Category Archives: Innovation

McKinsey is Wrong That 80% Companies Fail to Generate AI ROI

McKinsey is Wrong That 80% Companies Fail to Generate AI ROI

GUEST POST from Robyn Bolton

Sometimes, you see a headline and just have to shake your head.  Sometimes, you see a bunch of headlines and need to scream into a pillow.  This week’s headlines on AI ROI were the latter:

  • Companies are Pouring Billions Into A.I. It Has Yet to Pay Off – NYT
  • MIT report: 95% of generative AI pilots at companies are failing – Forbes
  • Nearly 8 in 10 companies report using gen AI – yet just as many report no significant bottom-line impact – McKinsey

AI has slipped into what Gartner calls the Trough of Disillusionment. But, for people working on pilots,  it might as well be the Pit of Despair because executives are beginning to declare AI a fad and deny ever having fallen victim to its siren song.

Because they’re listening to the NYT, Forbes, and McKinsey.

And they’re wrong.

ROI Reality Check

In 20205, private investment in generative AI is expected to increase 94% to an estimated $62 billion.  When you’re throwing that kind of money around, it’s natural to expect ROI ASAP.

But is it realistic?

Let’s assume Gen AI “started” (became sufficiently available to set buyer expectations and warrant allocating resources to) in late 2022/early 2023.  That means that we’re expecting ROI within 2 years.

That’s not realistic.  It’s delusional. 

ERP systems “started” in the early 1990s, yet providers like SAP still recommend five-year ROI timeframes.  Cloud Computing“started” in the early 2000s, and yet, in 2025, “48% of CEOs lack confidence in their ability to measure cloud ROI.” CRM systems’ claims of 1-3 years to ROI must be considered in the context of their 50-70% implementation failure rate.

That’s not to say we shouldn’t expect rapid results.  We just need to set realistic expectations around results and timing.

Measure ROI by Speed and Magnitude of Learning

In the early days of any new technology or initiative, we don’t know what we don’t know.  It takes time to experiment and learn our way to meaningful and sustainable financial ROI. And the learnings are coming fast and furious:

Trust, not tech, is your biggest challenge: MIT research across 9,000+ workers shows automation success depends more on whether your team feels valued and believes you’re invested in their growth than which AI platform you choose.

Workers who experience AI’s benefits first-hand are more likely to champion automation than those told, “trust us, you’ll love it.” Job satisfaction emerged as the second strongest indicator of technology acceptance, followed by feeling valued.  If you don’t invest in earning your people’s trust, don’t invest in shiny new tech.

More users don’t lead to more impact: Companies assume that making AI available to everyone guarantees ROI.  Yet of the 70% of Fortune 500 companies deploying Microsoft 365 Copilot and similar “horizontal” tools (enterprise-wide copilots and chatbots), none have seen any financial impact.

The opposite approach of deploying “vertical” function-specific tools doesn’t fare much better.  In fact, less than 10% make it past the pilot stage, despite having higher potential for economic impact.

Better results require reinvention, not optimization:  McKinsey found that call centers that gave agents access to passive AI tools for finding articles, summarizing tickets, and drafting emails resulted in only a 5-10% call time reduction.  Centers using AI tools to automate tasks without agent initiation reduced call time by 20-40%.

Centers reinventing processes around AI agents? 60-90% reduction in call time, with 80% automatically resolved.

How to Climb Out of the Pit

Make no mistake, despite these learnings, we are in the pit of AI despair.  42% of companies are abandoning their AI initiatives.  That’s up from 17% just a year ago.

But we can escape if we set the right expectations and measure ROI on learning speed and quality.

Because the real concern isn’t AI’s lack of ROI today.  It’s whether you’re willing to invest in the learning process long enough to be successful tomorrow.

Image credit: Microsoft CoPilot

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Is All Publicity Good Publicity?

Some Insights from Cracker Barrel

Is All Publicity Good Publicity?

GUEST POST from Pete Foley

The Cracker Barrel rebrand has certainly created a lot of media and social media attention.  Everything happened so fast that I have had to rewrite this introduction twice in as many days. Originally written when the new logo was in place, it has subsequently been withdrawn and replaced with the original one.

It’s probably been a expensive, somewhat embarrassing and sleepless week for the Cracker Barrel management team. But also one that generated a great deal of ‘free’ publicity for them. You could argue that despite the cost of a major rebranding and de-branding, this episode was priceless from a marketing penetration perspective. There is no way they could have spent enough to generate the level of media and social media they have achieved, if not necessarily enjoyed.

But of course, it raises the perennial question ‘is all publicity good publicity?’  With brands, I’d argue not always.  For certain, both good and bad publicity adds to ‘brand fluency’ and mental availability. But whether that is positively or negatively valanced, or triggers implicit or explicit approach or avoid responses is less straightforward. A case in point is of course Budweiser, who generated a lot of free media, but are still trying to drag themselves out of the Bud Light controversy.

Listening to the Customer: But when the dust settles, I suspect that Cracker Barrel will come out of this quite well. They enjoyed massive media and social media exposure, elevating the ‘mindshare’ of their brand. And to their credit, they’ve also, albeit a little reluctantly, listened to their customers. The quick change back to their legacy branding must ave been painful, but from a customer perspective, it screams ‘I hear you, and I value you’.

