Category Archives: Innovation

We Change the World with Ecosystems Not Inventions

We Change the World with Ecosystems Not Inventions

GUEST POST from Greg Satell

Imagine yourself as the CEO of a Dow component company in 1919. You are fully aware of the technological forces that would shape much of the 20th century, electricity and internal combustion. You may have even be an early adopter of these technologies. Still, everything seems like business as usual.

What you don’t see, however, is that these inventions are merely the start. Secondary technologies, such as home appliances, radio, highways and shopping malls, would reshape the economy in ways that no one could have predicted. Your company has a roughly 50% chance of remaining on the Dow a decade later.

We are at a similar point today. New inventions, such as quantum computing, neuromorphic chips, synthetic biology and advancements in materials science already exist. It is not those inventions, however, but the ecosystems they spawn that will shape the decades to come. We’re all going to have to learn how to compete in a new era of innovation.

A 50-Year Boom In Productivity

By 1919, electricity was already a 40-year old technology. In 1882, just three years after he had almost literally shocked the world with his revolutionary electric light bulb, Thomas Edison opened his Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was already servicing over 500 homes.

Yet although electricity and electric lighting were already widespread in 1919, they didn’t have a measurable effect on productivity and a paper by the economist Paul David helps explain why. It took time for manufacturers to adapt their factories to electricity and learn to design workflow to leverage the flexibility that the new technology offered. It was the improved workflow, more than the technology itself, that drove productivity forward.

Automobiles saw a similar evolution. It took time for infrastructure, such as roads and gas stations, to be built. Improved logistics reshaped supply chains and factories moved from cities in the north — close to customers — to small towns in the south, where labor and land were cheaper. That improved the economics of manufacturing further.

Yet all of that was just prelude to the massive changes that would come. Electricity spawned secondary innovations, such as household appliances and radios. Improved logistics reshaped the retail industry, shifting it from corner stores to supermarkets and shopping malls. As Robert Gordon explains in The Rise and Fall of American Growth, these changes resulted in a 50-year boom in productivity between 1920 and 1970.

The Digital Revolution

In 1984, Steve Jobs and Apple launched the Macintosh, which heralded a new era of computing. Based on technology developed for the Xerox Alto in the early 1970s, with a bitmapped screen, a graphical user interface and a mouse, it made computing far more accessible to regular consumers.

Before long, personal computers were everywhere. Kids would use them to write term papers and play video games. Lotus 1-2-3 spreadsheet software became a staple for small businesses and entrepreneurs. Desktop publishing helped democratize the flow of information. The computer age had begun in earnest.

Yet much like electricity and internal combustion earlier in the century, the effect on productivity was negligible, causing the Nobel Prize winning economist Robert Solow to quip, “You can see the computer age everywhere but in the productivity statistics.” In fact, it wouldn’t be till the late 90s that we saw a measurable impact from computers.

Once again, it wasn’t any particular invention that made the difference, but an ecosystem that built up over years. The Internet paved the way for open-source software. Hordes of application developers created industry specific tools to automate almost every imaginable business process. Computers converged with phones to create the mobile era.

The 30 Years Rule

Look back at the two major eras of technology in the 20th century and a consistent theme begins to emerge. An initial discovery of a new phenomenon, such as electricity and internal combustion, is eventually used to create a new invention, like the light bulb or the automobile. This creates some excitement, and builds the fortunes of a few entrepreneurs, but has little impact on society as a whole.

Yet slowly, an ecosystem begins to emerge. Roads and gas stations are built. Household appliances and personal computers are invented. Secondary inventions, such as shopping malls, home appliances, the Internet and application software help create new business models. Those business models create new value and drive productivity.

The truth is that innovation is never a single event, but a process of discovery, engineering and transformation. As a general rule of thumb, it takes about 30 years for all of this to take place, because thousands, if not millions of people need to change their behavior, coordinate their activity and start new businesses.

That’s why the future will always surprise us. It is not any one great event that tips the scales, but some hardly noticeable connection that completes the network. Network scientists call this type of thing an ‘instantaneous phase transition’ and there’s really no way to predict exactly when it will happen, but if you learn to look for telltale signs, you can see one coming.

