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

Allocating Resources to Solve Horizon 2

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Another Tough Challenge

Allocating Resources to Solve Horizon 2

GUEST POST from Geoffrey A. Moore

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

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

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

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

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

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

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

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

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

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

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

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Tackle Your Toughest Challenge This Year

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Tackle Your Toughest Challenge This Year

GUEST POST from Geoffrey A. Moore

This is the first in what I hope to be an extended series of blogs focused on a single topic: What is the toughest challenge your company faces today, and what would it take to overcome it? I’ve reached out to my network, so I have a few good ones to start with, but needless to say, I would be very interested to learn what you are up against in your enterprise. In the meantime, here is my first shot on goal:

“I think we had stopped innovating for a long time. Customers were disappointed. But over the past few years, we have made massive improvements to our products. In fact, many who use the products feel like they are best in class. Our big challenge is getting the market to recognize that we are not the company we were a decade ago. This tends to be very easy to accomplish in small pockets but is a huge challenge at scale.”

There is a whole cohort of global enterprises that are facing this conundrum, including the iconic enterprise tech companies that rode the client-server/Internet wave to become the great growth stocks of the 1990s, who then became overshadowed by the massive mobile/cloud wave that has driven consumer tech successes in this century, and who are now institutional, single-digit-growth anchor holdings in today’s value investors’ portfolios. What would it take to free their future from the pull of the past?

The answer comes in two parts. First, they have to participate in a wave of disruptive innovation that is inside the tornado, with AI and ML being likely current candidates. They don’t have to be the first mover or even the category leader, but they do have to gain a substantial share of some piece of the pie, enough for the world to see they are a real player and that their growth prospects have therefore materially changed. This is something that can — indeed must — be powered by internal forces, management committing to the risk, engineering committing to the task, go-to-market committing to the sales, and everyone competing like crazy to get enough share to be taken seriously.

This is a big deal in itself, but not as the quote above makes clear, the toughest challenge. Instead, it creates the toughest challenge, which is how to get the world to acknowledge and buy into the good work that has been done and that is continuing to be done. Specifically, the challenge is how to change the narrative.

Narratives are how we make sense of the world. They are the stories we tell about ourselves, our friends, our enemies, the products we use, the causes we participate in — you name it, if we have any stake in it, we tell stories about it. These stories circulate, and after a while, they become institutionalized as received wisdom or established reputation or brand image. As with “your father’s Oldsmobile,” everybody knows that so-and-so is such-and-such, without anyone giving it much thought. These narratives become signposts along the road of life. We expect them to stay the same. And that, of course, is what makes them so hard to change.

To change the narrative you need a forcing function. This has to be external to your enterprise, something that causes the world to reorient itself, and in so doing, to realize that its old signposts may no longer serve. In tech, we have been blessed with a plethora of forcing functions, something Joseph Schumpeter taught us to call “waves of creative destruction.” Such waves radically alter the allocation of budgets, and in so doing, they run roughshod over the old highways along with any of their signposts. To change your narrative, you have to position your enterprise in their path.

Satya Nadella’s “Cloud first, Mobile first” is a good example. Cloud threatened to creatively destroy Microsoft’s back office franchise, and mobile threatened to do the same to its PC operating system monopoly. Both were forcing functions. Now, it turns out that mobile did not work out for them, but cloud surely did. The point is, Satya’s tagline redefined Microsoft’s position, putting it in line for a whole new generation of investment. AMD is doing the same thing with AI chips, following Nvidia’s lead, just as Microsoft was following Amazon Web Services. Iconic companies do not have to lead the next wave. Nobody expects that, although Apple astoundingly did so not once, not twice, but three times within a space of little more than a decade. But because iconic enterprises have global footprints, because they are well positioned to capitalize on the new wave of change, they get the benefit of the doubt once they have demonstrated they can deliver products or services that make the grade.

That phrase “Satya’s tagline” leads me to my last point. You would think that changing the corporate narrative should be the function of corporate marketing, but it never is. First of all, it is unpopular, and marketing teams, aligned as they are with sales teams, are reluctant to do anything that would offend. Second, marketing does not have the clout. It wasn’t the tagline that anchored Microsoft’s change. It was the CEO himself, with the backing of the board.

