are the problem. It is the sneering. We can work our way out of the toughest situations if we respect each other’s perspectives. We cannot do so when we demean or demonize our opponents. Stories and storytelling are the currency of our being. We cannot let it be debased.

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

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The Slowing EV Market

The Slowing EV Market

GUEST POST from Geoffrey Moore

One initiative that is top-of-mind for curtailing climate change is the electrification of ground transportation. The meteoric rise of Tesla drew the world’s attention to EVs, and China’s fast-follower public-private partnership has taken the industry to a whole new level. But now it is encountering a lull, and that raises the question, where do we go from here?

A couple of years ago LG announced a breakthrough in a battery-manufacturing technology called dry-coating that is expected to lower cost from 17 to 30%, with expected deployment in 2028. In a steady-state market, this would be welcome news indeed, but for a market that is still developing, it is not the sort of risk-adjusted return on investment (ROI) nor the kind of rate of return (IRR) that will attract private equity. LG is looking to future growth in its existing battery business to reward its efforts and counting on its investors to have the patience to wait for it.

Meanwhile, in the US, the first wave of venture returns has come and gone, and the next wave depends upon enormous amounts of capital being invested in very long-term charging infrastructure projects, the kind that are normally funded by bonds. This is reminiscent of the national commitment that underwrote the interstate highway buildout in the 20th century, but it is not clear we have the political consensus to prioritize such a project.

Ironically, we do not lack for capital to fund these efforts. The past several decades of digital transformation have created enormous pools of wealth, and financial managers are anxious to put that capital to work. The problem is that, for this phase of investment, the ROI and IRR performance metrics that accompany the creation of that wealth are neither appropriate nor available.

Private capital, for better or for worse, is driven by its compensation systems. We saw this when we tried to leverage its expertise to create carbon-credits exchanges. Not surprisingly that led to a sustained gaming of the system that has generated plenty of fees but done nothing to improve the climate situation. What we need instead is a private-public partnership based on a genuine commitment to global good.

Such a partnership is possible, but only if our political leaders are committed to such values, something we should all keep in mind when we vote this fall. At present, the electoral conversation is so consumed with personalities seeking to score points with abusive rhetoric that there is little prospect for any such partnership to emerge. But we need not capitulate to that rhetoric. If the time to change course is now, then we should hold ourselves and our country accountable for doing so.

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

— Image credit: Pexels

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The Actual Future of AI

The Actual Future of AI

GUEST POST from Geoffrey Moore

AI is the number one topic in the boardroom this year, and everybody wants to know how it is going to play out and what that means for their enterprise. Well, it’s not as if we have never seen versions of this movie before. How did the Internet play out? The Worldwide Web? eCommerce? Cloud computing? Smartphones? Digital marketing? Ride-sharing? Streaming media?

This is the Technology Adoption Life Cycle at work, for sure, and has been the basis of my life’s work and that of many colleagues as well. That said, however, most of our time has been spent helping clients see how best to navigate the current state of that life cycle, either as a disruptor or a disruptee. That’s all well and good, but what the board really wants to know is what can we expect from the end state. Where will all this land, and what future do we need to prepare for?

To answer this question properly we need to lay out the landscape of work along two axes (shockingly, creating a 2X2 matrix, the gold standard for all consulting models). One axis discriminates between output that is differentiating, giving customers a reason to choose your offers over those of your competitors, in contrast to work that is industry standard, things every competitor is expected to deliver. The other axis discriminates on the basis of risk exposure, distinguishing between outcomes that are mission-critical where failure is not an option, in contrast to outcomes that can tolerate a certain amount of scrap or rework.

We call this the core/context framework, and when overlaid onto the future of AI, it can look something like this:

Core Context Framework Geoffrey Moore

In the context of this diagram here is how I predict the next ten years of AI will play out:

1. Stupid stuff first. One thing to which we will all testify is that there is no lack of stupid stuff encumbering the workflow of our daily lives. Wherever bureaucracy reigns, there will be an unending stream of compliance requirements, be that in the public or the private sector, and we suffer this burden because it does underpin the rule of law, albeit onerously.

Fulfilling these requirements does not take creative genius, it takes attention to detail and considerable patience. Humans are not strong on either front, but AI is, and this is where enterprises are already weighing in and will continue to do so for the rest of the decade and more.

That said, the ROI from such efforts is modest. Basically, we are automating an inefficient system, which does reduce cost, and does free up human talent to be used elsewhere. But what we find is that human talent is not as fungible as we would want, many displaced workers cannot find employment at a comparable salary, and the rest of the enterprise is not improved in any marked way. Things overall are better, but not a lot better.

2. Cool stuff in parallel. When it comes to new technology, wherever the risk barrier is low, technology enthusiasts will lean in regardless, whether that be on their own time or their employer’s. What they are doing is playing with an inefficient system, seeing what the bright new shiny object might bring to the table. This does take creative genius as well as some creative license, so once again, patience is required, but this time it is on the part of the investor or supervisor.

That said, in the domain of consumer products and services, there is the potential for blockbuster ROI here, as any number of freemium plays have demonstrated in the past. Many are short-lived, to be sure (remember ringtones?), but in their short life, they can capture an extraordinary amount of discretionary spend. And others can mature into abiding infrastructure as search, messaging, and file sharing have all demonstrated.

The key here is that these are not mission-critical and, therefore, do not attract regulatory regimes. If and when they should do so, as is happening with social media now, then their economics can turn upside down in a hurry.

