Category Archives: Innovation

Future Vision XPRIZE: The Top 50 Optimistic Futures

$2.6M+ to Film a Future Worth Building — And Why You Should Vote Now

Future Vision XPRIZE: The Top 50 Optimistic Futures

by Braden Kelley and Art Inteligencia

Innovation Shows Up First as a Story

Innovation almost always shows up first as a story. Someone writes down the submarine, the moon landing, the video call — and decades later we build it. Culture dreams of a destination. Engineering finds the path.

That is the remit of the Future Vision XPRIZE: a global competition — with a $3.5M+ prize pool and a $2.6M+ grand prize path to turn a short vision into a feature film — asking creators to show an optimistic, abundant, technology-enabled future worth wanting. Not a utopia without stakes. Not dystopia as the only imagination we fund. A future where humanity faces real danger and still figures something out — or at least believes it can.

The assignment was clear: a trailer of up to three minutes, plus a treatment of up to twelve pages, depicting a compelling hopeful future. Tools were wide open — traditional filmmaking, animation, AI, hybrids. The spirit was Star Trek’s deeper bet: that humanity can evolve intellectually, ethically, and socially toward greater understanding, possibility, and purpose. Judges for the competition include voices such as Neil deGrasse Tyson, Neal Stephenson, Mira Lane, and Rod Roddenberry. Finals land live at Moonshots LIVE in Los Angeles on September 25, 2026.

Why This Competition Matters Beyond the Prize

Incentive competitions are how XPRIZE has long pulled breakthroughs into the open. Future Vision flips the lens: the breakthrough here is collective imagination. Cautionary tales still matter — they help us navigate risk. But builders also need a north star. Soft landings for technology are designed. Soft landings for culture start with stories that make a better Tuesday feel real enough to pursue.

That is why this prize can inspire more than filmmakers and futurists. When the public watches fifty short visions of progress — climate and cities, longevity and memory, oceans and robotics, first contact and consciousness — people are not only entertained. They are rehearsing what “good” might look like. They are practicing hope with craft. Innovators get a richer brief than a white paper. Citizens get permission to want a future that is not only less bad, but more human.

Key Themes Across the Top 50

From more than 2,500 submissions, Range, XPRIZE, and Google selected fifty official films. Browse them and a pattern emerges — not a single prescribed future, but a cluster of human-centered themes:

Connection and consciousness — how we stay human to each other when tools get intimate with mind and dream.
Memory, biotech, and longevity — what we inherit, repair, and refuse to treat as disposable.
Nature, climate, oceans, and energy — technology solving real planetary constraints, not escaping them in costume.
AI, robotics, and cities — intelligence and infrastructure as partners in thriving, not only engines of extraction.
Space and first contact — exploration as shared purpose, not only conquest theater.

The competition’s own brief says it well: technology solving problems, humanity thriving (not merely surviving), a future worth building, and stories that move people emotionally. The Top 50 are the proof that creators worldwide answered that brief with ambition.

Trailers Beat Paper Scripts — And AI Changed Who Can Compete

For decades, “vision” in innovation and entertainment often traveled as a PDF: treatments, decks, and scripts that only a small room could feel. A trailer is different. In three minutes you either earn belief or you do not. You show the stakes, the texture, the emotional residue. Creative teams get to demonstrate their thinking — world, tone, character, craft — over and above the traditional paper scripts that usually get circulated and politely ignored.

AI did not invent storytelling. It did change the cost of a compelling, professional-looking trailer. Small teams can now prototype cinematic language that once required budgets only studios could touch. That is not a guarantee of soul — fluency without contact is still decoration — but it is a genuine opening. More than 2,500 submissions is not a marketing slogan. It is evidence that the barrier to showing a future dropped, and the world answered.

Used well, AI becomes a soft landing for creation: glue and production friction absorbed so human judgment, taste, and meaning stay in the frame. Used poorly, it becomes dystopia cosplay at higher RPM. The Future Vision XPRIZE rewards the former — visions with craft and hope that still feel earned.

Pairwise Voting Is Open on the 50 Finalists

Right now the public gets a real job. The SPECS Audience Choice Award puts $100,000 behind crowd favorites — $50K for first, $30K for second, $10K for third, and $5K each for fourth and fifth — decided entirely by vote. Crowdvoting is powered in partnership with SIV.org, and the experience is built as a simple, human question: Which future do you prefer?

That pairwise framing matters. You are not ranking fifty titles in the abstract. You are choosing between living visions — side by side — the way culture actually chooses what it wants more of. Watch. Compare. Vote. On September 25, the Top 5 also screen live in Los Angeles, with the grand prize path aimed at producing the winning feature with Range Media Partners and a $2.6M+ package ($100K cash for screenplay development plus $2.5M equity investment toward production), alongside runners-up and Top 10 prizes across the wider pool.

How to Vote — and a Preview of My Top 3

You can watch the Top 50 and cast your Audience Choice votes at https://vote.futurevisionxprize.com/. It takes about a minute to start — and every pairwise choice is a small act of futurology: telling the culture which north stars deserve oxygen.

Here is a preview of my Top 3 from the fifty. These are not the only films worth your time — watch widely — but they are the three I keep returning to:

1. PROVENANCE — Chris Winterton

Themes: Memory · Biotech · Connection. In 2160, ancestral memory is inherited through craft, and a young ceramicist starts inheriting the one memory she cannot hold. Human-centered sci-fi at its best: technology intimate with identity, dignity still in the room.

Watch PROVENANCE on YouTube · Official selection page

2. Somewhere Past Midnight — Felix Roumagnac

Themes: Consciousness · Connection. Two teenagers meet inside on-demand lucid dreams and go looking for the boundless world childhood promised. A reminder that optimistic futures are not only about machines — they are about what we still long for when the tools get powerful.

Watch Somewhere Past Midnight on YouTube · Official selection page

3. Rock Rider — Christof Vonbank

Themes: Space · First Contact. A space trucker hauling a town-sized asteroid to an Earth he’s never touched finds a stowaway carrying proof we were never alone. Exploration with grit, wonder, and a future that still has room for surprise.

Watch Rock Rider on YouTube · Official selection page

Then go vote for the futures you prefer: https://vote.futurevisionxprize.com/. Learn more about the competition at futurevisionxprize.com.

Stories shape what we fund, what we build, and what we forgive ourselves for wanting. Future Vision XPRIZE is a rare chance to put public imagination on a scoreboard that still has money, stages, and makers attached. Watch the fifty. Prefer a future on purpose. Soft landings for humanity start with north stars we can feel.

I’m curious! Please SHARE YOUR TOP 3 in the comments.

Frequently Asked Questions

What is the Future Vision XPRIZE?

Future Vision XPRIZE is a global sci-fi film competition from XPRIZE (with partners including Google and Range) inviting creators to submit up to three-minute trailers of optimistic, abundant futures. The prize pool is $3.5M+, with a $2.6M+ grand prize path to develop the winning vision into a feature film.

How do you vote in the Future Vision XPRIZE Audience Choice Award?

Go to https://vote.futurevisionxprize.com/ and compare finalist visions in a pairwise “Which future do you prefer?” experience. The SPECS Audience Choice Award distributes $100,000 based entirely on public voting. You can also browse all 50 official selections at https://fvxp.moonshots.com/.

How many submissions did Future Vision XPRIZE receive?

More than 2,500 films were entered worldwide. Fifty were selected as official finalists for public voting and the path toward live finals in Los Angeles on September 25, 2026.

What themes appear in Future Vision XPRIZE finalists?

Finalist themes span AI, biotech, cities, connection, consciousness, energy, first contact, longevity, memory, nature and climate, oceans, robotics, and space — unified by the remit of technology solving problems and humanity thriving in a future worth building.

Can AI be used to create a Future Vision XPRIZE trailer?

Yes. Competition guidelines allowed any production tools — traditional filming, animation, AI, or hybrids. AI lowered the barrier to professional-looking trailers and helped enable the scale of 2,500+ submissions, while human craft and hopeful storytelling remain what the remits reward.

Image Credits: Cursor

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Cursor to clean up the article.

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The Surprising Innovation History of the Bicycle

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Pedal Power

The Surprising Innovation History of the Bicycle

GUEST POST from John Bessant

Bicycles are big business. It’s hard to get an exact figure but estimates suggest there are around 2 billion bikes in the world today. And of course they exist in all sorts of shapes and sizes — town bikes, racing bikes, mountain bikes, foldable bikes, electric bikes and many more besides. They’re available in cutting-edge high tech versions but their underlying design is very simple. They’re very green — once built they can be repaired and resurrected, some live for ages, handed on from generation to generation.

But bicycles weren’t always around and perhaps it’s worth reflecting a little more on their history, not least because it can teach us some useful lessons about innovation. In particular how (or not) to manage it for impact and scale.