The Political Minefield. But there is some lingering complexity. Somehow the logo change became associated with politics. That is not exactly unusual these days, and when it happens, it inevitably triggers passion, polarization and outrage. I find it a quite depressing commentary on the current state of society that a restaurant logo can trigger ‘outrage. But like it or not, as change agents, these emotions, polarization and dubious political framing are a reality we all have to deal with. In this case, I personally suspect that any politically driven market effects will be short-lived. To my eye, any political position was unintentional, generated by social media rather than the company, and the connection between logo design and political affiliation is at best tenuous, and lacks the depth of meaning typically required for persistent outrage. The mobs should move on.

The Man on the Moon: But it does illustrate a broader problem for innovation derived from our current polarized society. If a logo simplification can somehow take on political overtones, pretty much any change or innovation can. Change nearly always comes with supporters and detractors, reflecting the somewhat contradictory nature of human behavior and cognition – we are change agents who also operate largely from habits. Our response to innovation is therefore inherently polarized, both as individuals and as a society, with elements of both behavioral inertia and change affinity. But with society deeply polarized and divided, it is perhaps inevitable that we will see connections between two different polarizations, whether they are logical or causal or not. We humans are pattern creators, evolved to see connections where they may or may not exist. This ability to see patterns using partial data protected us, and helped us see predators, food or even potential mates using limited information. Spotting a predator from a few glimpses through the trees obviously has huge advantages over waiting until it ambushes us. So we see animals in clouds, patterns in the stars, faces on the moon, and on some occasions, political intent where none probably exists.

My original intent with this article was to look at the design change for the logo from a fundamental visual science perspective. From that perspective, I thought it was quite flawed. But as the story quickly evolved, I couldn’t ignore the societal, social media and political element. Context really does matter. But if we step back from that, there are stillo some really interesting technical design insights we can glean.

1.  Simplicity is deceptively complex. The current trend towards reducing complexity and even color in a brands visual language superficially makes sense.  After all, the reduced amount of information and complexity should be easier for our brains to visually process.  And low cognitive processing costs come with all sorts of benefits. But unfortunately it’s not quite that simple.  With familiar objects, our brain doesn’t construct images from scratch, but instead takes the less intuitive, but more cognitively efficient route of unconsciously matching what we see to our existing memory.  This allows us to recognize familiar objects with a minimum of cognitive effort, and without needing to process all of the visual details they contain.  Our memory, as opposed to our vision, fills in much of the details.  But this process means that dramatic simplification of a well established visual language or brand, if not done very carefully, can inhibit that matching process.  So counterintuitively, if we remove the wrong visual cues, it can make a simplified visual language or brand more difficult to process than it’s original, and thus harder to find, at least for established customers.  Put another way, the way our visual system operates, it automatically and very quickly (faster than we can consciously think) reduces images down to their visual essence. If we try to do that ourselves, we need to very clearly understand what the key visual elements are, and make sure we keep the right ones. Cracker Barrel has lost some basic shapes, and removed several visual elements completely, meaning it has likely not done a great job in that respect.

2.  Managing the Distinctive-Simple Trade Off.  Our brains have evolved to be very efficient, so as noted above, we only do the ‘heavy lifting’ of encoding complex designs into memory once.  We then use a shortcut of matching what we see to what we already know, and so can recognize relatively complex but familiar objects with relatively little effort. This matching process means a familiar visual scene like the old Cracker Barrel logo is quickly processed as a ‘whole’, as opposed to a complex, detailed image.  But unfortunately, this means the devil is in the details, and a dramatic simplification like Cracker Barrels can unintentionally remove many of the cues or signals that allowed us to unconsciously recognize it with minimal cognitive effort. 

And the process of minimizing visual complexity can also remove much of what made the brand both familiar and distinctive in parallel.  And it’s the relatively low resolution elements of the design that make it distinctive.  To get a feel for this, try squinting at the old and new brand.  With the old design, squinting loses the details of the barrel, or the old man,  But the rough shape of them, and of the logo, and their relative positions remain.  That gives a rough approximation of what our visual system feeds into our brain when looking for a match with our memory. Do the same with the new logo, and it has little or no consistency or distinctivity.  This means the new logo is unintentionally making it harder for customers to either find it (in memory or elsewhere) or recognize it. 

As a side effect, oversimplification also risks looking ‘generic’, and falling into the noise created by a growing sea of increasingly simplified logos. Now, to be fair, historical context matters.  If information is not encoded into memory, the matching process fails, and a visual memory needs to be built from scratch.  So if we were a new brand, Cracker Barrels new brand visual language might lack distinctivity, but it would certainly carry ease of processing benefits for new customers, whereas the legacy label would likely be too complex, and would quite likely be broadly deselected.  But because the old design already owns ‘mindspace’ with existing customers, the dramatic change risks and removal of basic visual cues asks repeat customers to ’think’ at a more conscious level, and so potentially challenges long established habits.  A major risk for any established brand  

3.  Distinctivity Matters. All visual branding represents a trade off.  We need signal to noise characteristics that stand out from the crowd, or we are unlikely to be noticed. But we also need to look like we belong to a category, or we risk being deselected.  It’s a balancing act.  Look too much like category archetypes, and lack distinctivity, and we fade into the background noise, and appear generic.  But look too different, and we stand out, but in a potentially bad way, by asking potential customers to put in too much work to understand us. This will often lead a customer to quickly de-select us.  It’s a trade off where controlled complexity can curate distinctive cues to stand out, while also incorporating enough category prototype cues to make it feel right.  Combine this with sufficient simplicity to ease processing fluency, and we likely have a winning design, especially for new customers.  But it’s a delicate balancing act between competing variables

4.  People don’t like change. As mentioned earlier, we have a complex relationship with change. We like some, but not too much. Change asks their brains to work harder, so it needs to provide value. I’m skeptical the in this case, it added commensurate value to the customer.  And change also breaks habits. So any major rebrand comes with risk for a well established brand.  But it’s a balancing act, and we should remain locked into aging designs forever.  As the context we operate in changes, we need to ‘move with the times’, and remain consistent in our relationship with our context, at least as much as we remain consistent with our history. 