3. Serious stuff takes time. This is where most of the big and abiding ROI will come from. When work is mission-critical but not differentiating, it requires considerable investment in table-stakes processes, which garner no premium in the marketplace. To be brutally honest, there is no prize for doing this work well but considerable penalties for any mistakes you make (think ransomware for a bone-chilling example).

In the 1990s, there was an Internet-enabled revolution in enterprise manufacturing that introduced global outsourcing as a high-ROI way to address mission-critical context workloads—move the work from your company, where it is context, to their company, where it is core. This was a hugely disruptive innovation, allowing the economies of China, India, and now Southeast Asia, to expand at exponential rates, creating increasingly vibrant middle classes where there were none before. However, these benefits have come with a price, both in terms of geopolitical risks, supply chain vulnerabilities, and societal downsides, all of which we are still trying to come to terms with.

Here, AI can have a major impact, not by automating an efficient system, but by completely reengineering it. This will entail on-shoring a lot of manufacturing and displacing a lot of call centers as we introduce more and more AI into these mission-critical workflows. The gains will be in faster response to changing market demands, better returns from high-variability small-volume manufacturing runs, and reduced scrap and rework. At the outset, these changes will entail a considerable amount of human-in-the-loop processing, but eventually, because AI-enabled systems need never stop learning, the human will become the biggest source of error in the system, and we will transition to full autonomy (self-driving cars will be a case study of this transition).

4. Game-changing happens when it happens. There is a reason why so many billionaires have appeared in my lifetime (I personally forgot to become one). Their fortunes are the natural outcome whenever a disruptive innovation does not simply reengineer the existing inefficient system but instead completely replaces it. Amazon Prime, Uber, Netflix, Salesforce, NVIDIA, Apple — each company categorically changed the landscape, rendering the incumbents irrelevant, redirecting the cash flows of their entire industry to flow past their doors.

These outcomes are inevitable, but they are also unpredictable. They are what puts the venture in venture capital. The good news for incumbents is that they do not happen very often, and even when they appear to be succeeding, they can still stumble and fall. That said, sooner or later there will be a reckoning, and that is when the incumbents need to activate their Transformation Zone if they are going to survive the transition.

My altruistic wish is that for AI, this time around, the target will be the public sector. Higher education, social services, healthcare, and law enforcement are all staggering under increasingly untenable demands accompanied by shrinking workforces and restricted budgets. All of them are target-rich environments for applying AI both to stupid stuff and serious stuff. We have never disrupted these sanctums in the past, each having been ruled by regulatory regimes and professional guilds that have deeply conservative roots blocking the kinds of changes that are now needed. Displacing these systems will take decades, but the ROI, both financial and social, would be truly game-changing.

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

— Image credit: Gemini

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Is Your AI in the Zone to Win?

Whether you are catching up, keeping up, getting ahead, and fending off an existential threat, get in the zone!

Is Your AI in the Zone to Win?

GUEST POST from Geoffrey Moore

We’re already almost three years into the modern AI era, and everyone wants to know — What are we doing with AI? The board wants to know, the sales team wants to know, the customers want to know, the analysts want to know. Heck, you want to know.

So, how do you decide?

Start with a clear-eyed assessment of where your company stands relative to its peers in your industry. Are you behind? Are you on par but need to keep up? Are you out ahead or have a chance to be so? Or, in a darker vein, is AI opening your entire industry up to disruption, putting you and your peers under existential threat? The good news is that there are playbooks for dealing with each of these situations. The caveat is that they are all different. You need to execute them, if not linearly, then at least separately. And that’s where zone management can be a big help.

Catching Up

Industries in catch-up mode with respect to implementing AI might include retail (supply chain management, contact center productivity), higher education (admissions, alumni relations), and public sector (regulatory compliance services). The wolf is not at the door, but with AI moving as fast as it is, time is not your friend, so you need to get cracking. This is a job for the Productivity Zone.

Every organization in this zone — finance, HR, marketing, purchasing, customer success, security, you name it—is a candidate for implementing some kind of AI on a low-risk, get-acquainted basis. None of these applications will be so dramatic as to disrupt normal services, but each will give your AI team hands-on experience with the latest available technology, and most should deliver enough ROI to pay for themselves. Even when they don’t, they will contribute to the “Win or Learn” kitty, and that is what catching up is all about.

The key here is to move fast and on every front. That means every organization in this zone has to participate every quarter. Conduct AI progress reviews to hold each org leader accountable for net new wins or learnings every quarter. The goal is to catch up within a year, and it is important enough to tie performance to discretionary compensation to ensure both prioritization and inspection.

Keeping Up

Industries in a keep-up model with respect to implementing AI might include insurance (underwriting, claims), management consulting (tax, audit), and public sector (tax collection). All these areas represent customer-facing processes that are currently served by humans loaded down with routine work that can be done better, faster, and cheaper by AI applications. This is a job for the Performance Zone.

The goal here is to use AI to increase the competitiveness of your established lines of business, either through materially differentiating your products or dramatically reengineering your processes to lower costs, speed response times, and improve quality. The current generation of AI technology, because it is so remarkably approachable, is ready-made to take on this work. Your job is to make sure you use it to target those opportunities where there is the most trapped value to release. These will likely be a bit more gnarly than the others, but when you are mining for gold, you have to go where the gold is.

