Tag Archives: collaboration

Why Small Innovations Matter Now More Than Ever

Searching for Silver Linings

Why Small Innovations Matter Now More Than Ever

GUEST POST from Robyn Bolton

Do you feel like you’re drowning in a sea of bad news? You’re not alone. We’re standing in the eye of a storm of war, political division, and endless layoffs. In times like these, why bother with innovation when we’re using all our energy to survive and make sense of things?

I’ve asked myself this question with increasing frequency over the past months.  After hours of searching, querying, and reading to understand why you, me, or any other individual should bother with innovation, I can tell you two things:

  1. There’s no logical, data-backed reason why any individual should bother innovating (there are many logical, data-backed reasons why companies should innovate)
  2. Innovation is the only life raft that’s ever carried us from merely surviving to thriving.

If that seems like a big, overwhelming, and exhausting expectation to place on innovators, you’re right.  But it doesn’t have to be because innovation is also small things that make you smile, spark your curiosity, and prompt you to ask, “How might we…?”

Here are three small innovations that broke through the dark clouds of the news cycle, made me smile, and started a domino effect of questions and wonder.

LEGO Braille Bricks: Building a More Inclusive World

Lego Braille

You know them, and you love them (unless you’ve stepped on one), and somehow, they got even better.  In 2023, LEGO released Braille Bricks to the public.

By modifying the studs (those bumps on the top of the brick) to correspond with the braille alphabet, numbers, and symbols and complementing the toy with a website offering a range of activities, educator resources, and community support, LEGO built a bridge between sighted and visually impaired worlds, one tiny brick at a time.

How might a small change build empathy and connect people?


The Open Book: Fulfilling a Dream by Working on Vacation

The Open Book

Have you ever dreamed of going on vacation so that you could work an hourly job without pay?  Would you believe there is a two-year waitlist of people willing to pay for such an experience?

Welcome to The Open Book, a second-hand bookstore in Wigtown, Scotland, that offers “bibliophiles, avid readers, kindred book lovers, and adventure seekers” the opportunity to live out their dreams of running the bookstore by day and living above it in a tiny apartment by night.  The bookstore is owned and operated by a local nonprofit, and all proceeds, about $10,000 per year, go to supporting the Wigtown Book Festival.

How might you turn your passion into an experience others would pay for?


The Human Library: Checking Out Books That Talk Back

Human Library

If used books aren’t your thing, consider going to The Human Library.  This innovative concept started in Copenhagen in 2000 and has spread to over 80 countries, offering a unique twist on traditional libraries.  Readers “borrow” individuals from all walks of life – from refugees to rockstars refugees, from people with disabilities to those with unusual occupations – to hear their stories, ask difficult questions, and engage in open dialogue.

How might you create opportunities for dialogue and challenge your preconceptions?


Small Things Make a Big Difference

In a world that often feels dark, these small innovations are helpful reminders that if you are curious, creative, and just a bit brave, you can spark joy, wonder, and change.

How will you innovate, no matter how small, to brighten your corner of the world?

Image credit: Pixabay

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Don’t Listen to the ‘We Can’t Do That’ Lie

These Are the Truths

Don't Listen to the 'We Can't Do That' Lie

GUEST POST from Robyn Bolton

How many times have you proposed a new idea and been told, “We can’t do that?” Probably quite a few.  My favorite memory of being told, “We can’t do that,” happened many years ago while working with a client in the publishing industry:

Client: We can’t do that.

Me: Why?

Client: Because we already tried it, and it didn’t work.

Me: When did you try it?

Client: 1972

Me: Well, things certainly haven’t changed since 1972, so you’re right, we definitely shouldn’t try again.

I can only assume they appreciated my sarcasm as much as the idea because we eventually did try the idea, and, 30+ years later, it did work. But the client never would have enjoyed that success if my team and I had not seen through “we can’t do that” and helped them admit (confess) what they really meant.

Quick acknowledgment

Yes, sometimes “We can’t do that” is true.  Laws and regulations define what can and can’t be done.  But they are rarely as binary as people make them out to be.  In those gray areas, the lie of “we can’t do that” obscures the truth of won’t, not able to, and don’t care.

“I won’t do it.”

When you hear “can’t,” it usually means “won’t.”  Sometimes, the “won’t” is for a good reason – “I won’t do the dishes tonight because I have an urgent deadline, and if I don’t deliver, my job is at risk.”  Sometimes, the “won’t” isn’t for a good reason – “I won’t do the dishes because I don’t want to.”  When that’s the case, “won’t” becomes “can’t” in the hope that the person making the request backs off and finds another solution. 

For my client, “We can’t do that” actually meant, “I won’t do that because it failed before and, even though that was thirty years ago, I’m afraid it will fail again, and I will be embarrassed, and it may impact my reputation and job security.”

You can’t work with “can’t.”  You can work with “won’t.”  When someone “won’t” do something, it’s because there’s a barrier, real or perceived.  By understanding the barrier, you can work together to understand, remove, or find a way around it.

“I’m not able to do it.”

“Can’t” may also come with unspoken caveats.  We can’t do that because we’ve never done it before and are scared.  We can’t do that because it is outside the scope of our work.  We can’t do that because we don’t know how. 

