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

Bringing Yin and Yang to the Productivity Zone

Leave a reply

Bringing Yin and Yang to 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 1, 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?

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.

A Triumph of Artificial Intelligence Rhetoric

3 Replies

Understanding ChatGPT

A Triumph of Artificial Intelligence Rhetoric - Understanding ChatGPT

GUEST POST from Geoffrey A. Moore

I recently finished reading 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?

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.

Mission Critical Doesn’t Mean What You Think it Does

1 Reply

Mission Critical Doesn't Mean What You Think it Does

GUEST POST from Geoffrey A. Moore

God bless NASA for giving us the phrase “mission critical,” and God bless The Princess Bride for teaching us that not all words mean what we think they do.

In the case of mission-critical, specifically, the term has two distinct connotations, each of which leads to a distinctively different management priority.

1. Must achieve this outcome to succeed. This is what most people first think of when they hear the phrase. We will put a man on the moon and bring him back by the end of the decade. Anything that is on the critical path to that objective is mission critical.

2. Must not fall below this standard or we will be disqualified. This refers to a host of other things that, if not done properly, could have catastrophic consequences for the mission. Securing adequate funding, managing finances carefully, acquiring and maintaining proper facilities, and complying with pertinent regulations all come under this heading. You get no prize for doing any of these things right, but there can be a whopping penalty for getting them wrong.

When mission-critical equates to achieving success, the goal is to allocate the maximum amount of resources to the activity in question because it is the source of highest return. Indeed, it is your whole reason to be. Often in this situation there is no fixed upper boundary as to how much success can be achieved, so more is always going to be better here. That is why managers seeking budget for their efforts like to position them as mission-critical.

When mission-critical equates to disqualification risk, however, this approach backfires. That’s because there is a natural human tendency in risk-bearing situations to over-allocate resources as a hedge against what potentially could be a catastrophic failure. No one wants to get blamed for anything like this. Thus there is almost always an unproductive use of resources associated with these workloads and processes.

The proper goal for managing disqualification risk is to deploy the least amount of resources needed to achieve an acceptable level of risk, understanding that risk itself can never be eliminated entirely. To do this requires investing both in governance systems and in cultural discipline—the better the systems, the more disciplined the culture, the fewer the resources will be required.

Entrepreneurial cultures who grew up with the mantra “We don’t need no stinkin’ systems” will find it hard to execute this playbook, but until they do, they will be unable to scale. Conversely, risk-averse cultures who are unwilling to even approach the efficient frontier of risk will also fail here as well. You cannot compete effectively if a host of your best players are tied up on the sidelines. In short, there is no substitute for getting disqualification risk right, and successful organizations will testify this is always a work in progress.

So the next time you hear the word mission-critical, perk your ears up and apply this filter. Whatever is under discussion, for sure you are going to want to do this thing right. But before that, make sure you are doing the right thing.

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.

Understanding Permission

Leave a reply

Understanding Permission

GUEST POST from Geoffrey A. Moore

Permission is one of the most powerful concepts in strategic marketing, but it is an easy one to misinterpret if you are not careful. Here are five things you need to know:

1. Permission is anchored in the idea of what the world wants your company to be.

It may surprise you that the world has an agenda for your company, but it does—even if it has never heard of you. The world has unmet needs, and it is always looking for someone credible to enlist in meeting those needs. If you are a start-up, then you are credible at being highly disruptive. If you are an established and vibrant enterprise, then you are credible as a responsible steward. If you are an aging enterprise looking to rejuvenate, then you are credible as an agent of change within a conservative community.

2. Permission means you get more than one bite at the apple.

It means the customer base, and even the industry ecosystem, are willing to cut you some slack because, in their view, you represent the best chance for them to accomplish their agenda. In effect, you are granted a competitive advantage out of the box, given a status that none of your peers are getting. It is an amazing gift and is key both to start-up successes and enterprise turnarounds.

3. Permission is absolutely necessary at the point of business transformation.

There are plenty of times when you can overcome lack of permission through tenacious persistence, but not at the point of transformation. When you are turning the boat, when you are changing the direction of your enterprise, when you are entering a new space, your first encounters need to be with natural allies. They may not have bought in just yet, but they must be naturally aligned with your agenda, or you need to go elsewhere. You are simply too vulnerable otherwise.

4. Permission is an invitation to display generosity.

The prize you are after is a relationship of trust, one which will cause your target customers to privilege your company above other vendors. That’s what will secure your future in the new world. To accelerate getting to that point, begin with acts of strategic generosity, ones that demonstrate respect for the challenges your customers are hoping you can solve, and evidence that you have the wherewithal to solve them. Get these offers in play ASAP, and let the market’s viral properties drag you forward.