Generating such higher returns does not come without taking risk. Good as it is, AI is still a work in progress, so you will likely be taking a human-in-the-loop approach for the foreseeable future. The good news is your workforce is expert in your business, so you have the guard rails you need already in place. The challenge is that we humans are comfortable in our established routines, and you need everyone to break out of the old ways to free your company’s future from the pull of the past. This is more of a change management problem than an AI issue, so you should have no qualms about holding the leaders of this zone accountable.

Getting Ahead

Industries with a lot of built-in trapped value represent opportunities for first-movers to get ahead of their peers by radically reengineering the way business gets done. Examples might include residential real estate (title insurance, buyer agent compensation), health care (value-based care, home care), and public sector (social services). In each case, traditional bureaucracies are at odds with where the industry needs to go next, and implementing AI applications can be highly disruptive. This is a job for the Incubation Zone.

Venture-backed start-ups are normally the fastest movers here, but they take a long time to scale. Established enterprises have the customers, the ecosystems, and the balance sheets to get to the finish line first if they can get out of their own way. That’s what the Incubation Zone is designed to do. As described at length in Zone to Win, it emulates the VC operating model without attempting to replicate its financial model. The goal is to win early market marquee customers and cross the chasm, all without any help (or hindrance) from the core business. You have all the resources you need to do this, but it requires muscles you haven’t used in a long time, so funneling one or more acquisitions into the Incubation Zone is often a good tactic.

The key challenge will come when you reach enough scale to bring the new line of business into the Performance Zone. In the best of circumstances, you can leverage the more forward-thinking elements in your partner ecosystem and customer base to create a soft landing, running both the old and new lines side by side, as Netflix did for some time with its DVD and streaming businesses. Sooner or later, however, you will have to rip off the Band-Aid and make the transition to the new path, again as Netflix did.

Fending Off an Existential Threat

At present, the existential threat posed by Generative AI and its successors is still hard to predict, but two industries that have already sensed it are media entertainment (content creation, acting) and publishing (copyright, fair use). What should their playbook be?

This is a job for the Transformation Zone. The playbook requires all four zones to fly in formation to get through a very rough patch. The Productivity Zone goes into action first, launching legal actions against the invaders and pursuing lobbying efforts to get protective legislation. This is not a long-term solution, but it does buy some much needed time.

Meanwhile, the Incubation Zone is charged with catching up to the new wave as fast as possible. The goal here is not to out-innovate the innovators. That is what Yahoo tried to do to fend off Google, and Nokia to fend off Apple. The attackers are too good at what they do, and you are playing their game. Instead, take a lesson from how Microsoft has played catch-up throughout its storied history, beginning catching WordPerfect with Word, Lotus 123 with Excel, Aldus Persuasion with PowerPoint, and moving on to the Mac GUI with Windows, Novell with Windows NT, and Netscape Navigator with Internet Explorer. Most recently, they executed the catch-up-fast playbook to head off Amazon Web Services with Azure. The key to their success is to get to “good enough, fast enough,” not to out-perform the disruptor but to keep their own existing customer base on their side, again buying time to innovate further once it is clear they are in the game to stay.

One thing you do not want to do as an established enterprise is to merge with a successful disruptor. The Time Warner AOL merger provides a cautionary lesson here. The cultures are too different, and the necessary level of mutual trust just isn’t there, so instead of running in parallel, they work at cross purposes, and the result is a tangled mess.

On the Performance Zone side, you have to keep pedaling (and peddling) the legacy line of businesses. Absent private equity, they are your only source of capital, and they are still providing value. But you have to realize that their profit margins are under direct attack and can only be defended through rear-guard actions. That is, your legacy profit pool is the current site of trapped value, and draining it is what is funding the next wave of innovation. You don’t like it, and your investors hate it, but that’s the hand you have to play.

And that brings us to the Transformation Zone proper. You are going through a transition, the intermediate stages of which are ugly, making everyone cranky, and causing rampant second-guessing of every move you make. This is where the CEO must lead with clarity, transparency, and conviction, rallying the troops, reaching out to the customer base, providing an investable narrative to the stakeholders, and reassuring the partner ecosystem. Moreover, every senior executive must unequivocally support the chosen path or else be asked to leave. When you are under existential threat, there can be no fooling around.

Summing Up

The AI tsunami is upon us, and we can expect wave after wave of disruption for the rest of this decade and the next one as well. Clearly, it offers a wealth of opportunity, but as with all waves, catching it depends on getting your timing right and finding the right angle of attack. The four playbooks outlined above have been tested over many decades within the high sector as it dealt with the disruptive impact of the microprocessor, the Internet, cloud computing, SaaS applications, smartphones, and social media. You may not be as familiar with them as you would like, but the risk of waiting on the sidelines exceeds the risk of taking the plunge, so I can only encourage you to grab your nose plugs and jump in.

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

— Image credit: Gemini

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Focus on Delivering Your Customers’ Desired Outcomes, Not Delighting Them

Focus on Delivering Your Customers' Desired Outcomes, Not Delighting Them

GUEST POST from Geoffrey Moore

Now, let me be clear. I have nothing against delight. But the notion that it should be the goal of a business to delight its customers is folly. Delight, after all, is an evanescent experience that comes and goes pretty much as it pleases. It cannot be reliably evoked. More importantly, your customers, and particularly your B2B customers, are not paying you in order to be delighted. Indeed, while ostensibly they are purchasing your products and services, what they really want to buy is outcomes.