Like “won’t,” you can work with “not able to” to understand the gap between where you are now and where you want to go.  If it’s because you’re scared of doing something new, you can have conversations to get smarter about the topic or run small experiments to get real-world learnings.  If you’re not able to do something because it’s not within your scope of work, you can expand your scope or work with people who have it in their scope.  If you don’t know how, you can talk to people, take classes, and watch videos to learn how.

“I don’t care.”

As brave as it is devastating, “we can’t do that” can mean “I don’t care enough to do that.” 

Executives rarely admit to not caring, but you see it in their actions. When they say that innovation and growth are important but don’t fund them or pull resources at the first sign of a wobble in the business, they don’t care. If they did care, they would try to find a way to keep investing and supporting the things they say are priorities.

Exploring options, trying, making an effort—that’s the difference between “I won’t do it” and “I don’t care.”    “I won’t do that” is overcome through logic and action because the executive is intellectually and practically open to options. “I don’t care” requires someone to change their priorities, beliefs, and self-perception, changes that require major personal, societal, or economic events.

Now it’s your turn to tell the truth

Are you willing to ask the questions to find them?

Image credit: Unsplash

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False Choice – Founder versus Manager

False Choice - Founder versus Manager

GUEST POST from Robyn Bolton

Paul Graham, cofounder of Y Combinator, was so inspired by a speech by Airbnb cofounder and CEO that he wrote an essay about well-intentioned advice that, to scale a business, founders must shift modes and become managers.

It went viral. 

In the essay, he argued that:

In effect there are two different ways to run a company: founder mode and manager mode. Till now most people even in Silicon Valley have implicitly assumed that scaling a startup meant switching to manager mode. But we can infer the existence of another mode from the dismay of founders who’ve tried it, and the success of their attempts to escape from it.

With curiosity and an open mind, I read on.

I finished with a deep sigh and an eye roll. 

This is why.

Manager Mode: The realm of liars and professional fakers

On the off chance that you thought Graham’s essay would be a balanced and reflective examination of management styles in different corporate contexts, his description of Manager Mode should relieve you of that thought:

The way managers are taught to run companies seems to be like modular design in the sense that you treat subtrees of the org chart as black boxes. You tell your direct reports what to do, and it’s up to them to figure out how. But you don’t get involved in the details of what they do. That would be micromanaging them, which is bad.

Hire good people and give them room to do their jobs. Sounds great when it’s described that way, doesn’t it? Except in practice, judging from the report of founder after founder, what this often turns out to mean is: hire professional fakers and let them drive the company into the ground.

Later, he writes about how founders are gaslit into adopting Manager Mode from every angle, including by “VCs who haven’t been founders themselves don’t know how founders should run companies, and C-level execs, as a class, include some of the most skillful liars in the world.”

Founder Mode: A meritocracy of lifelong learners

For Graham, Founder Mode boils down to two things:

  1. Sweating the details
  2. Engaging with employees throughout the organization beyond just direct reports.  He cites Steve Jobs’ practice of holding “an annual retreat for what he considered the 100 most important people at Apple, and these were not the 100 people highest on the org chart.”

To his credit, Graham acknowledges that getting involved in the details is micromanaging, “which is bad,” and that delegation is required because “founders can’t keep running a 2000 person company the way they ran it when it had 20.” A week later, he acknowledged that female founders “don’t have permission to run their companies in Founder Mode the same way men can.”

Yet he persists in believing that Founder, not Manager, Mode is critical to success,

“Look at what founders have achieved already, and yet they’ve achieved this against a headwind of bad advice. Imagine what they’ll do once we can tell them how to run their companies like Steve Jobs instead of John Sculley.”

Leader Mode: Manager Mode + Founder Mode

The essay is interesting, but I have real issues with two of his key points:

  • Professional managers are disconnected from the people and businesses they manage, and as a result, their practices and behaviors are inconsistent with startup success.
  • Founders should ignore conventional wisdom and micromanage to their heart’s content.

Most “professional managers” I’ve met are deeply connected to the people they manage, committed to the businesses they operate, and act with integrity and authenticity. They are a far cry from the “professional fakers” and “skillful liars” Graham describes.

Most founders I’ve met should not be allowed near the details once they have a team in place. Their meddling, need for control, and soul-crushing FOMO (Fear of Missing Out) lead to chaos, burnout, and failure.

The truth is, it’s contextual.  The leaders I know switch between Founder and Manager mode based on the context.  They work with the passion of founders, trust with the confidence of managers, and are smart and humble enough to accept feedback when they go too far in one direction or the other.

Being both manager and founder isn’t just the essence of being a leader. It’s the essence of being a successful corporate innovator.  You are a founder,  investing in, advocating for, and sweating the details of ambiguous and risky work.  And you are a manager navigating the economic, operational, and political minefields that govern the core business and fund your paycheck and your team.

Image credit: Pexels

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The Runaway Innovation Train

The Runaway Innovation Train

GUEST POST from Pete Foley

In this blog, I return and expand on a paradox that has concerned me for some time.    Are we getting too good at innovation, and is it in danger of getting out of control?   That may seem like a strange question for an innovator to ask.  But innovation has always been a two edged sword.  It brings huge benefits, but also commensurate risks. 

