How Human-Centered Leadership Can Reimagine the Aerospace Industry

Move the Needle

GUEST POST from Kellee M. Franklin, PhD.

The aerospace industry is on a long flight, but subtle drifts in culture and practice have quietly moved it off its intended course. To get back on track, we don’t need a radical turn. We need to move the needle — one small, intentional correction at a time. This is the power of the 1-in-60 rule, a principle championed by former Thunderbird pilot Major Michelle Mace Curran: a onedegree error leads to being a mile off course after 60 miles. In the high-speed world of aerospace, those miles pass quickly, and the destination can be lost.

Reimagining this industry starts with recognizing that every decision, every interaction, is a chance to move the needle. A holistic educational campaign must be the first correction, teaching not just technical skills, but this very philosophy. It’s about empowering every team member to ask, “Is this choice moving us toward who we want to be?” When we let one “degree” slip — by skipping a quiet team member’s comment or bypassing a safety check because “it’s easier” — we compound a drift that, over time, takes us far from the vital human-centered power skills we need. In an era of increasing automation, skills like collaboration, critical thinking, empathy and ethical judgment are not soft — they are the critical systems that keep the mission on track. Yet, the industry remains focused on recruiting, hiring, and promoting for technical skills alone, placing it at risk of the pilot’s dreaded death spiral: a fatal, uncorrected descent caused by fixating on a single instrument while losing situational awareness.

This mindset shift is crucial for legacy employees — and necessary for an industry in need of refueling. Change can feel like a threat, but framing it as a series of small, needed adjustments to move the needle makes it manageable. It’s not about discarding experience, but about course-correcting outdated norms. Workshops and mentorship, inspired by experienced industry leaders like Curran and others, can offer profound insights. They can show how power skills — like maintaining broad situational awareness under pressure — enable teams to act decisively and create a culture that is far more dynamic, innovative, safe, and resilient. It requires leadership to invite challenge, conversation, and collaboration. In a traditionally hierarchical industry, these shifts can be difficult — but they are essential for real transformation.

How do I know human-centered leadership is not only needed but effective in the aerospace industry? Because I’ve had the good fortune of supporting leadership at the highest levels of the U.S. Air Force and Space Force, and within major corporate entities that design, develop, and secure aerospace technologies, where the stakes of every decision are immense. In those rooms, I’ve seen that while technical expertise is the foundation, the true innovation — and the true
innovators — are found among the airmen, guardians, and on the front lines. The real gift of leadership isn’t just knowing the technology; it’s knowing the people. It’s understanding their challenges, their potential, and having the wisdom to guide them through the full terrain of complexity. That human-centered insight is what transforms good missions into great ones. This is the essence of leadership that moves the needle — insight no instrument panel can ever provide.

My conviction is further reinforced by my years teaching global scholars at Hult International Business School, where I witnessed firsthand how creativity and collaborative problem-solving, critical thinking and sound judgment, and emotional intelligence and empathy are the true catalysts for success in a complex world. This is not just theory. It’s a strategic imperative. Consider EY, one of the Big Four professional services firms and an educational partner of Hult, which is putting $100 million behind human skills. They are actively recognizing and rewarding the value of uniquely human capabilities alongside technical adoption, proving that the most forward-thinking organizations understand that people-potential is the ultimate competitive advantage. This growing emphasis on human skills in the Age of AI is not a new trend for me; it’s the core of a conscious leadership integrative model I designed in 2018, built on the principle that sustainable innovation flows from empowered people, not just advanced systems.

This urgency is underscored by the 2026 Oliver Wyman “Lift Off Leadership” survey in partnership with the International Aerospace Women’s Association (IAWA), which found that 78% of aerospace leaders identify a critical gap in human-centered skills, and 65% believe that without a cultural shift, their organizations will struggle to innovate at the pace required for the next decade. The survey provides a clear roadmap: organizations must embed active sponsorship as a core leadership competency and address the everyday workplace cultures driving female attrition; leaders must move beyond passive mentoring to actively advocate for women in highlevel decision-making rooms; and the industry as a whole must adopt strict gender-neutral recruitment standards and properly fund proven leadership initiatives. Industry surveys are always insightful, but without proper and timely executive execution of strategic recommendations, these exercises continue to place emerging talent and the potential of aerospace in a perpetual holding pattern. For real “lift off”, employees require advocacy, intention, and support — because no mission ever launched on insight alone. These small, but critical, system-wide shifts demand human-centered leadership — not just technical expertise — to guide the way.

Inviting a new wave of dreamers is another powerful way to move the needle. We can start by promoting STEM/STEAM programs early, allowing current employees to work hand-in-hand with the future of the industry. By engaging with local colleges and universities in hack-a-thons and other idea-generating initiatives, we not only ignite the next generation’s passion but also tap into a wellspring of raw, unfiltered innovation. In our workspaces, actively dismantling exclusionary barriers and creating clear pathways — like targeted one-on-one and group coaching, upskill/reskill programs, and ongoing mentor/development initiatives — opens the cockpit to brighter skies and unseen horizons. We must also actively encourage employees to participate in professional development opportunities beyond our own organizations, empowering them to connect with and learn from peers across the industry, and return with fresh perspectives and renewed energy to elevate our teams. This is not just about fairness; it is about taking the field to elevated heights. Broader disciplines with a wider array of perspectives are the ultimate navigational tools, helping us spot drifts we might otherwise miss and chart a more enduring course.