As Ted Levitt taught many years ago, while a customer may need to buy a quarter-inch drill, what they really want to buy is a quarter-inch hole. A successful sales campaign, therefore, starts with getting clarity on what outcomes constitute success. This is harder than it sounds. Success is seen very differently from the perspectives of the executive sponsor, the department manager, the end user, the technical specialist, the CIO, and the CFO. All six of these have a stake in the game, and you will need their support to establish an enduring relationship.

Now, to be fair, a lot of business as usual doesn’t call for executive attention because inertial momentum is already on the side of the desired outcomes. It’s when the customer needs to change the status quo that we need to develop a multi-stakeholder current-state/future-state roadmap for success. So, let’s imagine you are in the IT industry and you are looking to land a major new account. What kind of a journey would that entail?

  • The Executive Sponsor. The process starts with engaging the executive sponsor in a discussion of the current state of their business, what potential future state they may have in mind, and what “value traps” are impeding their progress. In this discussion you have the opportunity to demonstrate genuine intellectual curiosity about the dynamics of their company and industry and to propose connections between your offerings and their aims. The deeper this conversation goes, the bigger the opportunity space becomes. This, in other words, is where five-figure deals can become six-figure, and six-figure deals become seven-figure, for the outcome the executive sponsor really wants is to move the big rocks, not just to smooth out the gravel.
  • The Department Manager. Department managers, on the other hand, are up to their ankles in gravel and they need your help to deal with it. Once again, engaging them in an intellectually curious conversation about their value traps allows you to identify the outcomes that will make a real difference and to make sure you highlight them in your proposal and prioritize them in your implementation. The outcome department managers want is productivity improvement for their team, as measured by faster response times, better quality, and greater throughput. The executive sponsor supports this sort of thing, but they have delegated it to the department manager, and so do not need to be directly involved.
  • The End Users. The end users who work for the department manager are the ones whose behavior you will directly impact and whose buy-in you must secure. The outcomes they seek are improvements in their personal effectiveness and efficiency. Most frequently they are looking for relief from mundane repetitive tasks that a smarter system would just do for them in the background. “Free me from the stupid stuff!” might be their battle cry. With the rise of RPA (Robotic Process Automation), complemented now with GenAI (Generative AI), this is becoming increasingly feasible to deliver. One thing to remember with end-user communities, however, is that they mirror the Technology Adoption Life Cycle in miniature, meaning they are comprised of enthusiasts, visionaries, pragmatists, conservatives, and skeptics. Each profile defines successful outcomes in very different terms, so the Customer Success team needs to identify the adoption profile of the individual they are working with before they go about prescribing tactics for meeting their needs.
  • The Technical Specialist. It is not until you get to the technical specialist that you find anyone who is really interested in your product. This, in other words, is the first person who actually wants to see your demo. Demoing to any of the prior three stakeholders is typically a waste of time, at least until you can tune the demo to highlight the outcome they seek. But with technical specialists, it is critical to your success. They are often the ones who get to make the call between competing products that have roughly the same functionality, and you need expertise in both yours and the competitors’ offers so you can answer their questions with authority. A successful outcome for this stakeholder is to have a high-performing product to support.
  • The CIO. The CIO has bigger fish to fry, and once again, you need to be sensitive to where they sit in the Technology Adoption Life Cycle. Visionaries who drive digital transformation will care a ton about platforms to support the future and be desperate to free themselves from the technical debt of legacy systems. Success for them is a next-generation infrastructure that can help modernize their company’s operating model, and they will move heaven and earth to get it. Pragmatists can have similar goals but will want to proceed more methodically, looking for predictable outcomes that come in on spec, on time, and on budget, as confirmed by customer references that are in production. Meanwhile, conservatives are secretly hoping they can just pass this baton to their successor, and skeptics will simply dig in their heels.
  • The CFO. The CFO is likely to view success in terms of verifiable ROI, yet again with a Technology Adoption Life Cycle wrinkle. Conservative CFOs will be looking for “hard dollar” savings—direct reductions in out-of-pocket costs. Pragmatic CFOs will look beyond these to include “soft dollar” savings from productivity gains in throughput, cycle time, and quality. Visionary CFOs (and, yes, there are such folk) look beyond this for step-function changes in competitive advantage that would change the multiple of their stock price. What unites all of the above is that all these success outcomes have some flavor of “Show me the money!”
  • The Account Plan. As sales teams well know, every account plays out in its own unique ways, but we can do our best to nudge it toward our goals. This starts with prioritizing the importance of our six stakeholders with respect to the buying decision on the table. If we have to create or redirect budget, then we need to call high, but if we are simply looking to consume budget, then we need to focus on the middle management instead. So, as an account manager, get your team to rank order the six stakeholders and then focus your efforts on the top two or three.

With respect to those top targets, the next step is to get the team to agree on their Technology Adoption profile. This is super important because you only get a limited amount of attention from any of these folks, and you don’t want to waste cycles on messages that won’t land.

Third, once you get a realistic sense of the outcome that are driving the sales cycle from the customer’s point of view, you need to differentiate your proposal both by calling them out as key goals and then customizing your offer to ensure they will get achieved.

All in all, it’s not rocket science, but it does require patience, and most of all, it calls for you to genuinely engage with the target personas to develop a differentiating understanding of what they are really after.

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

— Image credit: Pexels

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Category Creation

Category Creation

GUEST POST from Geoffrey Moore

Category creation is a critical success factor for start-ups bringing to market a disruptive innovation that calls for a new ecosystem, to support a new class of use cases, funded by a new budget line item. If the category does not form, the start-ups have no place to hang their hat. They can acquire early adopter customers via a bespoke project approach, but they cannot scale any further without help from the rest of the marketplace.

