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

Are You Leading in the Wrong Zone?

Leave a reply

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?

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

What We Have Learned About Digital Transformation Thus Far

Leave a reply

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?

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Are We Doing Social Innovation Wrong?

1 Reply

Are We Doing Social Innovation Wrong?

GUEST POST from Geoffrey A. Moore

The Volume Operations business model kicks in when you have hundreds of thousands of users and goes up from there. 100,000, for those of us who are not math majors, is 10 to the power of 5. Uber-successful volume ops businesses operate at 10 to the power of 9 and up—millions of users or customers. But if you are a start-up, you are looking at 10 or maybe 100. How do you get from here to there?

The key thought to keep in mind is the old chestnut “what got you here won’t get you there.” That is, whatever operating model you have, keep in mind it can scale to two exponents but never to three. That means for every two exponents you have to change operating models, which likely means you have to change executive leadership in order to go forward.

To illustrate this idea, I’d like to focus on the non-profit sector and ask the question, what would it take to really solve for any widespread social problem? Homelessness was the first one that came to mind, but hunger is another obvious one, drug addiction a second, street crime a third. They are all seemingly intractable issues that, despite the best intentions of a whole raft of people, and regardless of how much funding is supplied, stubbornly resist any sustainable improvement.

The question I want to address is not what programs would work—because I actually think a whole lot of programs would work—but rather, how could we organize to deploy these programs successfully at scale.

Following our principle of what got you here won’t get you there, we need a ladder of operating models that can take us, exponent by exponent, from 10 to the power of 1 to, say, 10 to the power of 7. What might that look like?

Scaling Social Innovation

Consider this a straw man, a place to start, something to edit. It conveys a key lesson from the high-tech sector, namely that the fastest way to kill a disruptive innovation is to race to scale by skipping over one or more of these “exponential steps.” It just doesn’t work. There are too many emergent factors at each new level you must learn to cope with in order to succeed. The only reliable way to scale is to ratchet your way up this staircase, adapting your systems and operations as you go.

Unfortunately, that’s not what politicians do. They want to make a big impact right away. That means they start everything on one of the upper stairs. Driven by impatience, they ignore the dynamics of adoption and demand mass deployment from the get-go. They think the problem is simply one of getting enough funding. It’s not. It’s one of operational innovation. Scaling prematurely simply wastes the funding. And then when programs do flounder, as they inevitably will, they blame it on execution when in reality they simply did not do the hard, time-consuming work of building up their foundation step by step from below.

One of the implications of this framework is that social services should be incubated in the private sector where freedom from regulatory constraints supports agile innovation. But as they scale, the importance of regulatory oversight increases and more communal engagement is required. The goal should be to keep this oversight as local as possible as long as possible, doing as much as we can to empower the people delivering the service itself. Once that operating model solidifies, then, and only then, is there a proper foundation for scaling to state and federal programs.

Today, we do not lack the empathy to support social services. Nor do we lack the funding. But we are failing nonetheless. We can do better. We need to do better.

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

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Career Development at Its Best

Leave a reply

Career Development at Its Best

GUEST POST from Geoffrey A. Moore

A colleague recently forwarded me an article about upskilling one’s team. I am on board with the first part—innovating from within—but I am not comfortable with the concept of “upskilling.” Here’s why.

Upskilling implies that the challenges you face lend themselves to known skilled responses. Combined with the idea of training, it also implies that you have that skills knowledge already in-house and simply need to transfer it to a new cohort. I can see both of these ideas being applicable to technical work, but I don’t think they reflect the realities of knowledge work. There, instead, I think we need to substitute learning for training and experience for upskilling.

Whereas training puts the responsibility for a successful outcome on the trainer, learning puts it on the learner. In the world of knowledge work, that’s where it has to sit. We need to develop ourselves—no one else can do it for us. But we need experience to do so, and this is where managers can have a big impact. It is not the training we give our teams but rather the assignments we entrust to them that let them build new muscles.

