Category Archives: Innovation

Innovation the Star of the 2024 NBA All-Star Game

Innovation the Star of the 2024 NBA All-Star Game

by Braden Kelley

Eight years ago, back in 2016, I wrote an article titled What April Fool’s Day Teaches Us About Innovation about an April Fool’s prank played my alma mater, the University of Oregon involving an announcement that football games at Autzen Stadium would no longer played on artificial turf, but would be played on a giant digital screen instead. Here is the video:

It seemed preposterous at the time (2016) during the era of the technologically ancient Apple iPhone 7 and Samsung Galaxy S7 when the average LCD TV size according to Statista was only 43 inches.

Fast forward to February 16, 2024 and NBA All-Star Weekend in Indianapolis, Indiana and we saw the first ever basketball game of note held on a glass basketball court. But isn’t glass slippery when wet? Yes, but so is a heavily lacquered hardwood court – believe me I know from repeated spills during pickup basketball games. To help give it the traction of a hardwood court they’ve engineered thousands (or maybe millions) of tiny raised dots onto the glass surface.

Sports are always experimenting with various technologies, some of which don’t work out (like the tail following the puck on hockey broadcasts), and others which are executed so well that they enhance the viewing experience (first down yardage line in American football) or that most people don’t even know that they exist (advertisements projected onto the court in basketball television broadcasts that aren’t actually on the court but look as if they are).

So, how has this 2016 April Fool’s prank visualization evolved into a 2024 reality? What does it look like? Here is a video that will give you a sense of its capabilities:

First let me say this a pretty incredible technology that has definitely added to the excitement of this year’s NBA All-Star Weekend, but second I must also say that I would NEVER want to watch a regular NBA, college or international game played on a court like this because for me, sporting events are a time to unplug from technology, not be over-stimulated by it. But, for a special event like NBA All-Star Game Weekend or maybe the Harlem Globetrotters I think it makes sense.

How does this court make the leap from invention to innovation you might ask?

How does this court not find itself in the digital trash can next to the tail on the hockey puck?

The short answer is that scores well on my Innovation is All About Value framework. It creates value by adding value to the contest (skills challenge, celebrity all-star game), translates that value very quickly because it’s all visual, and the barriers to value access are non-existent for all but the visually impaired.

The court allowed the NBA to hold different games with different rules and lines on the same court without changing courts or making physical modifications. For example, the celebrity all-star game had a four point line (sponsored by Frito Lay) and at times the three point and four point lines even were actively moving. There was also a micro competition in game where three people ran to stars that appeared on the floor and shot and when they made a shot there a new star appeared and you could see over time which side of the court was winning because you could see which side had more stars. There was another moment where for a limited time the coaches faces appeared on the court and six points were awarded for each shot made from that spot. The dynamic nature of the game meant that you almost didn’t know what might come next – which was kind of exciting.

The integration of the court into the competition occurring upon it is what helps this technology make the leap from invention to innovation. But again, for me, only in special use cases like an All-Star game, an entertainment-based event or skills competition, but NOT for a pure competition use case where in my mind it distracts from the sport.

Here is a video of the skills challenge relay race – notice that the floor shows the player which way to go, but despite that Tyrese Maxey still goes the wrong way and has to double back. 😉

Then in the skills challenge passing team event the floor showed players where to stand and how many points had been scored at each of three targets. Again, it felt like part of the event and it allows the court to be instantly and uniquely re-configured.

And here are video highlights of the celebrity all-star game where you can see some of what I mentioned above:

So, what do you think? Innovation or not?

Image credit: NBA.com

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This One Word Will Transform Your Approach to Innovation

This One Word Will Transform Your Approach to Innovation

GUEST POST from Robyn Bolton

Have you heard any of these sentences recently?

“We don’t have time”

“Our people don’t have the skills”

“We don’t have the budget”

“That’s not what we do”

I hear them all the time.  

Sometimes they’re said when a company is starting to invest in building their innovation capabilities, sometimes during one-on-one stakeholder interviews when people feel freer to share their honest opinions, and sometimes well after investments are made.

Every single time, they are the beginning of the end for innovation.

But one word that can change that.

“We don’t have time – yet.”

“Our people don’t have the skills – yet.”

“We don’t have the budget – yet.”

“That’s not what we do – yet.”

Yet.

Yet creates space for change.  It acknowledges that you’re in the middle of a journey, not the end.  It encourages conversation.

“We don’t have time – yet.”

“OK, I know the team is busy and that what they’re working on is important.  Let’s look at what people are working on and see if there are things we can delay or stop to create room for this.”

“Our people don’t have the skills – yet.”

“Understand, we’re all building new skills when it comes to innovation.  Good news, skills can be learned.  Let’s discuss what we need to teach people and the best way to do that.”

“We don’t have the budget – yet.”

“I get it.  Things are tight. We know this is a priority so let’s look at the budget and see if there’s a way to free up some cash.  If there’s not, then we’ll go back to leadership and ask for guidance.”

“That’s not what we do – yet.”

“I know.  Remember, we’re not doing this on a whim, we’re doing this because (fill in reason), and we have a right to do it because of (fill in past success, current strength, or competitive advantage.”

You need to introduce the YET.

It is very rare for people to add “yet” to their statements.  But you can.

When someone utters an innovation-killing statement, respond with “Yet.” Maybe smile mischievously and then repeat their statement with “yet” added to the end.

After all, you’re not disagreeing with them. You’re simply qualifying what they’re saying.  Their statement is true now, but that doesn’t mean it will be true forever.  By restating their assertion and adding “yet,” you’re inviting them to be part of the change, to take an active role in creating the new future state.

There’s a tremendous amount of research about the massive impact of this little word.  It helps underperforming students overachieve and is closely associated with Dr. Carol Dweck’s research into fixed and learning mindsets.

The bottom line is that “YET” works.

Put YET to work for you, your organization, and your efforts to innovate and grow.

Image credit: Unsplash

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Science Fiction Becomes Innovation Reality This Way

Science Fiction Becomes Innovation Reality This Way

GUEST POST from Greg Satell

When H.G. Wells was born in 1866, there was no electricity or cars or even indoor plumbing. Still, his active imagination conjured up a world of time machines, space travel and genetic engineering. This was all completely fantasy, but his books foresaw many modern inventions, such as email, lasers and nuclear energy.

It’s no accident that people who invent the future are often fans of science fiction. In fact, in Leading Transformation, the former head of Lowe’s innovation lab explains how he hired science fiction writers to help inspire the company to leverage virtual reality and build a new future for the company.