Similarly, established enterprises in mature categories also need to find new venues for growth if they are to break free from their value-investor-set market caps and create net new shareholder value. Whether through acquisition or in-house innovation, they, too, can have the challenge of category creation. So, in both cases, companies need to reengineer the marketplace in order to realize their ambitions. The question is, what would make the marketplace want to lean in?

Marketplaces are made up of ecosystem players, be they partners, competitors, or an installed base of customers. All these constituencies keep their eyes out for disruptive developments that could either benefit or jeopardize their future performance. The early adopters are typically motivated by the benefits, seeking a first mover advantage, while the early majority normally takes a wait-and-see approach, thereby creating a chasm, which in turn can be crossed wherever there is an urgent customer problem that is resisting standard solutions and thus warrants taking a novel approach to solve it. If the category does show it is getting traction, then all those wait-and-see pragmatists will begin to feel threatened by FOMO (Fear of Missing Out), and that is what creates a tornado of demand that puts the category permanently on the map.

Okay, so there is reason to believe that under the right circumstances, markets will support the creation of a new category. That said, we should not underestimate the power of inertia. Markets do not welcome transformational changes with open arms. Indeed, their default move is to deflect most attempts. What we need is a proven playbook. Fortunately, there is one, written some forty years ago, written by an old boss of mine, Regis McKenna.

The Regis Touch

It is hard to overstate the impact that Regis had on high-tech marketing, especially in its early days when it was trying to break free from advertising as its primary medium. At the time, the tech sector was just emerging, the bulk of spending was in B2B markets, the focus was on automating core business processes, and every buying decision entailed considerable risk, not only in terms of the product and vendor’s staying power but also in terms of the impact of the business processes themselves. As a result, advertising per se was not sufficiently informative or credible to drive purchasing. Regis saw this and, with the help of a talented set of consultants and communications professionals, developed a public-relations-led approach that successfully launched hundreds of new products and created dozens of new categories.

The key to his approach was a framework called the infrastructure model that organized the various audiences and constituencies that make up a marketplace in what one might call a ladder of communications:

Relationship Marketing Infrastructure Model Geoffrey Moore

Here’s how it works. The goal is to convert prospects into customers. In B2B markets, those prospects organize around three centers of interest—the technology itself, the impact on productivity, and the financial returns. These prospects get their information most directly from the media, the technologists from the technical press, the end users these days from social media (no such thing, of course, back in the day), and the executives from the business press. The agents of the press, in turn, get a lot of their information from opinion leaders, be they the industry analysts for the technical press, the influencers for social media, or the financial investment analysts for the business press. Those opinion leaders, in turn, get their information from their engagement with the marketplace itself, be they customers, partners, or competitors already involved with the disruptive innovation.

The point is, any claims about the disruptive innovation are verified and validated by working down this model, which means any communications program should organize around working up the same model. Skipping over any one of these audiences and going straight to the prospects directly—the way advertising does—is bound to fail because you have not got your references lined up and sufficiently informed to support and endorse a high-risk buying decision. Product launches and category creation initiatives, therefore, work up this ladder of communications, rung by rung, starting in the executive suite, moving from there to the product organization, and from there to the go-to-market team. That team, in turn, needs to start with educating the ecosystem players, typically with talks and panel sessions at industry conferences, then connecting with the opinion leaders, typically via one-on-one briefings that end up being two-way dialogs, and only then out to the media that will engage with the target prospects.

Category Creation Playbook

A lot of what would go into a complete playbook is product and market-specific, but there are audience-centric principles that remain relatively constant. The key question in each case is, what is it about the emerging category that would be of interest to this particular constituency? With that in mind, here is a brief take:

  1. Executive team. This team will value growth to boost market cap, something that participation in an emerging category can be expected to deliver, but it may well be reluctant to take transformational risk to achieve it. If this team is not 100% behind the effort, don’t start, as every other rung on the latter ultimately calls for investments that this team must endorse.
  2. Product team. This team has to be all in for a wild ride—and usually is. You have to pressure test their claims nonetheless, as they can often get over their skis, promising more than they can deliver within the window that matters.
  3. Go-to-market team. This team requires maturity and patience. The big sales commissions won’t come until the category enters the tornado, so for now, the focus is on creating a market, not harvesting it. That means paying deep attention to developing the ecosystem, including bringing along the installed base, helping to engage and enlist partners, and (oddly enough) encouraging competitors. The last one is important because, ultimately, a category is defined by a set of competitors, not just one company, so for a healthy growing category you need to have peers that are winning too—hopefully in target market segments that are distinct from yours.
  4. Ecosystem. These are the people your go-to-market team is engaging with. The sales team has the installed base, the business development team, the partners, and the marketing team, the competitors. The goal is to get everyone speaking from their own perspective to reinforce your story that something big is underway. One item of note: With respect to competitors, marketing needs to develop a narrative that has room for more than one winner while at the same time staking out turf where your own differentiation makes you the obvious choice. What you do not want to do is bad-mouth the other team’s products—that will create anxiety that will cause everyone to wait and see some more. So, save your sharp tongue for when you get inside the tornado—that’s the no-holds-barred battleground where a well-placed elbow can make a real difference.
  5. Opinion leaders. The goal here is to get conceptual endorsement for the claims you will be making via the media. Opinion leaders need to maintain their independence and do not want to shill for you or anyone else. What they do want to do is look intelligent and have something differentiated to say. What they want from you is enough context to do their job and no interference thereafter. In addition, opinion leaders want to share their opinions with you, in part to influence your future investments, and so it is just as important to listen and ask them questions as it is to present your own story. With respect to your presentation, demos can be useful, but repurposing a customer sales pitch is not, as this audience is not going to buy your product but rather is going to opine on the reasons why other people might.
  6. Media. This is the means by which you will communicate with the three prospect audience types—the technical team, the end users, and the executive sponsors. Each has a preferred media type—industry press, social media, and business press—and each of these types wants to be treated in its own special way. The technical press wants to talk about the product itself. They want facts, love demos, and like to talk to specialists more than generalists. They also are often happy to beta test products or get any other kind of advanced notice as to what’s coming next. Social media wants to talk about the applications of the product, and the ways in which it will impact end users’ lives. So demos can work here only if they are in service to an end-user story as opposed to a run-through of all the features and functions. The business press wants to talk about the “size of the prize,” the impact of the new technology on productivity, how it will reengineer bottlenecking processes, and thus how much trapped value it will be able to release. Demos are wasted here, but PowerPoint can help a lot.
  7. Prospects. When category creation is the focus, it is important to engage the three types of prospects in the right order. If the technology is outrageous, you need to start with the technical audience first just to earn the right to talk to anyone else. If it is not outrageous, then the executive sponsor needs to be your first port of call. The reason is that the other two audiences will actually be willing to meet with you to learn about the latest and greatest thing, but they will have budget, not permission to get new budget, if the executive sponsor is not on board. So a typical path through a major account would start with an executive from your company having a conversation with the prospective executive sponsor at your target customer, which would lead to a referral to the technical team to test your bona fides, and then on to the end-user team, to validate your productivity claims. Proof-of-concept projects are necessary at the very beginning, but one of the major milestones in category creation per se is to generate enough marketplace acceptance that future prospects will forgo these tests.

To sum up, category creation is an outbound communications effort to orchestrate a coalition of the willing across a laddered set of constituencies, each with its own set of interests. The goal is to build an inbound path of verification that reinforces the new category’s right to existence. Trying to shortcut the outbound process by skipping over one or more audiences will defeat the purpose, as any doubts raised this early in the game result in lost momentum that can never be recovered. There is no magic here, but patience and discipline are required.

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

— Image credit: Pexels

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A Tale of Two Narratives on Polarization

A Tale of Two Narratives on Polarization

GUEST POST from Geoffrey Moore

In a time of increasing polarization, amplified by social media and exacerbated by malicious actors, we all need to deepen our understanding of just what we are into. Polarization, as I described in a previous blog on this subject, is best understood as an artifact of people binding their identities to explanatory narratives that validate their experience of the world, especially those experiences that activate their deepest fears. Binding to narrative per se is fundamental to both psychological and social stability, and in that context, it is natural and healthy. But when the narrative is being deliberately corrupted in order to manipulate public opinion, it fosters increasingly antagonistic relationships, dehumanizing the antagonists and inflaming the protagonists, both of which encourage us to treat fellow human beings as targets for marginalization, incarceration, or elimination.

In contemporary culture, there are two framing narratives that are driving this kind of polarization (and let me give shout out to Tangle for calling them to my attention):

  1. Civilization vs the Barbarians. In this narrative, “we” are the defenders of what is good, noble, and sacred in human culture, and “they” are agents of evil, degradation, and blasphemy. Thus, “we” can consider ourselves exempt from ethical accountability in our actions against them because “they” are threatening the very foundation of ethics itself.
  2. Oppressed vs the Oppressors. In this narrative, “we” are the victims of political, social, and economic exploitation by “them,” an overclass that has acquired a disproportionate share of power, wealth, and entitlements illegitimately at our expense. Thus, “we” can consider ourselves exempt from ethical accountability in our actions against them because “they” have unethically disenfranchised us.

Both narratives can be legitimate under extreme conditions, but each also lends itself to inflammatory purposes as well. Historically, the role of news reporting has been to help us distinguish between these two states. What is disgraceful about today’s media is that major broadcast networks, as well as previously highly respected publications, have not just abandoned this role but are actively engaged in subverting it. Let’s look a little more closely at what they are up to.

Civilization vs the Barbarians

This is the narrative framework that underlies Israel’s stance about its war with Hamas. It is also the one the US used to justify its post-9/11 actions against both Iraq and Isis. In both instances, provoked by starkly violent surprise attacks against purely civilian targets, outrage and righteous indignation fueled a demand for massive retaliation. There was simply no room for acknowledging any mitigating circumstances, any possible responsibility for creating the conditions that might have led to the terrorist attacks, or any accountability for subsequent acts of retributive retaliation regardless of how appalling they, in turn, might have been.

Now, given the extremity of the provocations, it is hard to see how any of this could have been avoided. But the civilization-vs-barbarians narrative is being used much more broadly in contemporary political discourse to address concerns that are much less extreme, including the following:

  • Right-wing outrage over illegal immigration
  • Left-wing outrage over anti-abortion legislation
  • Right-wing outrage over students demonstrating over the war in Gaza
  • Left-wing outrage over climate change deriders
  • Right-wing outrage over DEI initiatives
  • Left-wing outrage over 2020 election deniers.
  • Right-wing outrage over atheism
  • Left-wing outrage over book-banning

The key term here, in case you missed it, is outrage. Outrage uses righteousness to legitimize an explosion of anger against a community-sanctioned target. But the roots of that anger are not in the object of its attention. They are in the subject that has been carrying that burden around internally and who has now found a socially acceptable way to release it. And don’t think this applies just to “other people.” No one (except maybe a saint) is exempt here. You and I are as subject to the power of narratives as anyone else—it is only the trigger narratives themselves that separate us.