And buried therein lies the third challenge — changing the narrative is deeply unpopular with value investors, particularly when it entails internal investments that impact earnings per share. It is not easy for a board of directors, who are continually reminded they are there to represent the interests of the shareholders, and the CEO, who is highly compensated to manage for shareholder value, to take a step back and do what they believe is the right thing for the long term.

Beneath a change in any corporate narrative, therefore, there is an underlying meta-narrative about the role of enterprise in relation to all its stakeholders. This includes its customers, partners, employees, and communities, as well as its investors. In that context, customers are family — they have skin in your game and are likely to stick with you through thick and thin. Investors, by contrast, do not. Your company is a financial instrument in their portfolio, and should it cease to perform the financial role they have in mind for it, they have no reason to hold onto it. You still need to take their interests seriously — they are your financial foundation — but they are not your reason for being. Customers are. So should you undertake to change your narrative, focus on why your customers need you to do so. They are your North Star.

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

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Reimagining Personalization

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Reimagining Personalization

GUEST POST from Geoffrey A. Moore

Personalization was one of the leading rationales for companies investing in digitalization. The idea was that you were going to delight your customers by proactively offering them goods and services they were predisposed to want. This would create customer loyalty, increase their lifetime value, spur word-of-mouth endorsement, drive up Net Promoter Scores (NPS), and solve world hunger.

OK, not so much. A decade or more in, it’s time we ask ourselves, what is the real value of personalization, and how should we allocate our future investments in it? This begins with getting ourselves onto the right playing field in the first place. Personalization has different dynamics depending on whether your enterprise is Business to Consumer (B2C), Business to Business (B2B), B2B2C or B2G2C. Here’s how it plays out.

B2C

Let’s face it — as consumers, we are tired of personalization in its current form. It isn’t really personal, it is just an unending barrage of re-targeted advertising that works statistically but not psychologically. Despite all its promises to the contrary, it is not in fact delightful. So, best to take all that language about delighting our customers and throw it in the trashcan.

Instead of looking for delighters, we should be examining our hygiene factors. These are the things that annoy customers most when they go awry — late shipping, lost luggage, long hold times, rejected passwords, tedious surveys — you name it. Getting hygiene right is hard, but doing so consistently drives brand loyalty through the roof — just ask Amazon. We love what they do so much we subscribe to them! The point is, the things we love are not personal, they are institutional. Amazon has invested enormously in systems that set expectations through timely communication, early anomaly detection, instant alerts, and the like. This is not marketing, it’s logistics, but it is personally delivered, and we feel empowered in a highly differentiated way. (BTW, note to Amazon — you are increasingly over-monetizing your landing pages with sponsored ads, thereby eroding your most valuable asset. You need to set limits and stick to them.)

B2B2C

Rethinking personalization creates a whole new wave of innovation for B2B2C companies to pursue. Instead of optimizing for clicks, help your customers better detect signals. To be fair, some of these could be buying signals, and they should be used to drive consumer traffic along existing lines. But machine learning is also extremely effective at monitoring hygiene factors wherever there is log data to exploit. Omniture was an early pioneer in using this technology for website optimization, and now with generative AI you can let your customers’ websites ask visitors what they are interested in seeing instead of playing whack-a-mole with their best guesses.

The point is, no company is happy with their website, ever — and frankly, for good reason. They are just too hard to navigate, too much about themselves, not enough about the customers and prospects they are there to serve. By focusing on hygiene factors rather than delighters, this can be changed.

B2G2C

OK, when it comes to dealing with government services, no one is really thinking about delighters. Nightmares, on the other hand, do come to mind. Once again, it’s all about hygiene factors. The services that are being offered meet real needs. It’s the obstacles that systems and bureaucracies put in the way of citizens seeking those services that drive everyone crazy.

The fastest way to cut through this mess is to embrace the adage Time is money. The goal is to relentlessly optimize for reducing latency while at the same time reducing fraud as well. This requires the very best in ML and AI, but those resources are available today, and there are plenty of socially minded entrepreneurs who are ready to put in the hard work to make them scale. The core metric of success is time to closure, the tracking of which will be no mean feat. One consequence of its success, to be frank, would be a reduction in bureaucratic employment — not just to free up more money for social services but rather to expedite transaction processing throughout the system. My hope would be that impacted agencies could redeploy their workforces into the field where face-to-face personal interaction actually can make a powerful difference in the moment.