Assigning an inexperienced person to a new challenge is always a risk—for them, for their manager, and for the customer of the work to be done. Unfortunately, without risk, there is no learning. There is no risk-free way to learn. So the manager’s goal is to create opportunity while mitigating risk.

One of the best means for so doing is assigning people the role of the Single Accountable Leader (SAL). The need for a SAL arises in any cross-functional initiative where hierarchy of authority is replaced by team collaboration. Just as a football team needs a quarterback to run a play that involves 11 people collaborating toward one outcome, so does a cross-functional initiative need a single accountable leader to be the focus of decision-making as the team adapts to unfolding events. This person need not be an expert. They need to be vigilant. They need to stay on top of things. They need to inquire and inspect, to detect when the effort is going off course, to focus the team on redirecting it, to get counsel from their mentors, and to escalate issues that are beyond their ability to address. Most of all, they need to care.

When people care, they learn. They go the extra mile. They bring out the best in others. And in so doing, they build the new muscle that will qualify them for a larger role in the enterprise. This to me is career development at its best. The SAL assignment is the most precious gift that managers and mentors can bestow upon their charges. I hope you can take advantage of it.

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

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Exploring Performance Management

Leave a reply

Exploring Performance Management

GUEST POST from Geoffrey A. Moore

Performance management is a tool for managing Performance Zone commitments. These are the outcomes and deliverables that your organization, or for that matter you yourself, are being funded to deliver. In the Vision, Value, Methods, Obstacles, and Measures (V2MOM) framework, they will be represented by one or more of your Methods and will be tied directly to a corresponding set of Measures.

The primary goal of performance management is to ensure success in meeting such commitments. This includes early detection of things going off track—hence the need for frequent check-ins. It includes coaching and mentoring to help team members succeed—something we all need at one time or another. It asks us all to balance empathy for times when people don’t succeed with accountability for the need to succeed. People need help when they are down, but it is not fair to continue to accept funding for outcomes that do not get delivered.

When people under-deliver against their commitments, nobody wins. Most importantly, and this is something a lot of people miss, the person who is under-delivering is not winning. When coaching and mentoring are not getting them to success, the likelihood is that they are in the wrong role. Keeping them in that role, which we sometimes think of as protecting them, just prolongs the agony. A far better response is to step back and assess what would be the right role for this person, whether it be another one on the same team, or one on a different team, or one in another organization, or one in another company. The point is, rather than obsessing about what they are doing badly, we need to focus instead on what they could be really good at and get them into that role as swiftly as possible.

Let me be even more clear. It is obvious that when under-performing folks are kept in a role, everyone else on the team has to work harder. What is not so obvious is that when under-performing folks move on, even if their roles are not back-filled, the team discovers it has less work to do! The reason is that under-performing people absorb everyone else’s time. After all, they are trying to help, they just aren’t succeeding. And since helping teammates is baked into collaborative cultures, we give them extra time even though it is not productive to do so.

Again, nobody is winning here. We need an intervention. In this context, policies that call for managing out the bottom five percent are simply a heuristic that says, in any organization at any time, there are bound to be some number of round pegs in square holes, and leaving them in place doesn’t help anyone.

So, why then do we still bristle at the notion of performance management? There’s a ton of psychology behind this question, more than I am competent to address, but the net effect is that performance management puts enormous pressure on a set of social skills many of us lack. That’s not going to change anytime soon, so we should not be surprised at our reluctance to engage. But it is not OK to dodge our responsibilities either. Our best bet, in my view, is to bake into our protocol a discussion of positive next steps that includes concrete recommendations, and cope with our emotional challenges as best we can.

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

Image Credit: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Time is Not Fundamental

1 Reply

Time is Not Fundamental

GUEST POST from Geoffrey A. Moore

For all my life I have been taught that time is the fourth dimension in a space-time continuum. I mean, for goodness sake, Einstein said this was so, and all of physics has followed his lead. Nonetheless, I want to argue that, while the universe may indeed have four dimensions, time is not one of them, nor is it a fundamental element of reality.