A New Era Of Innovation

Today, we appear to be in a very similar situation to what those executives faced in 1919. We have decoded the human genome. Artificial intelligence has become a reality that everyone, for the most part, accepts. New computing architectures, such as quantum computers and neuromorphic chips, are in late stages of development by a variety of companies.

Yet once again, the impact has been negligible and it’s not hard to see why. While these inventions, in some cases at least, are relatively mature, they have yet to create the ecosystems that can drive a true transformation. Today, however, we can clearly see those ecosystems being created.

In fact, in artificial intelligence we can already see a fairly well developed ecosystem emerging already. In synthetic biology and genomics we can begin to see one as well, although it is still nascent. IBM has created a Q Network of major companies, research labs and startups to support quantum computing.

Here’s what’s important to know: We can’t predict exactly when the system will tip, but it’s a good bet it will happen in the next decade. It is also likely that the impact will be equal to or greater than the 50 year boom that began in the 1920s. Finally, it won’t be driven by any particular invention, but by ecosystems. You need to start figuring out how you will connect.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Pixabay

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Two Kinds of Persistence – What’s Your Habit?

GUEST POST from Dennis Stauffer

I suspect you’ve heard all your life that it’s important to be persistent, whether that’s studying hard, practicing a sport, launching a new business, or attempting some innovation. You’re told that you need to stick with it until you find success. You need to have GRIT.

But what’s so often lost in that advice is that there’s more than one way to be persistent, and which one you have can make a HUGE difference.

Type 1

The first kind of persistence is sticking with something despite setbacks. That’s the marathoner who pushes through exhaustion and pain. It’s the student who studies until they really “get” the subject matter. It’s the entrepreneur putting in long hours to pursue a dream. That kind of persistence sees a target, pushes toward it, and blocks out any distractions that keep them from pursuing it.

Type 2

The other kind of persistence is about being creative and resourceful. It’s trying more than one way to reach your goals, and sometimes adjusting those goals to fit the realities you confront. It’s the entrepreneur that pivots to a new business model because the first one isn’t working. It’s the student who changes their career plans because it better fits their personal strengths and preferences. It’s the athlete who changes their technique to improve rather than just practicing the same approach.

Type 1 versus Type 2

These are radically different—opposing—strategies, and you can be quite good at one of them and lousy at the other.

That first kind of persistence is helpful when things are predictable and the rules are clear, when you know what will work. You just need to go do it. That’s useful at times, but much of life rarely works that way.

The challenges you face are often not so clear, and one of the biggest mistakes you can make is thinking they are when they’re not. That’s the entrepreneur that falls in love with an idea and keeps pursuing it long after getting signals that it’s not really working. Thinking: if I just push a little longer. When they need to change course.

It’s called being stubborn.

Skilled innovators—and those who are most effective generally—favor that second kind of persistence. They don’t just keep plugging along. They’re willing to rethink their strategy, seek feedback and gain new insights. Instead of assuming they know what works, they strive to figure out what works.

That’s not mindless pushing, and it’s not just trying random alternatives. It’s a disciplined process you can learn. A process of innovation that reflects a mindset that values flexibility, adaptability and resourcefulness, more than raw determination.

Which kind of persistence do you believe in? Which do you use?

Here is the video version of this post for all of you:

Image Credit: Pexels

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Stuff Your Stoking with Innovation for $4.24

Stuff Your Stoking with Innovation for $4.24

Wow! Exciting news!

While supplies last you can get the hardcover version of my best-selling book Stoking Your Innovation Bonfire for only $4.24 (88% off), including free delivery in the USA from Amazon!

Sorry, unfortunately Amazon doesn’t have a discount on the kindle version, which remains at $28.00, so this is quite the deal!

  • The offer is only valid while supplies list (or until Amazon changes the price) so act fast!

Quick reminder: Everyone can download lots of free tools from this web site, including:

  • 700+ quote posters
  • The Experiment Canvas™
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  • 10 Free Human-Centered Change Tools
  • Nine Innovation Roles card design

Follow this link to select multiple items and download them ALL AT ONCE!