B2B

One question that bugs the you-know-what out of CEOs of successful global enterprises is, Why do our customers keep telling us we are hard to do business with? Of course, the answer is because they are. The real question is what can they do about it? Here are some low-hanging-fruit places to start:

  • Disintermediate your salespeople from replenishment transactions. Instead, empower customers to transact on their own behalf through digital self-service portals. And extend the same courtesy to partners who are acting as agents on behalf of their customers.
  • Attack the long tail of your SKUs. Not only do they entangle your salespeople in majoring in minors, they confuse the heck out of your customers.
  • Stop imposing buying risks on your customers and take them upon yourself instead by tokenizing bundles to allow for swapping out unconsumed portions and truing up on overused ones.
  • Invest in customer success initiatives that build relationships higher up in the customer organization, leveraging thought leadership marketing, customer health scoring, and executive sponsors focused on deep listening. Customers can tell you what they really need from you if you’ll let them.

Here as elsewhere, the goal is not to delight the customer. Customers don’t want to be delighted. They want to be served – thoughtfully, reliably, and economically. Remember, it’s not about you. It’s about them.

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

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Rearchitecting the Landscape of Knowledge Work

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Rearchitecting the Landscape of Knowledge Work

GUEST POST from Geoffrey A. Moore

One thing the pandemic made clear to everyone involved with the knowledge-work profession is that daily commuting was a ludicrously excessive tax on their time. The amount of work they were able to get done remotely clearly exceeded what they were getting done previously, and the reduction in stress was both welcome and productive. So, let’s be clear, there is no “going back to the office.” What is possible, on the other hand, is going forward to the office, and that is what we are going to discuss in this blog post.

The point is, we need to rethink the landscape of knowledge work—what work is best done where, and why. Let’s start with remote. Routine task work of the sort that a professional is expected to complete on their own is ideally suited to remote working. It requires no supervision to speak of and little engagement with others except at assigned checkpoints. Those checkpoints can be managed easily through video conferencing combined with collaboration-enabling software like Slack or Teams. Productivity commitments are monitored in terms of the quality and quantity of received work. This is game-changing for everyone involved, and we would be crazy to forsake these gains simply to comply with a return-to-the-office mandate.

That said, there are many good reasons still to want a return. Before we dig into them, however, let’s spend a moment on the bad reasons first. First among them is what we might call “boomer executive control needs”—a carry-over from the days of hierarchical management structures that to this day still run most of our bureaucracies. Implicit in this model is the notion that everyone needs supervision all the time. Let me just say that if that is the case in your knowledge-work organization, you are in big trouble, and mandating everyone to come back to the office is not going to fix it. The fix needed is workforce engagement, and that requires personal intervention, not systemic enforcement. Yes, you want to do this in person, and yes, the office is typically the right place to do so, but no, you don’t need everyone to be there all the time to do it.

This same caveat applies to other reasons why enterprises are mandating a return. Knowledge work benefits from social interactions with colleagues. You get to float ideas, hear about new developments, learn from observing others, and the like. It is all good, and you do need to be collocated to do it—just not every day. What is required instead is a new cadence. People need an established routine to know when they are expected to show up, one they can plan around far in advance. In short, we need the discipline of office attendance, we just want it to be more respectful of our remote work. In that light, a good place to start is a 60/40 split—your call as to which is which. But for the days that are in office, attendance is expected, not optional. To do anything else is to disrespect your colleagues and to put your personal convenience above the best interests of the enterprise that is funding you.

So much for coping with some of the bad reasons. Now let’s look into five good ones.

  1. Customer-facing challenges. This includes sales, account management, and customer success (but not customer support or tech support). The point is, whenever things are up for grabs on the customer side, it takes a team to wrestle them down to earth, and the members of that team need to be in close communication to detect the signals, strategize the responses, and leverage each other’s relationships and expertise. You don’t get to say when this happens, so you have to show up every day ready to play (meaning 80/20 is probably a more effective in-office/out-of-office ratio).
  2. Onboarding, team building, and M&A integration. Things can also be up for grabs inside your own organization, particularly when you are adding new people, building a new team (or turning around an old one), or integrating an acquisition. In these kinds of fluid situations, there is a ton of non-verbal communication, both to detect and to project, and there is simply no substitute for collocation. By contrast, career development, mentoring, and performance reviews are best conducted one-on-one, and here modern video conferencing with its high-definition visuals and zero-latency audio can actually induce a more focused conversation.
  3. Mission-critical systems operations. This is just common sense—if the wheels start to come off, you do not want to lose time assembling the team. Cybersecurity attacks would be one good example. On the other hand, with proper IT infrastructure, routine system monitoring, and maintenance as well as standard end-user support can readily leverage remote expertise.
  4. In-house incubations. It is possible to do a remote-only start-up if you have most of the team in place from the beginning, leveraging time in collocation at a prior company, especially if the talent you need is super-scarce and geographically dispersed.