Before you think I have really jumped off the deep end, let me just say that my claim is that motion is a fundamental element of reality, and it is the one that time is substituting for. This is based simply on observation. That is, we can observe and measure mass. We can observe and measure space. We can observe and measure energy. We can observe and measure motion. Time, on the other hand, is simply a tool we have developed to measure motion. That is, motion is fundamental, and time is derived.

Consider where our concept of time came from. It started with three distinct units—the day, the month, and the year. Each is based on a cyclical motion—the earth turning around its axis, the moon encircling the earth, the earth and moon encircling the sun. All three of these cyclical motions have the property of returning to their starting point. They repeat, over and over and over. That’s how they came to our attention in the first place.

If we call this phenomenon cyclical time, we can contrast it with linear time. The latter is time we experience as passing, the one to which we apply the terms past, present, and future. But in fact, what is passing is not time but motion, motion we are calibrating by time. That is, we use the cyclical units of time to measure the linear distance between any given motion and a reference location.

As I discuss in The Infinite Staircase, by virtue of the Big Bang, the Second Law of Thermodynamics, and the ongoing rush to greater and greater entropy, the universe is inherently in motion. Some of that motion gets redirected to do work, and some of that work has resulted life emerging on our planet. Motion is intrinsic to our experience of life, much more so than time. As babies we have no sense of time, but we immediately experience mass, space, energy, and motion.

Because mass, space, energy, and motion are core to our experience, we have developed tools to help us engage with them strategically. We can weigh mass and reshape it in myriad ways to serve our ends. We can measure space using anything as a standard length and create structures of whatever size and shape we need. We can measure energy in terms of temperature and pressure and manipulate it to move all kinds of masses through all kinds of spaces. And we can measure motion through space by using standard units of time.

The equation for so doing is typically written as v = d/t. This equation makes us believe that velocity is a concept derived from the primitives of distance and time. But a more accurate way of looking at reality is to say t = d/v. That is, we can observe distance and motion, from which we derive time. If you have a wristwatch with a second hand, this is easily confirmed. A minute consists of a wand traveling through a fixed angular distance, 360°, at a constant velocity set by convention, in this case the International System of Units, these days atomically calibrated by specified number of oscillations of cesium. Time is derived by dividing a given distance by a given velocity.

OK, so what? Here the paths of philosophy and physics diverge, with me being able to pursue the former but not the latter. Before parting, however, I would like to ask the physicists in the room, should there be any, a question: If one accepted the premise that motion was the fourth dimension, not time, such that we described the universe as a continuum of spacemotion instead of spacetime, would that make any difference? Specifically, with respect to Einstein’s theories of special and general relativity, are we just substituting terms here, or are there material consequences? I would love to learn what you think.

At my end, I am interested in the philosophical implications of this question, specifically in relation to phenomenology, the way we experience time. To begin, I want to take issue with the following definition of time served up by Google:

a nonspatial continuum that is measured in terms of events which succeed one another from past through present to future.

From my perspective, this is just wrong. It calls for using events to measure time. The correct approach would focus on using time to measure motion, describing the situation as follows:

an intra-spatial continuum that can be measured in terms of time as one event succeeds another from a position of higher energy to one of lower energy.

The motive for this redefinition is to underscore that the universe is inherently in motion, following the Second Law of thermodynamics, perpetually seeking to cool itself down by spreading itself out. We here on Earth are born into the midst of that action, boats set afloat upon a river, moving with the current on the way to a sea of ultimate cool. We can go with the flow, we can paddle upstream, we can even divert the river of entropy to siphon off energy to do work. The key point to register is that motion abides, inexorably following the arrow of entropy, moving from hot to cold until heat death is achieved.