And of course, there is also a trade off between a visual language that resonates with existing customers and one designed to attract new ones, as ultimately, virtually every brand needs both trial and repeat.   But for established brands evolutionary change is usually the way to achieve reach and trial without alienating existing customers.  Coke are the masters of this.   Look at how their brand has evolved over time, staying contemporary, but without creating the kind of ‘cognitive jolts’ the Cracker Barrel rebrand has created.  If you look at an old Coke advertisement, you intuitively know both that it’s old, but also that it is Coke.

Brands and Politics.    I generally advise brands to stay out of politics. With a few exceptions, entering this minefield risks alienating 50% of our customers. And any subsequent ‘course corrections’ risk alienating those that are left. For a vast majorities of companies, the cost-benefit equation simply doesn’t work!

But in this case, we are seeing consumers interpreting change through a political lens, even when that was not the intent. But just because it’s not there doesn’t mean it doesn’t matter, as Cracker barrel is discovered.  So I’m changing my advice from ‘don’t be political’ to ‘try and anticipate if you’re initiative could be misunderstood as political’.  It’s a subtle, but important difference. 

And as a build, marketers often try to incorporate secondary messages into their communication.  But in todays charged political climate, I think we need to be careful about being too ‘clever’ in this respect.  Consumer’s sensitivity to socio-political cues is very high at present, as the Cracker Barrel example shows.  So if they can see political content where none was intended, they are quite likely to spot any secondary or ‘implicit’ messaging.   So for example, an advertisement that features a lot of flags and patriotic displays, or one that predominately features members of the LBGTQ community both run a risk of being perceived as ‘making a political statement’, whether it is intended to or not.  There is absolutely nothing wrong with either patriotism or the LBGT community, and to be fair, as society becomes increasingly polarized, it’s increasingly hard to create content that doesn’t somehow offend someone.  At least without becoming so ‘vanilla’ that the content is largely pointless, and doesn’t cut through the noise. But from a business perspective, in today’s socially and politically fractured world, any perceived political bias or message in either direction comes with business risks.  Proceed with caution.

And keep in mind we’ve evolved to respond more intensely to negatives than positives – Caution kept our ancestors alive.  If we half see a coiled object in the grass that could be a garden hose or a snake, our instinct  is to back off.  If we mistake a garden hose for a snake to cost is small. But if we mistake a venomous snake for a garden hose, the cost could be high. 

As I implied earlier, when consumers look at our content though specific and increasingly intense partisan lens, it’s really difficult for us to not be perceived as being either ‘for’ or ‘against’ them. And keep in mind, the cost of undoing even an unintended political statement is inevitably higher than the cost of making it. So it’s at very least worth trying to avoid being dragged into a political space whenever possible, especially as a negative.  So be careful out there, and embrace some devils advocate thinking. Even if we are not trying to make a point, implicitly or explicitly, we need to step back and look at how those who see the world from deeply polarized position could interpret us.  The ‘no such thing as bad publicity’ concept sits on very thin ice at this moment in time, where social media often seeks to punish more than communicate  

Image credits: Wikimedia Commons

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Seeing the Invisible

Seeing the Invisible

GUEST POST from Mike Shipulski

It’s relatively straightforward to tell the difference between activities that are done well and those that are done poorly. Usually sub-par activities generate visual signals to warn us of their misbehavior. A bill isn’t paid, a legal document isn’t signed or the wrong parts are put in the box. Though the specifics vary with context, the problem child causes the work product to fall off the plate and make a mess on the floor.

We have tools to diagnose the fundamental behind the symptom. We can get to root cause. We know why the plate was dropped. We know how to define the corrective action and implement the control mechanism so it doesn’t happen again. We patch up the process and we’re up and running in no time. This works well when there’s a well-defined in place, when process is asked to do what it did last time, when the inputs are the same as last time and when the outputs are measured like they were last time.

However, this linear thinking works terribly when the context changes. When the old processes are asked to do new work, the work hits the floor like last time, but the reason it hits the floor is fundamentally different. This time, it’s not that an activity was done poorly. Rather, this time there’s something missing altogether. And this time our linear-thinker toolbox won’t cut it. Sure, we’ll try with all our Six Sigma might, but we won’t get to root cause. Six Sigma, lean and best practices can fix what’s broken, but none of them can see what isn’t there.

When the context changes radically, the work changes radically. New-to-company activities are required to get the new work done. New-to-industry tools are needed to create new value. And, sometimes, new-to-world thinking is the only thing that will do. The trick isn’t to define the new activity, choose the right new tool or come up with the new thinking. The trick is to recognize there’s something missing, to recognize there’s something not there, to recognize there’s a need for something new. Whether it’s an activity, a tool or new thinking, we’ve got to learn to see what’s not there.

Now the difficult part – how to recognize there’s something missing. You may think the challenging part is to figure out what’s needed to fill the void, but it isn’t. You can’t fill a hole until you see it as a hole. And once everyone agrees there’s a hole, it’s pretty easy to buy the shovels, truck in some dirt and get after it. But if don’t expect holes, you won’t see them. Sure, you’ll break your ankle, but you won’t see the hole for what it is.

If the work is new, look for what’s missing. If the problem is new, watch out for holes. If the customer is new, there will be holes. If the solution is new, there will be more holes.