    But for public enterprises leveraging the Incubation Zone, as well as lines of business conducting nested incubation inside their own organizations, a cadence surrounding collocation is critical. The reason is that incubations call for agile decision-making, coordinated course corrections, fast failures, and even faster responses to them. You don’t have to be together every day—there is still plenty of individual knowledge work to be done, but you do need to keep in close formation, and that requires frequent unscripted connections.

  5. Cross-functional programs and projects. These are simply impossible to do on a remote basis. There are too many new relationships that must be established, too many informal negotiations to get resources assigned, too many group sessions to get people aligned, and too much lobbying to get the additional support you need. This is especially true when the team is led by a middle manager who has no direct authority over the team members, only their managers’ commitment and their own good will.

So, what’s the best in-office/remote ratio for your organization?

You might try doing a high-level inventory of all the work you do, calling out for each workload which mode of working is preferable, and totaling it up to get a first cut. You can be sure that whatever you come up with will be wrong, but that’s OK because your next step will be to socialize it. Once you get enough fingerprints on it, you will go live with it, only to confirm it is still wrong, but now with a coalition of the willing to make it right, if only to make themselves look better.

Ain’t management fun?

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

Image Credit: Google Gemini

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The Hidden Discipline for Transformation Success

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The Hidden Discipline for Transformation Success

GUEST POST from Geoffrey A. Moore

In Zone to Win, we lay out a playbook for transformational initiatives that focus on prioritizing a single effort across the entire enterprise for a period of no longer than two years. Core to success is the unswerving commitment of the CEO, the Executive Leadership Team, and the Board of Directors to see this through to completion come hell or high water. That means it is top of the agenda at every operational review and in between has an open-door escalation path to address any obstacles that come up in real time. It also means that the company as a whole is continually getting updates on the progress being made, the importance of the mission, the imperative that it get everyone’s support.

All necessary, all good. That said, there is a hidden discipline that makes the difference between success and failure, one that can be made visible in the annual operating plan, and thereby remove some of the mystery that surrounds transformational success. It begins with the transformation team simply calling out any dependencies it has on deliverables that come from divisions in the Performance Zone.

That list will get supplemented by additional unanticipated requests that inevitably crop up in the race to get to material scale. Taken together, these are the actions that are most subject to delay or deprioritization whenever the Performance Zone gets under performance pressure. The problem is that time is the one resource you cannot replenish, so you can never afford to delay or deprioritize any request from the Transformation Zone.

So, the discipline required for success is to call out every dependency as soon as it becomes visible, put it on a strict timeline, and then monitor it relentlessly through to completion. At every juncture, you will get pushback, not for the request per se but for the timeline on which it needs to be delivered. Capitulating to that pushback is the nice thing to do—the requests always have merit in their own right—but you cannot take that route and expect the transformation to succeed.

To make this brutally clear, if at any time during a transformational initiative, you lose momentum for any reason, that initiative will fall short of the game-changing goals you set for it. Said another way, inertia is a hugely powerful force, and the world does not naturally want to transform. Give it any other path, and it will take it. Your job is to block every other path. You don’t have to be brilliant to do this. You just have to be undistractedly vigilant.

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

Image Credit: Geoffrey Moore

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What Are We Going to Do Now with GenAI?

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What Are We Going to Do Now With GenAI?

GUEST POST from Geoffrey A. Moore

In 2023 we simply could not stop talking about Generative AI. But in 2024 the question for each enterprise became (continuing to today) — and this includes yours as well — is What are we going to do about it? Tough questions call for tough frameworks, so let’s run this one through the Hierarchy of Powers to see if it can shine some light on what might be your company’s best bet.