5. Permission has a sell-by date.

When issues and concerns come to the fore, there is a period of several years during which the pragmatist herd will wait to see who is going to step up to meet its new set of needs. If you have the wherewithal to lean in at this time but hold back instead, perhaps because you fear you will cannibalize some other aging product line, you will not be forgiven downstream. Gather the rosebuds while ye may.

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.

A Shortcut to Making Strategic Trade-Offs

1 Reply

A Shortcut to Making Strategic Trade-Offs

GUEST POST from Geoffrey A. Moore

I read with interest the following article posted on hbr.org. It highlights the challenge facing every Executive Leadership Team in securing alignment around what they should prioritize, short versus long-term gains, high versus low-risk initiatives, and disruptive versus sustaining innovation. The article notes that conflicts requiring sacrifices are common across industries, and that to handle them better, CEOs should introduce a “calculus of sacrifice” to ensure greater alignment in decision-making:

“By making the degree of sacrifice explicit among such conflicting objectives and quantifying it, CEOs can reframe decision-making and give executives the tools to make decisions aligned with their vision. Instead of advocacy-based deliberations, in which proponents of different courses of action make affirmative cases, discussion focuses on sacrifice: How much of one thing are we willing to give up in order to get more of something else?”

I take this to be a very reasonable point of departure, but from here the article goes on to propose a lengthy set of dialogs between the CEO and every member of the ELT digging into their personal approach to these issues and working toward a collaborative consensus about the best course of action. I don’t think this is either realistic or efficient. Instead, let me advocate for a zone-based approach.

As readers of this blog will be aware, the zone management model identifies four “zones of interest” within any enterprise, each with its own mission, metrics, and governance model, as follows:

  1. Performance Zone: Focus on executing this year’s annual plan with particular emphasis on meeting or beating the financial guidance given to investors.
  2. Productivity Zone: Focus on supporting the Performance Zone by attending to all the processes required to operate the enterprise efficiently, effectively, and in compliance with regulations.
  3. Incubation Zone: Focus on disruptive innovations that could have substantial impact on the enterprise’s future success, and develop real options for incorporating them into a future portfolio.
  4. Transformation Zone: Focus on taking a single disruptive innovation to scale, thereby changing the overall valuation of the enterprise’s portfolio.

Each of these four zones entails a different “calculus of sacrifice,” one that is built into the mission and metrics of that zone. Rather than ask the Executive Leadership Team to chart a path forward by keeping all four in mind, a simpler way forward is to use the annual budgeting process to allocate a percentage of the total available resources of the enterprise to each one of the four zones. The question is not, in other words, what should we do with this specific situation, but rather, how much of our operating budget do we want to spend in each of the four areas? It is still a tough question to answer, but it is bounded, and you can reach closure on it at any given point in time simply by having the CEO say, this is what it is going to be.

Once the allocations are settled, then decision-making can go much faster, because each member of the ELT is making calls in one, and only one, zone, using the calculus of that zone and ignoring those of the other three. In other words, stop trying to make your colleagues more or less innovative or risk-averse, and instead, let them play to their strengths in whatever zone represents their best fit.

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

Image Credit: 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.

Rethinking Customer Journeys

4 Replies

Rethinking Customer Journeys

GUEST POST from Geoffrey A. Moore

Customer journeys are a mainstay of modern marketing programs. Unfortunately, for most companies, they are pointed in the wrong direction!

Most customer journey diagrams I see map the customer’s journey through the vendor’s marketing and sales process. That’s not a customer journey. That is a vendor journey. Customers could not care less about it.

What customers do care about is any journey that leads to value realization in their enterprise. That means true customer journey mapping must work backward from the customer’s value goals and objectives, not forward from the vendor’s sales goals and objectives.

But to do that, the customer-facing team in the vendor organization has to have good intelligence about what value realization the customer is seeking. That means that sales teams must diagnose before they prescribe. They must interrogate before they present. They must listen before they demo.

That is not what the typical sales enablement program teaches. Instead, it instructs salespeople on how to give the standard presentation, how to highlight the product’s competitive advantages, how to counter the competition’s claims—anything and everything except the only thing that really matters—how do you get good customer intelligence from whatever level of management you are able to converse with?