When the work is new, you will twist your ankle. And when you do, grab the shovels and start to put in place what isn’t there.

Image credit: Pixabay

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Is Your Innovation Strategy on Track?

Is Your Innovation Strategy on Track?

GUEST POST from Stefan Lindegaard

A solid innovation strategy is key to setting your organization up for long-term success. But how do you know if you’re on the right path? Here are a few signs that your innovation strategy is sound – and some KPI/metrics tips to guide you along the way.

1. Alignment with Corporate Strategy

A strong innovation strategy doesn’t stand alone—it’s integrated with the overall corporate strategy. While innovation teams often lean more visionary, the core business balances daily execution with future growth. Finding the “sweet spot” between these perspectives helps shape an innovation strategy that is bold yet achievable.

KPI/metrics: Strategic alignment score. Are innovation initiatives aligned with overall business goals and timelines? Does the strategy push far enough to create the future, but close enough to today’s realities?

2. Clarity on Innovation Type

It’s critical to know what type of innovation your organization is pursuing. Incremental innovation? Breakthrough or radical? Or perhaps you’re aiming for “in-between” innovation – meaningful advancement without the high stakes of disruptive change.

KPI/metrics: Track innovation project distribution across types (incremental, in-between, breakthrough). Are you focusing on the sweet spot for your capabilities?

3. Understanding of Ecosystem Dynamics

In-between innovation, where companies push beyond small improvements but not into complete market disruption, often benefits from ecosystem collaboration. This means tapping into external assets and building alliances that complement internal capabilities.

KPI/metrics: Number and quality of ecosystem partnerships. How many productive partnerships are helping you access needed assets or knowledge?

Six Innovation Models by BCG

4. Balance Between Vision and Reality

The innovation team may lean toward bold, future-shaping ideas, while the core business focuses on today’s realities. A sound strategy balances both perspectives – pushing boundaries while staying feasible within current business structures.

KPI/metrics: Time-to-market for innovation projects. Are projects moving efficiently from concept to market, indicating a practical balance between vision and execution?

5. Talent and Skills Alignment

A clear innovation strategy should inform talent requirements. Are the right skills and roles in place to support the type of innovation you’re aiming for?

KPI/metrics: Skills gap analysis for innovation-related roles. Does your team have the capabilities needed to bring your strategy to life?

6. Adaptability and Resilience

Innovation doesn’t follow a straight line. A sound strategy allows for flexibility and quick pivots based on market feedback, technology shifts, and emerging opportunities.

KPI/metrics: Percentage of innovation projects adapted or redirected based on feedback. How adaptable is your team in responding to change?

Your innovation strategy should guide you in defining what’s possible, aligning with your corporate strategy, and fostering a collaborative yet grounded approach. The right KPIs help you measure progress and ensure alignment with your strategic vision.

I hope this shorter post can help spur some reflection and raise some guiding questions for your efforts and initiatives.

Image Credit: Pexels

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This AI Creativity Trap is Gutting Your Growth

This AI Creativity Trap is Gutting Your Growth

GUEST POST from Robyn Bolton

“We have to do more with less” has become an inescapable mantra, and goodness, are you trying.  You’ve slashed projects and budgets, “right-sized” teams, and tried any technology that promised efficiency and a free trial.  Now, all that’s left is to replace the people you still have with AI creativity tools.  Welcome to the era of the AI Innovation Team.

It sounds like a great idea.  Now, everyone can be an innovator with access to an LLM.  Heck, even innovation firms are “outsourcing” their traditional work to AI, promising the same radical results with less time and for far less money.

It sounds almost too good to be true.

Because it is too good to be true.

AI is eliminating the very brain processes that produce breakthrough innovations.

This isn’t hyperbole, and it’s not just one study.

MIT researchers split 54 people into three groups (ChatGPT users, search engine users, and no online/AI tools using ChatGPT) and asked them to write a series of essays.  Using EEG brain monitoring, they found that the brain connectivity in networks crucial for creativity and analogous thinking dropped by 55%.

Even worse? When people stopped using AI, their brains stayed stuck in this diminished state.

University of Arkansas researchers tested AI against 3,562 humans on a series of four challenges involving finding new uses for everyday objects, like a brick or paperclip.   While AI scored slightly higher on standard tests, when researchers introduced a new context, constraint, or modification to the object, AI’s performance “collapsed.” Humans stayed strong.

Why? AI relies on pattern matching and is unable to transfer its “creativity” to unexpected scenarios. Humans use analogical reasoning so are able to flex quickly and adapt.

University of Strasbourg researchers analyzed 15,000 studies of COVID-19 infections and found that teams that relied heavily on AI experts produced research that got fewer citations and less media attention. However, papers that drew from diverse knowledge sources across multiple fields became widely cited and influential.

The lesson? Breakthroughs require cross-domain thinking, which is precisely what diverse human teams provide, and, according to the MIT study, AI is unable to produce.

How to optimize for efficiency AND impact (and beat your competition)

While this seems like bad news if you’ve already cut your innovation team, the silver lining is that your competition is probably making the same mistake.

Now that you know better, you can do better, and that creates a massive opportunity.

Use AI for what it does well:

  • Data analysis and synthesis
  • Rapid testing and iteration to refine an advanced prototype
  • Process optimization

Use humans for what we do well:

  • Make meaningful connections across unrelated domains
  • Recognize when discoveries from one field apply to another
  • Generate the “aha moments” that redefine industries

Three Questions to Ask This Week

  1. Where did your most recent breakthroughs come from? How many came from connecting insights across different domains? If most of your innovations require analogical leaps, cutting creative teams could kill your pipeline.
  2. How are teams currently using AI tools? Are they using AI for data synthesis and rapid iteration? Good. Are they replacing human ideation entirely? Problem.
  3. How can you see it to believe it? Run a simple experiment: Give two teams an hour to solve a breakthrough challenge. Have one solve it with AI assistance and one without.  Which solution is more surprising and potentially breakthrough?