In the earliest days — around 3500 BC — the Mesopotamians used them to make pottery which seems to be the first application of this breakthrough idea. The problem with using them for transport wasn’t so much the wheel as finding an axle strong enough to enable the wheels to work. It took another 300 years before new materials and better carpentry techniques led to their being fixed to chariots and ushering in the era of mobile warfare. But once the wheels started rolling they were attached to an increasing variety of military and domestic vehicles, so it was only going to be a matter of time before someone came up with the idea of using them to enable personal transportation.

Well quite a lot of time, actually. Although there’s probably a sketch for something resembling a bike in Leonardo da Vinci’s notebooks or in some other inventor’s imagination, the reality is that it wasn’t until the early 19 century that the vehicle that we know and love began to see the light of day. That shouldn’t surprise us — innovation depends on a mixture of needs and means and the idea of personal transportation never mind the technologies to enable it was not a particularly high priority. People didn’t travel far — and if they did Nature had already supplied a robust solution in the form of horses (or mules, camels and other alternatives).

The average human being can walk at around 5 km per hour so covering any distance is going to take time and effort. Enter Baron von Drais, a minor aristocrat in Germany who in 1817 came up with the ‘Laufmaschine’ — walking machine — otherwise known as the Draisienne. He was already an experienced engineer and inventor, having come up with several working prototypes for devices like a piano music recording system, a periscope, and a typewriter. (All ideas which turned out, much later, to have considerable significance but not in the form he developed them). And he had a passion for horseless transportation.

This wasn’t some idle curiosity or pet project. Times were tough in the years of the Napoleonic wars and grain prices were high, something not helped by the failure of harvests in 1816. This was the so-called ‘year without a summer’ when the fallout (literally) from a volcanic eruption in south east Asia blotted out the sun. People died of starvation — and horses had an even harder time of it, either starving themselves or else used for food. The possibilities of their being used for transportation shrank faster than the animals themselves.

Drais was also aware of new technologies and materials which he could make use of and he developed a working prototype of his machine on which he could cover the kilometres around his home town of Karlsruhe. He experimented with variations including a four wheeled passenger carriage powered by an (unlucky) servant whose job was to pedal on planks connected to the wheels. But his breakthrough idea was a two-wheeler — the Draisienne. This did away with pedals; instead the rider sat and scooted along the ground with his feet — a kind of adult version of the child’s hobby-horse.

There was nothing childish about the impact this had on moving around the place though. On 12 June 1817, a crowd gathered along the best road in Mannheim, Germany to watch him climb aboard and set out for the Schwetzinger Relaishaus (a coaching inn, located in nearby Rheinau. Less than an hour later, he was back, having completed the 13km round trip in a quarter of the time it would take to walk.

He was a man of vision — and saw the potential for what he had built. By October 1817, he had produced 3-page brochure of laufmaschine designs which pictured possible applications (such as for military couriers or in the postal service) as well as general and leisure transport. He proposed different models with both 2 and 4 wheels and even a tandem and potential customers could choose between standard machiens or customised version. The French version of the brochure, published a year later, included accessories such as lamps, an umbrella and even a sail to help with extra momentum on windy days.

Drais’s laufmaschine was pretty heavy by today’s standards, weighing in at 22kg, made mostly of wood but with hoops of iron nailed to the wheels to function as tyres. This design had an unfortunate side-effect because it made any journey on the fairly primitive roads of the time somewhat less than comfortable. At least the machine was blessed with a brake on the rear wheel; perhaps more important were some of the technologies Drais put to use in his design, like the brass bushes inside the wheel bearings (which enabled the wheels to turn freely) and a trailer to the front wheel which helped the rider maintain balance.

Drais had the vision to see the possibilities in his machine — but he didn’t really have a business model to help him create and capture value from it. Although he staged a number of impressive demonstrations around Europe the reception was mixed and once the novelty wore off the market retreated to being one for hobbyists and pleasure seekers. Riding rinks (where customers could rent a machine for an hour or so) appeared in the parks of various European cities but the mainstream dream of providing personal transportation faded. It wasn’t helped by the appalling state of the roads at the time; without any form of shock absorbers the seat, despite being well-padded, was not a comfortable place to spend much of the day.

‘All’s fair in love and war’ is a principle which often also seems to extend to innovation. The pattern is one of imitation and the first mover is not always the one who can gain advantage, especially if they have inadequate protection for their intellectual property. Drais had tried to patent his idea but it only applied locally, a loophole quickly spotted and exploited by an Englishman, Denis Johnson. He’d seen the early demonstrations and guessed at the significant opportunity such machines might offer. So he set about patenting the idea in England and then building in more systematic fashion a business model around which it might be exploited.

Johnson was a coachmaker so he quickly worked out how to build the machines; what he had to do was create and grow the market. He advertised, offered demonstration machines, organised racing competitions and even established two riding schools where people could learn the skills involved. He adapted the product so that his ‘pedestrian curricle’ had a Ladies Walking Machine variant with a lower saddle such that women could mount the machine decorously.

He was particularly successful in attracting the attention of the young men of the time. This was the era of Beau Brummel and the London Dandies and they enthusiastically took up the idea, adding to it all sorts of fashion accessories — boots, gloves, etc — without which the daredevil owner would not be seen about town. Its popularity amongst this group was heightened by the inherently unsafe nature of something ridden about narrow streets at (relatively) high speed which offered thrills (and accidents) a-plenty until an increasing number of city authorities began banning the machine

It was an expensive hobby. Retailing for around £10 (about £750) it carried additional running costs. Riders wore out their expensive leather boots surprisingly rapidly, and the imposition of fines of £2 (£150 today) for riding on the pavement added to the burden. The fashion for draisiennes began to fade but the real reason for their failure to reach a wider market was down to much simpler economics. By 1820, the price of oats had come back down to pre-1815 levels, and horses were readily available to those who could afford them.

Innovation isn’t just a gleam in the eye, a flash of insight and then instant creation. It’s a lot of hard work, experimentation and improvisation to bring that dream to reality. But even when the first fruits are there there’s still plenty of room for improvement. As Johnson showed, there’s plenty of scope for doing things better, sorting out the bugs and wrinkles, continuously improving on the design. It’s a pattern of restless experimentation, pushing the frontiers of what might be possible. Metalworking technology in particular was improving such that machines could be made strong and (relatively) light, displacing wood as the only means of construction. People explored using different numbers of wheels — two, three, four, more even — opening up the possibilities of carrying multiple passengers.

But innovation is also about sudden leaps, of someone else very often picking up the baton and giving the wheel an extra hard push that sends it off in a new direction. Sometimes this is about timing — a technology which wasn’t available earlier on suddenly appears . or a market which didn’t exist begins to grow to the point where there is a demand for the innovation, pulling it in new refreshed directions. Whatever, this pattern of ‘punctuated equilibrium’ is at the heart of most innovation stories. And in the case of the bicycle it certainly was.

If you are going to have a mysterious legend to weave about the next phase of bicycle innovation where better to do it than Scotland? Land of towering mountains, shady glens, deep lochs and plenty of rain to fill them. Shrouded in mists and secrecy — and home, amongst others to a blacksmith named Kirkpatrick McMillan.

Macmillan completed construction of a pedal driven bicycle of wood in 1839, one which also included iron-rimmed wooden wheels, a steerable wheel in the front and a larger wheel in the rear which was connected to pedals via connecting rods. Various accounts tell of his travelling about the roads near Kier and regularly making the journey to the town of Dumfries (14 miles away) in less than an hour.

He was a modest man and his claim to innovation fame doesn’t rest on patents so much as PR, particularly the research of his relative James Johnston in the 1890s. Johnston wanted “to prove that to my native country of Dumfries belongs the honour of being the birthplace of the invention of the bicycle”. He might have been a little creative with his reworking of history, suggesting for example that Macmillan was the gentleman in question in a Glasgow newspaper report in 1842 of an accident in which an anonymous “gentleman from Dumfries-shire… bestride a velocipede… of ingenious design” knocked over a pedestrian in the Gorbals and was fined five British shillings”.

A criminal record is perhaps not the strongest piece of intellectual property protection and a more robust claim to be the pedal innovator lies with the French. Specifically a young blacksmith and machinist from the town of Nancy called Pierre Lallement. He developed his ideas in 1863 and showed them off publicly during the next year; moved to the USA in 1865 and in the following year registered US Patent number 59915 for his version of the ‘velocipede’.

So most people give the pedal crown — and with it the title of inventor of the modern bicycle — to Lallement. But he was not alone.

In the early 1860s Pierre Michaux (yet another blacksmith) had a successful business producing parts for the carriage trade and had diversified into making “vélocipède à pédales” on a small scale. Across Paris two brothers, Andre and Rene Olivier were students but also came from a wealthy family. This enabled them not only to be early adopters of the bicycle, (enjoying a memorable road trip in 1865 from Avignon to Paris which took them 8 days) but also to become the first entrepreneurs in the game. They saw the considerable potential in pedal cycles and teamed up with Michaux, brought in another friend George de la Boublise and in 1868 set up a partnership to make and sell them.