To create anything truly new and different, you often need to discard the constraints of the present. Yet that comes with a problem. How do you transform fantasy into something real and useful? What makes great innovators truly different is how they combine imagination with practical problem solving in order to bring even the wildest pipe dreams into reality.

How A “Memex” Machine Became The Internet

“Consider a future device for individual use,” Vannevar Bush wrote in The Atlantic in 1945, “which is a sort of mechanized private file and library. It needs a name, and, to coin one at random, “memex” will do. A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility. It is an enlarged intimate supplement to his memory.”

It was an unlikely vision for the time. The first computers were just being developed then and were themselves somewhat impractical devices, which is why Bush imagined that the memex would be based on microfilm. Yet Bush was no inveterate dreamer, but in many ways the architect of America’s path to scientific dominance and people took him seriously.

One of those was a young radar technician stationed in the Philippines named Douglas Engelbart, who would return to school to study electrical engineering. It was that expertise, along with Bush’s vision that led him to think of computers, still primitive at the time, as machines that could do more than merely calculate, but “augment the human intellect.”

Engelbart would showcase these ideas in what is now known as the Mother of All Demos in 1968 and Xerox began an enormous research project to bring his vision to market. By 1973, a functional prototype, called the Alto, was built and, a decade later, a young entrepreneur named Steve Jobs would use it to create the Macintosh. The world was never the same.

When Feynman Found “Plenty Of Room At The Bottom”

Richard Feynman was an usual scientist, known almost as much for his pranks as he was for his discoveries. So few were probably surprised at the unconventional title for his address the American Physical Society a few days after Christmas in 1959, There’s Plenty of Room at the Bottom. It was something they had come to expect from the young genius.

Feynman’s fantasy was not unlike Bush’s, except that it was more ambitious. While Bush imagined putting all the world’s knowledge on microfilm, Feynman imagined writing the entire 24 volumes of the Encyclopedia Britannica on the head of a pin. It was just the sort of impractical idea that usually gets people thrown out on physics conferences, not given the stage.

Yet Feynman immediately got down to brass tacks. He proposed using an electron microscope as a writing tool, much like a cathode ray oscilloscope projected images on television screens at the time. He then asked if we can write things on a microscopic scale, why not build things too? Again, he identified problems and proposed potential solutions.

That day, almost single handedly, Feynman invented the field of nanotechnology, although that term wasn’t coined until 1974. These days we use it to etch transistors in silicon wafers to make computer chips and create advanced materials for things like solar cells. Yet the truth is that even now, 60 years after that initial talk, we are just beginning to scratch the surface of Feynman’s vision.

Spacemen, Cavemen And Small World Networks

In the late 1990s, a young graduate student named Duncan Watts was struggling to understand an obscure phenomenon that had baffled scientists for centuries. Known as coupled oscillation, it was a mysterious force that allowed a disparate group of entities, like pacemaker cells in the human heart or certain species of crickets in a forest, to synchronize their behavior.

Nobody could figure out how it worked. Was there some kind of leadership structure with “conductor” leading the synchronized orchestra? Or maybe some complicated web of influence? As much as he pored through the research, tracked the chirping of crickets and tested out formulas to describe behavior, he was still baffled.

What helped break the logjam was two books by the science fiction writer Isaac Asimov. In the first, Caves of Steel, people lived in underground caves and, while everybody was connected to everybody else in their cave, they knew no one outside of it. In the second, The Naked Sun, space colonists led a hermit-like existence, linked to others only through long-range connections.

Neither of these, of course, told Watts anything about pacemaker cells or crickets, but it allowed him to reframe the problem as one of relationships. By imagining the two extremes of the cave people and the space colonists, he was able to come up with a model of relationships that led to the mass synchronization of coupled oscillators.

The paper he would write based on his fantasy-inspired formulas would prove to be a landmark. It would establish an exciting new field of small world networks and lead to a new era in the science of how things are connected, helping to transform fields as diverse as neuroscience, epidemiology and computer science.

Venturing Into The Visceral Abstract

Today we are beset with an dizzying array of problems in the world, climate change, income inequality and the rise of authoritarianism being just a few. Successful businesses face extinction by a seemingly endless wave of disruptions ranging from new technologies to new social phenomenons. It can all seem overwhelming.

It’s important to view these problems from a practical perspective. Each needs to be solved within constraints of economics, politics and competitive pressures. Yet it is also important to realize that the solutions to tough problems will rarely be found in the realm of our experiences. If a solution to any of these problems already existed, they wouldn’t be such tough problems.

The only path through that troubling tautology is fantasy. Once we have exhausted the realm of the possible, we often must venture into the realm of the impossible to see a new direction. A memex machine, a world with “plenty of room at the bottom,” cave societies and space colonies were all ideas of little practical import at the time they were conceived, but benefit us today in important ways through the discoveries they inspired.

We need to accept that we live in a world of the visceral abstract, where the technologies we use to solve the practical problems in our lives are all based on what were once considered utterly impractical ideas. That means to make an impact on reality, we often need to indulge ourselves with fantasy, identify a different path to travel and then begin the work anew.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credit: Pexels

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Will Innovation Management Leverage AI in the Future?

Will Innovation Management Leverage AI in the Future?

GUEST POST from Jesse Nieminen

What role can AI play in innovation management, and how can we unlock its true potential?

Unless you’ve been living under a rock, you’ve probably heard a thing or two about AI in the last year. The launch of ChatGPT has supercharged the hype around AI, and now we’re seeing dramatic progress at a pace unlike anything that’s come before.

For those of us into innovation, it’s an exciting time.

Much has been said about the topic at large so I won’t go over the details here. At HYPE, what we’re most excited about is what AI can do for innovation management specifically. We’ve had AI capabilities for years, and have been looking into the topic at large for quite some time.

Here, I share HYPE’s current thinking and answer some key questions:

  • What can AI do for innovation management?
  • What are some common use cases?
  • How can you operationalize AI’s use in innovation management?

The Current State of Innovation Management

Before we answer those questions, let’s review how most organizations carry out innovation management.

We’re all familiar with the innovation funnel.

Hype Innovation Image 1

To oversimplify, you gather ideas, review them, and then select the best ones to move forward to the pilot stage and eventual implementation. After each phase, poor ideas get weeded out.

It’s systematic, it’s conceptually simple, and investment is tiered so that you don’t spend too much time or money before an idea has shown its potential. What’s not to love?