The future of aerospace won’t be defined by a single, massive overhaul. It will be built on the collective commitment to make small, consistent adjustments. Leaders can begin today by:

Hosting a “Drift Check” Workshop: Use the 1-in-60 rule to facilitate a team discussion on current cultural norms and co-creating a vision for the future.
Launching a Reverse Mentorship Program: Pair senior leaders with junior employees, allowing diverse voices to be heard and fostering open, two-way learning.
Implementing a “Power Skills” KPI: Include empathy, collaboration, innovation, and other power skills in performance reviews, publicly acknowledging team members who exemplify them.
Celebrating “Course Corrections”: Transparently share small changes and their impact, making learning a core part of the culture.
Building a Balanced Workforce: Sponsor a Dreamer’s Fellowship to fund underrepresented talent and actively recruit diverse disciplines. Intentionally blend technical expertise with human-centered innovators to create a more resilient and visionary team.

By embracing a 1-in-60 philosophy, we can recalibrate our heading, one degree at a time, and navigate toward a future that’s not just technologically advanced, but truly human-centered.

Image credits: Kellee M. Franklin

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Why Your Strategic Planning Offsite Needs a Foresight Exercise, Not Just Another SWOT

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Why Your Strategic Planning Offsite Needs a Foresight Exercise, Not Just Another SWOT

by Braden Kelley and Art Inteligencia

I’ve sat in more strategic planning offsites than I can count, and I can predict the SWOT exercise before it starts. Someone draws a four-quadrant grid on the whiteboard. The room fills in Strengths and Weaknesses quickly, because those are about the company as it exists right now, and everyone in the room already agrees on most of them. Then it gets to Opportunities and Threats, and the energy noticeably drops — because now the exercise is quietly asking the room to predict the future, and SWOT gives them no actual tool for doing that. So they default to whatever opportunities and threats came up in last year’s version of the same exercise, lightly reworded.

SWOT was never built for what you’re using it for

SWOT is a genuinely useful tool for organizing what you already know about your current position. It was never designed to help a group reason about an uncertain future — there’s no mechanism in the exercise for surfacing real signals, testing which trends they suggest, or imagining more than one way things could unfold. When a room uses it to fill in “Opportunities” and “Threats,” what actually happens is everyone reaches for whatever future feels most familiar or most recently discussed in the trade press, and the exercise quietly becomes a confidence-building ritual around a single assumed future rather than genuine strategic thinking.

The offsite is the right room. It’s the wrong exercise.

Here’s what I’d push back on if someone suggested dropping the offsite structure entirely: getting your leadership team in a room together, away from daily operations, is exactly the right container for this kind of thinking. The problem isn’t the offsite. It’s that the exercise running inside it isn’t built for the actual question a strategic planning session needs to answer, which isn’t “what do we already know about ourselves” — it’s “what’s actually changing around us, and what should we do about it before it’s obvious to everyone else.”

What a foresight exercise does differently

A structured foresight exercise starts somewhere SWOT never goes: the real signals your team is picking up from the market, technology, customer behavior, and adjacent industries — not opinions about the future, but the actual early evidence of it. From there, it asks the room to genuinely work through which trends those signals suggest, and to hold more than one possible future seriously rather than converging immediately on whichever one the most senior person in the room already believes. Only after that does it narrow toward a most-probable future and, critically, a preferable one — the future you’d actually choose to build toward, and the specific path to get there. That’s a fundamentally different exercise than filling in a quadrant, and it produces a fundamentally different kind of strategic plan.

Why this matters more in the room than anywhere else

The offsite is where organizational alignment either happens or doesn’t. A room that’s just filled in a familiar SWOT grid leaves with a comfortable, mostly unchanged view of the future — which feels productive in the moment and shows up as a strategic plan that’s already outdated within a couple of quarters. A room that’s worked through real signals together, disagreed about what they mean, and built a shared view of multiple possible futures leaves with something SWOT structurally can’t produce: genuine, tested alignment on what’s actually likely to happen and what the team is going to do about it either way.

Bringing this into your next offsite

This is exactly the gap FutureHacking™ was built to close — a structured, visual, collaborative foresight methodology any leadership team can run in a room together, without needing a dedicated foresight function or an outside futurist facilitating every session. FutureHacking™ is the art and science of getting to the future first, and the fastest way to feel the difference is to bring it into the room where your planning conversations already happen.

Where to start before your next offsite

The free FutureHacking Signal Picker is a genuinely useful way to arrive at your next offsite with real signals already identified and prioritized, instead of starting the room from a blank whiteboard. It’s the foundational first step of the full methodology, and it’s free.