And finally, I created the Human-Centered Change methodology to help organizations get everyone literally all on the same page for change. The 70+ visual, collaborative tools are introduced in my book Charting Change, including the powerful Change Planning Canvas™. The toolkit has been created to help organizations:

  • Beat the 70% failure rate for change programs
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  • Get valuable tools for a low investment

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Don’t Waste Your Time Talking to Customers

(until you answer these 3 questions)

Don’t Waste Your Time Talking to Customers

GUEST POST from Robyn Bolton

You know that customer insights are important.

You spend time and money to collect customer insights. 

But are you using them?

And by “using,” I don’t mean summarizing, synthesizing, discussing, PowerPointing, and presenting the insights.  I mean making decisions, changing strategies, and rethinking plans based on them.

I posed this question to a few dozen executives.  The awkward silence spoke volumes.

Why do we talk to customers but not listen to them?

In a world of ever more constrained resources, why do we spend our limited time and money collecting insights that we don’t use meaningfully?

It seems wild to have an answer or an insight and not use it, especially if you spent valuable resources getting it.  Can you imagine your high school self paying $50 for the answer key to the final in your most challenging class, then crumpling it up, throwing it away, and deciding to just wing the exam?

But this isn’t an exam.  This is our job, profession, reputation, and maybe even identity.  We have experience and expertise.  We are problem solvers.

We have the answers (or believe that we do).

After all, customers can’t tell us what they want.  We’re supposed to lead customers to where they should be. Waiting for insights or changing decisions based on what customers think slows us down, and isn’t innovation all about “failing fast,” minimal viable products, and agility?

So, we talk to customers because we know we should. 

We use the answers and insights to ensure we have brilliant things to tell the bosses when they ask.

We also miss the opportunity to create something that changes the game.

But it doesn’t have to be this way.

What do you NEED to learn?

It’s easy to rattle off a long list of things you want to learn from customers.  You probably also know the things you should learn from customers.  But what do you need to learn?

What do you need to know by the end of a conversation so that you can make a decision?

What is the missing piece in the puzzle that, without it, you can’t make progress?

What insight do you need so badly that you won’t end the conversation until you have it?

If the answer is “nothing,” why are you having the conversation?

Will you listen?

Hearing is the “process, function, or power of perceiving a sound,” while listening is “hearing things with thoughtful attention” and a critical first step in making a connection.  It’s the difference between talking to Charlie Brown’s teacher and talking to someone you care about deeply.  One is noise, the other is meaning.

You may hear everything in a conversation, but if you only listen to what you expect or want to hear, you’ll miss precious insights into situations, motivations, and social dynamics.

If you’re only going to listen to what you want to hear, why are you having the conversation?

Are you willing to be surprised?

We enter conversations to connect with others, and the best way to connect is to agree.  Finding common ground is exciting, comforting, and reassuring.  It’s great to meet someone from your hometown, who cheers for the same sports team, shares the same hobby, or loves the same restaurant.

When we find ourselves conversing with people who don’t share our beliefs, preferences, or experiences, our survival instincts kick in, and we fight, take flight, or (like my client) freeze.

But here’s the thing – you’re not being attacked by a different opinion. You’re being surprised by it. So, assuming you’re not under actual physical threat, are you willing to lean into the surprise, get curious, ask follow-up questions, and seek to understand it? 

If you’re not, why are you having the conversation?

Just because you should doesn’t mean you must.

You know that customer insights are important.

You spend time and money to collect customer insights. 

But are you using them to speed the path to product-market fit, establish competitive advantage, and create value?

If you’re not, why are you having the conversation?

Image Credit: Pexels

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Re-engineering the Incubation Zone for a Downturn

Re-engineering the Incubation Zone for a Downturn

GUEST POST from Geoffrey A. Moore

In a prior post, written during the tech boom, I outlined how established enterprises could re-engineer their approach to managing innovation in order to catch the next wave before it caught them. Now we are in a different time, where capital is more expensive, and near-term profitability more necessary. We still need to innovate our way through the challenges ahead, and the management playbook is fundamentally the same, but there are enough nuances to attend to that it is worth revisiting the topic end to end.

