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

Company Power Strategy is a Team Sport

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Company Power Strategy is a Team Sport

GUEST POST from Geoffrey A. Moore

Company power is primarily a function of the amount of ecosystem support for your offerings, which in turn is due largely to the market-making opportunities you create for partners to resell or flesh out your whole product. Market share leaders enjoy the most extensive ecosystem support because their installed base creates the majority of partner opportunities.

Let me note, however, that in the context of our Hierarchy of Powers framework, market share is a misnomer. The correct phrase would be category share. That’s because in our taxonomy markets are defined by groups of customers whereas categories are defined by groups of competitors. When financial analysts talk about market share, they are referring to category share, and it is your share of the category that sets the upper bounds of the opportunities you can create for ecosystem partners, the percentage of the total category you can make available to the ecosystem.

After category share, the next most important determinants of company power are barriers to entry and barriers to exit, or what we often just call “stickiness.” Because sticky offerings create ongoing opportunities for up-sell and cross-sell, as well as resist being displaced by lower-cost competitors, they enable vendors to sustain above-commodity pricing margins for the life of the category.

Gorilla Royalty Game

The strongest form of stickiness comes from proprietary technology that is category-enabling, the kind that Oracle has had in databases, Qualcomm in smartphones, Microsoft in operating systems, and Intel in microprocessors. When a category consolidates around such companies, it creates a hierarchy of company power we call a Gorilla Game, entailing three roles — gorilla, chimp, and monkey. In the absence of proprietary technology, categories form an analogous hierarchy with much lower switching costs, something we call a royalty game, organized around a parallel set of roles — king, prince, and serf. Cellular telephony, Wintel PCs, WiFi networking, and DRAM memory chips all exemplify categories with this latter type of structure.

The difference in stickiness between these two hierarchies creates dramatic differences in market capitalization. In the gorilla game, the gorilla dominates the category for the entirety of its life cycle, and thus its market cap gets a very high premium indeed. Chimps also have proprietary technology, hence stickiness, but are not the market standard, hence more limited scope. Their best play is to develop an independent ecosystem organized around high-value use cases specific to particular vertical markets, the way the Unix workstation vendors competed successfully against PCs with CAD-like applications for cinema, semiconductor, oil exploration, fluid dynamics, and high-frequency trading. And finally, there is a very large market open to being served by monkeys who are able to clone the gorilla technology and deliver a plug-compatible alternative at a much lower price.

When it comes to royalty games, the absence of proprietary technology with high switching costs leads to a much more fluid hierarchy of power. The category leader is still the king, but it can be deposed by some up-and-coming prince, the way that Compaq displaced the IBM PC, the way that Micron can challenge Samsung in DRAMs, the way that Aruba can challenge Cisco in Wi-Fi. Here the low-cost providers, whom we termed the serfs, have an easier time gaining entry into a large and growing market, but a harder time sustaining even the most modest of margins, as there is always some hungrier low-cost competitor looking over their shoulder.

Overall, the key takeaway is that, while the gorillas and gorilla games get the bulk of the attention, especially from the investment community, all six of these strategies are perfectly viable provided you play within the parameters of your role. The key is not to hallucinate about what role that is.

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

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Portfolio Management and Category Power

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Portfolio Management and Category Power

GUEST POST from Geoffrey A. Moore

Portfolio management is the most consequential and the most challenging element in strategic planning. There is typically a ton of data, but none of it can really speak to the host of underlying risks that underpin long-range investments in net new lines of business, ones that pay off primarily in the out years. The best one can do is leverage experience, frameworks, and pattern recognition to navigate what are inevitably uncharted waters. With that in mind, here are some things to keep in view.

  1. Category Maturity Life Cycle: Tornadoes versus Main Street. Who doesn’t want a growth portfolio? To get one, however, means your enterprise must have meaningful plays in categories that are undergoing secular growth. Secular growth happens when net new budget is being created for a new purchase category across a broad spectrum of customers, a phase in technology adoption we have termed the tornado. Once the tornado has passed, the category will have an established place in these customers’ budgets going forward, a stage in the life cycle we call Main Street, one that is characterized by cyclical growth. Cyclical growth rewards inertial momentum, the goal being to leverage incumbency to grow wallet share more than market share. Secular growth rewards disruption, the goal being to displace an established profit pool by leveraging an emerging one. These dynamics transcend the efforts of most companies to influence (gorilla leaders being the exception), so assessing category power is first and foremost getting clarity on the hand you have been dealt. That will shape your ambitions for next year’s performance and set a baseline for future investment.