Something new I’m building

I’m also finishing a second tool — the FutureCanvas Picker — that carries a planning team further into the full arc in a single sitting: from signals, to the trends they suggest, to a genuine set of possible futures, narrowing to your most probable future, and then mapping the path toward the future you’d actually prefer to build. It’s the closest thing I’ve built yet to running a full FutureHacking™ session in miniature.

I’m opening early access to a select group first — strategic planners, CSOs, and leaders actively running planning processes right now — because I want real feedback from people using it under real offsite deadline pressure before it’s available more broadly. If that’s you, and you’d like to be considered for early access, reach out and let me know — I’ll be following up personally with the first few who get in.

Your next offsite is going to happen either way. The only real question is whether the room leaves with a shared view of one comfortable future, or a genuine head start on several possible ones.

Image Credits: Pexels

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

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Why the Truth Matters

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Why the Truth Matters

GUEST POST from Greg Satell

In 2012, when Marco Rubio was gearing up for a run at the Presidency, he sat for an in-depth interview with the magazine GQ to bolster his image. “I think the age of the universe has zero to do with how our economy is going to grow,” he proudly declared. “I’m not a scientist. I don’t think I’m qualified to answer a question like that.”

The attitude belies dangerous ignorance. The big bang is not just a theory, but a set of theories, including general relativity and quantum mechanics that underlie modern technologies such as computers, GPS satellites, lasers and solar cells, just to name a few. Our economy literally could not function without them.

As Vannevar Bush famously wrote, “There must be a stream of new scientific knowledge to turn the wheels of private and public enterprise.” Yet today we get “alternative truths” and book bans. Make no mistake: truth matters. History shows when we abandon the quest for discovery and design narratives to suit our preferences, the consequences tend to be severe.

Jewish Physics

In 1905, an unknown physicist working at the Swiss patent office named Albert Einstein unleashed four papers, written in his spare time, that would change the world so completely that it would come to be known as his miracle year. He would later follow up with his theory of general relativity and solidify his place as one of the greatest minds to ever live.

These breakthrough theories would change how scientists thought about the universe. We learned that time and space were not static, but relative, that light travels through discrete packets called “quanta” and that mass could be converted into energy. His discoveries would, within a few decades, be translated into revolutionary new technologies.

You would think he would be a hero in his home country of Germany, but just the opposite happened. As the Nazis gained power and Jews became scapegoated, Einstein’s theories became to be known as Jewish physics and the science of quantum theory and relativity was banned from schools. Philipp Lenard and Johannes Stark, both backed the shift and promoted anti-relativity Deutsche Physik.

The United States went a different way. It welcomed not only Einstein, but an entire generation of leading scientists. Over just a few short decades, America was transformed from a scientific backwater, where promising students would need to go abroad to receive advanced education, to a technological superpower.

In 1939, Leo Szilard, another refugee from fascist Europe, who had helped develop the idea of a nuclear chain reaction, went to see Einstein. Szilard alerted him that uranium could be used to make a bomb of unimaginable power. Together with emigres Eugene Wigner and Edward Teller, they drafted a letter to President Roosevelt which initiated the Manhattan project that led to the Allies ultimate victory in World War II.

Lysenko’s Biology

In the 1930s the Soviet Union was plagued by famines brought on by failed collectivization. The most famous of which, Holodomor in Ukraine, killed as many as seven million people. Clearly, something had to change and Stalin called on his favorite scientist, Trofim Lysenko, to figure out a way to increase agricultural production.

The problem was that Lysenko was both a fool and a fraud. He rejected the new science of genetics in favor of a wacky set of theories which collectively became known as Lysenkoism. At the heart of his thinking was that an organism’s environment can affect the germ line, so rather than selectively breeding for desired traits, he would try to “educate” crops by, for example, soaking crops in freezing water to help them grow in the winter.

It was all nonsense, of course. But ideology held sway over the scientific method and real scientists who questioned Lysenkoism faced serious consequences. Thousands of legitimate researchers were dismissed from their jobs and sent to the Gulag. Many were killed for nothing more than speaking the truth.

Stalin’s dedication to Lysenko and his pseudoscience worsened the famines and deepened the suffering of the Soviet people. Later, his ideas would be adopted by Mao Zedong and lead to the Great Chinese Famine. Tens of millions more would die needlessly. All of this happened for no other reason than the desire to defy what the Soviets called “Bourgeois pseudoscience.”

Identity—and the need to signal it—is a powerful thing.

Darwin And The Age Of The Earth

In 2012, Paul Broun, a US Congressman on the Science, Space and Technology Committee, asserted that evolution, embryology and big bang theory are “lies straight from the pit of hell.” A recent Gallup survey suggests that 40% of Americans still agree with him. Darwin’s theory remains controversial in many quarters.

Just recently, the Texas state Board of Education recently voted to teach creationism along with evolution. West Virginia and Florida also passed laws promoting the teaching of “Intelligent Design,” a pseudoscientific theory that is designed to undermine the theory of natural selection in schools and promote a religious alternative.

These moves have consequences. Darwin’s theory is no abstraction, but a working model that scientists use every day. It is used, for example, to help understand the spread of pandemics and how to fight cancer. Genetic algorithms based on natural selection are used for a variety of complex optimization functions, such as organizing logistics.