If motion is a primary dimension of the universe, there can be no standing still. Phenomenologically, this is quite different from the traditional time-based perspective. In a universe of space and time, events have to be initiated, and one can readily imagine a time with no events, a time when nothing happens, maybe something along the lines of Beckett’s Waiting for Godot. In a universe of space and motion, however, that is impossible. There are always events, and we are always in the midst of doing. A couch potato is as immersed in events as a race car driver. Or, to paraphrase Milton, they also move who only stand and wait.

A second consequence of the spacemotion continuum is that there is no such thing as eternity and no such thing as infinity. Nothing can exist outside the realm of change, and the universe is limited to whatever amount of energy was released at the Big Bang. Now, to be fair, from a phenomenological perspective, the dimensions of the universe are so gigantic that, experientially, they might as well be infinite and eternal. But from a philosophical perspective, the categories of eternity and infinity are not ontologically valid. They are asymptotes not entities.

Needless to say, all this flies in the face of virtually every religion that has ever taken root in human history. As someone deeply committed to traditional ethics, I am grateful to all religions for supporting ethical action and an ethical mindset. If there were no other way to secure ethics, then I would opt for religion for sure. But we know a lot more about the universe today than we did several thousand years ago, and so there is at least an opportunity to forge a modern narrative, one that can find in secular metaphysics a foundation for traditional values. That’s what The Infinite Staircase is seeking to do.

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

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Fighting for Innovation in the Trenches

Leave a reply

Fighting for Innovation in the Trenches

GUEST POST from Geoffrey A. Moore

The first principle of managing innovation is that there are three distinct returns on innovation one can invest to achieve.

They are:

  1. “Unmatchable” differentiation, which confers enormous bargaining power as customers who want what you have “must” select you and “must” pay a premium for your offer. We call this DIFF for short.
  2. “Speedy” neutralization, which catches you up to some new market norm set by a competitor, thereby enabling you to stay in the game rather than be eliminated for lacking this feature. This is NEUT for short.
  3. “Rigorous” optimization, which extracts high-value talent and other scarce resources from non-differentiating work in order to free up investment in highly differentiating work or high-speed neutralization efforts. This is OPT for short.

The second principle is that these three outcomes are mutually exclusive, meaning you do not want to combine any two of them into the same work stream. Most innovation programs bind DIFF objectives with NEUT objectives, tying both to the same release cadence. This either slows down NEUT or dumbs down DIFF, both of which outcomes are painfully counterproductive.

The third principle is that most innovation investment is wasted (which is actually good news, because it means you can get a much bigger bang for your innovation buck once you learn how to avoid the waste). The three great sources of waste are:

  1. DIFF initiatives that do not result in “unmatchable” offers that create unequivocal customer preference. You end up being different but not different enough to gain real bargaining power.
  2. NEUT initiatives that take too long or go too far (or, more typically, both). Here the team has become obsessed with its competitor and is doing extra work that the customer will not value, meanwhile delaying the “good enough” state that the customer would value.
  3. OPT initiatives that do not address “sacred cow” resources. You end up moving around a lot of junior resources, meanwhile leaving the senior ones trapped in context instead of being deployed against core.

A corollary that can help teams avoid waste is to pay attention to their reference points.

  • If your goal is DIFF, then your reference point should be a prospective customer’s use case, one where purchase preference will be determined by you achieving “unmatchable” performance in your key area of innovation.
  • If your goal is NEUT, then your reference point is a competitor, then your innovation focus should be to get “good enough” fast enough.
  • A behavior you must avoid is to use a competitor as a reference point for DIFF. The all too likely outcome here is that you will create a difference that the customer either will not notice, will not acknowledge, or will not value. Meanwhile, the competitor will debate the fact that you even achieved it or that it is relevant if you did.

Finally, in light of these principles, the role of the leader is to deconstruct the overall workload of the team to tease out the DIFF from the NEUT from the OPT, and to charter specific work-streams accordingly. This rarely results in a perfectly pure outcome, but the more pure it is, the more productive your team’s efforts will be.

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

Image Credit: Dall-E via Bing

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

What Have We Learned About Digital Transformation?

Leave a reply

What Have We Learned About Digital Transformation?