Ostensibly, change is good. Because of technology, today we mostly live more comfortable lives, and enjoy superior health, longevity, and mostly increased leisure and abundance compared to our ancestors.

Exponential Innovation Growth:  The pace of innovation is accelerating. It may not exactly mirror Moore’s Law, and of course, innovation is much harder to quantify than transistors. But the general trend in innovation and change approximates exponential growth. The human stone-age lasted about 300,000 years before ending in about 3,000 BC with the advent of metalworking.  The culture of the Egyptian Pharos lasted 30 centuries.  It was certainly not without innovations, but by modern standards, things changed very slowly. My mum recently turned 98 years young, and the pace of change she has seen in her lifetime is staggering by comparison to the past.  Literally from horse and carts delivering milk when she was a child in poor SE London, to todays world of self driving cars and exploring our solar system and beyond.  And with AI, quantum computing, fusion, gene manipulation, manned interplanetary spaceflight, and even advanced behavior manipulation all jockeying for position in the current innovation race, it seems highly likely that those living today will see even more dramatic change than my mum experienced.  

The Dark Side of Innovation: While accelerated innovation is probably beneficial overall, it is not without its costs. For starters, while humans are natural innovators, we are also paradoxically change averse.  Our brains are configured to manage more of our daily lives around habits and familiar behaviors than new experiences.  It simply takes more mental effort to manage new stuff than familiar stuff.  As a result we like some change, but not too much, or we become stressed.  At least some of the burgeoning mental health crisis we face today is probably attributable the difficulty we have adapting to so much rapid change and new technology on multiple fronts.

Nefarious Innovation:  And of course, new technology can be used for nefarious as well as noble purpose. We can now kill our fellow humans far more efficiently, and remotely than our ancestors dreamed of.  The internet gives us unprecedented access to both information and connectivity, but is also a source of misinformation and manipulation.  

The Abundance Dichotomy:  Innovation increases abundance, but it’s arguable if that actually makes us happier.  It gives us more, but paradoxically brings greater inequalities in distribution of the ‘wealth’ it creates. Behavior science has shown us consistently that humans make far more relative than absolute judgments.  Being better off than our ancestors actually doesn’t do much for us.  Instead we are far more interested in being better off than our peers, neighbors or the people we compare ourselves to on Instagram. And therein lies yet another challenge. Social media means we now compare ourselves to far more people than past generations, meaning that the standards we judge ourselves against are higher than ever before.     

Side effects and Unintended Consequences: Side effects and unintended consequences are perhaps the most difficult challenge we face with innovation. As the pace of innovation accelerates, so does the build up of side effects, and problematically, these often lag our initial innovations. All too often, we only become aware of them when they have already become a significant problem. Climate change is of course a poster child for this, as a huge unanticipated consequence of the industrial revolution. The same applies to pollution.  But as innovation accelerates, the unintended consequences it brings are also stacking up.  The first generations of ‘digital natives’ are facing unprecedented mental health challenges.  Diseases are becoming resistant to antibiotics, while population density is leading increased rate of new disease emergence. Agricultural efficiency has created monocultures that are inherently more fragile than the more diverse supply chain of the past.  Longevity is putting enormous pressure on healthcare.

The More we Innovate, the less we understand:  And last, but not least, as innovation accelerates, we understand less about what we are creating. Technology becomes unfathomably complex, and requires increasing specialization, which means few if any really understand the holistic picture.  Today we are largely going full speed ahead with AI, quantum computing, genetic engineering, and more subtle, but equally perilous experiments in behavioral and social manipulation.  But we are doing so with increasingly less pervasive understanding of direct, let alone unintended consequences of these complex changes!   

The Runaway Innovation Train:  So should we back off and slow down?  Is it time to pump the brakes? It’s an odd question for an innovator, but it’s likely a moot point anyway. The reality is that we probably cannot slow down, even if we want to.  Innovation is largely a self-propagating chain reaction. All innovators stand on the shoulders of giants. Every generation builds on past discoveries, and often this growing knowledge base inevitably leads to multiple further innovations.  The connectivity and information access of internet alone is driving today’s unprecedented innovation, and AI and quantum computing will only accelerate this further.  History is compelling on this point. Stone-age innovation was slow not because our ancestors lacked intelligence.  To the best of our knowledge, they were neurologically the same as us.  But they lacked the cumulative knowledge, and the network to access it that we now enjoy.   Even the smartest of us cannot go from inventing flint-knapping to quantum mechanics in a single generation. But, back to ‘standing on the shoulder of giants’, we can build on cumulative knowledge assembled by those who went before us to continuously improve.  And as that cumulative knowledge grows, more and more tools and resources become available, multiple insights emerge, and we create what amounts to a chain reaction of innovations.  But the trouble with chain reactions is that they can be very hard to control.    

Simultaneous Innovation: Perhaps the most compelling support for this inevitability of innovation lies in the pervasiveness of simultaneous innovation.   How does human culture exist for 50,000 years or more and then ‘suddenly’ two people, Darwin and Wallace come up with the theory of evolution independently and simultaneously?  The same question for calculus (Newton and Leibniz), or the precarious proliferation of nuclear weapons and other assorted weapons of mass destruction.  It’s not coincidence, but simply reflects that once all of the pieces of a puzzle are in place, somebody, and more likely, multiple people will inevitably make connections and see the next step in the innovation chain. 