Science And Pseudoscience

Today, the truth can seem like nothing more than a preference. We pick a side, form a group identity and set out to prove our worth by supporting the party line. In our quest for status, we try to top those around us, leading to a purity spiral in which everyone competes to see who can be the most true to the cause.

Yet truth is more than opinion. Facts are falsifiable. We can test them. Einstein’s relativity is a wacky theory, but unless we use it to calibrate GPS satellites, they won’t be accurate. Darwin’s theory may conflict with other beliefs, but it can help us cure terrible diseases like COVID and Cancer. These aren’t just ideas, but tools we use to create the modern world.

What we need to be careful about is those who assign identity to specific ideas. Once an idea becomes associated with a particular team, it can be used to manipulate our sense of self. The same basic urges that nearly robbed us of the ideas of Copernicus and Galilieo are no less pervasive today then they were centuries ago.

The telltale sign is leveraging identity to manipulate us, the use of an “us” and “them” to push us in a particular direction of what to believe. For those that are looking to con us, there can never be a “we together,” because that will undermine their narrative of an ideological battle, rather than a search for truth in the service for a greater good.

The need for truth is especially dire today when we have so many pressing problems to solve. We simply can’t afford anything less than an honest search to discover and ascertain facts.

— Article courtesy of the Digital Tonto blog
— Image credit: Dall-E

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The Hidden Cost of Strategic Planning Built on a Single Future

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The Hidden Cost of Strategic Planning Built on a Single Future

by Braden Kelley and Art Inteligencia

Nobody puts a line item in the budget for “cost of assuming we knew what was going to happen.” And yet, if you looked honestly at what a single-scenario strategic plan actually costs an organization when the future doesn’t cooperate, it would be one of the largest hidden expenses on the books. It just never gets counted, because it’s spread across a dozen decisions that never get traced back to the plan that caused them.

The cost of defending a plan past its expiration date

Once a strategic plan is approved, it develops a kind of institutional gravity. Budgets are allocated against it. Teams are staffed against it. Leaders have put their names on it in front of the board. When early signals suggest the assumed future isn’t materializing quite the way the plan predicted, the natural organizational instinct isn’t to update the plan — it’s to defend it, because updating it can feel like admitting the original thinking was wrong. I’ve watched organizations spend months, and real budget, propping up a strategy that the market had already started to move past, simply because nobody wanted to be the one to say so first.

The cost of the resources you didn’t allocate to what was actually happening

This is the harder cost to see, because it’s a cost of omission rather than a line item you can point to. Every dollar and every hour committed to executing a single assumed future is a dollar and an hour not available to the future that was actually starting to emerge in the market signals your team either didn’t collect or didn’t take seriously. You don’t see this cost in a budget review. You see it eighteen months later, when a competitor who built in flexibility is suddenly in a category you didn’t think was coming yet.

The cost of strategic surprise

There’s a specific, expensive kind of organizational chaos that happens when a shift arrives that the strategic plan gave leadership no framework for anticipating. It’s not just the scramble to react — it’s the credibility cost inside the organization when leadership is visibly caught off guard by something that, in hindsight, had been signaling for a year. Teams notice. Boards notice. The plan’s failure to hold more than one possible future becomes a trust problem, not just a strategy problem.

The cost of decision paralysis when the single future finally, visibly breaks

Counterintuitively, some of the most expensive moments I’ve seen come after a single-scenario plan visibly stops working. Leadership, having built no muscle for holding multiple futures at once, doesn’t know how to respond except by freezing — commissioning study after study, delaying decisions that can’t actually wait, because the organization has no established process for reasoning under genuine uncertainty. A team that’s practiced foresight moves faster in exactly this moment, not slower, because they’ve already done the work of imagining more than one path.

Why the fix isn’t more analysis — it’s a different structure

None of this means the answer is spending more time forecasting, or hiring more analysts to build a more detailed single prediction. A more detailed wrong future is still wrong. What actually closes this gap is a structured way of holding multiple possible futures at once — genuinely mapping from the real signals in your market, to the trends they suggest, to a real set of possible futures, then identifying which one is most probable while still building a deliberate path toward the future you’d actually prefer. That’s the specific gap FutureHacking™ was built to close — a structured, visual, collaborative methodology any leadership team can run, without needing to build an internal foresight department first. FutureHacking™ is the art and science of getting to the future first, and the organizations that practice it don’t avoid uncertainty — they get better at moving through it faster than everyone still defending last year’s single-scenario plan.

Where to start

If your team has never run a structured foresight exercise, the free FutureHacking Signal Picker is the fastest way to find out what it feels like — it walks you through identifying and prioritizing the real signals worth watching, at no cost, and it’s the foundational first step of the whole methodology.

Something new I’m building

I’m also finishing a second tool — the FutureCanvas Picker — that carries you further into the full arc: from signals, to the trends they suggest, to a genuine set of possible futures, narrowing to your most probable future, and then mapping the path toward the future you’d actually prefer to build. It’s the fastest, clearest way I’ve built yet to feel the full power of FutureHacking™ in a single sitting.