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.

Geoffrey Moore Three Models

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?

Image Credit: Pexels, Geoffrey Moore

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Humans Are Not as Different from AI as We Think

2 Replies

Humans Are Not as Different from AI as We Think

GUEST POST from Geoffrey A. Moore

By now you have heard that GenAI’s natural language conversational abilities are anchored in what one wag has termed “auto-correct on steroids.” That is, by ingesting as much text as it can possibly hoover up, and by calculating the probability that any given sequence of words will be followed by a specific next word, it mimics human speech in a truly remarkable way. But, do you know why that is so?

The answer is, because that is exactly what we humans do as well.

Think about how you converse. Where do your words come from? Oh, when you are being deliberate, you can indeed choose your words, but most of the time that is not what you are doing. Instead, you are riding a conversational impulse and just going with the flow. If you had to inspect every word before you said it, you could not possibly converse. Indeed, you spout entire paragraphs that are largely pre-constructed, something like the shticks that comedians perform.

Of course, sometimes you really are being more deliberate, especially when you are working out an idea and choosing your words carefully. But have you ever wondered where those candidate words you are choosing come from? They come from your very own LLM (Large Language Model) even though, compared to ChatGPT’s, it probably should be called a TWLM (Teeny Weeny Language Model).

The point is, for most of our conversational time, we are in the realm of rhetoric, not logic. We are using words to express our feelings and to influence our listeners. We’re not arguing before the Supreme Court (although even there we would be drawing on many of the same skills). Rhetoric is more like an athletic performance than a logical analysis would be. You stay in the moment, read and react, and rely heavily on instinct—there just isn’t time for anything else.

So, if all this is the case, then how are we not like GenAI? The answer here is pretty straightforward as well. We use concepts. It doesn’t.

Concepts are a, well, a pretty abstract concept, so what are we really talking about here? Concepts start with nouns. Every noun we use represents a body of forces that in some way is relevant to life in this world. Water makes us wet. It helps us clean things. It relieves thirst. It will drown a mammal but keep a fish alive. We know a lot about water. Same thing with rock, paper, and scissors. Same thing with cars, clothes, and cash. Same thing with love, languor, and loneliness.

All of our knowledge of the world aggregates around nouns and noun-like phrases. To these, we attach verbs and verb-like phrases that show how these forces act out in the world and what changes they create. And we add modifiers to tease out the nuances and differences among similar forces acting in similar ways. Altogether, we are creating ideas—concepts—which we can link up in increasingly complex structures through the fourth and final word type, conjunctions.

Now, from the time you were an infant, your brain has been working out all the permutations you could imagine that arise from combining two or more forces. It might have begun with you discovering what happens when you put your finger in your eye, or when you burp, or when your mother smiles at you. Anyway, over the years you have developed a remarkable inventory of what is usually called common sense, as in be careful not to touch a hot stove, or chew with your mouth closed, or don’t accept rides from strangers.

The point is you have the ability to take any two nouns at random and imagine how they might interact with one another, and from that effort, you can draw practical conclusions about experiences you have never actually undergone. You can imagine exception conditions—you can touch a hot stove if you are wearing an oven mitt, you can chew bubble gum at a baseball game with your mouth open, and you can use Uber.

You may not think this is amazing, but I assure you that every AI scientist does. That’s because none of them have come close (as yet) to duplicating what you do automatically. GenAI doesn’t even try. Indeed, its crowning success is due directly to the fact that it doesn’t even try. By contrast, all the work that has gone into GOFAI (Good Old-Fashioned AI) has been devoted precisely to the task of conceptualizing, typically as a prelude to planning and then acting, and to date, it has come up painfully short.

So, yes GenAI is amazing. But so are you.

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

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

How to Re-engineer the Incubation Zone

Leave a reply

How to Re-engineer the Incubation Zone

GUEST POST from Geoffrey A. Moore

Having spent the last several years working with public companies in the tech sector who want to apply zone management principles to catching their next wave, I finally had an epiphany.