The Hidden Competitive Advantage

As AI commoditizes pattern recognition, human analogical thinking and creativity become a competitive advantage.

The companies that figure out the right balance will eat everyone else’s lunch.

Image credit: Gemini

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The Future is Rotary

Human-Centered Innovation in Rotating Detonation Engines

The Future is Rotary - Human-Centered Innovation in Rotating Detonation Engine

GUEST POST from Art Inteligencia

For decades, the pursuit of more efficient and sustainable propulsion systems has driven innovation in aerospace and beyond. Among the most promising advancements on the horizon is the Rotating Detonation Engine (RDE). This technology, which harnesses supersonic combustion waves traveling in a circular channel, offers the potential for significant leaps in fuel efficiency and reduced emissions compared to traditional combustion methods. However, the true impact of RDEs will not solely be defined by their technical prowess, but by a human-centered approach to their development and integration.

A Paradigm Shift for a Better Future

Human-centered change innovation focuses on understanding and addressing the needs and aspirations of people affected by technological advancements. In the context of RDEs, this means considering not only the engineers and scientists developing the technology but also the pilots, passengers, communities living near airports, and the planet as a whole. The potential benefits are immense:

  • Enhanced Fuel Efficiency: RDEs promise a significant reduction in fuel consumption, leading to lower operating costs and a smaller carbon footprint for air travel and other applications.
  • Reduced Emissions: More efficient combustion can translate to lower emissions of harmful pollutants, contributing to cleaner air and a healthier environment.
  • Increased Performance: The unique properties of detonation combustion could lead to more powerful and lighter engines, opening up new possibilities for aircraft design and space travel.
  • Economic Growth: The development and adoption of RDE technology will create new jobs in research, manufacturing, and maintenance, fostering economic growth.

Navigating the Winds of Change: Key Areas for Innovation

Realizing the full potential of RDEs requires a concerted effort across various domains, guided by a human-centered perspective:

  • Materials Science: Developing materials that can withstand the extreme temperatures and pressures of detonation combustion is crucial. This requires innovative research and collaboration between material scientists and engineers.
  • Engine Design and Control Systems: Creating robust and reliable RDE designs, along with sophisticated control systems to manage the complex detonation process, is essential for safe and efficient operation. Human factors engineering will play a vital role in designing intuitive and user-friendly control interfaces.
  • Manufacturing Processes: Scaling up the production of RDE components will require innovative manufacturing techniques that are both cost-effective and environmentally sustainable.
  • Infrastructure Development: The widespread adoption of RDEs may necessitate changes in fuel production, storage, and delivery infrastructure. Planning for these changes with community needs and environmental impact in mind is critical.
  • Education and Training: A new generation of engineers, technicians, and pilots will need to be trained in the principles and operation of RDE technology. Educational programs must adapt to incorporate this emerging field.
  • Regulatory Frameworks: Governments and regulatory bodies will need to develop new standards and certifications to ensure the safe and responsible deployment of RDE-powered systems. Engaging stakeholders in the development of these frameworks is crucial.

Companies and Startups to Watch

The landscape of RDE development is dynamic, with several established aerospace companies and innovative startups making significant strides. Keep an eye on organizations like GE Aerospace and Rolls-Royce which have publicly acknowledged their research into detonation technologies. Emerging startups such as Venus Aerospace are focusing on leveraging RDEs for high-speed flight, while others like Purdue University’s research labs often spin out promising technologies. These entities are pushing the boundaries of RDE technology and demonstrating potential pathways for its future application, always with an eye on the practical and societal implications of their work.

Case Studies in Human-Centered RDE Application

Case Study 1: Sustainable Air Travel

Imagine a future where short-haul flights are powered by RDEs running on sustainable aviation fuels (SAFs). The increased fuel efficiency of RDEs could significantly reduce the amount of SAF required per flight, making sustainable travel more economically viable and environmentally friendly. This benefits passengers through potentially lower ticket prices in the long run and contributes to the well-being of communities near airports by reducing noise and air pollution. Aircraft manufacturers would need to prioritize designs that minimize noise impact and ensure passenger comfort within the new performance parameters of RDE-powered aircraft. This human-centered approach ensures that the technological advancement directly addresses the need for sustainable and accessible air travel.

Case Study 2: Enhanced Emergency Response

Consider the application of compact, high-power RDEs in heavy-lift drones for disaster relief. Their potential for increased payload capacity and range could enable faster and more efficient delivery of critical supplies to disaster-stricken areas. For first responders and affected populations, this translates to quicker access to necessities like medical equipment, food, and shelter. Developing user-friendly drone control systems and ensuring the safe operation of these powerful machines in complex, real-world scenarios are key human-centered considerations. The focus here is on leveraging RDE technology to improve the speed and effectiveness of humanitarian aid, directly impacting the lives and safety of vulnerable individuals.

A Future Forged Together

The future of rotating detonation engines is not just about technological advancement; it’s about creating a future where propulsion is more efficient, sustainable, and ultimately benefits humanity. By embracing a human-centered approach to innovation, we can navigate the challenges and unlock the transformative potential of RDEs, ushering in a new era of cleaner, more powerful, and more responsible propulsion.