For a while France (and Paris with its smooth flat roads) became the focus of a market which grew in popularity on both sides of the Atlantic. But a combination of the Franco-Prussian war of 1870 (which stopped French cyclists) and bad roads (whose boneshaking characteristics held back even the hardiest of north American users) meant that the centre of innovation gravity moved to Britain.

Pedal power depends on how much you can push — and cycle design next began to explore ways of maximising this. Two wheels of equal size aren’t particularly good in this equation; better is to have as long a stride as possible since the larger the wheel, the further you can go with one rotation of the pedals. So wheels became higher and higher, the only limit being the length of the rider’s legs. It’s an idea which is good for propulsion but not so good for steering or balance. And so bicycles became ever more exotic looking in their arrangements of wheels and sizes, not least giving birth to the familiar ‘penny farthing’ shape.

But although high wheelers experienced some market growth they weren’t really practical for the average man or woman on the street. Enter John Kemp Starley, an English inventor who came up with a winning idea for a “safety bicycle”, one which would appeal to a much bigger market. His first model was the “Ariel” launched in 1871 and although still featuring wheels of different sizes it was getting closer to a configuration which people would accept. Not least because he integrated many of the key features which people valued — improvements in stability, comfort, usability _especially steering), and all at a price they could afford.

Starley was a classic innovator and over the next fifteen years he developed an increasing range of machines, drawing in ideas and technologies from all over the place. Learning all the time with the market about what it actually wanted, not least through the experience of dissatisfied riders.

For example he sorted out the problem with the wheels. Early bikes had heavy wooden wheels with iron rims but in 1849 William Stanley had invented steel-wheel spider spokes. In 1868, Eugene Meyer in Paris developed an all-metal wheel that relied on the tension of wires rather than compression of heavy metal spokes to achieve structural integrity. Two years later, William Henry James Grout, a builder of velocipedes from Shadwell, London, patented spokes that had eyed nipples at the outer end. Starley drew these ideas together to create (and patent) the spoked wheel in 1874 which gave a much more comfortable ride because of its sprung nature and it also made bicycles much lighter.

In similar fashion he took other ideas and used them as ingredients in the innovation soup which was now coming nicely to the boil. Finally in 1885, Starley introduced the “Rover.” With its nearly equal-sized wheels, centre pivot steering and differential gears that operate with a chain drive, Starley’s “Rover” was the first highly practical iteration of the bicycle. Like Henry Ford with his Model T twenty years later he’d produced the bicycle for Everyman (and woman). It became the dominant design — and it’s pretty much the same shape as we’d recognise today.

Starley’s work kick-started the industry into its growth phase. His company grew and with it the product range, opening up cycling to a wide market in the ways Baron von Drais had dreamt about seventy years earlier. The safety bicycle completely displaced the high wheeler and by 1889 there were around 200,000 bicycles on the roads of Europe.

Ten years later over a million machines were being pedalled around the world. Innovation didn’t stop there — and with each new development the pace of growth accelerated. Pneumatic tyres made of rubber made for a smoother ride, chain drives meant the power came from the rear wheel leaving the front to steer and making cornering easier. The application of gears helped tame even the most stubborn of inclines and opened up the whole landscape to conquest by bicycle. And inventors began looking to provide alternatives to legs as the main power source, with a battery electric cycle appearing. And over in Germany Gottfried Daimler played around with hooking an internal combustion engine up to a cycle to create the motorbike…..

So it’s not entirely surprising that we now have 2 billion bicycles pedalling their way along roads and up and down the mountainsides of the world. There’s still plenty of scope for further innovation, for branching in new directions and picking up old ones — the e-scooter craze looks like a good candidate for becoming the next major shift, with not a few nods back in the direction of good old Baron von Drais. What’s clear , though, is that these innovations will only take hold and become widely adopted if we pay attention to working at the system level.

Successful scaling of innovation is all about wheels within wheels…

(A little song to close with….)

You can listen to a podcast of this story here

And watch a video version on my YouTube channel here

If you’d like more songs, stories and other resources on the innovation theme, check out my website here

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

Originally published at https://johnbessant.substack.com on July 24, 2026.

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Do Your Innovation Words Match Your Actions?

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Do Your Innovation Words Match Your Actions?

GUEST POST from Mike Shipulski

Innovation isn’t a thing in itself. Companies need to meet their growth objectives and innovation is the word experts use to describe the practices and behaviors they think will maximize the likelihood of meeting those growth objectives. Innovation is a catchword phrase that has little to no meaning. Don’t ask about innovation, ask how to meet your business objectives. Don’t ask about best practices, ask how has your company been successful and how to build on that success. Don’t ask how the big companies have done it – you’re not them. And, the behaviors of the successful companies are the same behaviors of the unsuccessful companies. The business books suffer from selection bias. You can’t copy another company’s innovation approach. You’re not them. And your project is different and so is the context.

With innovation, the biggest waste of emotional energy is quest for (and arguments around) best practices. Because innovation is done in domains of high ambiguity, there can be no best practices. Your project has no similarity with your previous projects or the tightest case studies in the literature. There may be good practice or emergent practice, but there can be no best practice. When there is no uncertainty and no ambiguity, a project can use best practices. But, that’s not innovation. If best practices are a strong tenant of your innovation program, run away.

The front end of the innovation process is all about choosing projects. If you want to be more innovative, choose to work on different projects. It’s that simple. But, make no mistake, the principle may be simple the practice is not. Though there’s no acid test for innovation, here are three rules to get you started. (And if you pass these three tests, you’re on your way.)

If you’ve done it before, it’s not innovation.
If you know how it will turn out, it’s not innovation.
If it doesn’t scare the hell out of you, it’s not innovation.

Once a project is selected, the next cataclysmic waste of time is the construction of a detailed project plan. With a well-defined project, a well-defined project plan is a reasonable request. But, for an innovation project with a high degree of ambiguity, a well-defined project plan is impossible. If your innovation leader demands a detailed project plan, it’s usually because they are used running to well-defined continuous improvement projects. If for your innovation projects you’re asked for a detailed project plan, run away.

With innovation projects, you can define step 1. And step 2? It depends. If step 1 works, modify step 2 based on the learning and try step 2. And if step 1 doesn’t work, reformulate step 1 and try again. Repeat this process until the project is complete. One step at a time until you’re done.

Innovation projects are unpredictable. If your innovation projects require hard completion dates, run away.

Innovation projects are all about learning and they are best defined and managed using Learning Objectives (LOs). Instead of step 1 and step 2, think LO1 and LO2. Though there’s little written about LOs, there’s not much to them. Here’s the taxonomy of a LO: We want to learn if [enter what you want to learn]. Innovation projects are nothing more than a series of interconnected LOs. LO2 may require the completion of LO1 or L1 and LO2 could be done in parallel, but that’s your call. Your project plan can be nothing more than a precedence diagram of the Learning Objectives. There’s no need for a detailed Gantt chart. If you’re asked for a detailed Gantt chart, you guessed it – run away.

The Learning Objective defines what you learn, how you want to learn, who will do the learning and when they want to do it. The best way to track LOs is with an Excel spreadsheet with one tab for each LO. For each LO tab, there’s a table that defines the actions, who will do them, what they’ll measure and when they plan to get the actions done. Since the tasks are tightly defined, it’s possible to define reasonable dates. But, since there can be a precedence to the LOs (LO2 depends on the successful completion of LO1), LO2 can be thought of a sequence of events that start when LO1 is completed. In that way, an innovation project can be defined with a single LO spreadsheet that defines the LOs, the tasks to achieve the LOs, who will do the tasks, how success will be determined and when the work will be done. If you want to learn how to do innovation, learn how to use Learning Objectives.

There are more element of innovation to discuss, for example how to define customer segments, how to identify the most important problems, how to create creative solutions, how to estimate financial value of a project and how to go to market. But, those are for another post.

Until then, why not choose a project that scares you, define a small set of Learning Objectives and get going?

Image credits: Pixabay

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Unleashing Your Innovation Potential

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Unleashing Your Innovation Potential

GUEST POST from Janet Sernack

It is not unusual, especially in the corporate world, to label someone who disrupts and challenges the status quo, or what others say, as argumentative and “oppositional”. According to Human Synergistics, the Oppositional Style, in their circumplex, when measured as a dominant leadership style, is summarized in their 360-degree Leadership Styles Inventory (LSI) by two items: “usually against things” and “opposes new ideas.” It labels the person, or leader as being aggressively defensive and causes them to disengage by avoiding engaging in any kind of conflict, dissent and disagreement. This inhibits and prevents them from unleashing their creative thinking and their innovation potential.

In my many years as a corporate trainer presenting high-performance cultures and transformational leadership programs, I learned to apply my imagination, curiosity and inquiry skills to be attentively present, listen deeply and ask generative questions. This helped me develop strategies to unleash a person’s innovation potential by encouraging and enabling thoughtful dissent and disagreement. I learned to uncover and recognize a leader’s energy and positive intent behind many of the scary, argumentative, hostile, contrary, critical, and aggressive behaviors directed at me, especially in my years upfront as a female corporate trainer in many toxic organizational cultures.