Every one of my clients had an Incubation Zone of one sort or another, and all of them had put concerted efforts into running it in an efficient and orderly way. This included crowd-sourcing a large funnel of potential ideas from the workforce, taking those ideas through a well-structured qualification process with clear benchmarks for progressing to the next stage, and funding a handful of the best ideas to get through to an MVP and market validation.

My epiphany was, this is a Production Zone operating model, not an Incubation Zone model. That is, these enterprises are treating the Incubation Zone as if it were another cost center. No venture capitalist operates in this manner. They are not process oriented—they are coin operated. But they do have a method, one that has proven itself countless times, and that’s what I want to describe here.

Anchor Tenets

In my view, there are five key principles that successful VCs keep close to their hearts. They are:

  1. Trapped value. If you are going to be coin operated, the first thing to do is find the coins. In B2B markets, this typically equates to identifying where there is trapped value in the current way of doing business. The value may be trapped in the infrastructure model (think cloud computing over data centers), the operating model (think self-organizing ride dispatching from Uber over the standard call center dispatcher), or the business model (think software subscription over license and maintenance). The point is, if you can release the trapped value, customers will enjoy dramatic returns, enough to warrant taking on the challenge of a Technology Adoption Life Cycle.
  2. 10X technology. VCs are fully aware that there are very good reasons why trapped value stays trapped. Normally, it is because the current paradigm has substantial inertial momentum, meaning it delivers value reliably, even though not optimally. To break through this barrier requires what Andy Grove used to call a 10X effect. Something has to be an order of magnitude better than the status quo to kick off a new Technology Adoption Life Cycle. Incremental improvements are great for reinforcing the status quo, as well as for defending it against the threat of disruption, but they do not have the horsepower to change the game.
  3. Technology genius. 10X innovations do not fall out of trees. Nor are they normally achieved through sheer persistence. Brilliance is what we are looking for here, and here public enterprises face a recruiting challenge. They simply cannot offer the clean slate, venture funding, and equity reward possibilities that private capital can. What they can do, however, is pick up talent on the rebound and integrate them into their own playbook (see more on this below). The point is, top technology talent is a must have. This puts pressure both on the general manager of any Incubation Zone operating unit and on the Incubation Zone board to do whatever it takes to put an A Team together.
  4. New design rules. The path for breakthrough technology to release trapped value involves capitalizing on next-generation design rules. The key principle here is that something that used to be expensive, complex, and scarce, has by virtue of the ever-shifting technology landscape, now become cheap, simple, and plentiful. Think of DRAM in the 1990s, Wi-Fi in the first decade of this century, compute cycles in the current decade, with data storage perhaps the next in line. Prior to these inflection points, solution designers had to work around these factors as constraints, be that in constricting code to run in 64KB, limiting streaming to run over dial-up modems, or operating their own data center when all they wanted to do was to run a program. Inertia holds these constraints in place because they are embedded in so many interoperating systems, they are hard to change. Technology Adoption Life Cycles blow them apart—but only when led by entrepreneurs who have the insight to reconceive these assets as essentially free.
  5. Entrepreneurial general manager. And that brings us to the fifth and final key ingredient in the VC formula: entrepreneurial GMs. They are the ones with a nose for trapped value, able to sell the next new thing on its potential to create massive returns. They are the ones who can evangelize the new technology, celebrate its game-changing possibilities, and close their first visionary customers. They must recruit and stay close to their top technology genius. They must intuit the new design rules and use them as a competitive wedge to break into a market that is stacked against them. Finally, they must stay focused on their mission, vision, and values while course-correcting repeatedly, and occasionally pivoting, along the way. It is not a job description for the faint of heart.

Now, these are what I claim to be the anchor tenets of the VC playbook. For the purposes of the rest of this blog, let’s take them as a given. Now the question becomes, how could a public enterprise, which does not have the freedom or flexibility of a venture capital firm, construct an Incubation Zone operating model that incorporates these principles in a way that plays to its strengths and protects itself against its weaknesses?

