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

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?

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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?

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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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Performance Management and Accountability

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Performance Management and Accountability

GUEST POST from Geoffrey A. Moore

Accountability begins with a voluntary commitment to put yourself in service to bringing about an outcome. To frame this effort for you and your team, I have found Salesforce’s V2MOM management system to be an invaluable tool. In that context:

  1. Vision describes the outcome you are all in service to.
  2. Values shape the approach you will all take to bringing it about.
  3. Methods present what each one of you will do to achieve the outcome and are assigned to single accountable leaders.
  4. Obstacles call out the challenges the leaders anticipate having to deal with, and
  5. Measures are the objective signals that everyone will use to assess your degree of success.

Performance management begins with securing each individual’s voluntary commitment to the outcomes associated with their jobs to be done as well as to the values to be honored while doing it. It then moves on to review their methods, obstacles, and measures to test them for coherence, feasibility, and credibility, and to ensure each person is confident they are set up to succeed and that they want to be held accountable for that success. The day-to-day work of performance management consists of inspecting, detecting, dissecting, course-correcting, and resurrecting the stream of work to keep it on track. Most of this effort consists of self-management, supported by regular check-ins with the team leader and quarterly reviews with the higher-ups. The majority of the work is focused on the near term, but this must be balanced with investments in the mid and long-term for sustained success.

That all said, that is not what most people think of when you bring up the topic of performance management. Instead, they associate it with a mandate to manage out under-performers. The word under-performer has unfortunate connotations, and this has cast a cloud over the entire effort.

To set things straight, begin by realizing that everyone is an under-performer at something. If you are unsure about what you personally under-perform at, just ask your spouse or your children, and they will let you know. The point is, there is no shame in under-performing per se. We just don’t want to persist in it.

When it comes to the workplace, under-performance shows up as a series of repeated shortfalls in our measures despite our best efforts to overcome our obstacles by course-correcting our methods. To ignore these signals without taking remedial action is to fall prey to Einstein’s definition of insanity, namely, doing the same thing over and over again and expecting a different result. Instead, one needs to intervene by invoking the “horse, rider, trail” principle. The horse is the offering, the rider is the person accountable for its success, and the trail is the target market. Changing any one of these factors will materially alter the dynamics of the situation such that you can expect a different result. Just understand that you probably won’t get to do this more than once, so choose wisely.

Finally, understand that while everyone is an under-performer at something, they are also likely to be an overachiever at something else. As a manager, you should act as a steward of your team members’ careers. If they are not the right fit for the job they are in, then both they and you need them to move on. Under-performing in this context is just nature’s way of telling us we are playing the wrong position, perhaps even playing the wrong game. Nobody likes to under-perform, and nobody is served by it. Meanwhile, our world is a needy place, so the sooner we can get people into their right roles, the better we all shall be.

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

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Everyone Clear Now on What ChatGPT is Doing?

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Everyone Clear Now on What ChatGPT is Doing?

GUEST POST from Geoffrey A. Moore

Almost a year and a half ago I read Stephen Wolfram’s very approachable introduction to ChatGPT, What is ChatGPT Doing . . . And Why Does It Work?, and I encourage you to do the same. It has sparked a number of thoughts that I want to share in this post.

First, if I have understood Wolfram correctly, what ChatGPT does can be summarized as follows:

  1. Ingest an enormous corpus of text from every available digitized source.
  2. While so doing, assign to each unique word a unique identifier, a number that will serve as a token to represent that word.
  3. Within the confines of each text, record the location of every token relative to every other token.
  4. Using just these two elements—token and location—determine for every word in the entire corpus the probability of it being adjacent to, or in the vicinity of, every other word.
  5. Feed these probabilities into a neural network to cluster words and build a map of relationships.
  6. Leveraging this map, given any string of words as a prompt, use the neural network to predict the next word (just like AutoCorrect).
  7. Based on feedback from so doing, adjust the internal parameters of the neural network to improve its performance.
  8. As performance improves, extend the reach of prediction from the next word to the next phrase, then to the next clause, the next sentence, the next paragraph, and so on, improving performance at each stage by using feedback to further adjust its internal parameters.
  9. Based on all of the above, generate text responses to user questions and prompts that reviewers agree are appropriate and useful.