  2. Valuation: Growth investors versus value investors. Both forms of growth, secular and cyclical, are valued by investors for their respective risk-adjusted returns, but in different ways for different reasons. Growth investors are looking for a big pop and are willing for you to take considerable risk to get it. Value investors by contrast seek predictably consistent performance—an earnings-oriented approach that outperforms bonds with a minimum of additional risk. Both groups discount the value of the other group’s approach which exposes the market cap of established enterprises to a “conglomerate discount,” a painful penalty given that their stock is the major currency that will fund any M&A. Managing for shareholder value, in other words, gets hung up on the question, which shareholders? The reality is that most publicly held companies have a mix across the board, so the salient issue to address is how much of our operating budget should we commit to the current year versus the out years? Having a principled discussion on this topic leading to a definitive commitment is essential to creating a coherent strategy.

  3. Capital market status: PE-backed versus publicly held. Strategic planning in privately held enterprises is typically more straightforward because the board of directors representing the investing firms share a common approach to risk-adjusted returns. This is why when publicly held companies like Dell reach a crossroads that requires a patch of difficult sledding, they choose to take themselves private in order to accelerate their course corrections. The price to pay for this option is committing to operating principles, performance milestones, and a management discipline that meets the PE investors’ approval.

  4. Leveraging M&A: Incubate before you commit. Pundits like to claim that most M&A transactions fail to deliver on their promise (although recent research puts the odds at closer to fifty-fifty). Some of the failures, however, are self-inflicted wounds that can be avoided by taking a multi-step approach. If your enterprise has a venture investment capability, taking positions in disruptive start-ups with observer rights is a good way to test the waters. In parallel, the goal is to incubate comparable initiatives internally and get them into the market as trial balloons. The difference between this and the early-stage venture model is that you cannot wait for these organic efforts to scale—it will simply take too long. So, you are not trying to win the game with your new offers, just learn it. Sooner or later, you will turn to M&A to acquire something of meaningful mass, the difference being, because you have spent the intervening time in the market competing, you will be a much more knowledgeable acquirer than you otherwise would be.

  5. Synergy management: Year One is the one that matters most. Value-oriented M&A is intended to consolidate mature categories with cyclical growth. It is based on an inside-out approach to cost reduction focusing on eliminating duplicated functions, typically in the back office and the supply chain. Growth-oriented M&A, by contrast, takes an outside-in approach focusing on accelerating bookings and revenues through a series of go-to-market and customer success initiatives. When a smaller high-growth enterprise gets acquired by a larger, slower-growing one, the opportunity is to galvanize the latter’s existing customer base and ecosystem relationships, as well as its global sales and service footprint, to capture market share under highly favorable selling conditions. The trick is to do this quickly, while the iron is still hot, and that requires special incentives and strong management support to build trust between the old and new guards and to overcome the initial inertial resistance that accompanies any acquisition. In sum, what looks good on paper could very well be good in actual fact, but only after you execute Captain Picard’s famous dictum: Make it so!

  6. M&A integration: Year Two is the one that matters most. If the first year is all about getting the go-to-market right as fast as possible, the second is about creating lasting relationships that will enable the two enterprises to operate as one. There are four areas of interest here—the product team, the sales team, the management team, and the culture overall—and each one calls for a slightly different approach. The single most important outcome is to keep the product talent in place—they have the keys to the new kingdom. The sales team can and normally should continue to function as an overlay during the second year, but in parallel a transition to an integrated organization must begin so that in Year Three the overlay is eliminated. The management team is a wild card. Despite all the best intentions on both sides of the table, including vesting incentives of various kinds, entrepreneurial CEOs rarely stay, nor should they. The skillset for disrupting does not translate well into the skillset for scaling and optimizing. This suggests that from the outset a leadership transition should be on the table, typically enlisting an up-and-coming executive from the acquiring enterprise to personally throw themselves into the gap and pull the two organizations together leveraging every talent and tool they have. Finally, large enterprises necessarily entail an enormous amount of process management, something that goes against the grain of entrepreneurial culture, so one needs to tread carefully here, with the understanding that long term there can only be one enterprise, and by virtue of its scale, it will be process-driven for much of its day-to-day work. To promise the acquired company anything else will only create disillusion and disintegration down the line.

  7. Decision Time: To play or not to play. There is no formula for making transformational decisions, but there are some guidelines to keep in mind. The first is few, and far between. Transformations are disruptive to the core business that is funding your overall operation, and it takes time for everything to stabilize around a new portfolio. A second principle is existential threat. If the emerging category obsoletes a pillar of your core business, the way digital photography obsoleted film, the way that streaming is obsoleting conventional TV, then you must take action. Absent such a forcing function, a third principle to consider is value to the existing customer base, with the corollary of opportunity for our existing ecosystem. In other words, does the world want you to do this? Transformation takes a village, and it matters a great deal how much your constituencies will lean in to help you through it. Finally, when your competitors hear about this, will they smile and laugh, or will they say Oh sh*t! If the latter, it just puts icing on the cake.