I often found that they were compromised in some way by their personal and family needs and values, their assumptions and beliefs about themselves and their performance at work, poor physical and mental health, and/or a lack of emotional well-being. Any one of these factors made them self-protective, leading to either overt aggression toward others, passive avoidance of conflict, or an unconscious refusal to engage in thoughtful dissent and disagreement because they did not want to be perceived as hostile and argumentative.

All of these unconscious reactive responses inhibited them from unleashing their creative thinking and innovative potential.

This blog explores the power of unleashing creative thinking and innovation potential through supporting people to thoughtfully dissent and disagree – by using conflict as a catalyst for better decision-making, problem-solving, and strengthened collaboration and innovation – not as a barrier.

Unconscious reactive responses

This manifests as a neurologically challenging reactive response, as people’s brains are wired to defend and protect them to ensure their survival. These defensive responses are composed of fight/flight/freeze/fawn reactions and arise when people face what their neurology (the limbic system) perceives as a threat to their security, safety, or survival.

These reactions stem from past experiences and traumas that are often stored in people’s somatic memories. They become neurologically wired and embedded in people’s habitual ways of being unless they are noticed, labelled, accepted, acknowledged and owned. Until there is a safe holding space for this to happen, it will be impossible to unleash their creative thinking and innovation potential.

Safe holding spaces

Once a safe holding space is established, an oppositional person can be carefully and empathetically challenged, disputed, deviated from, and redirected towards more self-regulated, resourceful, and emotionally healthy states and new approaches. This involves bravely engaging them in thoughtful dissent and disagreement, despite being encased in a toxic organizational culture. Its about building permission, safety and trust to encourage creative thinking that unleashes a persons innovation potential.

Fight-flight-freeze and fawn responses

The amygdala is designed to detect threats and trigger the fight-flight-freeze response to help people survive

A fight response involves standing our ground when we feel threatened, driven by anger, fear, and anxiety.
A flight response entails moving away from or avoiding a situation to reduce painful feelings.
A freeze response involves shutting down, feeling numb, or experiencing paralysis to reduce painful feelings, resulting in immobility.
A fawn response involves appeasing and placating others or seeking approval while neglecting the need to feel safe.

Role of smart conflict, thoughtful dissent and disagreement

This is particularly evident in political and organizational contexts, where people are suffering from change fatigue and overwork. As a result, they unconsciously disengage from their work, families, and daily lives through a flight-or-freeze response, driven by burnout, the pursuit of external validation (a fawn response), or frustration and anger (usually a fight response). A combination of any or all of these largely unconscious but fully present reactive responses creates toxic organizational cultures, in which leaders’ behaviors are either passively or aggressively defensive in their attempts to meet people’s core security, safety, and survival needs. Leaders avoid encouraging or engaging in thoughtful dissent and disagreement that mobilizes people’s creative and critical thinking and unleashes their innovation potential.

The constraints and challenges of the pandemic, coupled with threats to people’s stability and the desire for certainty, also led many people in organizations to fear that their needs for security, safety, and survival would not, and could not, be met. These fears unconsciously intensified people’s defensiveness and reactivity, leading to immobilization through passivity, helplessness, hopelessness, powerlessness, disengagement, and detachment. This indicates a lack of emotional intelligence, largely due to the absence of initial self-regulation and self-leadership strategies. It is easier and sometimes safer to be a victim and blame others for any negative, pessimistic, or painful feelings of shame, guilt, and embarrassment, resulting from competing commitments, value violations, thought distortions, and emotional dissociation.

These emotionally overwhelming and cognitively overloading factors are also accepted inhibitors to unleashing a person’s innovative potential, especially when they are unable to engage in thoughtful dissent and disagreement under the influence of a toxic organizational culture.

Making the shift

To support people to effectively shift this way of being and safely unleash their creative thinking and innovation potential:

It is crucial to develop and apply the generative discovery skillset to welcome dissent and thoughtful disagreement:

Notice: by being aware and attentively present to what is happening to, and within the person, neurologically and physiologically, emotionally, cognitively and physically.
Disrupt: by being curious and safely asking open, explorative discovery questions, and by listening carefully to hear and notice what is really going on for them.
Dispute: by safely summarizing and challenging their assumptions, perceptions and perspectives, asking evocative and provocative questions that encourage contrary thinking, diversity of thought, differences and constructive disagreement.
Deviate: by safely summarizing and eliciting a mindset flip or an agility shift in the oppositional person, directing their creative energy towards constructive behaviors that deliver a positive outcome.

This enables people to redirect their emotional energy and move away from unresourceful internal thought patterns and distortions. It also encourages them to open their minds to thoughtful dissent and disagreement, allowing them to think differently and enter creative and innovative realms.

This is impossible when toxic organizational cultures force people to hide behind conventional, rigid, and closed minds that won’t allow them to rock the boat and be, think and act differently by intentionally using conflict constructively by embracing dissent and thoughtful disagreement

At the same time, it’s crucial to safely, empathically and compassionately evoke and provoke an opening of people’s hearts by purposefully and meaningfully aligning their needs and values, so that the change motivates them to change meaningfully and purposefully. This creates the safe holding space that allows them to let go of the need to be in control and be open-willed, unleashing their creative thinking and innovation potential to make the shift to the creative and innovative realms.

Empowering people and teams to redirect their emotional energy towards opening their minds to thoughtful dissent and disagreement allows them to handle hard conversations with constructive and creative intent.

Welcoming dissent and thoughtful disagreement involves daring yourself and others to be and think differently. Being able to think creatively maximize a person or a teams innovation potential, unleashes their human ingenuity in the age of AI, and mobilizes their collective intelligence to lead, manage, or implement constructive and sustainable change.

Leveraging constructive conflict, dissent and thoughtful disagreement unleashes people’s creative thinking and innovation potential and is a necessary part of enabling AI, digital transformation and innovation initiatives to succeed in uncertain and disruptive times.

Find out more about our work at ImagineNation™ and The Start-Up Game.™ Discover our collective learning products and tools that can be customized as playful bespoke corporate learning programs. Our blended and transformational change and learning programs provide a deep understanding of the language, principles, and applications of an ecosystem-focused, human-centric approach and emergent structure (Theory U) to innovation and entrepreneurship. It will also upskill people and teams, developing their future fitness within your unique digital transformation and innovation initiatives. Please find out more about our products and tools.

Image Credit: Gemini

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Top 10 Human-Centered Change & Innovation Articles of July 2026

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Top 10 Human-Centered Change & Innovation Articles of July 2026 Drum 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 July’s ten most popular innovation posts:

What Happens When AI Becomes Your Customer? — by Shep Hyken
The Experience Economy 2.0 — by Braden Kelley
How to Calculate the ROI of Customer Experience — by Braden Kelley
Strategic Foresight: A Practitioner’s Guide to Thinking About the Future — by Braden Kelley
Innovation or Not — InTruth — by Braden Kelley
Innovation Framework Examples: 7 Real-World Cases That Show How They Work — by Braden Kelley
The Personal AI Renaissance — by Braden Kelley
Your 3 Phase AI Journey — by Geoffrey Moore
Why So Much Bullshit? — by Greg Satell
Creating an Innovation Edge — by John Bessant

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

The Neuroscience of Creativity — by Braden Kelley
The Synthetic Organization — by Braden Kelley
Use Failure as Rocket Fuel for Success Like SpaceX — by Robert B. Tucker
Crossing the Chasm of Fear — by Braden Kelley
4 Simple Rules That Make You Exponentially More Effective and Productive — by Greg Satell

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 five years:

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Case Study – Innovating Around a Disruption

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Škoda built a bike bell that beats noise-cancelling headphones

Case Study - Innovating Around a Disruption

GUEST POST from Jason Hauer

A near-miss on a London street became Škoda’s smartest marketing spend in years. The bigger idea: someone else’s AI has broken something in your category too, and fixing it might be your next growth play.

Ben Fraser was walking to work near Borough Market, headphones on, when a cyclist nearly hit him. The cyclist had been ringing his bell the whole way down the street. Fraser never heard a thing.

Fraser works at PHD Media, and the near-miss became a brief. Transport for London data showed bike-pedestrian collisions rose 24% in 2024, with cyclists set to outnumber car drivers in London for the first time this year. One quiet contributor: active noise cancellation. The bike bell had worked for a century. On a growing share of pedestrians, it simply stopped working, because an algorithm in their headphones was scrubbing it out of the air.

Škoda, the Czech carmaker owned by Volkswagen Group and one of Europe’s biggest auto brands, took the problem to acoustics researchers at the University of Salford. Testing turned up something useful: noise-cancelling algorithms struggle with a narrow band between 750 and 780 hertz. So Škoda built the DuoBell, a second resonator tuned to that gap, plus a hammer that strikes in an irregular rhythm the algorithms can’t predict. Fully mechanical. A piece of metal designed to beat software.