OK, I concede this is a radical oversimplification, but for the purposes of this post, I do not think I am misrepresenting what is going on, specifically when it comes to making what I think is the most important point to register when it comes to understanding ChatGPT. That point is a simple one. ChatGPT has no idea what it is talking about.

Indeed, ChatGPT has no ideas of any kind — no knowledge or expertise — because it has no semantic information. It is all math. Math has been used to strip words of their meaning, and that meaning is not restored until a reader or user engages with the output to do so, using their own brain, not ChatGPT’s. ChatGPT is operating entirely on form and not a whit on content. By processing the entirety of its corpus, it can generate the most probable sequence of words that correlates with the input prompt it had been fed. Additionally, it can modify that sequence based on subsequent interactions with an end user. As human beings participating in that interaction, we process these interactions as a natural language conversation with an intelligent agent, but that is not what is happening at all. ChatGPT is using our prompts to initiate a mathematical exercise using tokens and locations as its sole variables.

OK, so what? I mean, if it works, isn’t that all that matters? Not really. Here are some key concerns.

First, and most importantly, ChatGPT cannot be expected to be self-governing when it comes to content. It has no knowledge of content. So, whatever guardrails one has in mind would have to be put in place either before the data gets into ChatGPT or afterward to intercept its answers prior to passing them along to users. The latter approach, however, would defeat the whole purpose of using it in the first place by undermining one of ChatGPT’s most attractive attributes—namely, its extraordinary scalability. So, if guardrails are required, they need to be put in place at the input end of the funnel, not the output end. That is, by restricting the datasets to trustworthy sources, one can ensure that the output will be trustworthy, or at least not malicious. Fortunately, this is a practical solution for a reasonably large set of use cases. To be fair, reducing the size of the input dataset diminishes the number of examples ChatGPT can draw upon, so its output is likely to be a little less polished from a rhetorical point of view. Still, for many use cases, this is a small price to pay.

Second, we need to stop thinking of ChatGPT as artificial intelligence. It creates the illusion of intelligence, but it has no semantic component. It is all form and no content. It is a like a spider that can spin an amazing web, but it has no knowledge of what it is doing. As a consequence, while its artifacts have authority, based on their roots in authoritative texts in the data corpus validated by an extraordinary amount of cross-checking computing, the engine itself has none. ChatGPT is a vehicle for transmitting the wisdom of crowds, but it has no wisdom itself.

Third, we need to fully appreciate why interacting with ChatGPT is so seductive. To do so, understand that because it constructs its replies based solely on formal properties, it is selecting for rhetoric, not logic. It is delivering the optimal rhetorical answer to your prompt, not the most expert one. It is the one that is the most popular, not the one that is the most profound. In short, it has a great bedside manner, and that is why we feel so comfortable engaging with it.

Now, given all of the above, it is clear that for any form of user support services, ChatGPT is nothing less than a godsend, especially where people need help learning how to do something. It is the most patient of teachers, and it is incredibly well-informed. As such, it can revolutionize technical support, patient care, claims processing, social services, language learning, and a host of other disciplines where users are engaging with a technical corpus of information or a system of regulated procedures. In all such domains, enterprises should pursue its deployment as fast as possible.

Conversely, wherever ambiguity is paramount, wherever judgment is required, or wherever moral values are at stake, one must not expect ChatGPT to be the final arbiter. That is simply not what it is designed to do. It can be an input, but it cannot be trusted to be the final output.