The guiding principle is unchanged. Publicly-held enterprises routinely mismanage incubation to such an extent that, when they are successful, the market is actually surprised. Their approach is based on a process model, typically involving 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 a minimum viable product (MVP) and market validation. The problem is that this is a Productivity Zone operating model, not an Incubation Zone model. That is, these enterprises are treating the Incubation Zone as if it were another cost center. Needless to say, no venture capitalist operates in this manner.

Meanwhile, the venture capital industry is routinely successful at managing incubations, be they to successful exits or timely shut-downs. Their operating model has over forty years of established success—and yet it is a rare public enterprise indeed that even tries to implement it. Some of this is due to confusing the venture industry’s business model, which is not appropriate for a publicly held firm, with its operating model, which is perfectly suitable to emulate. It is that model that I want to describe here.

Anchor Tenets

There are at least five key principles that successful Venture Capitalists (VC’s) keep close to their hearts. They are:

  1. Trapped value. VC’s are nothing if not coin-operated, and in that context, 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, even in a downturn. This is key because in a downturn, absent a compelling reason to act immediately, pragmatic customers will defer their buying decisions as long as possible. So, innovation for innovation’s sake is not the play for today’s market. You should be looking for disease-preventing vaccines, not life-extending vitamins.
  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 far from optimally. To break through this barrier requires what Andy Grove taught us 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. So, do not let your Incubation Zone “major in minors.” If there is not something truly disruptive on your plate, wait for it, and keep your powder dry.
  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 publicly held 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 it 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. That said, there is a loophole here one can exploit in a downturn. If your enterprise needs to catch up to a disruptive innovation, that is, if it needs to neutralize a competitive threat as opposed to instigating a new adoption life cycle, then a “fast follower” leader is just the ticket. This person does not think outside the box. This person catches the box and jumps on it. Microsoft has been the premier example of this playbook from its very inception, so there is definitely money to be made here!
  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, and compute cycles in the current decade. 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. One last thing—in a downturn, instead of starting with visionaries in the Early Market, a far better play is to focus on a beachhead, chasm-crossing market segment from Day One. The TAM is smaller, but the time to close is much shorter, and this gets you traction early, a critical success factor when capital is costly and funders are impatient.

Now, assuming we can embrace these anchor tenets from the VC playbook, the key question becomes, How can 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 disruptor — 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. Another way to phrase this is that we are playing defense first, offense second. This is particularly critical in a downturn because that is a time when visionaries lose power and pragmatists in pain gain power.
  • Given a chasm-crossing mentality, the first piece of business is to identify potential use cases that 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.

a) 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.

b) 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 an array of possible value-creating futures. That is the primary goal of the Incubation Zone.

Whether the effort succeeds or fails, the enterprise will gain something of real value. That is, success will give it a viable path forward, and failure will suggest 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.

  • To pursue the opportunity, you want to create an independent operating unit that looks like a seed-stage start-up. Once funded, it should target a specific, value-trapping process in a single industry, ideally managed by a single department, and apply breakthrough technology and laser focus to re-engineering the process to a much better outcome. This will require developing a whole product, defined as the complete solution to the customer’s problem, organized around a core product plus ancillary supporting products and services. The latter can be supplied by third parties, but the effort has to be orchestrated by you.
  • With this problem-specific solution in hand, the final step is to bring it to market via 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.

In a downturn, crossing the chasm—not winning inside the tornado—represents the fulfillment of the Incubation Zone’s real option mandate. You want to create a cash-flow-positive entity that protects your franchise from disruption by coopting an emerging technology while at the same time solving a mission-critical problem for a customer who needs immediate help. That is value, in and of itself, over and above the optionality it creates for future category creation.