The SaaS business model with its emphasis on subscription and consumption creates a natural occasion for reforming these practices. Net Revenue Retention is the name of the game. Adoption, extension, and expansion of product usage are core to the customer’s Health Score. This only happens when value is truly being realized.

All this is casting the post-sales customer-facing functions of Customer Success and Customer Support in a new light. These relationships are signaling outposts for current customer status. Vendors still need to connect with the top management, for they are the ones who set the value realization goals and provide the budgets to fund the vendor’s offerings, but for day-to-day reality checks on whether the value is actually getting realized, nothing beats feet on the ground.

So, note to vendors. You can still use your vendor-centric customer journey maps to manage your marketing and sales productivity. Just realize these maps are about you, not the customer. You cannot simply assign the customer a mindset that serves your interests. You have to genuinely engage with them to get to actionable truth.

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 Have We Learned About Digital Transformation Thus Far?

1 Reply

What Have We 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.

Geoffrey Moore Pyramid Model

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 reengineering 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: Reengineer 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 reengineering. 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: 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.

What Disruptive Innovation Really Is

Leave a reply

What Disruptive Innovation Really Is

GUEST POST from Geoffrey A. Moore

I recently read an article in ZDnet by Sherin Shibu discussing disruptive innovation, primarily through the lens of Clay Christensen’s work at the Harvard Business School. The article itself is very sound, and yet I found myself disagreeing with it on a number of points. In this blog, I want to interleave what Shibu says (presented in standard font) with my own commentary (inserted in italics) so that readers can develop their own point of view from the interaction.

What is disruptive innovation?

Disruptive innovation theory is a cautionary concept for large, established companies: There’s danger in becoming too good at what you do best. Delivering to the mainstream market is good and all, but a disruptor could target a market underserved by your current product with a new business model.

For me, disruptive innovation has a much bigger footprint because it also underlies virtually all venture capital investment. Its fundamental promise is to release an enormous amount of trapped value by reengineering an established system or process. The reason it is a cautionary concept for large established companies is that they are the custodians of the legacy systems and processes that are trapping the value. Yes, they can reduce the overhead by optimizing what they have, but no, they cannot compete with a categorically better way of doing things.

Harvard Business School professor Clayton Christensen developed the concept of disruptive innovation in the 1990s with his groundbreaking book The Innovator’s Dilemma, and the theory became wildly popular in the decades to follow. But in some respects it has become a victim of its own success: “Despite broad dissemination, the theory’s core concepts have been widely misunderstood and its basic tenets frequently misapplied,” notes The Harvard Business Review.

Disruptive innovation is a process by which entrepreneurs break into a low-end or new market and create business models that are different from existing ones in those markets. Disruption has occurred when their business model becomes mainstream.

So, a new company targets an overlooked customer base — and manages to deliver a better product at a lower price point. At first, the incumbents don’t take the threat seriously, which allows the potential disruptors to gain a foothold. Then the disruptors target the incumbents’ mainstream customers. If the potential disruptors create something that the mainstream adopts in volume, they have successfully disrupted the market.

I think this reading of the model overemphasizes the need to attack the low end of the market. Yes, that is a proven path, but it is not the only one. The iPhone disrupted from the high end, for example, as has Tesla.

What is disruptive innovation not?

Defining disruptive innovation isn’t easy and not everyone is going to agree on every example. Classic disruptive innovation should not simply describe just any situation of upheaval. If a new company shakes things up a bit for incumbent competitors, that scene is not necessarily one of disruptive innovation — that could simply be a breakthrough. In order for this theory to have power and be used as an analytical and predictive model, it needs to be precisely defined.

My definition of disruptive innovation is one that overthrows and is incompatible with the existing business model or operating model of an industry. In the case of the iPhone, it was Apple’s ability to go over the top of the carrier to provide products and services directly to the consumer. In the case of Tesla, it is its ability to bypass the dealership model not only in sales but in services as well.

Christensen, for example, argued that Uber is not a disruptive innovator according to his definition. It fails to meet two requirements, in that it did not start in a low-end or new market. Instead, it built a name for itself in a mainstream market and then started drawing unserved customers with less expensive solutions. And being less expensive or creating an app to hail rides sustains the existing model rather than disrupts.

This is just wrong and shows the limitations of the “start at the low end” concept. Uber reengineered both the operating model and the business model of on-demand car transportation, allowing consumers to call a taxi to themselves, and allowing Uber to build a fleet of cars and drivers at no capital expense.

Not everyone thinks that’s the case and other perspectives can be found that argue Uber actually is a disruptive innovator. From this perspective, Uber started with a low-market foothold by offering on-demand black car services. It was only when the startup introduced UberX, a low-end market offering, that it was able to move into the mainstream.