I’m opening early access to a select group first — strategic planners, CSOs, and leaders actively running planning processes right now — because I want real feedback from people doing this work under real deadline pressure before it’s available more broadly. If that’s you, and you’d like to be considered for early access, reach out and let me know — I’ll be following up personally with the first few who get in.

The organizations that get to the future first aren’t the ones who guessed correctly. They’re the ones who stopped betting everything on a single guess.

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 Claude to clean up the article.

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Merging Two Customer Experiences After M&A

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Where to Start

Merging Two Customer Experiences After M&A

by Braden Kelley and Art Inteligencia

Every M&A announcement talks about synergies, market position, and combined capabilities. Almost none of them talk about the fact that, on day one, you now have two customer bases who each learned to expect something different from the companies they chose — and neither of them signed up for the other company’s version of the relationship.

The assumption that quietly sinks post-merger CX

The default assumption in most integrations is that the better-resourced or larger company’s experience simply becomes the standard, and the other customer base adjusts. I’ve watched this assumption cost companies real customers, because it skips a step that matters enormously: nobody has actually compared the two experiences at the touchpoint level to know which one is genuinely better, versus just louder or more familiar to the leadership team making the call.

Two journeys, two sets of expectations, one deadline

Integration timelines are usually set by finance and legal milestones — closing conditions, systems cutover dates, reporting deadlines — not by how long it actually takes to understand two customer journeys well enough to merge them intelligently. That mismatch is where the damage happens. Support processes get unified before anyone’s mapped where they genuinely differ. Pricing and billing experiences get standardized before anyone’s identified which parts of each were actually working. By the time customer complaints start flagging the problems, the systems decisions are already locked in, and unwinding them costs far more than getting it right the first time would have.

Start by mapping both journeys independently, before merging anything

The instinct in an integration is to move fast toward one unified experience, because ambiguity feels risky to the deal’s momentum. I’d argue the opposite is true here: the riskiest move is unifying before you understand what you’re unifying. Mapping both customer journeys independently — validated personas, current-state touchpoints, the data each company has been collecting, and, critically, walking both journeys firsthand rather than trusting either side’s internal narrative about how good their own experience is — gives you an honest picture before any integration decision gets made instead of after.

Whose employees explain the friction matters as much as whose customers report it

In an acquisition especially, frontline employees from the acquired company often sit on institutional knowledge about their customers’ real pain points and workarounds that never made it into any deck during diligence. They also, often, feel like their side of the business is being absorbed rather than genuinely evaluated — which makes them less likely to volunteer that knowledge unless someone specifically goes looking for it. An audit that treats both organizations’ frontline teams as equally credible sources, rather than defaulting to whichever side is running the integration, tends to surface friction neither leadership team knew existed.

Benchmark both experiences against the market, not against each other

The other trap is treating this purely as an internal comparison — which company’s process wins. The more useful question is how each one stacks up against what customers in the combined market now expect, especially if the merger changes your competitive position or brings you into contact with a new set of competitors either customer base is now implicitly being compared against.

What this actually buys you

Getting this right doesn’t just avoid a bad integration story — it turns the merger into a genuine opportunity to build a better combined experience than either company had running independently, using the best of what each side was actually doing well. That’s a very different outcome than the default of one side’s process quietly winning by default and both customer bases losing something in the process.

If you’re heading into an integration and want an independent, evidence-based read on both customer experiences before any systems or process decisions get locked in, a Customer Experience Audit scoped to both organizations is exactly the kind of diagnostic this moment calls for. And if you want a rough sense of what experience misalignment could cost during an integration before you scope that engagement, the CX ROI Calculator is a fast place to start.

Download the Customer Experience Audit Checklist as a PDF

Image Credits: Pexels

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

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What’s Your Learning Objective?

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What's Your Learning Objective?

GUEST POST from Mike Shipulski

Innovation is all about learning. And if the objective of innovation is learning, why not start with learning objectives?

Here’s a recipe for learning: define what you want to learn, figure how you want to learn, define what you’ll measure, work the learning plan, define what you learned and repeat.

With innovation, the learning is usually around what customers/users want, what new things (or processes) must be created to satisfy their needs and how to deliver the useful novelty to them. Seems pretty straightforward, until you realize the three elements interact vigorously. Customers’ wants change after you show them the new things you created. The constraints around how you can deliver the useful novelty (new product or service) limit the novelty you can create. And if the customers don’t like the novelty you can create, well, don’t bother delivering it because they won’t buy it.

And that’s why it’s almost impossible to develop a formal innovation process with a firm sequence of operations. Turns out, in reality the actual process looks more like a fur ball than a flow chart. With incomplete knowledge of the customer, you’ve got to define the target customer, knowing full-well you don’t have it right. And at the same time, and, again, with incomplete knowledge, you’ve got to assume you understand their problems and figure out how to solve them. And at the same time, you’ve got to understand the limitations of the commercialization engine and decide which parts can be reused and which parts must be blown up and replaced with something new. All three explore their domains like the proverbial drunken sailor, bumping into lampposts, tripping over curbs and stumbling over each other. And with each iteration, they become less drunk.