Category Power

Gen AI can have an impact anywhere in the Category Maturity Life Cycle, but the way it does so differs depending on where your category is, as follows:

  • Early Market. GenAI will almost certainly be a differentiating ingredient that is enabling a disruptive innovation, and you need to be on the bleeding edge. Think ChatGPT.
  • Crossing the chasm. Nailing your target use case is your sole priority, so you would use GenAI if, and only if, it helped you do so, and avoid getting distracted by its other bells and whistles. Think Khan Academy at the school district level.
  • Inside the tornado. Grabbing as much market share as you can is now the game to play, and GenAI-enabled features can help you do so provided they are fully integrated (no “some assembly required”). You cannot afford to slow your adoption down just at the time it needs to be at full speed. Think Microsoft CoPilot.
  • Growth Main Street (category still growing double digits). Market share boundaries are settling in, so the goal now is to grow your patch as fast as you can, solidifying your position and taking as much share as you can from the also-rans. Adding GenAI to the core product can provide a real boost as long as the disruption is minimal. Think Salesforce CRM.
  • Mature Main Street (category stabilized, single-digit growth). You are now marketing primarily to your installed base, secondarily seeking to pick up new logos as they come into play. GenAI can give you a midlife kicker provided you can use it to generate meaningful productivity gains. Think Adobe Photoshop.
  • Late Main Street (category declining, negative growth). The category has never been more profitable, so you are looking to extend its life in as low-cost a way as you can. GenAI can introduce innovative applications that otherwise would never occur to your end users. Think HP home printing.

Company Power

There are two dimensions of company power to consider when analyzing the ROI from a GenAI investment, as follows:

  • Market Share Status. Are you the market share leader, a challenger, or simply a participant? As a challenger, you can use GenAI to disrupt the market pecking order provided you differentiate in a way that is challenging for the leader to copy. On the other hand, as a leader, you can use GenAI to neutralize the innovations coming from challengers provided you can get it to market fast enough to keep the ecosystem in your camp. As a participant, you would add GenAI only if was your single point of differentiation (as a low-share participant, your R&D budget cannot fund more than one).
  • Default Operating Model. Is your core business better served by the complex systems operating model (typical for B2B companies with hundreds to thousands of large enterprises for customers) or the volume operations operating model (typical for B2C companies with hundreds of thousands to millions of consumers)? The complex systems model has sufficient margins to invest professional services across the entire ownership life cycle, from design consulting to installation to expansion. You are going to need deep in-house expertise to win big in this game. By contrast, GenAI deployed via the volume operations model has to work out-of-the-box. Consumers have neither the courage nor the patience to work through any disconnects.

Market Power

Whereas category share leaders benefit most from going broad, market segment leaders win big by going deep. The key tactic is to overdo it on the use cases that mean the most to your target customers, taking your offer beyond anything reasonable for a category leader to copy. GenAI can certainly be a part of this approach, as the two slides below illustrate:

Market Segmentation for Complex Systems

In the complex systems operating model, GenAI should accentuate the differentiation of your whole product, the complete solution to whatever problem you are targeting. That might mean, for example, taking your Large Language Model to a level of specificity that would normally not be warranted. This sets you apart from the incumbent vendor who has nothing like what you offer as well as from other technology vendors who have not embraced your target segment’s specific concerns. Think Crowdstrike’s Charlotte AI for cybersecurity analysis.

Market Segmentation for Volume Operations

In the volume operations operating model, GenAI should accentuate the differentiation of your brand promise by overdelivering on the relevant value discipline. Once again, it is critical not to get distracted by shiny objects—you want to differentiate in one quadrant only, although you can use GenAI in the other three for neutralization purposes. For Performance, think knowledge discovery. For Productivity, think writing letters. For Economy, think tutoring. For Convenience, think gift suggestions.

Offer Power

Everybody wants to “be innovative,” but it is worth stepping back a moment to ask, how do we get a Return on Innovation? Compared to its financial cousin, this kind of ROI is more of a leading indicator and thus of more strategic value. Basically, it comes in three forms:

  1. Differentiation. This creates customer preference, the goal being not just to be different but to create a clear separation from the competition, one that they cannot easily emulate. Think OpenAI.
  2. Neutralization. This closes the gap between you and a competitor who is taking market share away from you, the goal being to get to “good enough, fast enough,” thereby allowing your installed base to stay loyal. Think Google Bard.
  3. Optimization. This reduces the cost while maintaining performance, the goal being to expand the total available market. Think Edge GenAI on PCs and Macs.