What counts as disruption is up for debate, especially as Christensen’s theory is applied to shifting contexts.

In the case of Uber, focusing on the low end simply misses the point.

Why is it important to define disruptive innovation?

Disruption isn’t a fixed point; it’s the evolution of a product or service from the fringes of customers to the mainstream. It’s important to define it this way because then it becomes more about the experimental nature of the process than about the output. See, disruptive innovations don’t always succeed and not every successful company is a disruptor. The process is about building new business models previously unseen in the target industry and appealing to a more niche customer base at first.

In my view, disruptive innovation is a function of a breakthrough technology intersecting with a pool of trapped value, enabling the reengineering of a system or process that eliminates one or more whole categories of spend in its value chain. It is a categorical innovation as opposed to a product or marketing innovation.

Is disruptive innovation the primary way innovation operates?

No, it is not the primary factor of innovation. According to HBR, “disruption theory does not, and never will, explain everything about innovation specifically or business success generally.” It does, however, help predict which businesses will succeed and it provides a solid foundation for further research – it’s captured academic attention for 27 years.

I agree with the point that disruptive innovation is not the primary type. Most innovation is sustaining, meaning that it improves an existing system rather than overthrowing it—evolution, not revolution. What I disagree with wholeheartedly, on the other hand, is the notion that the theory helps predict which businesses will succeed. Historically, the advantage has gone to start-ups because they are unconflicted in their commitment to the new way. Established enterprises, however, have learned that they can neutralize start-ups if they are willing to be fast followers. Microsoft’s Azure is a superb example of a company that has done this. Disney’s response to Netflix is another good example, and it appears as if General Motors is on a comparable path toward neutralizing Tesla.

What is an example of disruptive innovation?

Netflix was around since 1997, and at first, it didn’t appeal to Blockbuster’s core clientele. Renting movies usually happened in person, and Netflix was all online. Plus, Netflix took a few days to deliver movies because selections came through the mail. Blockbuster could easily ignore Netflix because it didn’t have the brick-and-mortar infrastructure needed to dominate the market at that time.

This glosses over what was the initial disruptive innovation that Netflix provided with its home delivery model based on DVDs. The key differentiator at the beginning was designing out late fees.

Over time though, as streaming technology developed, Blockbuster’s target clients were drawn toward Netflix. The same impulsiveness that made renting a movie right away more desirable than getting a movie a few days later translated into wanting to watch movies with a click of a mouse instead of going to a physical location to rent a DVD. Disruptive innovation technology, in this case, streaming, goes hand in hand with implementing innovation.

There is another story playing out in Netflix’s transition from DVD shipping to streaming. It required the company to disrupt itself. This is an extraordinary ask, as most successful disruptive innovations attack someone else’s profit pool, not one’s own. Reed Hastings deserves enormous credit for leading the company through this change, and I would encourage the academy to focus its research lens on how in the world he was able to do so when so many CEOs have fallen short.

Are there any disruptive innovation technologies to keep an eye on?

Online learning is a technology to watch because it’s reaching a population that in-person learning can’t reach at a lower price point.

The main technologies to keep an eye on are the ones that tackle an underserved market and have the potential to expand their offerings to appeal to the mainstream.

Something like autonomous vehicles, for example, can seem innovative, but they aren’t disruptive according to the theory because they’ll be quickly absorbed into existing industries. The incumbent advantage is strong.

The important thing to remember is that innovation does not always lead to disruption.

I strongly support the idea that online education delivery has the power to disrupt the education market—again, a breakthrough technology intersecting with a boatload of trapped value. I think the point about autonomous vehicles is interesting as well because I agree they will be absorbed into the existing industries. But while they may not disrupt the automotive industry, I do think they can reengineer transportation and logistics.

Overall, I support Shibu’s main thesis which is that we have come to take disruptive innovation for granted and have become careless with how we apply the term. And while we part ways on how best to apply it, I still endorse Clay’s breakthrough insights in The Innovator’s Dilemma, which had a huge impact on a whole generation of companies in Silicon Valley.

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.

Winning in a Downturn Requires Delivering the Whole Product

Leave a reply

Winning in a Downturn Requires Delivering the Whole Product

GUEST POST from Geoffrey A. Moore

In a downturn, everyone has to prioritize. For sales prospects, this means funding their most pressing needs first. For vendors who want to thrive, it means focusing on offers that match those needs, marketing that speaks to those needs, and sales coverage that is targeted specifically at winning those deals. And the key to winning is to deliver the whole product.