If you create an innovation process that defines all the if-then statements, it’s too complicated to be useful. And, because the IF-THENs are rearward-looking, they don’t apply the current project because every innovation project is different. (If it’s the same as last time, it’s not innovation.) And if you step up the ladder of abstraction and write the process at a high level, the process steps are vague, poorly-defined and less than useful. What’s a drunken sailor to do?

Define the learning objectives, define the learning plan, define what you’ll measure, execute the learning plan, define what you learned and repeat.

When the objective is learning, start with the learning objectives.

Image credits: Pexels

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Why Going Above and Beyond Doesn’t Work

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Why Going Above and Beyond Doesn't Work

GUEST POST from Shep Hyken

This article answers the question: Should organizations aim to go above and beyond in every interaction, or focus on consistently meeting customer expectations?

This is a story about a disagreement I had with a client. I should mention, this was a friendly disagreement. His idea of an amazing experience was to go above and beyond, always exceeding the customer’s expectations.

His company is the one you call when a disaster, such as a flood, tornado, or fire, hits your home or office. The company specializes in cleanup and restoration. The owner believed it was important to go above and beyond in every interaction. So, I asked him for an example.

He said that when a customer calls – day or night, 365 days a year – someone will be there, and an emergency team will be dispatched immediately.

As nicely as I could, I told him that what he described was not an above-and-beyond example. No, what he described was what every customer expected. While the customer may be elated with how quickly the company responds to their emergency, that’s what his company is supposed to do.

Above and beyond experiences are reserved for unexpected moments. Not long ago, I wrote about the story Steve Wynn, the chairman of Wynn Resorts, a group of hotels and casinos, shared about how an employee helped a guest get medicine she had left at home. That was truly an above-and-beyond example.

It doesn’t always have to be something big.

However, it doesn’t always have to be something big. For example, the surprise piece of cake with a candle the server at a restaurant brings to the table, not because someone told him it was a guest’s birthday, but simply because he overheard the patrons talking about the birthday. He took advantage of that information and created the surprise-and-delight moment, another version of above-and-beyond.

But you can’t count on emergencies and birthdays to happen every time. You can take advantage of those moments when you know they’re coming, but if every day, in every interaction, you focus on giving the customer your best effort to meet, and even slightly exceed, their expectations, you’re operating in the zone of amazement.

Going above and beyond should never be the goal for every interaction. It’s not sustainable, and it’s definitely not a realistic goal. What is realistic is delivering consistent and predictable experiences that meet expectations every time and occasionally rise just a bit above them. The point is, customers don’t demand fireworks unless that’s the kind of experience you sell. What they want is reliability, ease, and empathy. When those are in place, the occasional above-and-beyond or surprise-and-delight moments become icing on the cake, not the foundation of your service. Do what customers expect, every time, and you’ll amaze them with your consistency. That’s what builds trust, loyalty, and the kind of reputation that gets customers to say, “I’ll be back.”

Image Credits: Pexels

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How to Learn Fast — and Kill Weak Bets Early

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The Experiment Canvas™: Five Gravity-Control Innovation Experiments Visualized

How to Learn Fast — and Kill Weak Bets Early

by Braden Kelley and Art Inteligencia

What Is The Experiment Canvas™? (Short Answer)

The Experiment Canvas™ is a one-page innovation tool for structuring experiments that prove or disprove the feasibility, viability, and desirability of a potential innovation — before you burn capital on the wrong bet. It forces a clear hypothesis, helpers, resources, risks, assumptions, barriers, a three-phase experiment plan (setup → execution → wrap-up), and learning metrics that can falsify the idea.

Below: why the canvas accelerates innovation speed and success rates — and five filled examples for a hypothetical gravity control appliance, showing how a radical idea can be broken into sequenced experiments that cull likely failures early.

Why Innovators Need to Instrument for Learning — Not Hope

Most innovation waste is not bad imagination. It is unfalsified imagination: teams fund prototypes, labs, and roadmaps without a written hypothesis, kill criteria, or a learning metric anyone would defend in a budget meeting. Activity photographs well. Learning does not — unless you design for it.

I created The Experiment Canvas™ as part of the Human-Centered Innovation Toolkit™ to help teams instrument for learning fast in iterative new product or service development. The canvas makes the experiment visual and collaborative — so alignment, accountability, and outcomes improve together. Specs can follow. Hope should not lead.

Used well, the canvas helps you:

Accelerate speed — by sequencing the questions that matter (physics before scale; safety before market theater; cost before Series B fantasy).
Raise odds of success — by naming helpers, resources, assumptions, and barriers before the first dollar of build.
Cull likely failures early — with fail-fast gates and learning metrics that can say “no” while the bet is still cheap.