Look back over the bullet points above. Each of them is encased in a narrative, be it based on fact or urban legend. We should not be naïve about the power of these narratives to shape public opinion and influence elections. Psychologically, they play upon some of our deepest fears and then offer us a protective shield that is both internally coherent and externally impenetrable. That’s what makes the civilization-vs-barbarians narrative such a powerful political tool.

Oppressed vs the Oppressors

This is the narrative framework that underlies US college student protests in support of the Palestinians and against Israel’s sustained offensive in the Gaza Strip, as well as NATO support for the Ukraine and US support for Taiwan. Inside the US, it underpins support for the homeless, defunding of the police, and decriminalization of drug use. In each case, in order to relieve the debilitating conditions these communities are living under, the narrative calls for a radical change in the status quo, including a willingness to deprioritize legal justice in order to achieve social justice.

There are two separate audiences this narrative seeks to engage. Ostensibly, it is the oppressed themselves, but this can be misleading. Under exceptional circumstances, it is true that such narratives can trigger a revolution of the oppressed, but more commonly, these folks are in no position to take action on their own behalf. The far more frequent audience is people of means who have the power to take action and who empathize with the cause. This results in two kinds of calls to action—a revolutionary path, led by the oppressed, which seeks to overthrow the oppressors through violent means, and a liberal path, led by the empathizers, which seeks reform by working within the system.

Although we associate the oppressed-vs-the-oppressors narrative primarily with the left, we should note that the far right is leveraging it as well, as witnessed by the following widely held claims:

  • The woke liberal establishment is imposing socialist agendas around climate change and DEI on the oppressed white middle class.
  • Parental rights are under attack, threatened by liberal ideologies that have taken over public schools.
  • The 2020 election was rigged by Democrats, and Republicans, therefore, need not accept the results of the 2024 election because it also could be rigged.
  • Donald Trump did not get a fair trial because it, too, was rigged.
  • (And at the far right) the tyranny of the Deep State is so oppressive it warrants patriotic citizens taking up arms and shedding blood.

The Implications

To sum up, both political parties are using both narratives, but in very different contexts.

  • US Right: “Oppressors are the woke liberal establishment imposing socialist agendas around climate change and DEI on the oppressed white middle class.”
  • US Right: “Barbarians are the illegal immigrants seeking to invade our country and take over our democracy by outnumbering the civilized native white citizenry.”
  • US Left: “Oppressors are the conservative capitalist establishment imposing unjust requirements on disadvantaged populations, including illegal immigrants, the homeless, and the addicted.”
  • US Left: “Barbarians are the far-right politicians and pundits undermining the rule of law with fake news and demagogic rhetoric to block reproductive rights, equal opportunity programs, and climate change initiatives.”

Any attempt to argue people off of any of these positions is almost certain to fail, not because the arguments that support them are especially persuasive, but because people have bound their identities to them so tightly that they cannot break with them. As part of this binding, society self-segregates into “Us” and “Them,” each with its own amplifying media sources, its own signals of solidarity, its own righteous indignation, its own contempt for the other side.

Given all that, what could anyone seeking a better way possibly do? That is a question for a future blog post, one that is still very much in the works. For now, we should just note when these narratives are being used in corrupt ways to legitimize illegitimate claims and do our best to detach ourselves from them.

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

— Image credit: Pixabay

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Search Engine Marketing in the Era of AI-Assisted Search

Search Engine Marketing in the Era of AI-Assisted Search

GUEST POST from Geoffrey A. Moore

My social media maven, Rich Stimbra, forwarded me the following as a potential blog topic:

Google’s revamped, AI-infused search is making businesses that depend on web search results anxious, and news publishers are already warning it could have “catastrophic” effects on the industry. Why? Google’s newly announced AI Overviews, set to launch this week in the U.S., synthesizes answers to users’ queries, and even though it will probably contain links, information from “know-it-all AI tools” could be thorough enough that users decide not to click through. News sites, whose audiences have already taken a hit from their content being downranked on social media, are bracing for further erosion from Google’s AI update.

Google unleashes AI in search, raising hopes for better results and fears about less web traffic

Boy, was he right. AI is bound to be a game-changer for both media and marketers alike, but not necessarily for the worst, provided that both communities up their games appropriately. Here’s what I think we have to prepare for:

  • Media — Yes, you are going to be disinter-media-ted (ouch!). But if your content is sufficiently differentiated, relevant, and impactful, its quality should cause it to rise to the top of the AI’s selection stack. Most of your material may not pass this test, which means you are going to have to acquire and retain your subscribers on your own. The result is almost certainly to be a smaller but more homogenous subscriber base that will be of more value to marketers targeting your core base and considerably less value to the “spray and pray” bunch. That, in turn, means you will likely be able to raise your CPM rates for those leads you do deliver while pivoting your business model to make more of your cash flow from subscribers rather than advertisers.
  • B2B Marketers — I expect this to be a boon for you because it should filter out a lot of low-quality leads and pass through higher-quality ones. The larger your ASP (Average Selling Price), the more important it is not to pursue underperforming lead-gen. But historically, lead-gen best practices have been developed by the B2C marketers, which encourages a very wide top-of-funnel in order to get as much market coverage as possible. B2B marketing wants a much more qualified top-of-funnel because the cost and time to qualify make low-quality leads a real burden. The CPM for more qualified leads will legitimately be higher, so the direct cost goes up, but the indirect cost of post-processing should decline more than enough to make up the difference. Additionally, business prospects are more likely to act on value-added responses than raw search results, which is good news, provided your content has sufficient relevance and impact to make the cut.
  • B2C Marketers — This is not good news for you. It narrows the top-of-funnel, potentially dramatically, and weeds out marginal leads which you are able to qualify much more cost-effectively than your B2B colleagues. For low-cost items, I expect your digital marketing dollars will shift increasingly to direct-to-consumer venues on popular social media platforms, spending more with influencers and less on raw coverage. For higher-priced ones, I expect a next-gen, AI-enhanced approach to email (text, messaging, etc.) marketing will pay off as well.

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

Image Credit: Pexels

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After the Chasm – Scaling Beyond the Beachhead

After the Chasm - Scaling Beyond the Beachhead

GUEST POST from Geoffrey A. Moore

Crossing the chasm is the single most important goal for a B2B application that seeks to disrupt the status quo. The playbook has held up for more than 30 years because it continues to just work. That said, it does not say anything about what to do if you’re stuck in the mud on the other side. So, let’s suppose your enterprise has successfully crossed the chasm, achieved tens of millions of dollars in ARR, but is no longer growing at a rate to keep pace with the Rule of 40 percent (the sum of your profit and your growth rate). Your investors are getting antsy. Now what?

First of all, know your place. You are still sub-scale for a customer CFO to consider you desirable as a go-to vendor. Same goes for a CIO who is trying to consolidate rather than expand the list of vendors they are working with. So, as with crossing the chasm, your only ally will be a process owner with a problem process that is not getting the IT support they need. This time, however, you are looking for an adjacent process owner, someone for whom your chasm-crossing sponsor would make a good reference. This lowers the bar for how problematic the use case may be because there is already some proof that the solution will work.

Note that we are still at the departmental level, still a point-product app, not a platform, not a suite. Those are all worthy ambitions for the future, but if you try to activate them now, the CFO and the CIO will get involved, and you will get bogged down in proof-of-concept exercises that will take forever to scale.

That said, it is not too early to recruit ecosystem partners to help secure your beachhead and expand your reach. The key here is to engage with companies that are big enough to help but small enough to give you their full attention—not Tier 1 systems integrators, more like outsourced service providers to small and medium businesses or specific departmental functions. You don’t need a lot of these, but the ones you do recruit have to lean in, so make sure that there is enough trapped value in the target use case to pay both you and them a premium for resolving it. To accelerate this effort, ask your professional services team to package up their hard-won knowledge and make it available to the partners who can expand your beachhead market. You want your team to be plowing in the adjacent field, not harvesting in the initial one.

On the go-to-market side, you still need to be disciplined in deploying most of your resources into the target market segment and not letting them get distracted by chasing one-off opportunities elsewhere. That said, you can relax a bit from the laser focus of chasm-crossing as long as, say, two-thirds of the marketing and sales resources are directly aligned with your current goal. Remember at this point that marketing is still a territory capture game, so you want to go after targets that are big enough to matter but small enough to lead, and as always, a good fit with your crown jewels.

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

Image Credit: Geoffrey Moore

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Your 3 Phase AI Journey

Your 3 Phase AI Journey

GUEST POST from Geoffrey A. Moore

As companies move from experimenting with GenAI to deploying for real ROI, executives should plan for three phases of development along the following lines:

Phase One: Optimize your operating model. This is the one everyone gets right away. Every business process is encumbered by ‘stupid stuff’ — low-value-adding tasks that are “how we do business around here.” These are all candidates from process re-engineering, but in the meantime, people have to work through them or around them to get anything done. RPA (Robotic Process Automation) can solve for the ones that are routine. GenAI expands the aperture to include those that demand creating situation-specific text, the sort of thing that would answer an FAQ, nudge a prospect to take a call, or check in on users that are at risk of churning out. Expediting this sort of work is a no-regrets move, entailing little risk while generating modest ROI.

Phase Two: Upgrade your infrastructure model. While you will likely start your Phase One journey leveraging out-of-the-box GenAI from Microsoft, Google, or Amazon, as you get deeper into it, you will want to add RAG (Retrieval-Augmented Generation) to the mix. Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model so it references an authoritative knowledge base outside of its training data sources before generating a response. Basically, it taps into confidential in-house knowledge stores, as well as any external sources that provide expertise specific to your business, to build a more effective prompt for the public GenAI to leverage. Coordinating the APIs, keeping the guard rails on the process, and capturing the reusable knowledge gained will all require additional investment in your in-house IT capabilities.

Phase Three: Revisit your business model. Sooner or later, AI is going to materially disrupt the way business is done in your industry, eliminating old sources of trapped value while creating new ones at the same time. Customers will still look to your company to help them achieve their business outcomes, but they will be paying for different things than they pay for today. Consultancies and legal firms, for example, can expect to re-engineer their billable hour model, financial services their transaction fee model, and search engines their sponsored-ad model. The larger your enterprise, the more disruptive this is likely to be, so this would be a good time to test out new models in your Incubation Zone.

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

Image Credit: Geoffrey Moore

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