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credit: Gemini

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Creative Confidence Beats Market Signals

And How Johnny Cash Used it to Resurrect His Career

Creative Confidence Beats Market Signals

GUEST POST from Robyn Bolton

The best business advice can destroy your business. Especially when you follow it perfectly.

Just ask Johnny Cash.

After bursting onto the scene in the mid-1950s with “Folsom Prison Blues”, Cash enjoyed twenty years of tremendous success.   By the 1970s, his authentic, minimalist approach had fallen out of favor.

Eager to sell records, he pivoted to songs backed by lush string arrangements, then to “country pop” to attract mainstream audiences and feed the relentless appetite of 900 radio stations programming country pop full-time.

By late 1992, Johnny Cash’s career was roadkill. Country radio had stopped playing his records, and Columbia Records, his home for 25 years, had shown him the door. At 60, he was marooned in faded casinos, playing to crowds preferring slot machines to songs.

Then he took the stage at Madison Square Garden for Bob Dylan’s 30th anniversary concert.

In the audience sat Rick Rubin, co-founder of Def Jam Recordings and uber producer behind Public Enemy, Run-DMC, and Slayer, amongst others. He watched in awe as Cash performed, seeing not a relic but raw power diluted by smart decisions.

The Stare-Down that Saved a Career

Four months later, Rubin attended Cash’s concert at The Rhythm Café in Santa Anna, California. According to Cash’s son, “When they sat down at the table, they said: ‘Hello.’ But then my dad and Rick just sat there and stared at each other for about two minutes without saying anything, as if they were sizing each other up.”

Eventually, Cash broke the silence, “What’re you gonna do with me that nobody else has done to sell records for me?”

What happened next resurrected his career.

Rubin didn’t promise record sales.  He promised something more valuable: creative control and a return to Cash’s roots.

Ten years later, Cash had a Grammy, his first gold record in thirty years, and CMA Single of the Year for his cover of Nine Inch Nails’ “Hurt,” and millions in record sales.

“I wasn’t prepared for what I saw, what I had written in my diary was now superimposed on the life of this icon and sung so beautifully and emotionally. It was a reminder of what an important medium music is. Goosebumps up the spine. It really made sense. I thought: ‘What a powerful piece of art.’ I never got to meet Johnny, but I’m happy I contributed in the way I did. It wasn’t my song anymore.” — Trent Reznor

When Smart Decisions Become Fatal

Executives do exactly what Cash did.  You respond to market signals. You pivot your offering when customer preferences shift and invest in emerging technologies.

All logical. All defensible to your board. All potentially fatal.

Because you risk losing what made you unique and valuable. Just as Cash lost his minimalist authenticity and became a casualty of his effort to stay relevant, your business risks losing sight of its purpose and unique value proposition.

Three Beliefs at the Core of a Comeback

So how do you avoid Cash’s initial mistake while replicating his comeback? The difference lies in three beliefs that determine whether you’ll have the creative courage to double down on what makes you valuable instead of diluting it.

  1. Creative confidence: The belief we can think and act creatively in this moment.
  2. Perceived value of creativity: Our perceived value of thinking and acting in new ways.
  3. Creative risk-taking: The willingness to take the risks necessary for active change.

Cash wanted to sell records, and he:

  1. Believed that he was capable of creativity and change.
  2. Saw the financial and reputational value of change
  3. Was willing to partner with a producer who refused to guarantee record sales but promised creative control and a return to his roots.

Your Answers Determine Your Outcome

Like Cash, what you, your team, and your organization believe determines how you respond to change:

  1. Do I/we believe we can creatively solve this specific challenge we’re facing right now?
  2. Is finding a genuinely new approach to this situation worth the effort versus sticking with proven methods?
  3. Am I/we willing to accept the risks of pursuing a creative solution to our current challenge?”

Where there are “no’s,” there is resistance, even refusal, to change.  Acknowledge it.  Address it.  Do the hard work of turning the No into a Yes because it’s the only way change will happen.

The Comeback Question

Cash proved that authentic change—not frantic pivoting—resurrects careers and disrupts industries. His partnership with Rubin succeeded because he answered “yes” to all three creative beliefs when it mattered most. Where are your “no’s” blocking your comeback?

Image credit: Wikimedia Commons

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Unlearning is More Important Than Learning

Unlearning is More Important Than Learning

GUEST POST from Greg Satell

When I first went overseas to Poland in 1997, I thought I knew how the media business worked. I had some experience selling national radio time in New York and thought I could teach the Poles who, after 50 years of communism, hadn’t had much opportunity to learn how a modern ad market functioned. I was soon disappointed.

Whenever I would explain a simple principle, they would ask me, “why?” I was at a loss for an answer, because these were thought to be so obvious that nobody ever questioned them. When I thought about it though, many of the things I had learned as immutable laws were merely conventions that had built up over time.

As I traveled to more countries I found that even basic market functions, such as TV buying, varied enormously from place to place. I would come to realize that there wasn’t one “right” way to run a business but innumerable ways things could work. It was then that I began to understand the power of unlearning. It is, in fact, a key skill for the next era of innovation.

The One “True” Way To Innovate?

Innovation has become like a religion in business today, with “innovate or die” as its mantra. Much like televangelists preaching the prosperity gospel to gullible rubes, there’s no shortage of innovation gurus that claim to have discovered the secret to breakthrough innovation and are willing to share it with you, for an exorbitant fee, of course.