But as innovation expands like a conquering army on multiple fronts, more and more puzzle pieces become available, and more puzzles are solved.  But unfortunately associated side effects and unanticipated consequences also build up, and my concern is that they can potentially overwhelm us. And this is compounded because often, as in the case of climate change, dealing with side effects can be more demanding than the original innovation. And because they can be slow to emerge, they are often deeply rooted before we become aware of them. As we look forward, just taking AI as an example, we can already somewhat anticipate some worrying possibilities. But what about the surprises analogous to climate change that we haven’t even thought of yet? I find that a sobering thought that we are attempting to create consciousness, but despite the efforts of numerous Nobel laureates over decades, we still have to idea what consciousness is. It’s called the ‘hard problem’ for good reason.  

Stop the World, I Want to Get Off: So why not slow down? There are precedents, in the form of nuclear arms treaties, and a variety of ethically based constraints on scientific exploration.  But regulations require everybody to agree and comply. Very big, expensive and expansive innovations are relatively easy to police. North Korea and Iran notwithstanding, there are fortunately not too many countries building nuclear capability, at least not yet. But a lot of emerging technology has the potential to require far less physical and financial infrastructure.  Cyber crime, gene manipulation, crypto and many others can be carried out with smaller, more distributed resources, which are far more difficult to police.  Even AI, which takes considerable resources to initially create, opens numerous doors for misuse that requires far less resource. 

The Atomic Weapons Conundrum.  The challenge with getting bad actors to agree on regulation and constraint is painfully illustrated by the atomic bomb.  The discovery of fission by Strassman and Hahn in the late 1930’s made the bomb inevitable. This set the stage for a race to turn theory into practice between the Allies and Nazi Germany. The Nazis were bad actor, so realistically our only option was to win the race.  We did, but at enormous cost. Once the ‘cat was out of the bag, we faced a terrible choice; create nuclear weapons, and the horror they represent, or chose to legislate against them, but in so doing, cede that terrible power to the Nazi’s?  Not an enviable choice.

Cumulative Knowledge.  Today we face similar conundrums on multiple fronts. Cumulative knowledge will make it extremely difficult not to advance multiple, potentially perilous technologies.  Countries who legislate against it risk either pushing it underground, or falling behind and deferring to others. The recent open letter from Meta to the EU chastising it for the potential economic impacts of its AI regulations may have dripped with self-interest.  But that didn’t make it wrong.   https://euneedsai.com/  Even if the EU slows down AI development, the pieces of the puzzle are already in place.  Big corporations, and less conservative countries will still pursue the upside, and risk the downside. The cat is very much out of the bag.

Muddling Through:  The good news is that when faced with potentially perilous change in the past, we’ve muddled through.  Hopefully we will do so again.   We’ve avoided a nuclear holocaust, at least for now.  Social media has destabilized our social order, but hasn’t destroyed it, yet.  We’ve been through a pandemic, and come out of it, not unscathed, but still functioning.  We are making progress in dealing with climate change, and have made enormous strides in managing pollution.

Chain Reactions:  But the innovation chain reaction, and the impact of cumulative knowledge mean that the rate of change will, in the absence of catastrophe, inevitably continue to accelerate. And as it does, so will side effects, nefarious use, mistakes and any unintended consequences that derive from it. Key factors that have helped us in the past are time and resource, but as waves of innovation increase in both frequency and intensity, both are likely to be increasingly squeezed.   

What can, or should we do? I certainly don’t have simple answers. We’re all pretty good, although by definition, far from perfect at scenario planning and trouble shooting for our individual innovations.  But the size and complexity of massive waves of innovation, such as AI, are obviously far more challenging.  No individual, or group can realistically either understand or own all of the implications. But perhaps we as an innovation community should put more collective resources against trying? We’ll never anticipate everything, and we’ll still get blindsided.  And putting resources against ‘what if’ scenarios is always a hard sell. But maybe we need to go into sales mode. 

Can the Problem Become the Solution? Encouragingly, the same emerging technology that creates potential issues could also help us.  AI and quantum computing will give us almost infinite capacity for computation and modeling.  Could we collectively assign more of that emerging resource against predicting and managing it’s own risks?

With many emerging technologies, we are now where we were in the 1900’s with climate change.  We are implementing massive, unpredictable change, and by definition have no idea what the unanticipated consequences of that will be. I personally think we’ll deal with climate change.  It’s difficult to slow a leviathan that’s been building for over a hundred years.  But we’ve taken the important first steps in acknowledging the problem, and are beginning to implement corrective action. 

But big issues require big solutions.  Long-term, I personally believe the most important thing for humanity to escape the gravity well.   Given the scale of our ability to curate global change, interplanetary colonization is not a luxury, but an essential.  Climate change is a shot across the bow with respect to how fragile our planet is, and how big our (unintended) influence can be.  We will hopefully manage that, and avoid nuclear war or synthetic pandemics for long enough to achieve it.  But ultimately, humanity needs the insurance dispersed planetary colonization will provide.  