They tested it with a fleet of Deliveroo riders in London, people whose income depends on being heard in traffic. One rider said that with the bell, he finally had a voice in the streets. The riders wanted to keep them.

Pedestrians in noise-cancelling headphones gained up to five extra seconds of reaction time and up to 22 metres of additional distance. Roughly four times the cut-through of a standard bell. Škoda published the underlying research as an open-source white paper, and the work took Silver in Creative Data at Cannes in June. One case-study breakdown projects €79 million in vehicle sales connected to the project, which fits how the company sees it. Škoda started life as a bicycle maker in 1895 and still sponsors the Tour de France. The fix sits inside a hundred-year-old brand truth.

Nobody at the headphone companies set out to make cyclists invisible. Noise cancellation was a good product decision that quietly broke a safety system in a completely different category, and the breakage sat unowned for years while collisions climbed. That pattern is everywhere now. Every AI deployment of the last three years created some downstream effect in somebody else’s business.

Somebody is absorbing that cost right now, and no line item owns it.

Look at your own category through that lens. A century-old bell stopped working because ears started running software. Every signal your company sends was built the same way, for a human on the receiving end, and a machine now sits between you and that person. Your buyer’s first impression of you is written by a model you’ve never briefed. Everything you send after that runs through software tuned by companies with no stake in whether you’re heard. Somewhere in that chain, something that worked in your category for decades is being scrubbed out of the air, and the loss surfaces in a metric you’ve been explaining some other way. The collision numbers sat in Transport for London’s data before anyone thought to blame headphones. Your version of that number already exists. It’s in a dashboard right now, filed under something else.

Škoda’s move was to treat the breakage as a market. Find the gap, spend the budget on fixing it, and let the fix carry the brand. The bell exists because someone measured a frequency nobody had bothered to look for.

Skoda DuoBell statistics

WHAT TO DO THIS WEEK

The first conversation moved. Your customer now asks a model before they ask you, whether that’s a buyer building a shortlist or a client second-guessing your advice. This week, put your customers’ most common questions to the major models, worded the way they’d word them. What comes back is your new first impression.

The unfiltered channels are still open. Every digital signal you send now clears someone else’s software before a human sees it. Nothing stands between a room and the people in it. Škoda answered an algorithm with a piece of metal; your equivalent might be a dinner, or a printed report that lives on a desk for a month. Pick the one message this quarter that can’t survive being flattened and spend real money delivering it by hand.

The next breakage is already in somebody’s data. The collision numbers sat in Transport for London’s files before anyone blamed headphones. Spend an hour with your team on two questions. What have our own AI deployments broken for the people downstream, the customer who needed a person, the partner whose emails our triage now buries? And what’s degrading in our category that nobody has claimed yet? One of those answers is a liability you can still price before a competitor does. The other is a bell nobody has built.

Whatever you find, take it all the way to metal. Škoda could have stopped at the white paper. The bell is the reason you’re reading about them.

A century-old bell needed one new frequency to work again. Your category has a gap like that somewhere.

What’s quietly stopped working in your category?

Image credit: Jason Hauer

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Category Creation

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Category Creation

GUEST POST from Geoffrey Moore

Category creation is a critical success factor for start-ups bringing to market a disruptive innovation that calls for a new ecosystem, to support a new class of use cases, funded by a new budget line item. If the category does not form, the start-ups have no place to hang their hat. They can acquire early adopter customers via a bespoke project approach, but they cannot scale any further without help from the rest of the marketplace.

Similarly, established enterprises in mature categories also need to find new venues for growth if they are to break free from their value-investor-set market caps and create net new shareholder value. Whether through acquisition or in-house innovation, they, too, can have the challenge of category creation. So, in both cases, companies need to reengineer the marketplace in order to realize their ambitions. The question is, what would make the marketplace want to lean in?

Marketplaces are made up of ecosystem players, be they partners, competitors, or an installed base of customers. All these constituencies keep their eyes out for disruptive developments that could either benefit or jeopardize their future performance. The early adopters are typically motivated by the benefits, seeking a first mover advantage, while the early majority normally takes a wait-and-see approach, thereby creating a chasm, which in turn can be crossed wherever there is an urgent customer problem that is resisting standard solutions and thus warrants taking a novel approach to solve it. If the category does show it is getting traction, then all those wait-and-see pragmatists will begin to feel threatened by FOMO (Fear of Missing Out), and that is what creates a tornado of demand that puts the category permanently on the map.

Okay, so there is reason to believe that under the right circumstances, markets will support the creation of a new category. That said, we should not underestimate the power of inertia. Markets do not welcome transformational changes with open arms. Indeed, their default move is to deflect most attempts. What we need is a proven playbook. Fortunately, there is one, written some forty years ago, written by an old boss of mine, Regis McKenna.

The Regis Touch

It is hard to overstate the impact that Regis had on high-tech marketing, especially in its early days when it was trying to break free from advertising as its primary medium. At the time, the tech sector was just emerging, the bulk of spending was in B2B markets, the focus was on automating core business processes, and every buying decision entailed considerable risk, not only in terms of the product and vendor’s staying power but also in terms of the impact of the business processes themselves. As a result, advertising per se was not sufficiently informative or credible to drive purchasing. Regis saw this and, with the help of a talented set of consultants and communications professionals, developed a public-relations-led approach that successfully launched hundreds of new products and created dozens of new categories.

The key to his approach was a framework called the infrastructure model that organized the various audiences and constituencies that make up a marketplace in what one might call a ladder of communications:

Relationship Marketing Infrastructure Model Geoffrey Moore

Here’s how it works. The goal is to convert prospects into customers. In B2B markets, those prospects organize around three centers of interest—the technology itself, the impact on productivity, and the financial returns. These prospects get their information most directly from the media, the technologists from the technical press, the end users these days from social media (no such thing, of course, back in the day), and the executives from the business press. The agents of the press, in turn, get a lot of their information from opinion leaders, be they the industry analysts for the technical press, the influencers for social media, or the financial investment analysts for the business press. Those opinion leaders, in turn, get their information from their engagement with the marketplace itself, be they customers, partners, or competitors already involved with the disruptive innovation.

The point is, any claims about the disruptive innovation are verified and validated by working down this model, which means any communications program should organize around working up the same model. Skipping over any one of these audiences and going straight to the prospects directly—the way advertising does—is bound to fail because you have not got your references lined up and sufficiently informed to support and endorse a high-risk buying decision. Product launches and category creation initiatives, therefore, work up this ladder of communications, rung by rung, starting in the executive suite, moving from there to the product organization, and from there to the go-to-market team. That team, in turn, needs to start with educating the ecosystem players, typically with talks and panel sessions at industry conferences, then connecting with the opinion leaders, typically via one-on-one briefings that end up being two-way dialogs, and only then out to the media that will engage with the target prospects.

Category Creation Playbook

A lot of what would go into a complete playbook is product and market-specific, but there are audience-centric principles that remain relatively constant. The key question in each case is, what is it about the emerging category that would be of interest to this particular constituency? With that in mind, here is a brief take:

Executive team. This team will value growth to boost market cap, something that participation in an emerging category can be expected to deliver, but it may well be reluctant to take transformational risk to achieve it. If this team is not 100% behind the effort, don’t start, as every other rung on the latter ultimately calls for investments that this team must endorse.
Product team. This team has to be all in for a wild ride—and usually is. You have to pressure test their claims nonetheless, as they can often get over their skis, promising more than they can deliver within the window that matters.
Go-to-market team. This team requires maturity and patience. The big sales commissions won’t come until the category enters the tornado, so for now, the focus is on creating a market, not harvesting it. That means paying deep attention to developing the ecosystem, including bringing along the installed base, helping to engage and enlist partners, and (oddly enough) encouraging competitors. The last one is important because, ultimately, a category is defined by a set of competitors, not just one company, so for a healthy growing category you need to have peers that are winning too—hopefully in target market segments that are distinct from yours.
Ecosystem. These are the people your go-to-market team is engaging with. The sales team has the installed base, the business development team, the partners, and the marketing team, the competitors. The goal is to get everyone speaking from their own perspective to reinforce your story that something big is underway. One item of note: With respect to competitors, marketing needs to develop a narrative that has room for more than one winner while at the same time staking out turf where your own differentiation makes you the obvious choice. What you do not want to do is bad-mouth the other team’s products—that will create anxiety that will cause everyone to wait and see some more. So, save your sharp tongue for when you get inside the tornado—that’s the no-holds-barred battleground where a well-placed elbow can make a real difference.
Opinion leaders. The goal here is to get conceptual endorsement for the claims you will be making via the media. Opinion leaders need to maintain their independence and do not want to shill for you or anyone else. What they do want to do is look intelligent and have something differentiated to say. What they want from you is enough context to do their job and no interference thereafter. In addition, opinion leaders want to share their opinions with you, in part to influence your future investments, and so it is just as important to listen and ask them questions as it is to present your own story. With respect to your presentation, demos can be useful, but repurposing a customer sales pitch is not, as this audience is not going to buy your product but rather is going to opine on the reasons why other people might.
Media. This is the means by which you will communicate with the three prospect audience types—the technical team, the end users, and the executive sponsors. Each has a preferred media type—industry press, social media, and business press—and each of these types wants to be treated in its own special way. The technical press wants to talk about the product itself. They want facts, love demos, and like to talk to specialists more than generalists. They also are often happy to beta test products or get any other kind of advanced notice as to what’s coming next. Social media wants to talk about the applications of the product, and the ways in which it will impact end users’ lives. So demos can work here only if they are in service to an end-user story as opposed to a run-through of all the features and functions. The business press wants to talk about the “size of the prize,” the impact of the new technology on productivity, how it will reengineer bottlenecking processes, and thus how much trapped value it will be able to release. Demos are wasted here, but PowerPoint can help a lot.
Prospects. When category creation is the focus, it is important to engage the three types of prospects in the right order. If the technology is outrageous, you need to start with the technical audience first just to earn the right to talk to anyone else. If it is not outrageous, then the executive sponsor needs to be your first port of call. The reason is that the other two audiences will actually be willing to meet with you to learn about the latest and greatest thing, but they will have budget, not permission to get new budget, if the executive sponsor is not on board. So a typical path through a major account would start with an executive from your company having a conversation with the prospective executive sponsor at your target customer, which would lead to a referral to the technical team to test your bona fides, and then on to the end-user team, to validate your productivity claims. Proof-of-concept projects are necessary at the very beginning, but one of the major milestones in category creation per se is to generate enough marketplace acceptance that future prospects will forgo these tests.