Well, there are a few key challenges: the process is slow, linear, and is usually biased due to the evaluation criteria selected for the gates or decision points (if you use a Phase-Gate model).

Each of these challenges can be mitigated with smart adaptations of the process, but the funnel has another fundamental limitation: It’s generally built for a world where innovation requires significant capital expenditures and vast amounts of proprietary information.

But, regardless of your industry, that just isn’t the case anymore. Now most information is freely available, and technology has come a long way, in many cases because of AI. For example, pharmaceutical companies use AI to accelerate drug discovery while infrastructure and manufacturing companies use advanced simulation techniques, digital twins (virtual replicas of physical objects or systems), and rapid prototyping.

It’s now possible to innovate, test, and validate ideas faster than ever with minimal investment. With the right guidance, these tasks don’t have to be limited to innovation experts like you anymore. That can be an intimidating thought, but it’s also an empowering one. Soon, thanks to AI, you’ll be able to scale your expertise and make an impact significantly bigger than before.

For more than 20 years, we’ve been helping our customers succeed in this era of systematic innovation management. Today, countless organizations manage trends at scale, collect insights and ideas from a wide and diverse audience, and then manage that funnel highly effectively.

Yet, despite, or maybe because of this, more and more seemingly well-run organizations are struggling to keep up and adapt to the future.

What gives?

Some say that innovation is decelerating. Research reveals that as technology gets more complex, coming up with the next big scientific breakthrough is likely to require more and more investment, which makes intuitive sense. This type of research is actually about invention, not innovation per se.

Innovation is using those inventions to drive measurable value. The economic impact of these inventions has always come and gone in waves, as highlighted in ARK Investment’s research, illustrated below.

Throughout history, significant inventions have created platforms that enable dramatic progress through their practical application or, in other words, through innovation. ARK firmly believes that we’re on the precipice of another such wave and one that is likely to be bigger than any that has come before. AI is probably the most important of these platforms, but it’s not the only one.

Mckinsey Hype Innovation Image 2

Whether that will be the case remains to be seen, but regardless, the economic impact of innovation typically derives from the creative combination of existing “building blocks,” be they technologies, processes, or experiences.

Famously, the more such building blocks, or types of innovation, you combine to solve a specific pain point or challenge holistically, the more successful you’re likely to be. Thanks to more and more information and technology becoming free or highly affordable worldwide, change has accelerated rapidly in most industries.

That’s why, despite the evident deceleration of scientific progress in many industries, companies have to fight harder to stay relevant and change dramatically more quickly, as evidenced by the average tenure of S&P500 companies dropping like a stone.

Hype Innovation 3

In most industries, sustainable competitive advantages are a thing of the past. Now, it’s all about strategically planning for, as well as adapting to, change. This is what’s known as transient advantage, and it’s already a reality for most organizations.

How Innovation Management Needs to Change

In this landscape, the traditional innovation funnel isn’t cutting it anymore. Organizations can’t just focus on research and then turn that into new products and expect to do well.

To be clear, that doesn’t mean that the funnel no longer works, just that managing it well is no longer enough. It’s now table stakes. With that approach, innovating better than the next company is getting harder and more expensive.

When we look at our most successful customers and the most successful companies in the world in general, they have several things in common:

  • They have significantly faster cycle times than the competition at every step of the innovation process, i.e., they simply move faster.
  • For them, innovation is not a team, department, or process. It’s an activity the entire organization undertakes.
  • As such, they innovate everything, not just their products but also processes, experiences, business models, and more.

When you put these together, the pace of innovation leaves the competition in the dust.

How can you then maximize the pace of innovation at your organization? In a nutshell, it comes down to having:

  • A well-structured and streamlined set of processes for different kinds of innovation;
  • Appropriate tools, techniques, capabilities, and structures to support each of these processes;
  • A strategy and culture that values innovation;
  • A network of partners to accelerate learning and progress.

With these components in place, you’ll empower most people in the organization to deliver innovation, not just come up with ideas, and that makes all the difference in the world.

Hype Innovation 4

What Role Does AI Play in Innovation Management?

In the last couple of years, we’ve seen massive advancements not just in the quality of AI models and tools, but especially in the affordability and ease of their application. What used to be feasible for just a handful of the biggest and wealthiest companies out there is now quickly commoditizing. Generative AI, which has attracted most of the buzz, is merely the tip of the iceberg.

In just a few years, AI is likely to play a transformative role in the products and services most organizations provide.

For innovation managers too, AI will have dramatic and widely applicable benefits by speeding up and improving the way you work and innovate.

Let’s dive a bit deeper.

AI as an Accelerator

At HYPE, because we believe that using AI as a tool is something every organization that wants to innovate needs to do, we’ve been focusing on applying it to innovation management for some time. For example, we’ve identified and built a plethora of use cases where AI can be helpful, and it’s not just about generative AI. Other types of models and approaches still have their place as well.

There are too many use cases to cover here in detail, but we generally view AI’s use as falling into three buckets:

  • Augmenting: AI can augment human creativity, uncover new perspectives, kickstart work, help alleviate some of the inevitable biases, and make top-notch coaching available for everyone.
  • Assisting: AI-powered tools can assist innovators in research and ideation, summarize large amounts of information quickly, provide feedback, and help find, analyze, and make the most of vast quantities of structured or unstructured information.
  • Automating: AI can automate both routine and challenging work, to improve the speed and efficiency at which you can operate and save time so that you can focus on the value-added tasks at the heart of innovation.

In a nutshell, with the right AI tools, you can move faster, make smarter decisions, and operate more efficiently across virtually every part of the innovation management process.

While effective on their own, it’s only by putting the “three As” together and operationalizing them across the organization that you can unlock the full power of AI and take your innovation work to the next level.

In a nutshell, with the right AI tools, you can move faster, make smarter decisions, and operate more efficiently across virtually every part of the innovation management process.

While effective on their own, it’s only by putting the “three As” together and operationalizing them across the organization that you can unlock the full power of AI and take your innovation work to the next level.

Putting AI Into Practice

So, what’s the key to success with AI?

At HYPE, we think the key is understanding that AI is not just one “big thing.” It’s a versatile and powerful enabling technology that has become considerably cheaper and will likely continue on the same trajectory.

There are significant opportunities for using AI to deliver more value for customers, but organizations need the right data and talent to maximize the opportunities and to enable AI to support how their business operates, not least in the field of innovation management. It’s essential to find the right ways to apply AI to specific business needs; just asking everybody to use ChatGPT won’t cut it.