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

Image Credit: Pixabay

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We Need To Stop Glorifying Failure

Here’s What To Do Instead

We Need To Stop Glorifying Failure

GUEST POST from Greg Satell

Over 50% of startups fail (and that number goes up to 75% for venture backed startups). The same is true of about three quarters of corporate transformations, which is probably why the average lifespan on the S&P 500 continues to shrink. These statistics tell a humbling story: few significant endeavors ever actually succeed.

So it’s probably not surprising that we’ve come to glorify failure. We are urged to “fail fast” and are cheered on when we do. Failure, after all, is hard evidence that you’ve tried something difficult and paid the price. Yet failure, as anyone who actually experienced it knows well, is a horrible, painful thing.

As I explain in Cascades, great transformations are achieved not by glorifying failure, but when we learn from mistakes and begin to do things differently. That’s how great enterprises are transformed, industries are disrupted and then remade a new and seemingly all powerful tyrants are overthrown. Failure is something we should never accept, but rather overcome.

Ask The Hard Questions

Go to just about any innovation conference and you will find some pundit on the stage telling the story of some corporate giant, usually Blockbuster, Kodak or Xerox, that stumbled and failed. It is then explained that these firms were run by silly, foolish people who simply didn’t want to see the signs of disruption around them.

These stories are almost never true and, in fact, should be seen as ridiculous on their face. It takes no small amount of intelligence, drive and ambition to run a significant enterprise so to suggest that executives managing highly successful businesses were utter dopes beggars belief. The truth is that smart, hard working people fail all the time.

Once you realize that it forces you to ask some hard questions. Why did these smart, successful people fail? Why weren’t the dangers lurking more obvious? What hidden forces were working against them? Why did they think that they actions they undertook, after no small amount of deliberation, were the best of the available options?

Consider the case of Mahatma Gandhi and his Himalayan miscalculation. In 1919, he organized a series of demonstrations to protest against unjust laws passed by the British Raj. These were successful at first, but soon got out of hand and eventually led to the massacre at Amritsar, in which British soldiers left hundreds dead and more than a thousand wounded.

Most people would have simply concluded that the British were far too cruel and brutal to be dealt with peacefully. Gandhi, however, looked for the error in his own actions and learned from his mistakes. A decade later, rather than embark on a wholesale revolt, he identified a keystone change that would break the logjam. Today, both the salt march that resulted, and Gandhi himself, have become icons.

Test Your Hypotheses (Cheaply)

If you want to get a project going in a typical organization, the first thing you do is try to procure a big budget. So you write up an impressive business plan, examine the political tea leaves and work your contacts. If you’re successful, you can build out a great staff, line up tier-one partners and really hit the ground running.

You also can’t make any mistakes. Unless your plan was truly bulletproof from conception (and it never is) or you just get really lucky, you’re going to make some big, well-funded, well-staffed blunder that you’ll have to scramble to recover from. Unless you catch it early or have the political clout within your organization to get more money, you are likely to fail.

Now consider how Nick Swinmurn started his business. As Eric Ries explained in The Lean Startup, instead of spending money on some expensive marketing study to see if people would buy shoes online, he simply built a cheap site. When he got an order, he would go to the store, buy the pair at retail, and ship it out. He lost money on every sale.

That’s a terrible way to run a business, but a great way to test a business hypothesis. Once he knew that people were willing to buy shoes online, he started Zappos, which quickly grew to dominate the market for selling shoes online. It was sold to Amazon in 2009, ten years after Swinmurn started, for $940 million.

Build A Network

We tend to think that success is the result of hard work and talent. Yet look at any category and one brand tends to dominate. There are many search engines, but only one Google, just like there are many smartphone manufacturers, but only one Apple. Both are great products, but they end up taking the vast majority of profits in their industry. Are they really that much better than their competitors?

The truth is, as Albert-László Barabási explains in The Formula, is that performance is bounded, but success isn’t. You can be better than your competitors, but not that much better. On the other hand, there are no limits to success because networks tend to be dominated by a central node.

To understand why, consider the case of Albert Einstein. Until April 3rd, 1921, he was a prominent scientist, but by no means an icon. In fact, much of his press coverage was negative. But on that date, he arrived in America with the Zionist leader Chaim Weizmann. Reporters covering the event mistook the enormous crowds there to meet Weizmann as fans of Einstein and the story made the first page of all major newspapers.