Image credits: Microsoft Copilot

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Why Modifying This One Question Changes Everything

Why Modifying This One Question Changes Everything

GUEST POST from Robyn Bolton

You know that asking questions is essential.  After all, when you’re innovating, you’re doing something new, which means you’re learning, and the best way to learn is by asking questions.  You also know that asking genuine questions, rather than rhetorical or weaponized ones, is critical to building a culture of curiosity, exploration, and smart risk-taking.  But did you know that making a small change to a single question can radically change everything for your innovation strategy, process, and portfolio?

What is your hypothesis?

Before Lean Startup, there was Discovery-Driven Planning.  This approach, first proposed by Columbia Business School professor Rita McGrath and Wharton School professor Ian MacMillan in their 1995 HBR article, outlines a “planning” approach that acknowledges and embraces assumptions (instead of pretending that they’re facts) and relentlessly tests them to uncover new data and inform and update the plan.

It’s the scientific method applied to business.

How confident are you?

However, not all assumptions or hypotheses are created equal.  This was the assertion in the 2010 HBR article “Beating the Odds When You Launch a New Venture.”  Using examples from Netflix, Johnson & Johnson, and a host of other large enterprises and scrappy startups, the authors encourage innovators to ask two questions about their assumptions:

  1. How confident am I that this assumption is true?
  2. What is the (negative) impact on the idea if the assumption is false?

By asking these two questions of every assumption, the innovator sorts assumptions into three categories:

  1. Deal Killers: Assumptions that, if left untested, threaten the idea’s entire existence
  2. Path-dependent risks: Assumptions that impact the strategic underpinnings of the idea and cost significant time and money to resolve
  3. High ROI risks: Assumptions that can be quickly and easily tested but don’t have a significant impact on the idea’s strategy or viability

However, human beings have a long and inglorious history of overconfidence.  This well-established bias in which our confidence in our judgment exceeds the objective (data-based) accuracy of those judgments resulted in disasters like Chernobyl, the sinking of the Titanic, the explosions of the Space Shuttle Challenger and Discovery, and the Titan submersible explosion.

Let’s not add your innovation to that list.

How much of your money are you willing to bet?

For years, I’ve worked with executives and their teams to adopt Discovery-Driven Planning and focus their earliest efforts on testing Deal Killer assumptions. I was always struck by how confident everyone was and rather dubious when they reported that they had no Deal Killer assumptions.

So, I changed the question.

Instead of asking how confident they were, I asked how much they would bet. Then I made it personal—high confidence meant you were willing to bet your annual income, medium confidence meant dinner for the team at a Michelin-starred restaurant, and low confidence meant a cup of coffee.

Suddenly, people weren’t quite so confident, and there were A LOT of Deal Killers to test.

Make it Personal

It’s easy to become complacent in companies.  You don’t get paid more if you come in under budget, and you don’t get fired if you overspend.  Your budget is a rounding error in the context of all the money available to the company.  And your signing authority is probably a rounding error on the rounding error that is your budget.  So why worry about ten grand here and a hundred grand there?

Because neither you, your team, nor your innovation efforts have the luxury of complacency.

Innovation is always under scrutiny.  People expect you to generate results with a fraction of the resources in record time.  If you don’t, you, your team, and your budget are the first to be cut.

The business of innovation is personal.  Treat it that way. 

How much of your time, money, and reputation are you willing to risk?  What do you need your team to risk in terms of their time, money, and professional aspirations?  How much time, money, and reputation are your stakeholders willing to risk?

The answers change everything.

Image credit: Pixabay

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Who is More Creative – Women or Men?

753 Studies Have the Answer

Who is More Creative – Women or Men?

GUEST POST from Robyn Bolton

You were born creative. As an infant, you had to figure many things out—how to get fed or changed, get help or attention, and make a onesie covered in spit-up still look adorable.  As you grew older, your creativity grew, too.  You drew pictures, wrote stories, played dress-up, and acted out imaginary stories.

Then you went to school, and it was time to be serious.  Suddenly, creativity had a time and place.  It became an elective or a hobby.  Something you did just enough of to be “well-rounded” but not so much that you would be judged irresponsible or impractical.

When you entered the “real world,” your job determined whether you were creative.  Advertising, design, marketing, innovation?  Creative.  Business, medicine, law, engineering?  Not creative.

As if Job-title-a-determinant-of-creativity wasn’t silly enough, in 2022, a paper was published in the Journal of Applied Psychology that declared that, based on a meta-analysis of 259 studies (n=79,915), there is a “male advantage in creative performance.”

Somewhere, Don Draper, Pablo Picasso, and Norman Mailer high-fived.

But, as every good researcher (and innovator) knows, the headline is rarely the truth.  The truth is that it’s contextual and complicated, and everything from how the original studies collected data to how “creativity” was defined matters.

But that’s not what got reported.  It’s also not what people remember when they reference this study (and I have heard more than a few people invoke these findings in the three years since publication).

That is why I was happy to see Fortune report on a new study just published in the Journal of Applied Psychology. The study cites findings from a meta-analysis of 753 studies (n=265,762 individuals) that show men and women are equally creative. When “usefulness (of an idea) is explicitly incorporated in creativity assessment,” women’s creativity is “stronger.”

Somewhere, Mary Wells LawrenceFrida Kahlo, and Virginia Woolf high-fived.

Of course, this finding is also contextual.