The anecdotal evidence we’re hearing highlights that learning to use a plethora of different AI tools and operationalizing these across an organization can often become challenging, time-consuming, and expensive.

To overcome these issues, there’s a real benefit in finding ways to operationalize AI as a part of the tools and processes you already use. And that’s where we believe The HYPE Suite with its built-in AI capabilities can make a big difference for our customers.

Final Thoughts

At the start of this article, we asked “Is AI the future of innovation management?”

In short, we think the answer is yes. But the question misses the real point.

Almost everyone is already using AI in at least some way, and over time, it will be everywhere. As an enabling technology, it’s a bit like computers or the Internet: Sure, you can innovate without them, but if everyone else uses them and you don’t, you’ll be slower and end up with a worse outcome.

The real question is how well you use and operationalize AI to support your innovation ambitions, whatever they may be. Using AI in combination with the right tools and processes, you can innovate better and faster than the competition.

At HYPE, we have many AI features in our development roadmap that will complement the software solutions we already have in place. Please reach out to us if you’d like to get an early sneak peek into what’s coming up!

Originally published at https://www.hypeinnovation.com.

Image credits: Pixabay, Hype, McKinsey

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3 Steps to Building a Psychologically Safe Environment

or The No-Cost, No-Hug Secret to Smarter Teams

3 Steps to Building a Psychologically Safe Environment

GUEST POST from Robyn Bolton

Welcome to the exciting conclusion of “Everything You Ever Wanted to Know About Psychological Safety but Were Afraid to Ask.”

Our generous expert, Alla Weinberg, CEO and Culture designer at Spoke & Wheel, has been patiently leading us beyond and through the buzzy frothiness that we (I) usually associate with Psychological Safety and into the deeply powerful and absolutely essential core elements.

In Part 1, we learned that psychological safety is more neuroscience than psychology (and required to be your smartest self).

In Part 2, we learned the first step to creating safety (and why corporate mandates are antithetical to the goal). 

Today, we’re going where we need but don’t want to go – how to create a psychologically safe environment so everyone can thrive.


If Step 1 in creating Psychological Safety is verbalizing your emotions and understanding others’ emotions, I’m hoping Step 2 is easier.

Step two is relational intelligence.

There are three intelligences: emotional, relational, and systems

Relational intelligence is about understanding how to connect with different people, being aware when disconnection happens, and then acknowledging and repairing it. That last part is the most important because, without repair, there’s no safety.

Are you saying that saying, “I’m sorry” is essential to building psychological safety?  Because I would much rather ignore the issues and move on.  Or, better yet, pretend it never happened.

Nice try.  But you know as well as I do that people are messy, and when we come together, there’s tension and conflict, and someone will get hurt or make mistakes. It’s normal.  It’s okay as long as you know how to recover, repair, and heal.

The issue isn’t the conflict but how we handle it and whether we can repair it. I have a diagram of a relationship, which is a circle of connection, disconnection, and repair. We go around this circle just like breathing is inhaling and exhaling.  Relating, connecting, disconnecting, and repairing is what a relationship is.

OK, step 2 is relational intelligence which requires repairing relationships, so how do I do that?  Bonus points if I don’t have to admit to being wrong.

Not only do you have to admit that, but you also need to take responsibility for your impact, not just your intentions. Intentions are great, but without action, they don’t mean much.

When apologizing, we tend to try to explain ourselves.  For example, we say, “I didn’t say anything in that meeting, and I’m sorry, but that wasn’t my intention, and I wanted to, but I had my own issue.” Instead, we should say, “I didn’t say anything in that meeting, and I’m sorry.”

When you apologize, don’t say “but.” To repair a relationship, you must take responsibility for your actions and their impact. Saying “but” negates all of that.

(head now on the desk because this is a lot to take in): I’m afraid to ask what Step 3 is, but I will practice verbalizing my feelings and ask anyway.  What’s Step 3?

You’re doing great.  This is a lot, and it’s ok that you feel overwhelmed.

Step 3 is systems intelligence, which focuses on the relationships within an organization that gives rise to its culture. Systems thinking is about understanding how structures, policies, processes, and relationships interact to create a greater whole,

Systems thinking!  We’re getting back to left-brained stuff now.  I’m feeling better.

Yes, and since connection is core to psychological safety, systems thinking tells us that we must fundamentally rethink how people work together by centering connection.

How do we do that?

We must reinvent, innovate, and rethink how we work together.

Lack of safety leads to power struggles, walls, and departmental rivalries, creating divisions and “othering.”

Hierarchy doesn’t align with connection, but shared leadership does. Hierarchy erodes trust because you need manager approvals, beg for budgets, or are told to prove your worth to get a seat at the table.

Silos are another problem because they lead to turf wars and people making decisions to protect themselves or their team rather than do what’s best for the greater good. 

Look, I love challenging the status quo, but you’re suggesting that we burn it all to the ground and start over.

(Laughing) I don’t lead with that.  When I work with organizations, I start with meetings.

Most meetings focus on work topics like status, decisions, and updates. But where are the meetings where we discuss emotions, share personal stories, and express hurt feelings? Everything shifts when we center connection.

Isn’t that called therapy?

Organizations value information, right?  Emotions are information.

Emotions reside in our bodies, but in many organizations, the focus is on the intellect.  It’s as if the head is the only important part, and the body is merely a vessel to transport the head from meeting to meeting.

And that brings us full circle to why psychological safety is mostly neuroscience.  Our body houses our nervous system, where we feel safety or the lack thereof. So, when people talk about bringing their whole selves to work, I mean our entire body, not just the intellect. Our bodies contain wisdom and information that we often overlook and undervalue, yet this is where the crucial information resides to create psychological safety.

We don’t think of emotions as information.  We think of them as signs of weakness, and you can’t be weak and successful.

It’s a lot of fear because how we’ve worked for the last 50 years gave us an illusion of certainty.  Acknowledging that there is no certainty and that we’re in entirely uncharted territory is scary, and there’s a fear that everything will fall apart. We think the business won’t survive if we do it the other way.

I respect that fear. It’s okay to be afraid. But if we acknowledge that all of this comes from fear, we will be open to new ideas or thoughts. For organizations that want to innovate, they must change how they work. You can’t keep doing the same thing and expect different results. You need to innovate your approach to work.

Thank you so much for all of this.  You’ve shared so much.  Some of it was hard to hear, but I think that’s also a sign that it’s important to hear.  Any last words of advice?