For most of us, GenAI will be an added ingredient rather than a core product, which makes the ROI question even more important. The easiest way to waste innovation dollars is to spend them on differentiation that does not go far enough, neutralization that does not go fast enough, or optimization that does not go deep enough. So, the key lesson here is, pick one and only one as your ROI goal, and then go all in to get a positive return.

Execution Power

How best to incorporate GenAI into your existing enterprise depends on which zone of operations you are looking to enhance, as illustrated by the zone management framework below:

Zone Management Framework

If you are unsure exactly what to do, assign the effort to the Incubation Zone and put them on the clock to come up with a good answer as fast as possible. If you can incorporate it directly into your core business’s offerings at relatively low risk, by all means, do so as it is the current hot ticket, and assign it to the Performance Zone. If there is not a good fit, consider using it internally instead to improve your own productivity, assigning it to the Productivity Zone. Finally, although it is awfully early days for this, if you are convinced it is an absolutely essential ingredient in a big bet you feel compelled to make, then assign it to the Transformation Zone and go all in. Again, the overall point is manage your investment in GenAI out of one zone and only one zone, as the success metrics for each zone are incompatible with those of the other three.

One final point. Embracing anything as novel as GenAI has to feel risky. I submit, however, that in 2025 not building upon meaningful GenAI action taken in 2024 is even more so.

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

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Modeling Good Board Governance

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Modeling Good Board Governance

GUEST POST from Geoffrey A. Moore

There are cartloads of checklists and commentary on the duties and responsibilities of a board of directors, none of which are particularly surprising, but collectively, somewhat mind-numbing. As a frameworks person, I need to see things in a more simple and integrated way, hence the diagram below:

Board of Directors Responsibilities Framework

Public boards should tackle this framework from the bottom up as they are liable for damages if the company fails to address risk and compliance properly, or improperly reports performance results. Foundational to their recruiting and staffing efforts should be securing strong chairpersons for each of the three anchor committees—Nominating and Governance, Audit, and Compensation. That’s table stakes. High-performing boards do their best to handle these obligations in committee so they can spend quality time on the upper levels of the framework. The obstacle here tends to be management’s presentation of the past quarter’s performance. This is necessary to bring the board up to speed on the current state of the company, but it is something that most boards spend way too much time on, given how little the board can do to move the needle. This limits the time available to devote to strategy and resource allocation, where their outside-in perspective can add a ton of value. Big bets, on the other hand, do get the full attention they deserve—they just should not happen very often given the risk-averse nature of public market shareholders.

Venture-backed companies, on the other hand, are a different kind of animal. They should approach this framework from the top down. They are big bets, and their first responsibility is to get those bets across the chasm and inside a tornado. Resource allocation and strategy are core to accomplishing these ends. Performance matters, but early on it is more about accumulating power than delivering profits. Risk and compliance are still relevant, but the shareholders have a higher tolerance for risk, and the relatively small size of the enterprise as a whole makes compliance a whole lot simpler. And finally, the board is typically comprised primarily of investors and founders with an independent director for balance—not really a governance model, built more for guidance instead.

The disparity between the public and private market board models creates a shock when venture-backed companies get acquired by public companies. The newly acquired team wakes up one morning inside a public enterprise with all its established processes and procedures and feels like it is being smothered to death. There is no halfway house here, so when we talk about acquisition integration, we need to include a deep-dive orientation to public-market expectations, and the work enterprises must do to address them. In parallel, the acquiring company needs to adopt zone management to ensure that they are holding the acquired company accountable to the right goals and metrics. This goes all the way up to the board, where people are likely still smarting from the high premium they had to pay and looking to get it back as fast as possible. Thrusting the new team into the Performance Zone is a proven path to crushing innovation and destroying shareholder value.

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

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Bringing Energy Back to Work

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Bringing Energy Back to Work

GUEST POST from Geoffrey A. Moore

There are all kinds of survey data these days indicating that morale in the workplace is lower than it used to be and, more importantly, than it ought to be. This has got managers scurrying about trying to find ways to make their employees happier. One word of advice on this: Stop!