To sum up, category creation is an outbound communications effort to orchestrate a coalition of the willing across a laddered set of constituencies, each with its own set of interests. The goal is to build an inbound path of verification that reinforces the new category’s right to existence. Trying to shortcut the outbound process by skipping over one or more audiences will defeat the purpose, as any doubts raised this early in the game result in lost momentum that can never be recovered. There is no magic here, but patience and discipline are required.

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

— Image credit: Pexels

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What Are the Different Types of Innovation?

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What Are the Different Types of Innovation?

by Braden Kelley and Art Inteligencia

What Are the Different Types of Innovation? (Short Answer)

Types of innovation are usually grouped in two ways: by how big the change is (incremental, adjacent or sustaining, radical, and disruptive) and by what changes (product, service, process, business model, experience, and ecosystem). The useful question isn’t “which list is right?” It’s “which type fits the problem, the customer, and our capacity to adopt?”

Don’t pick a type of innovation because it sounds impressive. Pick the type the customer’s job and your organization can actually absorb.

Search “types of innovation” and you’ll get competing lists — ten types, four types, three horizons, incremental versus radical. Below you’ll find a practical way to use both lenses, clear definitions with examples, how incremental differs from disruptive, and five questions for choosing the right type. One reminder up front: type doesn’t override the definition. If it isn’t widely adopted and valued above alternatives, it isn’t innovation yet — see What Is Innovation? A Clear Definition, With Examples.

How Should You Group Types of Innovation?

There isn’t one correct list. There are two useful lenses:

Lens 1 — Degree of change: how far the idea is from today’s offering and operating model (incremental → adjacent → radical / disruptive).
Lens 2 — Where you innovate: which part of the offering or organization changes (product, service, process, business model, experience, ecosystem).

You can mix the lenses. An incremental process innovation is different from a disruptive business-model innovation. Lists conflict because consultants name categories for books; leaders need a decision tool. I also describe how decision-makers feel about these leaps as Safe, Stretch, and Splatter in 3 Innovation Types That Actually Determine Success — that framing sits on top of degree of change, not instead of it.

Taxonomies describe the map. Strategy chooses the route.

What Are the Types of Innovation by Degree of Change?

Type	What it means	Example	When to use
Incremental	Improve what already exists — better, faster, cheaper, more reliable	Successive smartphone camera upgrades	Keep winning today’s customers
Adjacent / sustaining stretch	Apply known capabilities to new customers, channels, or use cases — or known customers to new capabilities	A B2B tool adapted for consumers (or the reverse)	Grow without betting the whole firm
Radical	A fundamentally new approach that remakes how a job gets done	Contact lenses or laser surgery vs. glass spectacles	The current approach is hitting limits
Disruptive	Usually starts simpler, cheaper, or more accessible — often for overlooked customers — then improves until it displaces incumbents (Christensen’s sense)	Streaming video vs. DVD rental for many households	A market ignores a segment or overserves with complexity

Mislabel tells: calling a feature tweak “transformational”; calling adjacency “safe” when it still needs a new go-to-market; inventing something novel that nobody adopts and labeling it radical; using “disruptive” as a synonym for “cool” or “big.” That last habit is a classic costume — see 7 Types of Innovation Theater.

Incremental isn’t lesser. Over time, most value often comes from sustained incremental innovation plus a smaller set of bigger bets. For how invention, innovation, and lasting impact differ, see 7 Differences Between Invention, Innovation, and Impact.

What Are the Types of Innovation by What Changes?

The second lens asks where the innovation lives:

Product — a new or meaningfully improved offering (for example, a bagless vacuum that changed performance expectations).
Service — how help and support create value (empowered service that becomes a reason to choose you).
Process — how work gets done (the shipping container; the surgical safety checklist).
Business model — how you create, deliver, and capture value (razor-and-blades; subscription where ownership was the norm).
Experience — the end-to-end journey and how it feels (retail experiences designed so people can try before they buy).
Ecosystem / system — partnerships, platforms, and networks (app stores and open ecosystems that multiply value).

Finer frameworks (for example, Doblin’s ten types) slice these further into profit model, channel, brand, and more. For most teams, these six are enough to start. Innovating in more than one place at once — product and business model, process and experience — often beats a single feature race.

What Is the Difference Between Incremental and Disruptive Innovation?

	Incremental	Disruptive
Customers	Improves for existing customers	Often starts with overlooked or new customers
Business model	Fits the current model	Often requires a new model
Uncertainty	Lower	Higher; payoff may take longer
Effect on the core	Protects and extends the core	Can threaten the core
How you measure	Performance gains on today’s metrics	Adoption along a new trajectory

Organizations that only fund “disruptive” starve the core. Organizations that only fund incremental get surprised. You need both — with different owners, metrics, and patience. For measures that go beyond idea count, see 12 Metrics That Actually Measure Innovation Value.

How Do You Choose the Right Type of Innovation?

Use these five questions before you fund the next bet:

What job is the customer hiring us to do — and is the current solution failing?
How much change can our customers absorb right now?
How much change can our operating model absorb — skills, channels, metrics, partners?
Are we trying to win today’s game, enter an adjacent game, or change the game?
Who owns adoption — not only the build?

Portfolio advice: run a mix. Most of the portfolio should be incremental and adjacent. A smaller share can be radical or disruptive, with different metrics and more patience. Soft landings match the type to capacity. Hard landings choose the type for the slide title.

The best type of innovation is the one that gets adopted — by the people you meant to serve.

Ready to Take the Next Step?

Knowing the types of innovation is table stakes. Knowing which barriers stop your organization from funding and adopting the right mix — incremental where it belongs, bolder bets where they’re earned — is the real work.

Find out where you stand. Take the free Innovation Maturity Assessment: 50 questions, about 10–15 minutes, scored against a five-level Innovation Maturity Model so you can see your biggest barriers and set a baseline to improve from.

Learn how to remove the barriers. Read Stoking Your Innovation Bonfire, my roadmap for identifying what’s blocking innovation in your organization and building a culture where it can flourish.

A clear taxonomy helps you name the work. A clear picture of your barriers helps you fund the right mix.

FAQ: Types of Innovation

What are the main types of innovation?

The main types are usually grouped by degree of change — incremental, adjacent or sustaining, radical, and disruptive — and by what changes — product, service, process, business model, experience, and ecosystem. Many organizations use both lenses together.

What is the difference between incremental and disruptive innovation?

Incremental innovation improves an existing offering for current customers within the current business model. Disruptive innovation often starts simpler or more accessible for overlooked customers, may require a new business model, and can eventually displace incumbents as it improves.

What is radical innovation?

Radical innovation is a fundamentally new approach that remakes how a job gets done, rather than improving the current method. Contact lenses and laser eye surgery versus glass spectacles are classic examples of radical change compared with incremental improvements to existing lenses.

What are examples of different types of innovation?

Examples include smartphone camera upgrades (incremental), adapting a B2B tool for consumers (adjacent), laser eye surgery versus spectacles (radical), streaming versus DVD rental (disruptive), the shipping container (process), subscription models replacing ownership (business model), and app-store ecosystems (ecosystem).

How do I know which type of innovation to pursue?

Match the type to the customer’s job, how much change customers and your operating model can absorb, whether you aim to win today’s game or change it, and who owns adoption. Most portfolios should emphasize incremental and adjacent innovation, with a smaller share of radical or disruptive bets.