Give yourself and others permission to be human beings again.  Not robots or cogs, not human resources, but to be human beings. That includes our bodies, our emotions, our messiness, and our relationships with each other.


If you would like to learn more about Alla and her work, please visit her firm’s website, www.spokeandwheel.coand definitely download a FREE digital copy of her book, A Culture of Safety: Building a Work Environment Where People Can Think, Collaborate, and Innovate

Image Credit: Pexels

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The Event That Made Einstein an Icon

The Event That Made Einstein an Icon

GUEST POST from Greg Satell

On April 3rd, 1921, a handful of journalists went to interview a relatively unknown scientist named Albert Einstein. When they arrived to meet his ship they found a crowd of thousands waiting for him, screaming with adulation. Surprised at his popularity, and charmed by his genial personality, the story of Einstein’s arrival made the front page in major newspapers.

It was all a bit of a mistake. The people in the crowd weren’t there to see Einstein, but Chaim Weizmann, the popular Zionist leader that Einstein was traveling with. Nevertheless, that’s how Einstein gained his iconic status. In a way, Einstein didn’t get famous because of relativity, relativity got famous because of Einstein.

This, of course, in no way lessens Einstein’s accomplishments, which were considerable. Yet as Albert-László Barabási, another highly accomplished scientist, explains in The Formula, there is a big difference between success and accomplishment. The truth is that success isn’t what you think it is but, with talent, persistence and some luck, anyone can achieve it.

There Is Virtually No Limit To Success, But There Is To Accomplishment

Einstein was, without a doubt, one of the great scientific minds in history. Yet the first half of the 20th century was a golden age for physics, with many great minds. Niels Bohr, Einstein’s sparring partner at the famous Bohr–Einstein debates (which Bohr is widely considered to have won) was at least as prominent. Yet Einstein towers over all of them.

It’s not just physicists, either. Why is it that Einstein has become a household name and not, say, Watson and Crick, who discovered the structure of DNA, an accomplishment at least as important as relativity? Even less known is Paul Erdős, the most prolific mathematician since Euler in the 18th century, who had an outrageous personality to boot?

For that matter, consider Richard Feynman, who is probably the second most famous physicist of the 20th century. He was, by all accounts, a man of great accomplishment and charisma. However, his fame is probably more due to his performance on TV following the Space Shuttle Challenger disaster than for his theory of quantum electrodynamics.

There are many great golfers, but only one Tiger Woods, just as there are many great basketball players, but only one Lebron James. The truth is that individual human accomplishment is bounded, but success isn’t. Tiger Woods can’t possibly hit every shot perfectly any more than Lebron James can score every point. But chances are, both will outshine all others in the public consciousness, which will drive their fame and fortune.

What’s probably most interesting about Einstein’s fame is that it grew substantially even as he ceased to be a productive scientist, long after he had become, as Robert Oppenheimer put it, “a landmark, not a beacon.”

Success Relies On Networks

Let’s try and deconstruct what happened after Einstein’s arrival in the United States. The day after thousands came to greet Weizmann and the reporters mistakenly assumed that they were there for Einstein, he appeared on the front pages of major newspapers like The New York Times and the Washington Post. For many readers, it may have been the first time they had heard of any physicist.

As I noted above, this period was something of a heyday for physics, with the basic principles of quantum mechanics first becoming established, so it was a topic that was increasingly discussed. Few could understand the details, but many remembered the genius with the crazy white hair they saw in the newspaper. When the subject of physics came up, people would discuss Einstein, which spread his name further.

Barabási himself established this principle of preferential attachment in networks, also known as the “rich get richer” phenomenon or the Matthew effect. When a particular node gains more connections than its rivals, it tends to gain future connections at a faster rate. Even a slight change in early performance leads to a major advantage going forward.

In his book, Barabási details how this principle applies to things as diverse as petitions on Change.org, projects on Kickstarter and books on Amazon. It also applies to websites on the Internet, computers in a network and proteins in our bodies. Look at any connected system and you’ll see preferential attachment at work.

Small Groups, Loosely Connected

The civil rights movement will always be associated with Martin Luther King Jr., but he was far from a solitary figure. In fact, he was just one of the Big Six of civil rights. Yet few today speak of the others. The only one besides King still relatively famous today is John Lewis and that’s largely because of his present role as a US congressman.

Each of these men were not solitary figures either, but leaders of their own organizations, such as the NAACP, The National Urban League and CORE and these, in turn, had hundreds of local chapters. It was King’s connection to all of these that made him the historic icon we know today, because it was all of those small groups, loosely connected, that made up the movement.

In my book, Cascades, I explain how many movements fail to bring change about by trying to emulate events like the March on Washington without first building small groups, loosely connected, but united by a shared purpose. It is those, far more than any charismatic personality or inspirational speech, that makes a movement powerful.

It also helps explain something about Einstein’s iconic status. He was on the ship with Weizman not as a physicist, but as a Zionist activist and that dual status connected him to two separate networks of loosely connected small groups, which enhanced his prestige. So it is quite possible, if not probable, that we equate Einstein with genius today and not, say, Bohr, because of his political activity as much as for his scientific talent.

Randomness Rewards Persistence

None of this should be taken to mean that Einstein could have become a legendary icon if he hadn’t made truly landmark discoveries. It was the combination of his prominence in the scientific community with the happy accident of Weizmann’s adoring crowds being mistaken for his own, that made him a historic figure.

Still, we can imagine an alternate universe in which Einstein becomes just as famous. He was, for example, enormously quotable and very politically active. (He was, at one time, offered the presidency in Israel). So it is completely possible that some other event, combined with his very real accomplishments, would have catapulted him to fame. There is always an element of luck and randomness in every success.

Yet Einstein’s story tells us some very important things about what makes a great success. It is not, as many tell us, simply a matter of working hard to achieve something because human performance is, as noted above, bounded. You can be better than others, but not that much better. At the same time, it takes more than just luck. It is a combination of both and we can do much to increase our chances of benefiting from them.

Einstein was incredibly persistent, working for ten years on special relativity and another ten for general relativity. He was also a great connector, always working to collaborate with other scientists as well as political figures like Weizmann and even little girls needing help with their math homework. That’s what allowed him to benefit from loosely connected small groups.

Perhaps most importantly, these principles of persistence and connection are ones that any of us can apply. We might not all be Einsteins, but with a little luck, we just might make it someday.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credit: misterinnovation.com

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Resistance to Innovation – What if electric cars came first?