The whole product, as Ted Levitt taught us a generation ago, is the complete set of products and services needed to fulfill the compelling reason to buy for the target customer. In normal times, it is often OK to deliver most of the whole product, as either the customer or a channel partner will likely have resources and motive to fill in the rest. But in a downturn, not only are budgets scarce, so is expertise. Moreover, in a downturn, it is more critical than ever to deliver 100% on the promised outcome, as the customer is counting on that ROI to make their plans work.

Creating a bill of materials for your whole product is a straight exercise in design thinking. Just put yourself in the shoes of your target customer, get the compelling reason to buy square in your sights, and figure out what you would need to take that problem completely off the table. Once you have a draft, then test drive it with friendly prospects and let them show you all the things you missed. Take that input back to the team and construct a go-to-market offer that fills the bill, with every need taken care of. That’s what’s going to differentiate you from the competition. That’s what’s going to get you not only the sale but a radiating customer reference. That’s what’s going to let you thrive in a downturn.

Start-ups have an inherent advantage here over established enterprises because for them a single whole product focused on a single target market with an urgent use case is enough to get them across the chasm and into the mainstream market as a viable long-term player. But product managers in established enterprises can orchestrate the same play if they can garner executive support. The trick is to get the product team to prioritize some slightly off-road-map features, the service team to create a small corps of use-case experts, and the go-to-market team to field a dedicated target market initiative. The resources are always there to do this, but the inertial momentum of large enterprises works against such tightly focused efforts—hence the advantage to start-ups.

Whole product delivery has been greatly advanced by two seminal developments in the software world in this century. The first is the SaaS business model, especially when augmented by managed services. This transfers a large portion of success responsibility from the customer to the vendor. The second is the emergence of telemetry data processed by AI and ML. This allows service providers to get better and better at delivering customer success.

One company I am on the board of illustrates these advantages to a T. WorkFusion, experts in Intelligent Robotic Automation, no longer offer high-tech projects to early adopting visionaries. Instead, they supply digital workers to financial services companies needing to staff their regulatory compliance functions in a time of staff attrition (the job really is not that much fun) and high demand (the crooks are out in force). The point is, their digital workers do not just automate a task—they act like real colleagues who do the work and deliver the needed results. You can fund them out of the IT budget, of course, but you can also fund them out of your HR headcount (and they are a lot cheaper, don’t mind coming to the office, and actually appear to enjoy their work—certainly the people that program them do).

The key takeaway here is that downturns create new, pressing needs that prospects will prioritize over their traditional budget spend. These are problems that are both urgent and important—real threats that need to be addressed quickly and efficiently. To thrive in a downturn, you need to detect these opportunities quickly and pivot to meet them head on and let the other chips fall where they may.

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

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

What the Current Round of Layoffs Tells Us

Leave a reply

What the Current Round of Layoffs Tells Us

GUEST POST from Geoffrey A. Moore

When layoffs hit one or two companies, you might blame it on management, but when they hit market leader after market leader, you know something structural is afoot. The important thing then is to extract the signal from all the noise. Here is my cut at it.

First of all, it is the digital consumer sector that is under fire—not all of tech. But note that when you click on the Tech Section of any major publication, all you get is consumer tech news. B2C has eclipsed B2B in the public perception of what tech is all about. The downturn may not change this for consumers, but it sure will for investors. B2B tech actually has the opportunity to thrive in a downturn if it focuses on solving urgent problems that have short time to payback.

Second, the digital consumer model has such attractive economics when it is operating at scale that it led to a massive overvaluation of the sector per se. As with prior bubbles in tech, overvaluing is primarily due to extrapolating present growth as perpetual and ignoring global economic and geopolitical downside risks. Downturns simply call this out and demand a recalibration of valuation based on a more balanced mix of positive and negative factors.

Third, when enterprises have hyper-valued market caps, management does everything it can to sustain them, eventually to the point of counterproductive actions driven more by inertia than any sensible investment strategy. Given the peer pressures of investor relations, this is almost impossible to stop, so ultimately we end up where we are, in need of a correction that everyone saw coming, but no one acted upon. And to be fair, guessing when the correction will come is not a winning play. Better to accept the dynamics you have in front of you and then adapt as fast as you can once they change.

Net net, it is time to own the correction, put our houses in order, accept the deflation in stock price, refocus on our core mission, reset our performance metrics, and get back out on the field.

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

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.