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

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Push versus Pull in the Productivity Zone

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Push versus Pull in the Productivity Zone

GUEST POST from Geoffrey A. Moore

Digital transformation is hardly new. Advances in computing create more powerful infrastructure which in turn enables more productive operating models which in turn can enable wholly new business models. From mainframes to minicomputers to PCs to the Internet to the Worldwide Web to cloud computing to mobile apps to social media to generative AI, the hits just keep on coming, and every IT organization is asked to both keep the current systems running and to enable the enterprise to catch the next wave. And that’s a problem.

The dynamics of productivity involve a yin and yang exchange between systems that improve efficiency and programs that improve effectiveness. Systems, in this model, are intended to maintain state, with as little friction as possible. Programs, in this model, are intended to change state, with maximum impact within minimal time. Each has its own governance model, and the two must not be blended.

It is a rare IT organization that does not know how to maintain its own systems. That’s Job One, and the decision rights belong to the org itself. But many IT organizations lose their way when it comes to programs — specifically, the digital transformation initiatives that are re-engineering business processes across every sector of the global economy. They do not lose their way with respect to the technology of the systems. They are missing the boat on the management of the programs.

Specifically, when the CEO champions the next big thing, and IT gets a big chunk of funding, the IT leader commits to making it all happen. This is a mistake. Digital transformation entails re-engineering one or more operating models. These models are executed by organizations outside of IT. For the transformation to occur, the people in these organizations need to change their behavior, often drastically. IT cannot — indeed, must not — commit to this outcome. Change management is the responsibility of the consuming organization, not the delivery organization. In other words, programs must be pulled. They cannot be pushed. IT in its enthusiasm may believe it can evangelize the new operating model because people will just love it. Let me assure you — they won’t. Everybody endorses change as long as other people have to be the ones to do it. No one likes to move their own cheese.

Given all that, here’s the playbook to follow:

  1. If it is a program, the head of the operating unit that must change its behavior has to sponsor the change and pull the program in. Absent this commitment, the program simply must not be initiated.
  2. To govern the program, the Program Management Office needs a team of four, consisting of the consuming executive, the IT executive, the IT project manager, and the consuming organization’s program manager. The program manager, not the IT manager, is responsible for change management.
  3. The program is defined by a performance contract that uses a current state/future state contrast to establish the criteria for program completion. Until the future state is achieved, the program is not completed.
  4. Once the future state is achieved, then the IT manager is responsible for securing the system that will maintain state going forward.

Delivering programs that do not change state is the biggest source of waste in the Productivity Zone. There is an easy fix for this. Just say No.

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

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Coping with the Chasm

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Coping with the Chasm

GUEST POST from Geoffrey A. Moore

I’ve been talking about crossing the chasm incessantly for over thirty years, and I’m not likely to stop, but it does beg the question, how should you operate when you are in the chasm? What is the chasm itself about, and what actions is it likely to reward or punish?

The chasm is a lull in the Technology Adoption Life Cycle, one that comes after the enthusiasts and visionaries have made their splash and before the pragmatists are willing to commit. At this time the new category is on the map, people are talking about it, often quite enthusiastically, but no one has budgeted for it as yet. That means that conventional go-to-market efforts, based on generating and pursuing qualified leads with prospects who have both budget and intent to purchase, cannot get traction. It does not mean, however, that they won’t entertain sales meetings and demos. They actually want to learn more about this amazing new thing, and so they can keep your go-to-market engine humming with activity. They just won’t buy anything.

Crossing the Chasm says it is time for you to select a beachhead market segment with a compelling reason to buy and approach them with a whole product that addresses an urgent unsolved problem. All well and good, but what if you don’t know enough about the market (or your own product for that matter) to make a sound choice? What if you are stuck in the chasm and have to stay there for a while? What can you do?

First of all, take good care of the early adopter customers you do have. Give them more service than you normally would, in part because you want them to succeed and be good references, but also because in delivering that service, you can get a closer look at their use cases and learn more about the ones that might pull you out of the chasm.