  8. Plan B: Leverage the updraft. The stars have to align to make any transformational portfolio play work, and sometimes they simply won’t. Plan B is to incorporate a portion of the tornado category into your existing portfolio as a supplement. Take Gen AI, for example. You don’t have to be in the category like Open AI or Anthropic to participate in the new spending. Virtually any enterprise application can benefit from a Gen AI bolt-on to improve the user experience or simplify the administrative one. Prior experiences with adding mobile applications and digital commerce to legacy systems have delivered similarly positive returns. You don’t have to be in the lead, but customers do want to see you are still in the game, and assuming you show up with a working product, they are more than happy to consume it.

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

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Re-Framing Your Strategy for the Chaos of 2025

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Re-Framing Your Strategy for the Chaos of 2025

GUEST POST from Geoffrey A. Moore

Spring is in the air, which brings to mind the season’s favorite sport — no, not baseball, strategic planning! Let’s face it, 2025 has been a tough year for most of us (and it’s still early days), with few annual plans surviving first contact with an economy that was not so much sluggish as simply hesitant. With the exception of generative AI’s growing impact, most technology sectors have been more or less trudging along, and that begs the question, what do we think we can do with the rest of 2025? Time to bring out the strategy frameworks, polish up those crystal balls that have been a bit murky of late, and chart our course forward.

This post will kick off a series of blogs about framing strategy, all organized around a meta-model we call the Hierarchy of Powers:

The inspiration for this model came from looking at how investors prioritize their portfolios. The first thing they do is allocate by sector, based primarily on category power, referring both to the growth rate of the category as well as its potential size. Rising tides float all boats, and one of the toughest challenges in business is how to manage a premier franchise when category growth is negative. In conjunction with assessing our current portfolio’s category power, this is also a time to look at adjacent categories, whether as threats or as opportunities, to see if there are any transformative acquisitions that deserve our immediate attention.

Returning to our current set of assets, within each category the next question to answer is, what is our company power within that category? This is largely a factor of market share. The more share a company has of a given category, the more likely the ecosystem of partners that supports the category will focus first on that company’s installed base, adding more value to its offers, as well as to recommend that company’s products first, again because of the added leverage from partner engagement. Marketplaces, in other words, self-organize around category leaders, accelerating the sales and offloading the support costs of the market share leaders.

But what do you do when you don’t have company power? That’s when you turn your attention to market power. Marketplaces destabilize around problematic use cases that the incumbent vendors do not handle well. This creates openings for new entrants, provided they can authentically address the customer’s problems. The key is to focus product management on the whole product (not just what your enterprise supplies, but rather, everything the customer needs to be successful) and to focus your go-to-market engine on the target market segment. This is the playbook that has kept Crossing the Chasm on entrepreneur’s book lists some thirty years in, but it is a different matter to execute it in a large enterprise where sales and marketing are organized for global coverage, not rifle-shot initiatives. Nonetheless, when properly executed, it is the most reliable play in all of high-tech market development.

If market power is key to taking market share, offer power is key to maintaining it, both in high-growth categories as well as mature ones. Offer power is a function of three disciplines—differentiation to create customer preference, neutralization to catch up to and reduce a competitor’s differentiation, and optimization to eliminate non-value-adding costs. Anything that does not contribute materially to one of these three outcomes is waste.

Finally, execution power is the ability to take advantage of one’s inertial momentum rather than having it take advantage of you. Here the discipline of zone management has proved particularly valuable to enterprises who are seeking to balance investment in their existing lines of business, typically in mature categories, with forays into new categories that promise higher growth.

In upcoming blog posts I am going to dive deeper into each of the five powers outlined above to share specific frameworks that clarify what decisions need to be made during the strategic planning process and what principles can best guide them. In the meantime, there are still three more quarters in 2025 to make, and we all must do our best to make the most of it.

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

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Contemporary Science versus Natural Language

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Contemporary Science versus Natural Language

GUEST POST from Geoffrey A. Moore

Item 1. The fastest human-created spacecraft goes 165,000 mph. Pretty amazing. But for it to travel one light year would take roughly 3000 years—basically, the length of recorded human history. The closest star system that hosts an earth-like planet (Alpha Centauri) is 4.4 light years away. Thus, it would take today’s fastest vehicle 14,000 years to make a one-way trip. On our earth, 14,000 years ago humanity’s most sophisticated technology was a stone axe. Thus, while we love to talk about space travel outside the solar system, as well as aliens in UFOs coming to Earth, neither is remotely possible, not now, not ever.

Item 2. There are 30 trillion cells in the average human body. There are 100 trillion atoms in a typical human cell. That means there are three thousand trillion trillion atoms, give or take, in you or me. Atoms are so small that it is not clear any words we have would apply to how they actually operate. Particle and wave are two of the ones we end up using the most. Neither of them, however, can coherently explain something as simple as the double-slit experiment.

Item 3. The metabolic reactions that support all life are mind-bogglingly fast. Take mitochondria for example. They are the organelles that produce the bulk of our ATP, the energy molecule that drives virtually all life’s chemical reactions. Of the 30 trillion cells in your body, on average each one uses around 10 million molecules of ATP per second and can recycle all its ATP in less than a minute. There is simply no way to imagine something happening a million times per second simultaneously in thirty million different places inside your own body.