How The Experiment Canvas™ Structures a Bet

Each canvas asks the same disciplined questions, in roughly this flow:

Zone	What it forces
Hypothesis	The question, feasibility/viability/desirability angles, fatal flaws, adoption blockers
Who can help / resources / risks	Real people, real tools, real downside — not a slide of optimism
Phases 1–3	Setup, execution, wrap-up with evidence, insight, and next gate
Assumptions & barriers	What must be true — and what can stop you
Learning metrics	Three measures that can falsify the bet

To show how this works on something intentionally extreme, I recently built five Experiment Canvas examples (CLICK THEM to get the big version) for a hypothetical gravity control appliance. The point is not sci-fi cosplay. The point is method: even a moonshot becomes manageable when you break it into experiments that can fail honestly.

Example 1 — Physics Feasibility: Is There Any Measurable Effect?

Core hypothesis: Can we create >0.1% weight reduction on a 1kg mass — or is there any measurable effect at all?

This first canvas attacks the fatal question: is there a signal, or are we chasing EMI / magnetic tricks and reputational risk? Helpers include a chief scientist, a gravimetry lab, metrology, and an external skeptic reviewer. Learning metrics demand delta-G, signal-to-noise (>3 sigma), and repeatability. Next gate: if yes → energy test; if no → pivot or kill.

The Experiment Canvas example 1 — physics feasibility for a gravity control appliance testing measurable weight reduction — Example 1 — Physics feasibility: measurable effect, SNR, and repeatability before any product story.

Example 2 — Energy Efficiency: Is the Cost Per Newton Survivable?

Core hypothesis: Can we achieve >1 Newton of lift per kW — and modulate ±2% for 60 seconds — without an energy cost that makes the product impossible?

Prerequisite: Example 1 success. This canvas puts power electronics, thermal management, and fail-fast gates on the page (>5 kW/N kills the path). Metrics: watts per Newton, modulation accuracy, thermal stability. Insight: is the curve linear — or a cliff? Soft landings for radical tech start with honesty about energy economics.

The Experiment Canvas example 2 — energy efficiency and modulation for a gravity control appliance — Example 2 — Energy efficiency: cost per Newton, modulation, and thermal limits with a fail-fast gate.

Example 3 — Safety Envelope: Is Exposure Safe Enough to Sell?

Core hypothesis: Is 8-hour exposure at 0.5G at 1 meter safe — for cells, electronics, and humans?

Prerequisite: a stable Example 2. Here feasibility, desirability, and viability collide: bio impact, EMC, nausea, regulatory classification, liability. Metrics include cell viability (>95% vs control), bit-error rate / EMC compliance, and human symptom reports. Next: define a safety manual and exclusion zone — or stop before market theater begins.

The Experiment Canvas example 3 — safety and exposure envelope for a gravity control appliance — Example 3 — Safety: biological, electronic, and human-factor metrics that define the operating envelope.

Example 4 — Market Desirability: Who Has Gravity Pain Worth Paying For?

Core hypothesis: Which segment has ~$10M gravity-related pain — and will they sign LOIs at real price points ($120k+ / $520k+), or is this cool tech nobody wants?

Prerequisite: safety envelope from Example 3. This is the desirability canvas — interviews, pain scores, willingness to pay, and traction via pilot LOIs. Done when you have enough contact evidence for a go or a clear no-go. Building without a segment that hurts is innovation theater with better physics.

The Experiment Canvas example 4 — market desirability, pain scores, and LOIs for a gravity control appliance — Example 4 — Market desirability: segment pain, willingness to pay, and LOI traction before beta spend.

Example 5 — Manufacturing Viability: Can We Build 10 Betas Under $50k BOM?

Core hypothesis: Can we build 10 beta units at under $50k bill of materials — with a real path through supply chain, yield, and compliance?

This viability canvas asks whether the existing supply chain works, whether FCC/OSHA/product safety is a path or a wall, and whether cost or yield kills margin. Fail fast if BOM exceeds $100k. Metrics: unit cost, manufacturability (yield and hours), compliance blockers. Next: if cost and path are clear → fund the next round; if not → redesign before you scale a fantasy.

The Experiment Canvas example 5 — manufacturing BOM, yield, and compliance for a gravity control appliance — Example 5 — Manufacturing viability: BOM, yield, and compliance path before you scale.

What These Five Canvases Teach About Speed and Success

Read the five examples in sequence and a pattern appears:

Sequence the fatal questions. Physics before energy. Energy before safety. Safety before market. Market before manufacturing scale.
Write the kill criteria in advance. Null result, >5 kW/N, unsafe exposure, no LOIs, BOM blowout — each canvas names how to stop.
Make learning metrics falsifiable. Three metrics per canvas beat a hundred vanity KPIs.
Surface helpers, risks, assumptions, and barriers. Innovation fails politically as often as it fails scientifically.
Treat wrap-up as a decision, not a report. Evidence → insight → next gate. No cemetery of unfinished experiments.

You do not need a gravity appliance to use the method. You need a bet you are tempted to fund on enthusiasm alone — and the discipline to instrument learning before the money gets loud.