Second, keep your go-to-market organization lean and mean. You cannot sell your way out of the chasm. You cannot market your way out either. The only way out is to find that targetable beachhead segment with the compelling use case that they cannot address through any conventional means. This is an exercise in discovery, so your go-to-market efforts need to be provocative enough to get the meeting (this is where thought leadership marketing is so valuable) and your sales calls need to be intellectually curious about the prospect’s current business challenges (and not presentations about how amazing your company is or flashy demos to show off your product). In short, in the chasm, you are a solution looking for a problem.

Third, get your R&D team directly in contact with the customer, blending engineering, professional services, and customer success all into one flexible organization, all in search of the beachhead use case and the means for mastering its challenges. You made it to the chasm based on breakthrough technology that won the hearts of enthusiasts and visionaries, but that won’t get you across. You have to get pulled out of the chasm by prospective customers who will make a bet on you because they are desperate for a new approach to an increasingly vexing problem, and you have made a convincing case that your technology, product, talent, and commitment can fill the bill.

Finally, let’s talk about what you should not do. You cannot perform your way out of the chasm. You have no power. So, this is not a time to focus on execution. Instead, you have to find a way to increase your power. In the short term, you can do this through consulting projects—you have unique technology power that people want to consume; they just don’t want to consume through a product model at this time. They are happy to pay for bespoke projects, however, and that is really what the Early Market playbook is all about. Of course, projects don’t scale, so they are not a long-term answer, but they do generate income, and they do keep you in contact with the market. What you are looking for is solution power, tying your technology power to a specific use case in a specific segment, one that you could deliver on a repeatable basis and get you out of the chasm. Often these use cases are embedded in bespoke projects, just a part of the visionary’s big picture, but with more than enough meat on the bone to warrant a pragmatist’s attention.

Sooner or later you have to make a bet. You can recognize a good opportunity by the following traits:

  • There is budget to address the problem, and it is being spent now.
  • The results the prospect is getting are not promising and, if anything, the situation is deteriorating.
  • You know from at least one of your projects that you can do a lot better.

That’s about all the data you are going to get. That’s why we call crossing the chasm a high-risk, low-data decision. But it beats staying in the chasm by a long shot.

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

Image Credit: Microsoft Copilot

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Are You Leading in the Wrong Zone?

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Are You Leading in the Wrong Zone?

GUEST POST from Geoffrey A. Moore

I get tired of listening to “experts” explain how leaders need to be bolder. Usually what they are advocating for is more disruptive innovation, less business as usual. But this completely ignores the impact of context and ends up patronizing behavior that may actually be well-grounded. It depends on which zone you are operating out of.

In the Performance Zone, the goal is to deliver on the quarterly plan. It is not the time or place for disruptive innovation. Leadership means getting your team to the finish line despite whatever roadblocks may crop up. Grit and resourcefulness, combined with attention to tactics, is what is wanted here.

In the Productivity Zone, the goal is to be there for the long haul. Again, disruptive innovation is not on the docket. Analysis and optimization are the keys here, and leaders must be willing to step back, take a systems view of things, and invest in efforts that will enable the Performance Zone to perform better in the future.

By contrast, the Incubation Zone is all about disruptive innovation, and most pundits champion a leadership style that is a perfect fit for this zone. So, if you are in this zone, by all means embrace hypothesis testing, agility, fast failure and the like. Just remember that what works here does not work well in any of the other three zones.

Finally, the Transformation Zone is where the pundits ought to be focusing because transformation is a bear, and no one can ever really tame it. Business lore celebrates the amazing disrupters here — Jobs, Musk, Bezos, etc. — as well we should. But in so doing we should not ignore the amazing disruptees, the leaders who redirected their enterprises to bring them kicking and screaming into a new age — Gerstner, Nadella, Iger, and company. For my money, their leadership style is the single most important one for any aspiring CEO to master.

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

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What We Have Learned About Digital Transformation Thus Far

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What We Have Learned About Digital Transformation Thus Far

GUEST POST from Geoffrey A. Moore

We are well into our first decade of digital transformation, with both the successes and the scars to show for it, and we can see there is a long way to go. Realistically, there is probably never a finish line, so I think it is time for us to pause and take stock of what we have learned, and how best we can proceed from here. Here are three lessons to take to heart.