Image credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini and M365 CoPilot to clean up the article, add images and create infographics.

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What is Your Problem?

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What is Your Problem?

GUEST POST from Mike Shipulski

If you don’t have a problem, you’ve got a big problem.

It’s important to know where a problem happens, but also when it happens.

Solutions are 90% defining and the other half is solving.

To solve a problem, you’ve got to understand things as they are.

Before you start solving a new problem, solve the one you have now.

It’s good to solve your problems, but it’s better to solve you customers’ problems.

Opportunities are problems in sheep’s clothing.

There’s nothing worse than solving the wrong problem – all the cost with none of the solution.

When you’re stumped by a problem, make it worse then do the opposite.

With problem definition, error on the side of clarity.

All problems are business problems, unless you care about society’s problems.

Odds are, your problem has been solved by someone else. Your real problem is to find them.

Define your problem as narrowly as possible, but no narrower.

Problems are not a sign of weakness.

Before adding something to solve the problem, try removing something.

If your problem involves more than two things, you have more than one problem.

The problem you think you have is never the problem you actually have.

Problems can be solved before, during or after they happen and the solutions are different.

Start with the biggest problem, otherwise you’re only getting ready to solve the biggest problem.

If you can’t draw a closeup sketch of the problem, you don’t understand it well enough.

If you have an itchy backside and you scratch you head, you still have an itch. And it’s the same with problems.

If innovation is all about problem solving and problem solving is all about problem definition, well, there you have it.

Image credits: Pixabay

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Innovation or Not — InTruth

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Innovation or Not — InTruth

by Braden Kelley and Art Inteligencia

Section I: The Context — The Friction of Unfiltered Information

We live in an age of hyper-abundant, instantaneous media. Live-streamed political debates, rapid-fire press conferences, corporate town halls, and unscripted interviews broadcast continuously across our screens. Yet, alongside this unprecedented access lies a compounding crisis: information pollution. Misinformation, selective statistics, and outright falsehoods move at the speed of light — frequently outpacing traditional journalism, post-event debriefs, and manual fact-checking by hours or even days.

By the time a correction is published, the narrative has already taken root in the public consciousness. The damage is done, and the systemic cost to societal trust is immense.

The Human Dilemma: Cognitive Load in the Attention Economy

For the average media consumer, keeping up with live information requires an exhausting mental calculus. Viewers are caught between two undesirable options:

Passive Acceptance: Consuming content at face value to save energy, thereby absorbing unverified claims and out-of-context assertions.
Active Skepticism: Continuously pausing, opening secondary tabs, and manually searching primary sources to verify claims — a process that destroys flow and creates severe cognitive friction.

In an attention economy built around low-effort, lean-back viewing, asking users to perform manual research while watching live video is a fundamental experience design failure. The friction is simply too high.

Enter InTruth: Shrinking the “Truth Latency”

This is where InTruth enters the frame. Operating as a Chrome extension, InTruth aims to bridge the gap between real-time consumption and rigorous verification. By pairing live automated voice-to-text transcription with continuous, real-time database lookups against verified primary sources, InTruth introduces an automated contextual layer directly over any live video stream.

It seeks to collapse the “truth latency” — closing the critical gap between the moment a claim is uttered and the moment a viewer receives verified context. But does having the capability to cross-reference audio in real time make InTruth a true innovation, or merely a powerful technical demo?

Section II: The Innovation Test — Applying the Value Equation

To evaluate whether InTruth is a genuine breakthrough or merely an intriguing technical novelty, we must look beyond raw technology capabilities and apply a core principle of human-centered change:

Innovation = Value Creation × Value Access × Value Translation

Innovation is never just the underlying technology — it is the holistic system that turns potential value into realized human impact. Because this relationship is multiplicative, if any single variable in the equation drops to zero, the total innovation value collapses to zero. Let’s stress-test InTruth across all three dimensions.

1. Value Creation: Closing the “Truth Latency”

Value Creation represents the raw potential utility of a solution. In the case of InTruth, the potential value is immense. By compressing hours of investigative research into split-second automated lookups, it transforms complex, multi-step investigative work into live, contextual intelligence.

Traditional fact-checking suffers from high “truth latency” — the delay between when a misleading claim is broadcast and when verified facts reach the public. InTruth attacks this latency directly, creating value by:

Automating the Research Loop: Instantly translating spoken dialogue into structured search queries against primary databases, public records, and vetted archives.
Democratizing Verification: Giving everyday viewers access to research capabilities previously restricted to newsrooms and investigative analysts.
Neutralizing Misinformation Velocity: intercepting falsehoods at the exact moment of delivery before they can anchor in the viewer’s memory.

2. Value Access: Reducing Cognitive and Experience Friction

Capability without access is useless. Value Access measures how easily a user can tap into the created value within their existing habits and workflows. This is where experience design becomes the ultimate differentiator.

If InTruth forces users to switch tabs, click through complex menus, or read dense paragraphs of text while trying to watch a fast-paced debate, it introduces severe cognitive friction. To succeed on Value Access, the tool must observe key human-centered principles:

In-Flow Delivery: Surfacing unobtrusive, glanceable notifications directly inside the existing video player (whether on YouTube, X, or news networks) without forcing context switching.
Cognitive Ergonomics: Presenting live receipts using visual micro-cues (such as color-coded trust vectors or short source snippets) that can be processed at a glance without disrupting the viewing experience.
Zero Setup Effort: Functioning ambiently in the background so the user gains immediate insight without configuring complex rules or query filters.

3. Value Translation: Overcoming the Trust Paradox

Great capability and seamless access mean nothing if the user doesn’t believe or understand the output. Value Translation is the art of framing information so that it builds trust and inspires meaningful action.

In fact-checking, Value Translation faces a massive hurdle: human confirmation bias and institutional skepticism. Simply labeling a speaker’s statement as “False” often triggers a defensive psychological reaction, causing viewers to reject the tool rather than reconsider the claim. InTruth must solve this trust paradox by:

Sourcing Over Assertion: Shifting away from judgmental labels (e.g., “Pants on Fire”) toward objective, primary-source evidence (e.g., “Congressional Record, Vol. 168: Voted YES on Bill X”).
Radical Transparency: Making the verification logic clear, showing exact source documents so users feel empowered to make their own judgment rather than being dictated to by an algorithm.
Contextual Nuance: Distinguishing between outright fabrication, missing context, or minor statistical rounding, ensuring the audience trusts the nuance and neutrality of the tool.

Section III: Human-Centered Change & Experience Design Lens

Building a powerful real-time fact-checking engine is fundamentally a human experience challenge, not just an algorithmic one. Technology enables capabilities, but human-centered design enables adoption. To transform InTruth from a novel browser extension into an indispensable daily tool, we must examine the behavioral realities of how people consume media, process conflicting information, and react to real-time feedback.

Designing for Cognitive Load: Preserving the Viewing Flow

Watching live video — whether a town hall, press conference, or political debate — is inherently a passive, low-effort experience. Viewers lean back, absorb narratives, and follow emotional cues. By introducing a real-time verification overlay, InTruth asks the brain to switch into an active, analytical processing mode.

If designed poorly, this extra layer leads to immediate cognitive overload and outrage fatigue. Human-centered experience design must protect the user’s focus through careful interface discipline:

Glanceable Micro-Interactions: Information must be visual and bite-sized. Complex policy documents should be distilled into clear, single-line contextual highlights with expandable detail for those who want to dig deeper.
Temporal Breathing Room: Notifications must not flash continuously across the screen. Applying intelligent thresholding ensures the overlay only triggers when high-confidence discrepancies or critical missing contexts arise.
Visual Hierarchy & Ambient Cues: Utilizing peripheral, non-intrusive status indicators allows viewers to remain immersed in the video stream while maintaining awareness of real-time source verification.

The Source Transparency Model: Spectrum vs. Binary Truth

Traditional fact-checking often relies on reductive binary tags: True or False. In human discourse, however, statements rarely fall into neat black-and-white categories. Rhetoric is built on selective framing, outdated statistics, exaggerated figures, and omitted context.

A rigid binary approach degrades user trust and creates friction. InTruth must adopt a Source Transparency Model that reflects nuance across a spectrum of context:

Verified Primary Record • Missing Context • Outdated Data • Unsubstantiated Assertion

By presenting a spectrum rather than a verdict, InTruth respects the user’s intelligence. It transforms the experience from an automated referee telling the audience what to think into a personal research assistant providing the receipts needed to draw independent conclusions.

Overcoming Psychological Defense Mechanisms

When people are presented with facts that contradict their deeply held beliefs, their immediate instinct is rarely acceptance — it is defensiveness. Cognitive dissonance kicks in, and the brain’s immune system seeks reasons to discredit the source, the algorithm, or the platform delivering the correction.