Item 4. Craig Venter has been quoted as saying, “If you don’t like bacteria, you’re on the wrong planet. This is the planet of the bacteria.” In one-fifth of a teaspoon of seawater, there are a million bacteria (and perhaps 10 million viruses). The human microbiome, which has staked out territory all over our body, in our gut, mouth, skin, and elsewhere, harbors upwards of three thousand kinds of bacteria, comprising some 3 million distinct genes, which they swap with each other wherever they congregate. How in the world are we supposed to keep track of that?

Okay, okay. So what’s your point?

The point is that contemporary science engages with reality across a myriad of orders of magnitude, from the extremely small to the extremely large, somewhere between sixty and one hundred all told. Math can manage this brilliantly. Natural languages cannot. All of which means: philosophers beware!

Philosophers love analogies, and well they should. They make the abstract concrete. They enable us to transport a strategy from a domain where it has been proven effective and test its applicability in a completely different one. Such acts of imagination are the foundation of discovery, the springboard to disruptive innovation. But to work properly they have to be credible. That means they must stand up to the kind of pressure testing that determines the limits to which they can be applied, the boundaries beyond which they must not stretch. This is where the orders of magnitude principle comes in.

It is not credible that there could be a cause that is a million million times smaller than its effect. Yes, it is theoretically conceivable that via a cascading set of emergent relationships, one could build a chain from such an A to such a B, but the amount of coordination that would be required to lever something up a million million times is just ridiculously improbable. So, when philosophers refer to the uncertainty principles embedded in quantum mechanics, and then infer or imply that such uncertainty permeates human affairs, or when they trace consciousness down to quantum fluctuations in messenger RNA, when, in short, they are correlating things that are more than a trillion, trillion times different in size and scope, then they are misusing both the mathematics of science and the resources of natural language. We simply have to stay closer to home.

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

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The Role Platforms Play in Business Networks

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The Role Platforms Play in Business Networks

GUEST POST from Geoffrey A. Moore

A decade and a half ago, my colleague at TCG Advisors, Philip Lay, led a body of work with SAP around the topic of business network transformation. It was spurred by the unfolding transition from client-server architecture to a cloud-first, mobile-first world, and it explored the implications for managing both high-volume transactions as well as high-complexity relationships. Our hypothesis was that high-volume networks would be dominated by a small number of very powerful concentrators whereas the high-complexity networks would be orchestrated by a small number of very influential orchestrators.

The concentrator model has played out pretty much as expected, although the astounding success of Amazon in dominating retail is in itself a story for the ages. The key has been how IT platforms anchored in cloud and mobile, now supplemented with AI, have enabled transactional enterprises in multiple sectors of the economy to scale to levels previously unimaginable. And these same platforms, when opened to third parties, have proved equally valuable to the long tail of small entrepreneurial businesses, garnering them access to a mass-market distribution channel for their offerings, something well beyond their reach in the prior era.

The impact on the orchestrator model, by contrast, is harder to see, in part because so much of it plays out behind closed doors “in the room where it happens.” Enterprises like JP Morgan Chase, Accenture, Salesforce, Cisco, and SAP clearly extend their influence well beyond their borders. Their ability to orchestrate their value chains, however, has historically been grounded primarily in a network of personal relationships maintained through trustworthiness, experience, and intelligence, not technology. So, where does an IT platform fit into that kind of ecosystem?

Here it helps to bring in a distinction between core and context. Core is what differentiates your business; context is everything else you do. Unless you are yourself a major platform provider, the platform per se is always context, never core. So, all the talk about what is your platform strategy is frankly a bit overblown. Nonetheless, in both the business models under discussion, platforms can impinge upon the core, and that is where your attention does need to be focused.

In the case of the high-volume transaction model, where commoditization is an everyday fact of life, many vendors have sought to differentiate the customer experience, both during the buying process and over the useful life of the offer. This calls for deep engagement with the digital resources available, including accessing and managing multiple sources of data, applying sophisticated analytics, and programming real-time interactions. That said, such data-driven personalization is a tactic that has been pursued for well over a decade now, and the opportunities to differentiate have diminished considerably. The best of those remaining are in industries dominated by an oligopoly of Old Guard enterprises that are so encumbered with legacy systems that they cannot field a credible digital game. If you are playing elsewhere, you will likely fare better if you get back to innovating on the offering itself.

In the case of managing context in a high-complexity relationship model, it is friction that is the everyday fact of life worth worrying about. Most of it lies in the domain of transaction processing, the “paperwork” that tags along with every complex sale. Anything vendors can do to simplify transactional processes will pay off not only in higher customer satisfaction but also in faster order processing, better retention, and improved cross-sell and up-sell. It is not core, it does not differentiate, but it does make everyone breathe easier, including your own workforce. Here, given the remarkable recent advances in data management, machine learning, and generative AI, there is enormous opportunity to change the game, and very little downside risk for so doing. The challenge is to prioritize this effort, especially in established enterprises where the inertia of budget entitlement keeps resources trapped in the coffers of the prior era’s winning teams.