That, along with his brilliance and endearing personality, is what catapulted Einstein to iconic status. In a similar vein, Google launched its product on the techie-dense Stanford computer network and Apple introduced the iPhone to its already expansive fan base. It’s networks, not nodes, that drive success.

Stop Disrupting And Start Solving Problems

Walk down any grocery store aisle and it becomes clear that there is no shortage of ideas. At any given time there are countless opportunities for line extensions, expansions into new categories, partnerships and other things. Executives spend countless hours discussing the merits and demerits of ideas like these.

Yet innovation isn’t about ideas, it’s about solving problems. That’s why most ideas fail, because they don’t address a meaningful problem that people really need solved. Nobody really needs a different flavor of cereal, but Zappos, Google and Apple all met needs that people cared about and that made all the difference.

That’s why companies that last not only look to solve problems for today’s customers, but also take on grand challenges. These are not “bet the company” type of propositions, but long, sustained efforts that seek to fundamentally change the realm of the possible, like Google’s more than decade long quest to create a self-driving car or IBM’s generational pursuit of quantum computing.

The truth is that you never really have to fail because, if you make your efforts sustainable, you can always learn from mistakes and try again. Failure rarely stems from a lack of effort, but is guaranteed by a myopic vision.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Unsplash

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The Amazing Efficiency of Systematic Guessing

The Amazing Efficiency of Systematic Guessing

GUEST POST from Dennis Stauffer

Are you as personally efficient as you could be? Most of us aren’t, and that may be because we’re not as innovative as we could be. Being efficient—for people and for organizations—isn’t just about doing things more quickly and automatically. It’s about rapidly adapting to change and discovering new strategies.

Most organizations—and most innovators—are convinced that innovation takes extra time and resources. That’s certainly true at times, but also misleading. Because being innovative can also make you dramatically more efficient. Finding solutions, making improvements and inventing new ways of doing things can save countless hours and resources—and there’s a more immediate gain than those future benefits.

Let me explain it this way.

Imagine that your challenge is to figure out how to spell a simple ten letter word: INNOVATION. (And let’s pretend you don’t already know.) You can of course start guessing, but that will take a while—a long while. There are 26 letters in the English alphabet and ten in this word. So that’s 26 to the 10th power, or more than 141-trillion, possibilities! If you guess once per second—without repeating any—it will take you more than four-and-a-half million years to cover them all.

Suppose instead that you’re at a computer, one that won’t tell you how to spell innovation, but will tell you when you’ve guessed the right letter. In other words, you can do what skilled innovators do. You can continually check whether your ideas—your guesses—are working. Now, each letter will require at most 26 guesses, one for each letter in the alphabet. You can cover all possibilities in 26 times 10 or 260 attempts. At one attempt per second, that will take you less than four-and-a-half minutes. And you don’t need to know anything about how to spell the word when you start.

Of course, the challenges you face are probably more complex than spelling a ten-letter word, and it will probably take longer than a second to explore possible solutions. But as complexity grows, so does the relative efficiency of this kind of systematic guessing.

Suppose the word you want to spell has eleven letters—INNOVATIONS. Just trying to guess it will now take you 26 times longer. That’s more than a hundred million years! When you check each of your guesses, it only adds another 26 seconds. You’re still done in less than five minutes. A hundred-million years, vs. five minutes. That’s the astronomical gain in efficiency you achieve when you know how to systematically investigate what works.

It’s as though you’re facing a genie with a puzzle. You need to solve that puzzle to make your wishes come true, and the genie won’t tell you the answer. But the genie is willing to give you clues—in the form of consequences. So to solve the puzzle, you must attempt possible solutions that will generate consequences—feedback—that will tell you whether you’re on the right track. That’s what skilled innovators do—and anyone else who hopes to successfully handle uncertainty—which is all of us.

So, if someone tells you, you don’t have time to be innovative, tell them you don’t have time not to.