It is not your job to make the people on your team happy. That is their job. Your job is to make their work important. Now, as a bonus, there is a strong correlation between meaningful work and worker happiness, so there is a two-birds-for-one-stone principle operating here. It’s just that you have to keep your eye on the lead bird. Employee happiness is a trailing indicator. Customer success is the leading one.

Your team’s customers can be internal or external — it just depends on your performance contract, the one that sets out the outcomes your organization has been funded to deliver. To be meaningful, in one way or another, those outcomes must contribute materially to the overall success of your enterprise’s mission. Your job is to highlight that path, to help your team members see it as a North Star to guide the focus and prioritization of their work. That is what gives their work meaning. Their performance metrics should align directly with the outcomes you have contracted to deliver – else why are they doing the work?

Performance management in this context is simply redirecting their energy to align as closely as possible to the deliverables of your organization’s performance contract. The talent you recruit and develop should have the kind of disposition and gifts that motivate them to want to do this kind of work. If there is a mismatch, help them find some other kind of work that is a better fit for them, and backfill their absence with someone who is a better fit for you. Performance management is not about weeding out—it is about re-potting.

Finally, if we bring this mindset to our current challenges with institutionalizing remote/hybrid operating models, too often this is being framed as an issue of improving employee happiness. Again, not your job. Instead, the focus should be on how best to meet the needs of the customers you have elected to serve. That is, instead of designing enterprise-out, with our heads down in our personal and team calendars, we need to design customer-in, with our heads up looking at where the trapped value is in their world, aligning our energies to release that trapped value, and organizing our operating model to maximize our impact in so doing. If we are not in service to our customers, what use are we?

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

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How Knowledge Emerges

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Understanding Epistemology

How Knowledge Emerges - Understanding Epistemology

GUEST POST from Geoffrey A. Moore

Epistemology is that branch of philosophy that addresses the theory of knowledge. But what do philosophers mean by knowledge? Traditionally, it is defined as justified true belief, and it is established by applying logic and reason to whatever set of claims is under discussion. That is the path we are going to follow here as well. But to get the full picture, we need to look at both knowledge and knowing through the lens of emergence.

In The Infinite Staircase, we offered a global model of emergence that seeks to span all of reality, organizing itself around eleven stairs, as follows:

Infinite Staircase Geoffrey Moore

Justified true belief is a product of reason employing the top four stairs of language, narrative, analytics, and theory to test claims to truth. It is the cumulative impact of all these stairs building one atop the next that allows knowledge to ultimately emerge in its fullest sense. That is the path we are about to trace. Before so doing, however, we should acknowledge that there are seven stairs below language, all of which are “pre-linguistic,” that also seep into the way we know things. A complete epistemology would therefore go all the way down to the bottom stair, with particular attention to culture (what we learn from others) and values (what we learn from mammalian nurture and governance). Nonetheless, we are going to focus on just the top four because that is where the bulk of the action is.

Beginning with the stair of language, its major contribution to justified true belief is its ability to communicate facts. All facts are expressed through declarative sentences. Each sentence makes a claim. What makes a claim a fact is that we are willing to accept its assertion without further verification or validation. For the ultimate skeptic who is never willing to do this, there are no facts. For the rest of us, who are continually making real-life decisions in real-time, facts are necessary, and we accept or reject claims of fact based on the information we have at hand, including the reliability of the source and the probability of the claim given current circumstances.

That said, facts by themselves don’t mean much. What gives them meaning are narratives. Narrative is the cornerstone of all knowledge, the medium by which we communicate beliefs. The book of Genesis represents one such belief-supporting narrative, The Origin of Species another, the Big Bang a third. Each of these narratives not only explains how things have come to be as they are, at the same time they foreshadow how they can be expected to turn out in the future. Whether it is the hand of God, the workings of natural selection, or the ceaseless operation of the Second Law of Thermodynamics, narratives spotlight the governing forces in whatever situation they describe. That in turn lets us identify actions we can take to turn our situation to best advantage. Narratives, in other words, are essential equipment for any kind of decision-making. The question, however, is are they credible?