The key takeaway from all this is that for most of us platforms are not strategic so much as they are operational. That is, the risk is less that you might choose an unsuitable platform and more that you may insufficiently invest in exploiting whatever one you do choose. So, the sooner you get this issue off the board’s agenda and into your OKRs, the better.

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

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Unlocking Trapped Value with AI

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Unlocking Trapped Value with AI

GUEST POST from Geoffrey A. Moore

Anyone who has used Chat GPT or any of its cousins will testify to its astonishing ability to provide valuable responses to virtually any query. This is hardly a threat—indeed, it is a boon. So, what are we worrying about?

Well, there is the issue of veracity, of course, and it is true, GPT-enabled assistants can indeed make mistakes. But, come on—humans don’t? We are not looking for gospel truth here. We want highly probable, highly informed answers to questions where we need guidance, and it is clear that GPT-enabled applications are outstanding at meeting this need, for at least three reasons. They are remarkably well-informed. They are available 24/7 on demand with no hold time. And they have infinite patience. So, let’s not kid ourselves. We are massively better off for their emergence on the scene.

What we should be worrying about, on the other hand, is their impact on jobs to be done, employment, and career development. A simple way to think about this is that for any of us to earn money, we have to release some form of trapped value. A bank clerk helps a customer get access to the trapped value in their savings account. A bus driver helps a passenger cope with their trapped value by transporting them to the location where they need to be. A lawyer helps a client get access to trapped value by constructing a contract that meets their needs while protecting against risk. A teacher helps a student access trapped value by helping her solve problems she couldn’t handle before. The principle applies to every job. All systems have points of trapped value, and all jobs are organized around releasing and capturing that value.

Now, let’s introduce generative AI. All of a sudden, a whole lot of trapped value that funded a whole lot of jobs can now be released for free (or virtually for free). Those jobs can be protected in the short term but not forever. In other words, the environment really has changed, and we must assess our new circumstances or fall behind. This is Darwinism at work. Evolution never stops. It can’t. As long as there is change, there will be dislocation, which in turn will stimulate innovation. That’s life.

But here’s the good news. The universe can never eliminate trapped value, it can only move it from place to place. That is, there are always emergent problems to solve, always new opportunities to capitalize on, because every system always traps value somewhere. What Darwinism requires is that we detect the new value traps and redirect our activity to engage with them.

Publicly funded agencies sometimes interpret this as a mandate for training programs, but we have to be careful here. Training works well for disseminating established skills that address known problems. It does not work well, however, where the problems are still being determined and the skills are as yet undeveloped. Novelty, in other words, demands creativity. It is simply not negotiable.

Getting back to the impact of generative AI, we should understand that it is an advisory technology. It is not automation. That is, it is not eliminating the need for human beings to make judgment calls. Rather, it is accelerating the preparation for so doing and framing the options in ways that make decision-making more straightforward. By solving for the old value traps, it is giving us the opportunity to up our game. It’s our job to step up to add net new value to the equation.

The best way to do this is to ferret out the emerging new value traps. Who is the customer now? What is the bottleneck that is holding them back? How could that bottleneck be broken open? What is the reward for so doing? These are the fundamental questions that drive any business model. We know how to do this. It’s just that we have been riding on the inertia of the past set of solutions for so long we may have atrophied in some of the muscles we need now. One thing we need not worry about is the universe running out of trapped value. If you are ever in doubt, just read the day’s headlines and be reassured. The world needs our help. Any tool that helps us do our part better is a blessing.

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

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Which Go to Market Playbook Should You Choose?

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Which Go To Market Playbook Should You Choose?

GUEST POST from Geoffrey A. Moore

Life-cycle go-to-market has been the focus of much of my life’s work, and I had the opportunity to recap that experience at a recent chalk talk at the HackerDoJo in Mountain View. It turned out that most of what I had to say was captured on a single slide. For readers over the age of X, this may be familiar territory; for those under the age of Y, it may prove new.

This framework highlights four different go-to-market playbooks, each optimized for a different stage of the Technology Adoption Life Cycle. The two key takeaways are:

  1. The playbook that creates success in any given stage will under-perform at any of the other three, and
  2. The playbooks do not blend; instead, they actually undercut each other when combined.

Thus, the number one job of the go-to-market strategy-setting leader is to get the entire team aligned around one, and only one, playbook.

Now, full disclosure, because different segments of the market can be in different phases of the life cycle, a go-to-market organization can be running more than one play at the same time. What they must not do is run more than one at the same time in the same place!