Here is a video version of this post:

The Innovator Mindset YouTube channel brings you weekly tips, tricks and insights into how to be more creative, innovative and personally effective.

Image Credit: Pexels

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Top 10 Human-Centered Change & Innovation Articles of November 2023

Top 10 Human-Centered Change & Innovation Articles of November 2023Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are November’s ten most popular innovation posts:

  1. A Quantum Computing Primer — by Greg Satell
  2. Disagreements Can Be a Good Thing — by Mike Shipulski
  3. What’s Your Mindset — by Dennis Stauffer
  4. We Are Killing Innovation in America — by Greg Satell
  5. Two Kinds of Possible — by Dennis Stauffer
  6. Eddie Van Halen, Simultaneous Innovation and the AI Regulation Conundrum — by Pete Foley
  7. Five Secrets to Being a Great Team Player — by David Burkus
  8. Be Clear on What You Want — by Mike Shipulski
  9. Overcoming Your Assumptions — by Dennis Stauffer
  10. Four Things All Leaders Must Know About Digital Transformation — by Greg Satell

BONUS – Here are five more strong articles published in October that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last three years:

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Competing Successfully in an Ecosystem World

Competing Successfully in an Ecosystem World

GUEST POST from Greg Satell

In 1980, a young Harvard Business School professor named Michael Porter published Competitive Strategy, which drove thinking on the subject for the next 30 years. In essence, he argued that you build sustainable competitive advantage by maximizing bargaining power throughout a value chain.

Yet more recently, that kind of single firm level analysis has been called into question and leaders have learned to look more broadly at ecosystems. In fact, a recent report by Accenture Strategy found that because business models are being constantly disrupted, ecosystems have become a “cornerstone” of future growth.”

While value chains are strictly defined by “primary activities” such as “inbound logistics” and “support activities” like technology, ecosystems have mostly been a nebulous term. Clearly that’s not good enough. If we are going to compete in an ecosystem-driven world, we need to understand how they function and how we can leverage them to drive a business forward.

What Is An Ecosystem?

Ecosystem is a term that gets thrown around quite a bit, but people never seem to define what one is. All too often, it alludes to some indescribable ether that surrounds an enterprise. When you can’t define how an action would impact a customer or partner, you simply invoke “the ecosystem” and that’s supposed to make it all make sense.

Yet it’s important that we define terms that have meaning, because if we don’t they just become a catchall for things that we can’t describe. That’s a problem. As Wittgenstein pointed out long ago, if we can’t define something we don’t really understand it and if we don’t understand something we can’t hope to manage it very well.

Ecosystems are best understood as networks of networks and that tells us a lot. In fact, there is a whole science of networks to guide us. What’s most important about networks is that they are driven by links not nodes, so the most important network activity is connection. Networks are dynamic, always evolving, not static.

That’s where focusing on value chains runs into problems. Maximizing bargaining power within a value chain almost compels us to see things as a static, “winner take all” type of challenge in which you play one partner off against another. When you see things as an ecosystem, however, there is clear value in investing in connections and building up the nodes around you to improve your position.

It Is Ecosystems, Not Inventions That Drive The Future

We tend to think of history as a series of “great men” driving events. So electricity conjures up visions of Edison and his light bulb and automobiles remind us of Henry Ford creating the Model T. Yet the truth is that the impact from those inventions didn’t come till decades after those men brought those inventions to life.

In both cases, it was secondary inventions that drove the impact. Electricity allowed businesses to redesign factories to optimize workflow and drive productivity. Home appliances replaced backbreaking work and freed up energy for other tasks. Roads and gas stations revolutionized product distribution and led to the modern retail industry.

Computers followed a similar path. Digital technology had been around for decades when IBM launched the PC in 1981, yet it wouldn’t be till the late 90s that we first started to see an impact on productivity. The truth is that computers don’t do much by themselves. Applications need to be designed and people need to figure out how to put them to good use.

Notice that it’s impossible to point to any one thing that tipped the scale, because what drove impact was an ecosystem of connections between partners, suppliers and customers who needed to learn how to collaborate effectively. That has far less to do with technology than it does with forging meaningful human relationships and it takes time.