Resistance to Innovation - What if electric cars came first?

GUEST POST from Dennis Stauffer

In his acclaimed book the The Diffusion of Innovations—the most-cited work in all the social sciences—Everett Rogers explained how innovations frequently meet resistance. Resistance that isn’t always rational. How all-too-often we’re willing to accept the status quo despite its flaws and reject new options despite their benefits.

We’re seeing exactly this phenomenon with electric vehicles. Demand from what Rogers identified as the early adopters—wealthy buyers who can pay a premium for the newest technology—has largely been met. The challenge now is to reach a broader market of buyers with more practical concerns about cost, range, reliability, and safety. News articles and commentary are popping up noting those concerns and expressing doubts about just how useful electric cars really are. The lack of charging stations, the environmental impact of mining lithium, the danger of battery fires, and potential strains to the electrical grid. There are some legitimate concerns, but how much of that skepticism is grounded in the reality of electrification and how much is good old-fashioned resistance to change?

To answer that question, let’s turn the tables. What if electric cars came first, and we’re trying to introduce internal combustion engines? Here are some predictable—and quite similar—objections.

  • How can we possibly build all the gas stations we’re going to need, and should we? (If electrification is the entrenched technology, we’d have plenty of charging stations everywhere.)
  • Do you really want trucks carrying 10,000 gallons of highly explosive gasoline driving down the highway next to you? Accidents happen! Do you want 20 gallons of it parked in your garage, waiting for just one spark to set it off—taking your house with it?
  • You can charge your electric car at home while you sleep, or at a charging station while at work. You can’t do that with a gasoline engine. You must go somewhere to buy gas, take time to get there, and then stand next to a hose pumping one of the most flammable liquids we know of.
  • We’re going to need a lot of that gasoline. Where will we find it, and at what environmental cost? Are we going to start drilling everywhere? Even in the ocean, the arctic, and in fragile ecosystems?  Are we going to have massive tankers crisscrossing the oceans? What if there’s a leak or a spill?
  • How are we going to build all the refining capacity we’ll need to process and transport all that gas? That’s a massive investment. Who’s going to pay for it?
  • What if we need to get that gas from countries that don’t like us? Will they refuse to sell to us or charge exorbitant prices? Will we make our enemies rich?
  • Gasoline is more expensive per mile driven than electricity, and because it’s a commodity, its price fluctuates—sometimes a lot. You never know what you may have to pay.
  • Gasoline engines are a lot more expensive than electric motors. They’re much more complex and since we’re building them in smaller numbers at first, carmakers don’t have the same economies of scale.
  • Internal combustion engines are more complex to repair. How often will your car need to be fixed? Will your mechanic know how?
  • What about air pollution? Just one internal combustion car emits 4.6 metric tons of carbon dioxide each year. Multiply that by all the cars on the road!
  • Would you like a car that’s slower? The most powerful—and most expensive—internal combustion cars on the road have less torque than a typical electric vehicle. That means less acceleration when you need to pass someone.

Some of these concerns are a bit overblown — just like some of the concerns about electric cars. But others are entirely valid. Yet too often we shrug them off because we’ve already accepted those costs, inconveniences, and dangers.

What we’re seeing with electric cars is the same progression we saw with early automobiles, airplanes, hybrid crops, personal computers, and many other now widely popular innovations. We’ll get there, but not without some pushback.

Image Credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of January 2024

Top 10 Human-Centered Change & Innovation Articles of January 2024Drum 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 January’s ten most popular innovation posts:

  1. Top 40 Innovation Bloggers of 2023 — Curated by Braden Kelley
  2. Creating Organizational Agility — by Howard Tiersky
  3. 5 Simple Steps to Team Alignment — by David Burkus
  4. 5 Essential Customer Experience Tools to Master — by Braden Kelley
  5. Four Ways To Empower Change In Your Organization — by Greg Satell
  6. AI as an Innovation Tool – How to Work with a Deeply Flawed Genius! — by Pete Foley
  7. Top 100 Innovation and Transformation Articles of 2023 — Curated by Braden Kelley
  8. 80% of Psychological Safety Has Nothing to Do With Psychology — by Robyn Bolton
  9. How will you allocate your time differently in 2024? — by Mike Shipulski
  10. Leadership Development Fundamentals – Work Products — by Mike Shipulski

BONUS – Here are five more strong articles published in December 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 four years:

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Are You Engaging in Innovation Theater?

Are You Engaging in Innovation Theater?

GUEST POST from Mike Shipulski

When you go to the cinema or the playhouse you go you see a show. The show may be funny, it may be sad, it may be thought-provoking, it may be beautiful, and it may take your mind off your problems for a couple of hours; but it’s not real. Sure, the story-line is good, but it came from someone’s imagination. And because it’s a story, it doesn’t have to bound by reality. Sure, the choreography is catchy, but it’s designed for effect. Yes, the cinematography paints a good picture, but it’s contrived. And, yes, the actors are good, but they’re actors. What you see isn’t real. What you see is theater.

If you are asked to focus on the innovation process, that’s theater. Innovation doesn’t care about process; it cares about delivering novel customer value. The process isn’t most important, the output is. When there’s an extreme focus on the process that usually means an extreme focus on the output of the process would be embarrassing.

If you are tasked to calculate the net present value of the project hopper, that’s theater. With innovation, there’s no partial credit for projects you’re not working on. None. The value of the projects in the hopper is zero. The song about the value of the project hopper is nothing more than a catchy melody performed to make sure the audience doesn’t ask about the feeble collection of projects you are working on. And, assigning a value to the stagnant project hopper is a creative story-line crafted to hide the fact you have too many projects you’re not working on.

If you are asked to create high-level metrics and fancy pie charts, that’s innovation theater. Process metrics and pie charts don’t pay the bills. Here’s innovation’s script for paying the bills: complete amazing projects, launch amazing products, and sell a boatload. Full stop. If your innovation script is different than that, ball it up and throw it away along with its producer.

If the lame projects aren’t stopped so better ones can start, if people aren’t moved off stale projects onto amazing ones, if the same old teams are charged with the innovation mandate, if new leaders aren’t added, if the teams are measured just like last year, that’s innovation theater. How many mundane projects have you stopped? How many amazing projects have you started? How many new leaders have you added? How many new teams have you formed? How will you measure your teams differently? How do you feel about all that?