This is where analytics comes in. The role of analytics is to justify belief in the claims embedded in the narrative. In The Infinite Staircase, I summarize Stephen Toulmin’s model for conducting such an analysis. It is organized around six elements:

  1. What are the claims being made? Are they clear, precise, and unambiguous?
  2. What evidence is there that these claims might be true? What are the facts of the case as best we can determine them?
  3. What warrants us to believe that this evidence supports these claims? Are there clear lines of reasoning that take us from the facts to the claims and back?
  4. Do the warrants themselves require additional backing to be credible? Is there evidence to support their claims?
  5. What counter-arguments could potentially invalidate our claims, and do we have a credible rebuttal to refute them?
  6. Where do we draw the line between our claims and these alternatives?
  7. Based on all five precious steps, is there some qualification we can apply to our claim to secure its overall justification more firmly? What is our final statement of our core claim?

By applying this model to our beliefs, we can transform them into justified beliefs. But that still begs one question: are they true?

To address the question of truth, we have to draw upon the resources of the highest stair in our model, the one labeled theory. There are multiple theories of truth, but three stand out in particular:

  1. The correspondence theory, which says that claims are true when they are consistent with how things actually turn out to be, leading to a verifiable view of the world.
  2. The coherence theory, which says that claims are true when they are consistent with all the other claims you believe, leading to a coherent view of the world.
  3. The pragmatism theory, which says that claims are true when you act on them and your actions are consistent with your intentions, leading to an effective view of the world.

Rather than think of these theories as competing with one another, consider them as three dimensions of one and the same thing, namely knowledge that helps further one’s strategy for living. In that context, knowledge does indeed consist of justified true beliefs. It emerges from language contributing facts, interacting with narratives contributing beliefs, tested by analytics contributing justification, and confirmed by theory contributing truth. In this context, it is neither complicated nor mysterious.

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

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The Evolution of Trapped Value in Cloud Computing

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The Evolution of Trapped Value in Cloud Computing

GUEST POST from Geoffrey A. Moore

Releasing trapped value drives the adoption of disruptive technology and subsequent category development. The trapped part inspires the technical innovation while the value part funds the business. As targeted trapped value gets released, the remaining value is held in place by a secondary set of traps, calling for a second generation of innovation, and a second round of businesses. This pattern continues until all the energy in the system is exhausted, and the economic priority shifts from growth to maintenance.

Take cloud computing for example. Amazon and Salesforce were early disrupters. The trapped value in retail was consumer access anytime anywhere. The trapped value in SaaS CRM was a corporate IT model that prioritized forecasting and reporting applications for upper management over tools for improving sales productivity in the trenches. As their models grew in success, however, they outgrew the data center operating model upon which they were based, and that was creating problems for both companies.

Help came from an unexpected quarter. Consumer computing, led by Google and Facebook, tackled the trapped value in the data center model by inventing the data-center-as-a-computer operation. The trapped value was in computers and network equipment that was optimized for scaling up to get more power. The new model relentlessly focused on commoditizing both, with stripped-down compute blocks and software-enabled switching—much to the consternation of the established hardware vendors who had no easy place to retreat to.

Their situation was further exacerbated by the rise of hyperscaler compute vendors who offered to outsource the entire enterprise footprint. But as they did, the value trap moved again, and this time it was the hyperscaler pricing model that was holding things back, particularly when switching costs were high. That has given rise to a hybrid architecture which at present is muddling its way through to a moderating norm. Here companies like Equinix and Digital Realty are helping enterprises combine approaches to find their optimal balance.

As this norm takes over more and more of the playing field, we may approach an asymptote of releasable trapped value at the computing layer. If so, that just means it will migrate elsewhere—in this case, up the stack. We are already seeing this in at least three areas of hypergrowth today:

  1. Cybersecurity, where the trapped value is in patching together component subsystems to address ongoing exposure to catastrophic risk.
  2. Content generation, where the trapped value is in time to market, as well as unfulfilled demand, for fresh digital media, both in consumer markets and in the enterprise.
  3. Co-piloting, where the trapped value is in low-yielding engagement with high-value digital services due to topic complexity and the lack of sophistication on the part of the end user.

All three of these opportunities will push further innovation in cloud computing, but the higher margins will now migrate to the next generation.

The net of all this is a fundamental investment thesis that applies equally well to venture investing, enterprise spending, and personal wealth management. As the Watergate pair of Woodward and Bernstein taught us many decades ago, Follow the money! In this case, the money is in the trapped value, so before you invest in any context, first identify the trapped value that when released will create the ROI you are looking for, and then monitor the early stages to determine if indeed it is getting released, and if so, that a fair share of the returns are coming back to you.

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

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