Download The Experiment Canvas™ and Run Your Next Bet

The Experiment Canvas™ is available as a free, premium 35″ × 56″ scalable PDF — suitable for wall-sized workshops, 11″ × 17″ (A3) printing, or as a background in Miro, Mural, Lucid, Microsoft Whiteboard, and similar tools. It is one of the optional components of the Human-Centered Innovation Toolkit™.

Go download The Experiment Canvas™ here:
https://bradenkelley.com/product/experiment-canvas-35″-x-56″-poster-size/

Write the hypothesis. Name the metrics that can kill the bet. Run the experiment. Soft landings for innovation are designed — one falsifiable canvas at a time.

Frequently Asked Questions

What is The Experiment Canvas™?

The Experiment Canvas™ is a free innovation tool by Braden Kelley for structuring experiments that test feasibility, viability, and desirability. It covers hypothesis, helpers, resources, risks, setup/execution/wrap-up phases, assumptions, barriers, and learning metrics.

How does The Experiment Canvas™ accelerate innovation?

It forces teams to write a falsifiable hypothesis, sequence fatal questions, name kill criteria and learning metrics, and decide next steps based on evidence — so weak bets die early and strong bets get clearer gates before capital scales.

What are feasibility, viability, and desirability in innovation experiments?

Feasibility asks whether it can work technically. Desirability asks whether humans want it enough to hire it. Viability asks whether it can be made, sold, and sustained economically and legally. The Experiment Canvas™ helps you instrument learning across all three.

Where can I download The Experiment Canvas™?

Download the free 35″ × 56″ poster-size PDF from Braden Kelley’s product page: https://bradenkelley.com/product/experiment-canvas-35″-x-56″-poster-size/

Why use a gravity control appliance as an Experiment Canvas example?

An intentionally extreme hypothetical shows the method under stress: physics, energy, safety, market, and manufacturing each get their own canvas with kill criteria. If the tool works for a moonshot-style idea, it works for the bets already on your roadmap.

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 Cursor to clean up the article.

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

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

Time to Rethink Pitch Fests and Business Plan Competitions — by Arlen Meyers
What If You Could Prove the Government is Ripping Us Off? — by Braden Kelley
The Surprising Innovation History of the Bicycle — by John Bessant
Dead Actors Society — by Art Inteligencia
Amazon Connect Combines Human Empathy with AI to Redefine Service — by Shep Hyken
AI Will Create a More Human Future, Not a Less Human One — by Braden Kelley
Managing Your Work Friends — by David Burkus
Building the Business Case for a Customer Experience Audit — by Braden Kelley
Customer Experience Audit vs. Customer Satisfaction Survey — by Braden Kelley
Case Study – Innovating Around a Disruption — by Jason Hauer

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

What Happens When AI Becomes Your Customer? — by Shep Hyken
How to Calculate the ROI of Customer Experience — by Braden Kelley
How to Keep Learning as a Leader — by David Burkus
Why Collective Intelligence is the New Scarce Resource in an Age of Abundant AI — by Braden Kelley
Why Conversations Are the New Digital Gold — by Braden Kelley

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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The Slowing EV Market

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The Slowing EV Market

GUEST POST from Geoffrey Moore

One initiative that is top-of-mind for curtailing climate change is the electrification of ground transportation. The meteoric rise of Tesla drew the world’s attention to EVs, and China’s fast-follower public-private partnership has taken the industry to a whole new level. But now it is encountering a lull, and that raises the question, where do we go from here?

A couple of years ago LG announced a breakthrough in a battery-manufacturing technology called dry-coating that is expected to lower cost from 17 to 30%, with expected deployment in 2028. In a steady-state market, this would be welcome news indeed, but for a market that is still developing, it is not the sort of risk-adjusted return on investment (ROI) nor the kind of rate of return (IRR) that will attract private equity. LG is looking to future growth in its existing battery business to reward its efforts and counting on its investors to have the patience to wait for it.

Meanwhile, in the US, the first wave of venture returns has come and gone, and the next wave depends upon enormous amounts of capital being invested in very long-term charging infrastructure projects, the kind that are normally funded by bonds. This is reminiscent of the national commitment that underwrote the interstate highway buildout in the 20th century, but it is not clear we have the political consensus to prioritize such a project.

Ironically, we do not lack for capital to fund these efforts. The past several decades of digital transformation have created enormous pools of wealth, and financial managers are anxious to put that capital to work. The problem is that, for this phase of investment, the ROI and IRR performance metrics that accompany the creation of that wealth are neither appropriate nor available.

Private capital, for better or for worse, is driven by its compensation systems. We saw this when we tried to leverage its expertise to create carbon-credits exchanges. Not surprisingly that led to a sustained gaming of the system that has generated plenty of fees but done nothing to improve the climate situation. What we need instead is a private-public partnership based on a genuine commitment to global good.

Such a partnership is possible, but only if our political leaders are committed to such values, something we should all keep in mind when we vote this fall. At present, the electoral conversation is so consumed with personalities seeking to score points with abusive rhetoric that there is little prospect for any such partnership to emerge. But we need not capitulate to that rhetoric. If the time to change course is now, then we should hold ourselves and our country accountable for doing so.

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

— Image credit: Pexels

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