What I learned researching my book Mapping Innovation, however, is that there is no one “true” path to innovation. In fact, if you look at companies like IBM, Google and Amazon, although they are all world-class innovators, each goes about it very differently. IBM focuses on grand challenges that can take decades to solve, Google integrates a portfolio of innovation strategies and Amazon has embedded a customer obsession deep within its culture and practice.

What I found most interesting was that most people defined innovation in terms of how they’d been successful in the past, or in the case of self-described gurus, what they’d seen and heard to be successful. By pointing to case studies, they could “prove” that their way was indeed the “right” way. In effect, they believed that what they experienced was all there is.

Yet as I’ve explained in Harvard Business Review, innovation is really about finding novel solutions to important problems and there are as many ways to innovate as there are different types of problems to solve. Many organizations expect the next problem they need to solve to be like the last one. Inevitably, they end up spinning their wheels.

The Survival Of The Fittest?

The survival of the fittest is a thoroughly misunderstood concept. Although it arose out of Darwin’s work, it did not originate from him. It was coined by Herbert Spencer to connect Darwin’s work to his own ideas. Darwin’s theory was so novel and powerful at the time, it was difficult to articulate it clearly, and the phrase caught on.

All too often, people assume that Darwin’s theories predicted some sort of teleological end state in which one optimized form will dominate. If that were true, then the optimal strategy for every organism, as well as every business model and every organization, would be to strive to achieve that optimal state and dominate the competition.

Yet that’s not what Darwin meant at all. In fact, his theory rested on three pillars, limited resources, changing environments and super-fecundity, which is the tendency of organisms to produce more offspring that can survive. “Fittest” refers to a temporary state, not a permanent advantage. What is “fit” for one environment may be detrimental in another.

Eastern Europe was, for me, similar to the Galápagos Islands where Darwin first formed his famous theory. Seeing different business environments, in close proximity, give rise to so many different business models opened my eyes to new possibilities. Once I unlearned what I thought I knew, I was able to learn more than I could have imagined.

Turning The Page On Welchism

At the beginning of this century, Fortune magazine proclaimed Jack Welch to be the optimal manager of the last one. American industry had grown sclerotic and bureaucratic. It was in great need of some trimming down and Welch was truly an optimized fit for the environment.

Nicknamed “Neutron Jack” for his penchant of getting rid of all the people and only leaving the buildings standing, he voraciously cut through GE’s red tape. Profits soared, Welch became something of a prophet and “Welchism” a religion. Corporate boards heavily recruited GE executives as CEOs to replicate Welchism at their companies.

Yet as David Gelles explains in his book about Welch’s tenure at GE, The Man Who Broke Capitalism, not all was as it seemed. Yes, Welch made GE more efficient and profitable, but he also increased risk through “financializing” the industrial company, undermined engineering and innovation by moving manufacturing facilities overseas and cooked the books to make profits seem much smoother than they were.

GE would eventually implode, but the damage went much further and deeper than one company. Because Welchism was seen as the “one best way” to run a business, many other firms replicated its methods. The results have been alarming. In fact, a 2020 report by the Federal Reserve found that business dynamism in America has steadily declined since Jack Welch took the helm at GE in 1981.

Clearly we have some unlearning to do.

Moving Boldly Into An Uncertain Future

I’ve thought for some time that the 2020s would look a lot like the 1920s. That was the last time that we had such a convergence of technological, demographic and political forces at one time (and a pandemic as well!). Yet historical analogies can often be misleading. History is long and, if you look enough, you can find an analogy for almost anything.

It is certainly true that history seems to converge and cascade on particular moments and we seem to be at one of these moments now. We will need to unlearn much of what we thought we knew about shareholder value and other things as well. Yet correcting the mistakes of the past is never enough. We need to create anew.

The recently passed CHIPS Act is a good model for how to do this. Much of the $280 billion bill goes to tried and true programs that we under-invested in recent years, such as science programs at the NSF and the DOE as well as programs that support manufacturing and, of course, subsidies to support semiconductors. We know these things work.

Yet other programs are experiments. Some, such as a new Technology Directorate at the NSF are controversial. Others, such as $10 billion that will be spent on regional technology hubs and $1 billion that will go to a RECOMPETE pilot program to empower distressed communities, are new and innovative. We can almost guarantee that there will be hiccups and outright failures along the way.

It is tautologically true that the well-trod path will take us nowhere new. We need to unlearn the past if we are to learn how to build a new future.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

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Decoding the Code of Life

Human-Centered Innovation in Synthetic Biology

Decoding the Code of Life

GUEST POST from Art Inteligencia

From my vantage point here in Seattle, I’m constantly tracking emerging technologies that hold the potential to reshape our world. One area that consistently sparks my interest, and demands a strong human-centered lens, is synthetic biology. This revolutionary field combines biology and engineering principles to design and build new biological parts, devices, and systems—essentially allowing us to program life itself. While the possibilities are immense, so too are the ethical and societal considerations, making a human-centered approach to its innovation crucial.

Synthetic biology stands at the intersection of several scientific disciplines, leveraging our increasing understanding of genomics, molecular biology, and genetic engineering. It moves beyond simply reading the code of life to actively writing and rewriting it. This capability opens doors to addressing some of humanity’s most pressing challenges, from developing new medicines and sustainable fuels to creating novel materials and revolutionizing agriculture. However, as we gain the power to manipulate the fundamental building blocks of life, we must ensure that our innovation is guided by ethical principles, societal needs, and a deep understanding of the potential consequences.