To navigate this psychological hurdle, InTruth must incorporate key behavioral design tactics:

Neutral, Non-Judgmental Language: Avoid emotionally charged terms like “Debunked” or “Lies.” Instead, use objective phrasing such as “Official Treasury data shows…” or “Voting records reflect…”
Direct Primary Links: Build instant credibility by linking directly to raw, unedited source files — such as legislative bills, economic reports, or court transcripts — rather than third-party commentary.
Empowering User Autonomy: Frame corrections as optional context layers that enrich understanding, ensuring users feel empowered rather than challenged.

Section IV: The Futurology Perspective — FutureHacking™ Live Truth

To understand the long-term strategic trajectory of InTruth, we must look beyond its current implementation as a desktop browser extension. By applying a FutureHacking™ framework — scanning weak signals in technological adoption and anticipating systemic shifts — we can map how real-time truth engines will re-architect the broader media landscape over the next 5 to 10 years.

From Weak Signals to Mainstream Realities

Today, real-time fact-checking overlayed on web video is a weak signal — a niche capability used primarily by journalists, policy analysts, and tech-savvy early adopters. However, several converging trends will accelerate this capability into a baseline expectation for ambient intelligence:

The Explosion of Synthetic and AI-Generated Media: As deepfakes, automated audio cloning, and AI-driven propaganda proliferate, unassisted human perception will no longer be sufficient to determine authenticity. Real-time verification will evolve from an optional feature into an essential cognitive defense layer.
Ultra-Low-Latency Edge AI: On-device AI models and localized vector databases will allow voice transcription, semantic analysis, and cross-referencing to occur locally with zero network latency, making verification instantaneous and completely private.
The Shift to Conversational and Live Streams: As traditional written journalism continues to give way to long-form podcasts, live video streams, and interactive town halls, context tools must operate natively in live audio visual environments.

From Browser Extensions to Native Ambient Interfaces

The Chrome extension is merely a stepping stone. As computing paradigms shift away from traditional screens, tools like InTruth will migrate directly into native hardware and ubiquitous spatial interfaces:

Spatial Computing & AR Glasses: In augmented reality environments, real-time verification layers will move from screen overlays to ambient heads-up displays during live, in-person events, political rallies, or public lectures.
Smart TV and Broadcast Integration: Streaming platforms and television hardware manufacturers will embed native “truth engines” directly into set-top boxes and smart OS environments, allowing viewers to toggle contextual overlays with a button on their remote.
Enterprise Video Conferencing: In business settings, real-time verification tools will be integrated into platforms like Zoom and Teams, serving as automated compliance and fact-verification assistants during corporate board meetings, earnings calls, and sales presentations.

The Strategic Counter-Maneuver: Adaptations in Public Rhetoric

Whenever a transformative technology alters the dynamic between speaker and audience, the speaker’s behavior adapts. The widespread adoption of live, automated truth engines will trigger a fundamental evolution in public rhetoric and media strategy:

Rhetorical Obfuscation vs. Precision: Bad actors will adapt by shifting from falsifiable statements to hyper-vague, highly emotive language designed to bypass database queries entirely. Conversely, transparent communicators will structure their speeches to explicitly cite primary sources in real time, encouraging instant automated validation.
Source Poisoning and Database Wars: The strategic battleground will shift from the speaker’s podium to the underlying reference databases. Public figures and interest groups will actively attempt to flood primary source repositories or manipulate public records to influence real-time algorithmic outputs.

Ultimately, InTruth is not just a tool for today’s web browsing — it is a prototype for the ambient, real-time context infrastructure that will define the future of human communication and public accountability.

Section V: The Verdict — Innovation or Novelty?

When we weigh InTruth against our core criteria for human-centered change, a clear distinction emerges: technological capability alone does not equal innovation. A product can feature cutting-edge machine learning and instantaneous audio transcription, yet remain an intrusive novelty if it fails to solve the broader human experience challenge.

To determine whether InTruth represents a category-defining breakthrough or just another temporary browser plugin, we must compare the characteristics of an incremental feature against those of a true, human-centered innovation:

Dimension	Incremental Feature (Novelty)	True Human-Centered Innovation
Core Focus	Speed, raw transcription accuracy, and automated database lookups.	Trust, context retention, and enhancing human comprehension without fatigue.
User Experience	Intrusive pop-up overlays that interrupt viewing flow and increase cognitive friction.	Non-intrusive micro-insights that empower individual judgment smoothly and ambiently.
Perceived Value	An authoritative “referee” dictating rigid binary judgments (True/False).	A transparent research assistant providing accessible primary-source receipts.
Systemic Impact	A niche fact-checking widget for political hobbyists and journalists.	A foundational layer for public accountability in the attention economy.

The Final Verdict

InTruth possesses all the technical ingredients necessary to become a transformative tool. However, its ultimate success will not be decided in the code base — it will be decided in the user experience layer.

If InTruth focuses merely on real-time execution speed and automated scorekeeping, it risks becoming a distraction that users disable after the initial novelty wears off. But if the team designs for low cognitive load, prioritizes source transparency over judgmental scoring, and seamlessly embeds context into the user’s natural viewing flow, InTruth will move from a clever browser extension to a vital engine of trust in the modern digital ecosystem.

Section VI: Strategic Recommendations for the InTruth Team

To successfully cross the chasm from a promising technical prototype to a category-defining human-centered innovation, the InTruth team must execute on four strategic imperatives. These recommendations focus on maximizing value translation, optimizing experience design, and building systemic trust across the entire ecosystem.

1. Prioritize Sourcing Over Scoring

Avoid the trap of playing “automated referee.” Assigning rigid, top-down truth scores or binary labels creates immediate psychological friction and invites accusations of algorithmic bias. Instead, shift the design emphasis entirely toward rapid, neutral receipt delivery:

Provide Direct Evidence: Present exact quotes from official public records, legislative documents, or peer-reviewed data alongside the spoken transcript.
Highlight Context Gaps: Explicitly show what information was omitted (e.g., “Stat represents 2021 data, excluding 2024 updates”) rather than declaring a statement flatly false.
Empower Human Judgment: Frame every overlay as an objective research receipt that respects the viewer’s intelligence to draw their own conclusion.

2. Empower the Nine Innovation Roles

Systemic adoption requires engaging users across distinct behavioral profiles. Product design should specifically accommodate the full spectrum of user roles from the Nine Innovation Roles, particularly:

The Troubleshooter: Provide deep-dive analytical modes allowing researchers, journalists, and policy analysts to inspect raw source metadata, API logs, and verification pipelines in real time.
The Customer Champion: Ensure the experience is continuously tuned to human needs, minimizing cognitive friction and preventing outrage fatigue so the tool feels like a trusted personal assistant.
The Evangelist: Build friction-free “shareable receipt” mechanics, enabling everyday users to export verified video clips and primary-source overlays directly to social networks with a single click.

3. Design for Zero-Friction Cognitive Ergonomics

The ultimate goal of experience design is making powerful capabilities feel effortless. If using InTruth requires conscious effort, adoption will stall among mainstream audiences:

Ambient Micro-Interactions: Keep overlays compact, glanceable, and peripheral to the primary video frame. Use non-intrusive status indicators that expand only upon intent.
Smart Thresholding: Implement confidence scoring models behind the scenes so the UI only interrupts the viewer when high-value, high-certainty discrepancies occur.
Zero-Setup Onboarding: Ensure the extension works immediately out of the box on major video platforms without requiring complex filter configurations or custom API setups.

4. Institutionalize Radical Transparency and Decentralized Trust

In an environment marked by deep institutional skepticism, the platform itself must be beyond reproach. Trust cannot be requested; it must be structurally demonstrated:

Open-Source Verification Logic: Make the underlying matching algorithms, prompt architectures, and scoring heuristics publicly auditable on GitHub.
Pluralistic Primary Databases: Draw from a diverse, transparently published set of non-partisan archives, government databases, and academic repositories rather than proprietary black-box datasets.
Community Audit Mechanisms: Allow trusted independent researchers and public ombudsmen to review, flag, and continuously refine source mappings.

Frequently Asked Questions

Is InTruth a fact-checker or an automated referee?

InTruth functions as a real-time research assistant rather than a judgmental referee. Instead of assigning arbitrary “True” or “False” ratings, it provides instant primary-source receipts — such as official government records, voting histories, and economic datasets — so users can verify live statements and draw their own conclusions without leaving their video stream.

How does InTruth reduce cognitive overload during live videos?

By shifting from active searching to ambient discovery, InTruth eliminates the friction of pausing videos or opening secondary browser tabs. Its glanceable, non-intrusive micro-overlays deliver contextual highlights in real time, preserving the viewer’s natural flow while ensuring critical facts are instantly accessible.

Why is experience design critical for automated fact-checking tools?

Technology enables capability, but experience design enables adoption. If a fact-checking tool uses intrusive pop-ups or accusatory language, it triggers user fatigue or cognitive defensiveness. Human-centered design ensures the tool delivers high value with zero setup effort, low cognitive friction, and maximum source transparency.

Image credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article, add images and create infographics.

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