If a return on investment (ROI) calculation is the gating criterion before starting an amazing project, that’s innovation theater. Projects that could create a new product family with a fundamentally different value proposition for a whole new customer segment cannot be assigned an ROI because no one has experience in this new domain. Any ROI will be a guess and that’s why innovation is governed by judgment and not ROI. Innovation is unpredictable which makes an ROI is impossible to predict. And if your innovation process squeezes judgment out of the story-line, that’s a tell-tale sign of innovation theater.

If the specifications are fixed, the resources are fixed, and the completion date is fixed, that’s innovation theater. Since it can be innovation only when there’s novelty, and since novelty comes with uncertainty, without flexibility in specs, resources, or time, it’s innovation theater.

If the work doesn’t require trust, it’s innovation theater. If trust is not required it’s because the work has been done before, and if that’s the case, it’s not innovation.

If you know it will work, it’s innovation theater. Innovation and certainty cannot coexist.

If a steering team is involved, it’s innovation theater. Consensus cannot spawn innovation.

If more than one person in charge, it’s innovation theater. With innovation, there’s no place for compromise.

And what to do when you realize you’re playing a part in your company’s innovation theater? Well, I’ll save that for another time.

Image credit: Pexels

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Pathways to Scale

Why planning your innovation expedition helps avoid a lot of trouble on the journey…

Image: Dall-E via Bing

GUEST POST from John Bessant

When I was a child a big feature of the social landscape was the annual visit to my uncle’s house on Christmas Eve. My dad came from a big family and they’d gather at his brother’s place to celebrate; my kid brother would already be asleep but I would sit in the small room next to the place they were all gathered, drinking, talking, occasionally singing. It was warm there; a small electric fire in the grate and a blanket to wrap myself in if I felt the cold.

Which was just as well since I invariably spent the evening with my nose in a book. Not just any book; as soon as we arrived I’d make a beeline for the bookshelf and haul out John Hunt’s account of the ascent of Everest. And I’d spend the evening while the ice crawled up the windows outside the room I’d imagine hearing the wind howling against the flimsy side of my tent as we shivered over a primus stove, trying to warm ourselves and get some rest before tomorrow’s big day. The last painful yards towards the summit…..

I was fascinated by the scale of the thing; a huge expedition, involving over 400 people (362 of them porters helping carry the 5000-plus kilograms of equipment) and relying on the intimate knowledge of the mother mountain held by the 20 Sherpas in the team. Those Nepalese guides had grown up in the shadow of the peak and knew to fear and respect it. The months of planning in smoky rooms in London clubs, the assembly and trek towards the base camp and the allocation of roles to help lay the foundations for what would certainly not be a simple walk in the park.

The extended discussions around which paths to take, the weighing up of different challenges along the prospective routes. Obstacles reckoned into the equation and balanced with the specialist skills and equipment needed to tackle them. A whole new language of cols and crevasses, of pitons and crampons to be learned, a crash-course in high altitude physiology and technology to be mastered.

And that was all before they even took their first tentative steps up the slopes.

It was engrossing, exciting and scary; for an 8-year-old kid whose experience of mountaineering extended to scrambling over the South Downs during our annual trip to see Grandma this was heady stuff. And as the evening wore on and we approached the summit, so it became a race against time. For the climbers, whittled down to Hilary and Tenzing, struggling up the last stage, their oxygen and energy running low and storms looming.

And for me hearing the chatter from next door rise to the climax which portended the taking of farewells, the wrapping of my kid brother in a blanket to continue his pre-Santa sleep in the car and me being bundled into a coat. Would I get to the summit in time — or have to wait until next year to continue the journey, abandoning mine at the eleventh hour?

I took a couple of lessons from that book, the first being that I’m not cut out for mountain climbing. There have to be easier and still thrilling ways to get your kicks and ‘because it is there’ isn’t a good enough reason for me to devote my energies to that particular kind of madness.

But the other is a healthy respect for people who scale mountains successfully. It takes a lot of planning, great team work and an approach to uncertainty which is all about agility and pivoting, adapting and improvising your way upwards.

Pretty much the key ingredients for successful innovation — and certainly relevant to another kind of scaling journey, enabling great innovations to have impact.

Because taking an innovation from a small-sized success story to something which delivers value at scale is not an easy one. The Holy Grail of impact has a lot in common with that elusive quest pursued by King Arthur’s knights, taking them along strange paths, meeting with dragons and disasters and lasting a long time. Similar odds of success too.

Having spent a long time focused on the challenges facing start-ups the innovation spotlight is now moving to the question of scaling — and there’s a helpfully growing body of knowledge and codified experience around this theme. Including the important decision about which route to take for the journey to scale.

One thing about mountain climbing which I remember thinking about when reading my Everest book was how they chose which route to take. Faced with 29,000 feet of sheer white walls with the occasional dangerous looking black rock poking its jagged edge through the snow like a knife through a curtain, how do you decide which path to take? It’s not as if there are well-worn tracks and clear signposts which you can follow — all you have is a lot of very unfriendly and treacherous ground on which to try to make your way.

It’s the same with scaling your innovation. Choosing your preferred pathway to scale is a key first stage on the journey; fortunately — like today’s Everest climbers — there’s a wealth of experience available from previous attempts and some important lessons on which we can build.

In particular we need to see the choices available as lying on a spectrum where we trade off additional external involvement with giving up a degree of control.

It’s a strategic decision, trying to balance the resource commitments you’ll need to make with the amount of control you want to retain. And with deciding what parts of your innovation knowledge are core, what parts are modular and can be adapted and customized with others in mind and what parts are you prepared to let others engage with, ‘hacking’ their own version of your ideas. Scale stories give us valuable clues about possible options, which include not doing it!

Some innovations aren’t really about a scaling journey. They work for a particular problem in a particular context; what’s needed for impact over the long-term is sustainability, being able to continue to deliver over an extended period of time and becoming something which is used and relied upon.

But if you are going to aim for scale then your choices include:

· Parachute — develop the venture, then try to get acquired, a classic start-up exit strategy. Let someone with the experience and the resources buy your solution, let it go. Easy on paper but you give up all your control and can only watch from the side-lines as your venture develops, and hope it’s in safe hands…

· Go it alone — keep on adding staff and spreading your solution across different geographies, gradually paint the world (or your chosen part of it) in your colors. There are plenty of advantages to doing this — mostly you keep control and you can directly manage quality, message, brand, etc. But the downside is you’ll need a lot of people and resources and you’ll pretty soon reach the point where you need to rethink your structure. The old tight-knit start-up team has to give way to a structured organization, complete with policies, procedures and a slowing down of the decision-making process. Plus you’ll need to adapt your solution to different local conditions — compatibility. And cost management will be important, finding ways to grow without bloating.