What makes someone “creative?”

Both studies defined creativity as “the generation of novel and useful ideas.”

However, while the first study focused on how context drives creativity, the second study looked deeper, focusing on two essential elements of creativity: risk-taking and empathy. The authors argued that risk-taking is critical to generating novel ideas, while empathy is essential to developing useful ideas.

Does gender influence creativity?

It can.  But even when it does, it doesn’t make one gender more or less creative than the other.

Given “contextual moderators” like country-level culture, industry gender composition, and role status, men tend to follow an “agentic pathway” (creativity via risk-taking), so they are more likely to generate novel ideas.

However, given the same contextual moderators, women follow a “communal pathway” (creativity via empathy), so they are more likely to generate useful ideas.

How you can use this to maximize creativity

Innovation and creativity go hand in hand. Both focus on creating something new (novel) and valuable (useful).  So, to maximize innovation within your team or organization, maximize creativity by:

  • Explicitly incorporate novelty and usefulness in assessment criteria.  If you focus only on usefulness, you’ll end up with extremely safe and incremental improvements.  If you focus only on novelty, you’ll end up with impractical and useless ideas.
  • Recruit for risk-taking and empathy.  While the manifestation of these two skills tends to fall along gender lines, don’t be sexist and assume that’s always the case.  When seeking people to join your team or your brainstorming session, find people who have demonstrated strong risk-taking or empathy-focused behaviors and invite them in.
  • Always consider the context.  Just as “contextual moderators” impact people’s creative pathways, so too does the environment you create.  If you want people to take risks, be vulnerable, and exhibit empathy, you must establish a psychologically safe environment first.  And that starts with making sure there aren’t any “tokens” (one of a “type”) in the group.

Which brings us back to the beginning.

You ARE creative.

How will you be creative today?

Image credit: Unsplash

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I Sent AI a Survey

… and the Results Were Brilliant … and Dangerous

I sent AI a survey and the results were brilliant and dangerous

GUEST POST from Robyn Bolton

AI is everywhere: in our workplaces, homes, schools, art galleries, concert halls, and even neighborhood coffee shops.  We can’t seem to escape it.  Some hope it will unlock our full potential and usher in an era of creativity, prosperity, and peace. Others worry it will eventually replace us. While both outcomes are extreme, if you’ve ever used AI to conduct research with synthetic users, the idea of being “replaced” isn’t so wild.

For the past month, I’ve beta-tested an AI research tool that allows you to create surveys, specify segments of respondents, send the survey to synthetic respondents (AI-generated personas), and get results within minutes. 

Sound too good to be true?

Here are the results from my initial test:

  • 150 respondents in 3 niche segments (50 respondents each)
  • 51 questions, including ten open-ended questions requiring short prose responses
  • 1 hour to complete and generate an AI executive summary and full data set of individual responses, enabling further analysis

The Tool is Brilliant

It took just one hour to gather data that traditional survey methods require a month or more to collect, clean, and synthesize. Think of how much time you’ve spent waiting for survey results, checking interim data, and cleaning up messy responses. I certainly did and it made me cry.

The qualitative responses were on-topic, useful, and featured enough quirks to seem somewhat human.  I’m pretty sure that has never happened in the history of surveys.  Typically, respondents skip open-ended questions or use them to air unrelated opinions.

Every respondent completed the entire survey!  There is no need to look for respondents who went too quickly, chose the same option repeatedly, or abandoned the effort altogether.  You no longer need to spend hours cleaning data, weeding out partial responses, and hoping you’re left with enough that you can generate statistically significant findings.

The Results are Dangerous

When I presented the results to my client, complete with caveats about AI’s limitations and the tool’s early-stage development, they did what any reasonable person would do – they started making decisions based on the survey results.

STOP!

As humans, we want to solve problems.  In business, we are rewarded for solving problems.  So, when we see something that looks like a solution, we jump at it.

However, strategic or financially significant decisions should never rely ona single data source. They are too complex, risky, and costly.  And they definitely shouldn’t be made based on fake people’s answers to survey questions!

They’re Also Useful.

Although the synthetic respondents’ data may not be true, it is probably directionally correct because it is based on millions and maybe billions of data points.  So, while you shouldn’t make pricing decisions based on data showing that 40% of your target consumers are willing to pay a 30%+ premium for your product, it’s reasonable to believe they may be willing to pay more for your product.

The ability to field an absurdly long survey was also valuable.  My client is not unusual in their desire to ask everything they may ever need to know for fear that they won’t have another chance to gather quantitative data (and budgets being what they are, they’re usually right).  They often ignore warnings that long surveys lead to abandonment and declining response quality. With AI, we could ask all the questions and then identify the most critical ones for follow-up surveys sent to actual humans.

We Aren’t Being Replaced, We’re Being Spared

AI consumer research won’t replace humans. But it will spare us the drudgery of long surveys filled with useless questions, months of waiting for results, and weeks of data cleaning and analysis. It may just free us up to be creative and spend time with other humans.  And that is brilliant.

Image credit: Microsoft Copilot

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ISO Innovation Standards

The Good, the Bad, and the Missing

ISO Innovation Standards

GUEST POST from Robyn Bolton

In 2020, the International Standards Organization, most famous for its Quality Management Systems standard, published ISO 56000Innovation Management—Fundamentals and Vocabulary. Since then, ISO has released eight additional innovation standards. 