The Early Market Playbook

The focus of this play is to engage with a visionary customer executive who wants to leverage disruptive technology to change the world. Because your technology has yet to be adopted, the category does not yet exist, and thus there is no budget for your product. As a result, it must be funded as a project, and the customer executive has to be senior enough to have the clout to extract the necessary funds from the enterprise’s existing resource pool. Your job is to inspire that executive, hence the emphasis on thought leadership marketing to connect your breakthrough technology to their compelling business vision. It makes for a wild ride, to be sure, but when successful, it puts your company on the map as the company that did what!?!? There still is no market, there still is no budget, but there is buzz, and that buzz is associated with you, provided, that is, that your target customer is a marquee brand that people look up to. For Salesforce in its early days, this was Merrill Lynch. For Amazon Web Services in its early days, this was the CIA. For OpenAI recently, this was Microsoft.

The Bowling Alley Playbook

This is the playbook described in Crossing the Chasm. Its focus is to engage with a pragmatic business manager who is responsible for a deteriorating business process that is causing increasing problems for their enterprise, and thus, urgently needs a fix. All the conventional approaches have been found wanting, and so this prospect is open to a disruptive approach, but only if it commits to solving its specific problem. There is budget to spend here although at present it is allocated to traditional approaches. As a result, the sales cycle begins with winning the right to redirect that spend. Sales success depends on your company demonstrating a deep understanding of the problem state followed by a clear explanation of why your technology can succeed where traditional approaches fail. Implementation success depends on bringing together a team that can solve the problem end to end, leveraging domain expertise with technological leverage, to deliver what Ted Levitt taught us to call the whole product (the minimum set of products and services needed to eliminate the problem). From a market development strategy point of view, the key is to focus on a single use case in a single industry in a single geography, the goal being to develop a congregation of successful companies that will serve as a reference base as well as a loyal customer base. That is how desktop publishing helped give birth to the Mac Faithful.

The Tornado Playbook

This is the playbook that drives The Gorilla Game, a market share land grab that catapults a single company to stratospheric valuation, dragging a cohort of close contenders in its wake, resulting in the gigantic market caps that motivate early-stage venture capital investing. It is triggered by a tipping point in the adoption life cycle when pragmatic customers’ resistance to early adoption is overcome by their fear of missing out. In a flash, the new paradigm becomes the new mandate—we must have mobile apps, we must transition to cloud computing, we must procure software as a service. Budgets sprout up everywhere like mushrooms, and they are there for the picking. All this rewards a “Just win, baby” approach to go-to-market, characterized by as broad a coverage model as possible combined with highly disciplined sales tactics. RFPs (Requests for Proposals) are prevalent, driving both pilot projects and bake-offs, with marketing focusing primarily on competitive differentiation and pricing discounts. Importantly, whichever vendor wins the first pick becomes that customer’s incumbent, giving it privileged access to future purchases. Just as importantly, if one company becomes the clear market share leader, then the ecosystem of supporting companies rallies around it, elevating its competitive advantage to gorilla status.

The Main Street Playbook

This is the playbook that drives sustained earnings growth in markets that have adopted the new technology and now seek to maintain it over as long a useful lifetime as possible. At this stage, customers prefer to work with their incumbent vendors and over time to consolidate around a smaller set of integrated suites. These suites serve as platforms for ongoing innovations that are sustaining rather than disruptive, something that bores visionaries but appeals greatly to pragmatists and even more so to conservatives. In the land-and-expand as-a-service business model, we are in the expansion phase, and the growth goal is to cross-sell and up-sell new service transactions, and the earnings goal is to maximize renewals and minimize attrition. Telemetry about user adoption and feature usage is mission-critical to this effort, enabling both account managers as well as the software itself to guide the customer’s buying decisions. Product-led growth supported by self-service transactions is mission-critical for consumer applications and other user-driven offers. For enterprise sales, packaging up sets of requirements and aligning with the customer’s procurement cycle calls for the kind of account management we used to call farming and now call customer success.

Final Takeaway

Each of these playbooks makes distinctly different demands of the marketing, sales, and services teams running the go-to-market effort. People talented at one type of play may struggle with another. Our tendency as human beings is to want to stick with what we are good at, so it is usually wise to empower a new leader whenever you change playbooks.

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

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Is it Time to ReLearn to Work?

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Is it Time to ReLearn to Work?

GUEST POST from Geoffrey A. Moore

In white-collar industries where remote work is not only viable but often highly productive, we are still struggling to find a post-pandemic formula for integrating office attendance into our weekly routine. Continuing to waffle, however, does no one any good, so we need to get on with things. Part of what has been holding us back is that we have been talking about getting back to the office as an end. It is not. It is a means. The question it begs is, what is the end we have in mind? Why should we get back to the office?

Let’s start by eliminating one reason which gets frequent mention—we can manage better. This is not a good why. Supervision is an artifact of a prior era. Digitally enabled work logs itself, and we can hold each other accountable for all our KPIs, OKRs, and MBOs without having to be collocated. Managers may feel more in control with people in sight, but that is a poor return on the overall commute investment entailed.