Lesson 1: There are three distinct levels of transformation, and operating model transformation is the one that deserves the most attention.

The least disruptive transformation is to the infrastructure model. This should be managed within the Productivity Zone, where to be fair, the disruption will be considerable, but it should not require much in the way of behavior change from the rest of the enterprise. Moving from data centers to cloud computing is a good example, as are enabling mobile applications and remote work centers. The goal here is to make employees more efficient while lowering total cost of IT ownership. These transformations are well underway, and there is little confusion about what next steps to take.

By contrast, the most disruptive transformation is to the business model. Here a company may be monetizing information derived from its operating model, as the SABRE system did for American Airlines, or overlaying a digital service on top of its core offering, as the automotive makers are seeking to do with in-car entertainment. The challenge here is that the economics of the new model have little in common with the core model, which creates repercussions both with internal systems and external ecosystem relationships. Few of these transformations to date can be said to be truly successful, and my view is they are more the exception than the rule.

The place where digital transformation is having its biggest impact is on the operating model. Virtually every sector of the economy is re-engineering its customer-facing processes to take advantage of ubiquitous mobile devices interacting with applications hosted in the cloud. These are making material changes to everyday interactions with customers and partners in the Performance Zone, where the priority is to improve effectiveness first, efficiency second. The challenge is to secure rapid, consistent, widespread adoption of the new systems from every employee who touches them. More than any other factor, this is the one that separates the winners from the losers in the digital transformation game.

Lesson 2: Re-engineer operating models from the outside in, not the inside out.

A major challenge that digital transformation at the operating model level must overcome is the inertial resistance of the existing operating model, especially where it is embedded in human behaviors. Simply put, people don’t like change. (Well, actually, they all want other people to change, just not themselves.) When we take the approach of internal improvement, things go way too slowly and eventually lose momentum altogether.

The winning approach is to focus on an external forcing function. For competition cultures, the battle cry should be, this new operating model poses an existential threat to our future. Our competitors are eating our lunch. We need to change, and we need to do it now! For collaboration cultures, the call to action should be, we are letting our customers down because we are too hard to do business with. They love our offers, but if we don’t modernize our operating model, they are going to take their business elsewhere. Besides, with this new digital model, we can make our offers even more effective. Let’s get going!

This is where design thinking comes in. Forget the sticky notes and lose the digital whiteboards. This is not about process. It is about walking a mile in the other person’s shoes, be that an end user, a technical buyer, a project sponsor, or an implementation partner, spending time seeing what hoops they have to go through to implement or use your products or simply to do business with you. No matter how good you were in the pre-digital era, there will be a ton of room for improvement, but it has to be focused on their friction issues, not yours. Work backward from their needs and problems, in other words, not forward from your intentions or desires.

Lesson 3: Digital transformations cannot be pushed. They must be pulled.

This is the hardest lesson to learn. Most executive teams have assumed that if they got the right digital transformation leader, gave them the title of Chief Transformation Officer, funded them properly, and insured that the project was on time, on spec, and on budget, that would do the trick. It makes total sense. It just doesn’t work.

The problem is one endemic to all business process re-engineering. The people whose behavior needs to change—and change radically—are the ones least comfortable with the program. When some outsider shows up with a new system, they can find any number of things wrong with it and use these objections to slow down deployment, redirect it into more familiar ways, and in general, diminish its impact. Mandating adoption can lead to reluctant engagement or even malicious compliance, and the larger the population of people involved, the more likely this is to occur.

So what does work? Transformations that are driven by the organization that has to transform. These start with the executive in charge who must galvanize the team to take up the challenge, to demand the digital transformation, and to insert it into every phase of its deployment. In other words, the transformation has to be pulled, not pushed.

Now, don’t get me wrong. There is still plenty of work on the push side involved, and that will require a strong leader. But at the end of the day, success will depend more on the leader of the consuming organization than that of the delivery team.

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

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