In reality this organic growth kind of approach can’t be a solo act — there will be things you need to outsource like legal services, manufacturing, distribution or maintenance. And it can also take time to build your own networks.

· Replicate — maybe your solution idea is one you think will work simply by replicating, placing the same offer in different geographies with only minor tweaks to help it fit. If your solution is something which can be ‘packaged’ and exported — a plug’n’play option — then this can work. It can either be a ‘grow your own’ approach, repeating the pattern by putting down your footprints on an increasingly broad geography. That’s the kind of route followed by IKEA and many other retailers, embodying their innovation solution in something which can be replicated.

Or you can franchise, allow others to take on the task and replicate on your behalf, sharing the revenues and building on your original innovative efforts. That’s the route which McDonalds has followed, exporting its original innovative fast-food format to over 39,000 locations around the world. But as Ray Croc, their scale architect realized, there’s a critical need to make sure the rules are clearly codified and then control via the franchise agreement so your proxies don’t damage the brand, compromise quality or change the core product. It’s a kind of remote control based on a clear constitution….

· ‘Relay replication’ — another version which involves another organization adopting and using your solution. Like franchising it requires protocols, training, standardization of core elements and processes but it also allows the adopting unit to continue to adapt and innovate within agreed parameters. A classic model here might be the diffusion of chemical plants like oil refineries; the core technology is transferred and the user learns to operate. It needs more than simple delivery, not plug n play — it involves a shared extended handover process until the user can make ‘product in a bottle’ with its own staff operating the equipment.

The advantages here are that you learn every time as you coach different organizations in the use of your innovation, plus there’s the chance that their downstream learning feeds back to you and allows you to improve your innovation. But it takes time and resources to ensure a successful handover, with key knowledge being shared through training, manuals and protocols and a long-term commitment to support.

· Licensing is another variation on the replication theme where other players can take on and (depending on the terms of the license) do things ranging from simply selling the core package through to adapting and extending it to suit local conditions. The big advantage is that other players are putting their shoulder to the wheel, helping spread the innovation, plus there’s a direct financial return to the original innovator. But once again it does involve letting go of control.

· Open source/open licensing — much commercial innovation is about finding ways to appropriate the benefits. So there’s pressure to keep a tight rein on what’s shared and how. But if you want to spread something, especially a novel approach, you might want to open up more to accelerate diffusion and seek your returns from being a first mover, growing with the market. There’s plenty of examples — Philips wanted to change the way we consumed recorded music in 1993 when they launched the Compact Cassette and so licensed it for free to others like Sony and Matsushita. It makes sense — if you are trying to establish a new ‘dominant design’ and move the world away from the current incumbent then recruiting others via open licensing is a good road to take.

And in the world of social innovation this has particular relevance; innovators who want to change the world for the better face the same challenge and recruiting others to the cause offers one way of doing so.

There are several advantages to such an open approach, not least it recruits many innovators who may help improve on your ideas. Communities of practice and using the crowd have become powerful innovation engines through this approach of free sharing; Linux is a good example.

Image: Dall-E via BIng

Lego’s approach to the hackers who started to modify the original ‘Mindstorms’ product is interesting here; they were presented with a different option to the traditional lawsuit which they might have been expecting. They were invited to Denmark to add their innovative ideas to those of the core design team!

But the downside, of course, in such open approaches is the loss of control and the risk that the innovation may be hijacked or developed in directions which do not match those of the original authors or reflect their social values.

· Strategic partnerships make sense where there is a clear need for ‘complementary assets’ of knowledge or other key resources and where win-win arrangements and contracts can be put in place. Christopher Sholes and colleagues had developed a great solution to the typewriter opportunity back in the 1850s but it took their strategic partnership with Remington and their accompanying mass-manufacturing and marketing to scale their innovation.

· Multi-player consortia may be needed when the range of complementary assets needed goes beyond a single partner. Sears and Roebuck pioneered the remote retailing model with their mail order catalogue approach but they needed to bring together many other players into the model to make it work — finance houses, logistics and distribution and a wide range of different suppliers. Boeing and Airbus do the same today, orchestrating extensive networks of players and partners to deliver their aerospace solutions at scale.

Such consortia bring real power to the scaling challenge but also require careful integration around a core mission. Managing such ‘strategic networks’ is well-known for its high transaction costs and co-ordination challenges.

· Value network and ecosystems — today’s innovation language extends this multi-player game, recognizing that there is a need for multiple players to work together to create value at scale. The challenge is that not all of these players have the same goals or aspirations so balancing their needs with the overall ‘mission’ becomes a tricky balancing act. It’s also important to recognize that such ecosystems don’t just have shared value creators in the mix like our strategic partnerships; they may also involve other players who affect the journey to scale by shaping the ways in which the value creation game is played. Examples of such shapers include government regulators, trade unions and standards organizations.

Once again this has particular relevance for scaling social innovation where system change which delivers real impact may depend on finding ways to bring many diverse players, like government agencies or regional authorities onside. As an influential IDB report puts it, such collaborations require ‘…different actors to coalesce around a shared set of priorities and best practices’.

· Platforms — we’re also now seeing the rise of platform businesses which enable scaling through linking innovators and markets more effectively. The Taobao market approach pioneered in China mimics in many ways the ecosystems around Apple’s developer platform or much of the Amazon operation. For small start-up innovators such platforms become a powerful alternative route to scale, but at the cost not only of accessing the platform but also in letting go some degree of control.

For any innovator climbing Mount Scale remains a key challenge. Meandering around the foothills may be a pleasant way to pass the time but if you want your innovation to have real impact then that peak has got to be climbed. Which means putting together and planning your expedition with the kind of care and attention John Hunt brought to his Everest team. And my guess is that his reflections probably have relevance in the world of innovation. Working out the most appropriate route up those slopes is something best done in the comfort of base camp rather than halfway up the mountain with the wind howling and the snow lashing at your face as you realise that the other path might have been a better one to take….

Image: Dall-E via Bing

This blog is based on our forthcoming book ‘The Scaling Value Playbook’ — click here for more details and to pre-order

You can find my podcast here and my videos here

And if you’d like to learn with me take a look at my online course here

Image credits: Dall-E via Bing, John Bessant

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