A far better reason to return to the office is to reactivate learning. The biggest problem with remote work is that we do not learn. Specifically, we do not:

  • Learn anything new about ourselves, because we need the input of others to do so.
  • Learn new soft skills, because online courses don’t cut it.
  • Learn about our teammates, because video calls lack the needed intimacy.
  • Learn about our customers, because we need to go to their offices to do so (going to our offices would at least let us share the ride)
  • Learn about the current state of our company, because that kind of thing never gets published.

In short, just as our children experienced a learning gap at school, so we inherit the same dynamics with remote work. We consume the skills we have, but we do not develop the ones we need next. We are harvesting, but we are not seeding, and there will be a reckoning if we do not alter our course.

So, there is a good why for returning to the office, but that in turn begs the question of how? Here we need to be clear. We do not know how. We do not know what is the right formula. Unfortunately, waiting won’t help either, so now what?

Let me suggest that the best course of action is to implement a clear policy effective immediately with the following provisos.

  1. We publicly acknowledge that we suspect this policy is wrong.
  2. We are putting it in place for 90 days.
  3. We want everyone to abide by it religiously so that we get the right signals.
  4. We will review the policy publicly and transparently after 90 days and implement a new policy at that time.
  5. We will put that policy in place for 90 days, following the same protocols as before.
  6. We will rinse and repeat until no longer necessary.

The point is, we have to get on with getting on, and running the experiment is the fastest way to get there.

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

Image Credit: Pixabay

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Don’t Slow Roll Your Transformation

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Don't Slow Roll Your Transformation

GUEST POST from Geoffrey A. Moore

Business pundits love to talk about transformation, and consultants drool at the opportunity to tap into a limitless budget, but the truth is, transformations suck.

At minimum, transformation consists of re-engineering your operating model while continuing to operate, with even greater disruption involved if you are revamping your business model at the same time. Now, if you are a privately held enterprise, you might be able to sell this to your board as a “pivot,” and indeed, in the venture world, there is some accommodation built in for such moves. Not so, however, for companies whose shares are publicly held. If this describes you, fasten your seatbelt and read on.

Transformations come with “J curves”—financial projections that have you swimming underwater for some considerable period before you emerge reborn on the other side. Public investors hate J curves. They also worry prospective customers, as well as ecosystem partners, not to mention your own employees. Only a VC loves a J curve, but their attention is on a younger generation.

Nonetheless, everyone understands there are situations where transformation is warranted. For public companies, the most common cause is when the entire franchise is under existential threat. A new technology paradigm is going to categorically obsolete the core franchise, as digital photography did to Kodak, as digital media did to BusinessWeek, as wireless telephony is doing to wireline. It was an existential threat that caused Microsoft to displace its back office software business with Azure’s cloud services, even though the gross margins of the latter were negative while the net margins of the former were stupendous. It was an existential threat that drove Lou Gerstner to reengineer IBM’s hardware-centric business model to focus on services and software. Failure to transform means dissolution of the enterprise. If you are to survive, there are times when you simply have to bite the bullet.

That said, you still have to confront the issue of time. Everyone understands that a transformation will take more than one year, but no one is willing to tolerate it taking three. That is, by the end of the second year you have to be verifiably emerging from the J curve, head out of water, able to breathe positive cash flow, or else you are likely to be written off. That means transformational initiatives should be planned to complete in seven quarters, plus or minus one. That’s the amount of time you can be in the ICU before you risk getting transferred to hospice care.

So, if a transformation is in your future, and you really cannot work around it, then start your planning with the end in mind and calendar that end for seven quarters out. Now, work backward to determine where you will have to be by each of the intervening quarters in order to meet your completion date. When you get back to the current quarter, expect to see you are already two or three quarters behind schedule (not fair, I know, but I already told you that transformations suck). Suppress panic, conduct triage, and start both your engines and the clock.

Final point: given the lack of time and the amount of risk involved, there is only one sensible way to approach a transformation. Prioritize it above everything else, and keep everyone focused on making the intermediate milestones until you are well and truly out of danger. Transformations are no joking matter. Most companies lose their way. Don’t let that be true of you and yours.

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

Image Credit: Pixabay

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Back to the Basics of the Performance Zone

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Back to the Basics of the Performance Zone

GUEST POST from Geoffrey A. Moore

As the global economy gropes its way to a new normal, with buyers still looking to regain their confidence to invest, most companies are dealing with sluggish performance—not terrible, but not great. In such circumstances, management attention gravitates to the Productivity Zone, where the focus is internal on ourselves, and the goal is to optimize our processes to prop up our operating margins. All good, but only half the solution.

The other half is to reengage with the Performance Zone. The goal of this zone is to not to improve–it is to win the game. There is no process for doing this (if there were, then Germany would win the World Cup every year), so internal focusing will not help. Instead, we need to reexamine our relationship with others, specifically with our customers and our competitors. Strategy begins, in other words, when we divert our attention from us and put it on them.