But is it possible to create international standards for innovation, or are we killing creativity?

That’s the question that InnoLead founder and CEO Scott Kirsner and I debated over lunch a few weeks ago.  Although we had heard of the standards and attended a few webinars, but we had never read them or spoken with corporate innovators about their experiences.

So, we set out to fix that.

Scott convened an all-star panel of innovators from Entergy, Black & Veatch, DFW Airport, Cisco, and a large financial institution to read and discuss two ISO Innovation Standards: ISO 56002, Innovation management – Innovation management systems – Requirements and ISO 56004, Innovation Management Assessment – Guidance.

The conversation was honest, featured a wide range of opinions, and is absolutely worth your time to watch

Here are my three biggest takeaways.

The Standards are a Good Idea

Innovation doesn’t have the best reputation.  It’s frequently treated as a hobby to be pursued when times are good and sometimes as a management boondoggle to justify pursuing pet ideas and taking field trips to fun places.

However, ISO Standards can change how innovation is perceived and supported.

Just as ISO’s Quality Management Standards established a framework for quality, the Innovation Management Standards aim to do the same for innovation. They provide shared fundamentals and a common vocabulary (ISO 56000), requirements for innovation management systems (ISO 56001 and ISO 56002), and guidance for measurement (ISO 56004), intellectual property management (ISO 56005), and partnerships (ISO 56003). By establishing these standards, organizations can transition innovation from a vague “trust me” proposition to a structured, best-practice approach.

The Documents are Dangerous

However, there’s a caveat: a little knowledge can be dangerous. The two standards I reviewed were dense and complex, totaling 56 pages, and they’re among the shortest in the series. Packed with terminology and suggestions, they can overwhelm experienced practitioners and mislead novices into thinking they have How To Guide for success.

Innovation is contextual.  Its strategies, priorities, and metrics must align with the broader organizational goals.  Using the standards as a mere checklist is more likely to lead to wasted time and effort building the “perfect” innovation management system while management grows increasingly frustrated by your lack of results.

The Most Important Stuff is Missing

Innovation is contextual, but there are still non-negotiables:   

  • Leadership commitment AND active involvement: Innovation isn’t an idea problem. It’s a leadership problem.  If leadership delegates innovation, fails to engage in the work, and won’t allocate required resources, you’re efforts are doomed to fail.
  • Adjacent and Radical Innovations require dedicated teams: Operations and innovation are fundamentally different. The former occurs in a context of known knowns and unknowns, where experience and expertise rule the day. The latter is a world of unknown unknowns, where curiosity, creativity, and experimentation are required. It is not reasonable to ask someone to live in both worlds simultaneously.
  • Innovation must not be a silo: Innovation cannot exist in a silo. Links must be maintained with the core business, as its performance directly impacts available resources and influences the direction of innovation initiatives.

These essential elements are mentioned in the standards but are not clearly identified. Their omission increases the risk of further innovation failures.

Something is better than nothing

The standards aren’t perfect.  But one of the core principles of innovation is to never let perfection get in the way of progress. 

Now it’s time to practice what we preach by testing the standards in the real world, scrapping what doesn’t work, embracing what does, and innovating and iterating our way to better.

Image credit: Pixabay

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Why Neglecting New Hire Ideas Hurts Revenue

The Cost of Silence

Why Neglecting New Hire Ideas Hurts Revenue

GUEST POST from Robyn Bolton

Stop me if this sounds familiar. A new hire bounces into your office and, with all the joy and enthusiasm of a new puppy, rattles off a list of ideas. You smile and, just like with new puppies, explain why their ideas won’t work, and encourage them to be patient and get to know the organization. 

Congratulations!  You just cost your company money. Not because the new hire’s idea was the silver bullet you’ve been seeking but because you taught them that it’s more critical for them to do their jobs and maintain the status quo than to ask questions and share ideas.

If that seems harsh, read the new research from Harvard Business School professor Amy Edmondson.

Year 1: Rainbows and Unicorns (mostly)

From 2017 through 2021, Dr. Edmonson and her colleagues collected data from over 10,000 physicians.  Using biannual (every two years) surveys, they asked physicians to rate on a 5-point scale how comfortable they felt offering opinions or calling out the mistakes of colleagues or superiors. 

It was little surprise that agreement with statements like “I can report patient safety mistakes without fear of punishment” were highest amongst people with less than one year of service at their employer.

These results all come down to one thing: high levels of psychological safety.

Years 2+: Resignation and Unhappiness

However, psychological safety erodes quickly in the first year because:

  • There’s a gap between words and actions: When new hires join an organization, they believe what they hear about its culture, values, priorities, and openness.  Once they’re in the organization and observe their colleagues’ and superiors’ daily behavior, they experience the disconnect, lose trust, and shift into self-protection mode.
  • Their feedback and ideas are rebuffed: This scenario is described above, but it’s not the only one.  Another common situation occurs when a new hire responds to requests for feedback only to be met with silence or exasperation, a lack of follow-through or follow-up, or is openly mocked or met with harsh pushback
  • Expectations increase with experience: It’s easier to ask questions when you’re new, and no one expects you to know the answers.  Over time, however, you are expected to learn the answers and you no longer feel comfortable asking questions, even if there’s no way you could know the answer.