Power Today Lies In The Center Of Ecosystems, Rather Than At The Top Of Hierarchies

Traditionally we’ve seen the world as driven by hierarchies. Kings and queens ruled the world through aristocracies that carried out their orders. Corporate CEO’s outlined strategies that underlings would have to execute. Discipline was enforced through a system of punishments and rewards.

In a hierarchy driven world, you progress by climbing your way to the top. So you do your best to drive the performance of those under you to impress those above you. Success is determined by how high you rise. You learn to put great emphasis on signals that you have made it, such as the title on your business card and the size and location of your office.

In an ecosystem driven world, however, power does not lie at the top of hierarchies, but emanates from the center of networks. So an office on the executive floor may, in fact, diminish your ability to shape events if it leads to disconnection. At the same time, being seen as approachable, rather than high status, may enhance your power.

Here’s where Porter’s ideas about value chains can get you into trouble. If you are constantly trying to maximize your bargaining power, you are likely to weaken connections and find yourself at the periphery, rather than at the center, of networks. In an ecosystem driven world, displaying your power can often serve to undermine it.

You Move To The Center By Connecting Out

As I explain in my book Cascades, the best way move to the center of networks is by connecting out. At first, that may seem counterintuitive because it seems simpler to identify a central hub and connect in. Yet those nodes, by definition, already have a lot of links and your connection is less likely to be meaningful.

Once you understand that networks are dynamic and evolving, it becomes clear that a better strategy is to identify emergent nodes and connect to them early on. As the network grows, the center shifts and you are more likely to improve your position. In an ecosystem world, the best strategy is to widen and deepen connections throughout the network.

AnnaLee Saxenian gives an apt description of how this works in Regional Advantage, where she tells the story of how Boston’s “Technology Highway” lost relevance and Silicon Valley moved to the center of the technology universe. The Boston-based companies saw things in terms of value chains and focused on vertical integration to maximize their bargaining power. The Silicon Valley upstarts, on the other hand, saw an ecosystem and thrived on connection.

Today, of course, technology has exponentially increased our ability to make connections. However, what is crucial to understand is that relationships are essentially a very human activity. You don’t build them through gadgets or algorithms, but my investing your most valuable resource — yourself.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Pixabay

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Mental Orgasm – The Joy of Discovery

Mental Orgasm - The Joy of Discovery

GUEST POST from Dennis Stauffer

Recall a time when you made some discovery or figured something out for yourself. No one told you the answer. You didn’t look it up on your phone. You got there on your own. It might have been something recent, or you may have to go back, maybe even to your early childhood, to recall that moment of discovery. That thrill you felt. That excitement! It’s such pure joy that some researchers have described it as a mental orgasm.

Babies often experience this as they first learn about the world. It’s a moment scientists live for. A feeling that even the most jaded businessperson takes delight in. When something just works—and you made it happen. You solved the puzzle.

It was a frequent experience when we were babies, with a brain constantly driven to discover how the world worked. But it’s something we experience far less often as adults. From the moment you started school, you were gradually pulled away from personal discovery, and instead pushed to memorize things someone else discovered. Like how to solve a math problem, spell a word, or learn the periodic table. Those things are important, but not nearly as much fun as figuring things out for yourself.

So instead of moments of discovery, you’ve probably become conditioned to take pride in what you know. And that very pride can become an obstacle to making new discoveries. The more we identify with our knowledge, the more we want to defend it, making us resistant to understanding the world in new ways. It shouldn’t be hard to see how that might interfere with your ability to innovate, or adapt to changes in your life. The challenge we so often face is not just coming up with new ideas. It’s letting go of the ones we already have.

Innovators, and those who are most effective generally, are open to discovery. Instead of looking for reinforcement of what they already know, they seek experiences that will challenge their beliefs, always being open to revising those beliefs—open to discovery. An innovator mindset frees you to move beyond what you already know, to unleash your own brilliance. Giving you the mental agility needed to make discoveries again—and experience the kind of mental orgasm that creates.

Here is a video version of this post:

Image Credit: Pixabay

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