Investigating our Customers

In a doldrums economy, we know that existing budgets are tight, so if we are to find growth opportunities, we need to detect where new budgets are emerging. In other words, we are looking for forces at work in our target markets that are changing the investment priorities of our target customers. The key unit of examination here is the use case.

Use cases live at the intersection of our portfolio of offerings and customer value realization. We already have libraries of established use cases, but those are the ones that are under budget constraint. We are looking for emerging use cases, typically gnarly problems that are possible to solve with our stuff, but only with net new innovation and additional attention from us. Such use cases are at odds with our Productivity Zone focus on efficiency, but they are key to finding growth opportunities in trying times.

Each use case is a shorthand representation for a mini-TAM (Total Addressable Market). We are not looking for big here, we are looking for urgent. We want use cases that will activate customers to invest now, even when budgets are tight, keeping in mind that even the most highly focused use case with the smallest immediate TAM is normally a harbinger of bigger things to come. First-mover advantage in an emerging use case is like winning an early primary election—it is modestly valuable in itself, but even more so in terms of its impact on later competitions in bigger venues.

To detect these opportunities we need to interrogate our customer-facing teams in sales, solution engineering, and customer success to extract from them anecdotal evidence of novel use cases, regardless of who the vendor is. We also want to hear stories about customers struggling with problems that no one is solving. The question we are trying to answer is, what does the world really want from our company now? What would cause prospective customers to line up to spend money with us today?

To be sure, pursuing net new use cases requires investment at our end, and we too are under budget pressure, so there can be no “spray and pray” here. We need to stack rank whatever opportunities we detect on a risk/reward gradient and focus on the top one or two only, the limiting factor being that whatever we do fund must get “all the way to bright.” Adding even just one more opportunity than there is budget to fund results in all opportunities getting underfunded and nothing getting over the finish line. It is the most common cause of companies losing their way and drifting into irrelevance.

Learning from our Competitors

Here again we should divide up the landscape into legacy versus future competitors, as we will treat each differently. The legacy group are competing for the same constrained budgets as we are, using tactics we are now quite likely to be familiar with. This is the realm of execution, not strategy. It rewards campaigns led by the Productivity Zone focused on extracting the best returns we can from what is a low-yield, but also a low-risk, situation. Our customers are not going away, but they are going to sweat their assets and consolidate vendors wherever they can. Inertia here is our friend, and we need to leverage it as best we can by eliminating any sources of friction that would diminish our returns.

On the other hand, our future competitors do warrant strategic attention, for any number of reasons. For example, any recent wins they may have had could signal an emerging new use case, one that we too should be checking out. Alternatively, we may learn they are attacking our own target use case, in which case we need to differentiate quickly and dramatically in order to block them out early (a mini-TAM is too small for more than one winner). A third possibility is that we may be getting blindsided altogether, our installed base under some whole new form of attack, potentially jeopardizing the future of our entire franchise. It’s a wake-up call nobody likes to get, essentially forecasting an existential threat, but that is often what it takes to prod an established enterprise to adjust to a changing market landscape.

The standard unit of work for investigating future-oriented competition is the win/loss analysis. Again, we need to bring in the customer-facing teams to get their anecdotal evidence. Analyst reports don’t help much—they tend either to track us and our legacy competitors in established markets, or to glom onto the next potential disruptive technology and make extravagant extrapolations of its future returns. Instead, we want to look closely at the new use cases, regardless of whether we have won or lost, to see what the customer ended up prioritizing and why that drove their buying decision. As always, we prefer to win, but it is imperative regardless that we learn.

Changing the Narrative

Once we have focused on others, once we have revised our understanding of what the world wants from us, and who we are going to be competing with, we can now legitimately focus our attention on ourselves and our stakeholders. These include our installed base, our ecosystem partners, our investors, and our employee workforce. Our new strategy calls for a change in our course and speed, and we need everyone in our boat to row in the same direction. This can only happen if we change the narrative.

It is hard to overemphasize this point, so let me put it another way. If we do not change the narrative, nothing new will happen. No one will change course and speed. Even if we make clear the course corrections we are making, things still won’t change. That’s because everyone always assumes that things will be more or less the same, and that goes especially for established franchises. Getting stakeholders to turn a big boat requires a big signal.

The structure of the successful new narrative is always the same. It is never about you. Nobody cares about you (well, except your mom, of course, God bless her). Stakeholders have plenty on their own plates to worry about without taking on stuff on yours. What they do care about, on the other hand, is what is happening in their world, how it impinges on their hopes and plans, where it is creating risk for them, and what, if anything, you might be able to do to help them mitigate that risk. That’s what your new narrative must be all about. It’s a new you because it is a new world, and you are rising to meet the occasion. Not only does this change people’s focus, it energizes those whom it attracts, giving a real boost to the team at a time when everyone can use one.

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

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