20 years to regain what was lost in 1

According to Edmondson’s research, it takes up to 20 years to rebuild the safety lost in the first year.

As a leader, you can slow that erosion and accelerate the rebuilding when you:

  • Recognize the Risk: Knowing that new hires will experience a drop in psychological safety, staff them on teams that have higher levels of safety
  • Walk the Talk: Double down on demonstrating the behaviors you want. Immediately act on feedback that points out a gap between your words and actions.
  • Ask questions: Demonstrate your openness by being curious, asking questions, and asking follow-up questions.  As Edmonson writes, “You are training people to contribute by constantly asking questions.”
  • Promises Made = Promises Kept: If you ask for feedback, act on it.  If you ask for ideas, act on some and explain why you’re not executing others.
  • Be Vulnerable: Admit your mistakes and uncertainties.  It sets a powerful example that it’s okay to be imperfect and to ask for help. It also creates an environment for others to do the same.

The Cost of Silence vs. The Cost of Time

Building and maintaining psychological safety takes time and effort.  It takes 5 minutes to listen to and respond to an idea.  It takes hours to ensure new hires join safe teams.  It takes weeks to plan and secure support for post-hackathon ideas. 

But how does that compare to 20 years of lost ideas, improvements, innovations, and revenue?  To 20 years of lost collaboration, productivity, and peak effectiveness? To 20 years of slow progress, inefficiency, and cost?

How many of your employees stick around 20 years to give you the chance to rebuild what was lost?

Image credit: Pixabay

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How to Build Innovation Resilience in Uncertainty

Reality Strikes Back

How to Build Innovation Resilience in Uncertainty

GUEST POST from Robyn Bolton

“This time feels different.”  I’ve been hearing this from innovation practitioners and partners for months  We’ve seen innovation resilience tested in times of economic uncertainty and geopolitical volatility.  We’ve seen it flourish when markets soar and capital is abundant.  We’ve seen it all, but this time feels different.

In fact, we feel a great disturbance in the innovation force.

Disturbances aren’t always bad.  They’re often the spark that ignites innovation.  But understand the disturbance you must, before work with it you can.

So, to help us understand and navigate a time that feels, and likely is, different, I present “The Corporate Innovator’s Saga.”

Episode I: The R&D Men (are) Aces

(Sorry, that’s the most tortured one.  The titles get better, I promise)

A long time ago (1876), in a place not so far away (New Jersey), one man established what many consider the first R&D Lab.  A year later, Thomas Edison and his Menlo Park colleagues debuted the phonograph.

In the 20th century, as technology became more complex, invention shifted from individual inventors to corporate R&D labs. By the late 1960s, Bell Labs employed 15,000 people, including 1,200 PhDs.  In 1970, Xerox’s famed Palo Alto Research Center (PARC) opened.

Episode II: Attack of the Disruptors

For most of the twentieth century, R&D labs were the heroes or villains of executives’ innovation stories.  Then, Harvard Business School professor Clayton Christensen published, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. 

He revealed that executives’ myopic focus on serving their best (most profitable) customers caused them to miss new waves of innovation. In example after example, he showed that R&D often worked on disruptive (cheaper, good enough) technologies only to have their efforts shut down by executives worried about cannibalizing their existing businesses.

C-suites listened, and innovation went from an R&D problem to a business one.

Episode III: Revenge of the Designers

Design Thinking’s origins date back to the 1940s, its application to business gained prominence with l Tim Brown’s 2009 book, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation.

This book introduced frameworks still used today’s: desirability, feasibility, and viability; divergent and convergent thinking; and the process of empathy, problem definition, ideation, prototyping, and testing. 

Innovation now required business people to become designers, question the status quo, and operate untethered from the short-termism of business,

Episode IV: A New Hope (Startups)

The early 2000s were a dizzying time for corporate innovation. Executives feared disruption and poured resources into internal innovation teams and trainings. Meanwhile, a movement was gaining steam in Silicon Valley.

Y Combinator, the first seed accelerator, launched in 2005 and was followed a year later by TechStars. When Eric Ries published The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses in 2011, the US was home to nearly 100 startup accelerators.

Now, businesspeople needed to become entrepreneurs capable of building, and scaling startups in environments purpose-built to kill risk and change.

In response, companies spun up internal accelerators, established corporate venture capital teams, and partnered with startup studios.

Episode V: Reality Strikes Back

Today, the combination of a global pandemic, regional wars, and a single year in which elections will affect 49% of the world’s population has everyone reeling. 

Naturally, this uncertainty triggered out need for a sense of control.  The first cut were “hobbies” like innovation and DEI.  Then, “non-essentials” like “extra” people and perks.  For losses continued into the “need to haves,” like operational investments and business expansion.

Recently, the idea of “growth at all costs” has come under scrutiny with advocates for more thoughtful growth strategies emerging There is still room for innovation IF it produces meaningful, measurable value.

Episode VI: Return of the Innovator (?)

I don’t know what’s next, but I hope this is the title.  And, if not, I hope whatever is next has Ewoks.

What do you hope for in the next episode?

Image credit: Pexels

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