An Enterprise Playbook for the Incubation Zone

We should acknowledge at the outset that every enterprise has its own culture, its own crown jewels, its own claim to fame. So, any generic playbook has to adapt to local circumstances. That said, it is always good to start with a framework, and here in outline form is the action plan I propose:

  • Create an Incubation Board first, and charter it appropriately. Its number one responsibility is not to become the next disrupter—the enterprise already has a franchise, it doesn’t need to create one. Instead, it needs to protect the existing franchise against the next technology disruption by getting in position to ride the next wave as opposed to getting swamped by it.
  • In this role, the board’s mission is to identify any intersections between trapped value and disruptive technologies that would impact, positively or negatively, the enterprise’s current book of business. We are in the realm of SWOT threats and opportunities, where the threats take precedence because addressing them is not optional.
  • The first piece of business is to identify potential use cases that could emerge at the intersection of trapped value and breakthrough technology, to prioritize the list in terms of import and impact, and to recruit a small team to build a BEFORE/AFTER demo that highlights the game-changing possibilities of the highest priority case. This team is built around a technology leader and an entrepreneur. The technology leader ideally would come from the outside, thereby being less prone to fall back on obsolete design rules. The entrepreneur should come from the inside, perhaps an executive from a prior acquisition who has been down this path before, thereby better able to negotiate the dynamics of the culture.
  • The next step is to socialize the demo, first with technology experts to pressure test the assumptions and make improvements to the design, and then with domain experts in the target use case, whether from the customer base or the enterprise’s own go-to-market team, who have a clear view of the trapped value and a good sense of what it would take to release it.
  • The next step is to pitch the Incubation Zone board for funding.

> This is not an exercise in TAM or SAM or anything else of the sort. Those are tools for determining ROI in established sectors, where category boundaries are more or less in place. Disruptive innovation creates whole new boundaries, or fails altogether in the process, neither of which outcomes are properly modeled in the normal market opportunity analysis frameworks.

> Instead, focus on beachhead market potential. Could this use case gain sufficient market adoption within a single target segment to become a viable franchise? If so, it will give the enterprise a real option on a possible future. That is the primary goal of the Incubation Zone.

Whether the effort succeeds or fails, the enterprise can gain something of real value. That is, success gives it a viable path forward, and failure suggests that it need not spend a lot of resources protecting against this flank. The job of the board is to determine if the proposal being pitched is worth prioritizing on this basis.

  • Once funded, the focus should be on building a Minimum Viable Product and using it as the basis for selling a bespoke project to a visionary executive working at a marquee brand. The intent is to build a whole product for this customer on a project basis, doing whatever it takes to release the trapped value, thereby showing the world what good could look like. This project will require a ton of custom engineering, so it is key to price this on a time and materials basis, giving away the license while protecting the IP rights. Success consists of creating a marquee reference that garners the attention of the tech sector analysts and media.
  • The next funding milestone focuses on productizing the MVP for initial distribution. Ideally, this would be done internally with the enterprise IT department serving as Customer Zero. That allows for deeper dives into what’s working and what’s not as well as data collection to verify that trapped value is not only being released but recovered. It also positions the CIO as a highly credible reference to support New Product Introduction.
  • With productized offering in hand, the final step is to introduce the new product into restricted distribution, not general availability. Your goal is to target a beachhead market with a single use case—just the opposite of what general distribution is designed to accomplish. Thus, the entire go-to-market effort, from product launch, to pipeline generation, to sales, post-sales implementation, and customer success needs to be under the direct management of the GM of the Incubation Zone operating unit. Success here is measured by classic chasm-crossing metrics, focused on winning a dominant share of the top 30 accounts in the target market segment.

Crossing the chasm represents the fulfillment of the Incubation Zone’s real option mandate. This sets up a second set of funding milestones depending on what exit path is to be targeted. We can dig into those dynamics at another time.

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

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.