A human-centered approach to innovation in synthetic biology means prioritizing the well-being of individuals and the planet. It involves engaging with the public to understand their concerns and aspirations, fostering transparency in research and development, and proactively addressing potential risks. It requires us to ask not just “can we do this?” but “should we do this?” and “what are the potential impacts on human health, the environment, and the fabric of society?” This proactive ethical framework is essential for building trust and ensuring that the transformative potential of synthetic biology is harnessed responsibly and for the benefit of all.

Case Study 1: Engineering Microbes for Sustainable Fuel Production

The Challenge: Dependence on Fossil Fuels and Climate Change

Our current reliance on fossil fuels is a major driver of climate change and environmental degradation. Finding sustainable and renewable alternatives is a critical global challenge. Synthetic biology offers a promising pathway by enabling the engineering of microorganisms to produce biofuels from renewable resources, such as agricultural waste or even captured carbon dioxide.

The Innovation:

Companies and research labs are now engineering yeast and algae to efficiently convert sugars and other feedstocks into biofuels like ethanol, butanol, and even advanced hydrocarbons that can directly replace gasoline or jet fuel. This involves designing new metabolic pathways within these organisms, optimizing their growth conditions, and scaling up production in bioreactors. The human-centered aspect here lies in the potential to create a cleaner, more sustainable energy future, reducing our carbon footprint and mitigating the impacts of climate change. Furthermore, these bioproduction processes can potentially utilize waste streams, contributing to a more circular economy.

The Potential Impact:

Successful development and deployment of these bio-based fuels could significantly reduce our dependence on finite fossil fuel reserves and lower greenhouse gas emissions. Imagine fueling our cars and airplanes with fuels produced by engineered microbes, utilizing resources that would otherwise go to waste. This innovation has the potential to create new jobs in biorefineries and contribute to energy independence, while simultaneously addressing a critical environmental need. However, careful consideration of land use, water resources, and the potential for unintended environmental consequences is paramount to ensure a truly sustainable solution.

Key Insight: Synthetic biology offers powerful tools to engineer sustainable solutions to global challenges like climate change, but a human-centered approach requires careful consideration of the entire lifecycle and potential impacts.

Case Study 2: Cell-Based Agriculture for a Sustainable Food System

The Challenge: Environmental Impact and Ethical Concerns of Traditional Animal Agriculture

Traditional animal agriculture has a significant environmental footprint, contributing to deforestation, greenhouse gas emissions, and water pollution. It also raises ethical concerns about animal welfare. Synthetic biology is paving the way for cell-based agriculture, where meat and other animal products are grown directly from animal cells in a lab, without the need to raise and slaughter animals.

The Innovation:

Companies are now developing methods to cultivate animal cells in bioreactors, providing them with the necessary nutrients and growth factors to proliferate and differentiate into muscle tissue, fat, and other components of meat. This “cultured meat” has the potential to drastically reduce the environmental impact associated with traditional farming and address ethical concerns about animal treatment. From a human-centered perspective, this innovation could lead to a more sustainable and ethical food system, ensuring food security for a growing global population while minimizing harm to the planet and animals.

The Potential Impact:

Widespread adoption of cell-based agriculture could revolutionize the food industry, offering consumers real meat with a significantly lower environmental footprint. It could also reduce the risk of zoonotic diseases and the need for antibiotics in animal agriculture. However, challenges remain in scaling up production, reducing costs, and gaining consumer acceptance. Addressing public perceptions, ensuring the safety and nutritional value of lab-grown meat, and understanding the potential socio-economic impacts on traditional farming communities are crucial human-centered considerations for this transformative technology.

Key Insight: Synthetic biology can contribute to a more sustainable and ethical food system through cell-based agriculture, but public engagement and careful consideration of societal impacts are essential for its responsible adoption.

Startups and Companies to Watch

The field of synthetic biology is rapidly evolving, with numerous innovative startups and established companies making significant strides. Keep an eye on companies like Ginkgo Bioworks, which is building a platform for organism design; Zymergen, focused on creating novel materials and ingredients through microbial engineering; Impossible Foods and Beyond Meat, leveraging synthetic biology for plant-based and cell-based meat alternatives; Moderna and BioNTech, who utilized mRNA technology (a product of synthetic biology advancements) for their groundbreaking COVID-19 vaccines; and companies like Pivot Bio, developing sustainable microbial fertilizers. This dynamic landscape is constantly generating new solutions and pushing the boundaries of what’s biologically possible.

As we continue to unlock the power of synthetic biology here in America and around the world, it is imperative that we do so with a strong sense of human-centered responsibility. By prioritizing ethics, engaging with society, and focusing on solutions that address fundamental human needs and environmental sustainability, we can ensure that this remarkable technology truly serves the betterment of humanity.

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credit: Gemini

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Top 10 Human-Centered Change & Innovation Articles of July 2025

Top 10 Human-Centered Change & Innovation Articles of July 2025Drum 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:

  1. Three Executive Decisions for Strategic Foresight Success or Failure — by Robyn Bolton
  2. 3 Secret Saboteurs of Strategic Foresight — by Robyn Bolton
  3. Five Unsung Scientific Discoveries Driving Future Innovation — by Art Inteligencia
  4. Unblocking Change — by Mike Shipulski
  5. Why Elastocalorics Will Redefine Our World — by Art Inteligencia
  6. People Will Be Competent and Hardworking – If We Let Them — by Greg Satell
  7. The Unsung Heroes of Culture — by Braden Kelley and Art Inteligencia
  8. Making it Safe to Innovate — by Janet Sernack
  9. Strategic Foresight Won’t Save Your Company — by Robyn Bolton
  10. Your Work Isn’t Transformative — by Mike Shipulski

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

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

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Have something to contribute?

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

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

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