Category Archives: Leadership

The Language of Thought

GUEST POST from Geoffrey Moore

Where do thoughts come from? Is there any structure to them before they manifest themselves in language? Is there a universal grammar that underlies every actual grammar?

These questions have been asked many times before. My answers are as follows:

They come from below, not above.
They do have a readily describable structure.
That structure does indeed underly every actual grammar.

The first answer is the most important one. If the language of thought precedes symbolic language, then symbolic language is emergent from it, and the way to study is not through self-examination but rather by observing the behavior of non-language speaking agents. Of these my favorite two are babies and dogs. Both exhibit a myriad of strategic behaviors that imply thought but clearly do not entail language. So, based on observing them, what can we say about the structure of such thinking?

Babies and dogs, I propose, process the following five concepts routinely and effectively:

Agents. They recognize and respond to people and animals that can interact with them, as indicated by their eye contact, their coming and going, and response to commands and gestures.
Objects. They recognize and can discriminate among objects that interest them, both inanimate and animate, including foods, toys, playmates, and parents. They do not distinguish between animate and inanimate objects in any consistent way.
Actions. They initiate and respond to actions in ways that further their interests, be that in feeding, playing, or getting attention. They are inherently attracted to action in any form.
Valence. They discriminate between things they like and things they don’t like, seeking the former and avoiding the latter, as witnessed by their eating and their expressions of mood.
Uncertainty. When uncertain, they hesitate and respond tentatively until they can resolve their uncertainty.

My claim is that these five concepts map directly to the fundamental syntax of every one of the six thousand or so symbolic languages currently in use. Agents and objects both convert to nouns and noun-like entities that serve as subjects and predicate objects in declarative statements. Similarly, actions convert to verbs and verb-like phrases. When we combine nouns with actions, we get predications, or what I like to term claims, which are the fundamental units of symbolic discourse. Valences foreshadow the use of adjectives, adverbs, and other modifiers that add nuances to our claims, and uncertainty is represented by modal verbs expressing possibility, probability, or necessity.

As much ground as all this covers, it is important to understand what the language of thought does not entail. Take the sentence “John is tall.” That thought would never occur to either a baby or a dog. It is inherently symbolic in nature, and until you have a symbolic language, it cannot exist. In The Infinite Staircase, it belongs to the stairstep of analytics, whereas the language of thought can reach no higher than the stairstep of narrative.

It is on the stairstep of narrative that the language of thought passes the baton to symbolic language. We cannot tell stories without symbolic language, but it is clear from the behavior of both toddlers and long-term pets that we want to. The connection that binds the two at this point is a realization of cause and effect. Narrative is how we process cause and effect. The breakthrough of symbolic language is that we can not only be a lot more precise in our communication, increasing its efficacy, but also that we can abstract from one narrative concepts and patterns that can be applied elsewhere. This is the miracle of analytics, and it only comes with symbolic language.

To close, let’s revisit our first question—where exactly do our (symbolic-language-expressed) thoughts originate from? This is not a brain-processing question—that landscape is still under investigation—but rather a question of lived experience. Where does it feel like they come from?

My answer is that they are chemically generated responses that represent fluctuations in our homeostatic balance. Like all organisms, we are compelled to seek this balance all the time. The more we get out of balance, the stronger the chemical signal to respond, the more intense the resultant stream of thoughts will be. This applies to dreams as well as to when we are awake. We are continually processing a stream of thoughts that emerge into consciousness and finding their linguistic expression as they do. We register these thoughts through listening to ourselves and shape them further through talking to ourselves. It is only when we get to the talking that we are fully immersed in symbolic language.

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

— Image credit: Pixabay

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The 8 Best Teamwork Books That Actually Improve Collaboration

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The 8 Best Teamwork Books That Actually Improve Collaboration

GUEST POST from David Burkus

Most leaders know teamwork matters. But few take the time to study what actually makes teams work.

We rely on instinct, gut feel, or experience from past teams—good or bad—and assume it’ll all work out. But in today’s complex, collaborative, cross-functional world, those assumptions often lead us astray.

If you want to lead high-performing teams consistently, you need better inputs. And for me, some of the best inputs have come from books—not just books about leadership, but books specifically about teamwork. The kind that change how you think about team culture, team dynamics, and the actual work of working together.

These aren’t just good reads. They’re the best teamwork books I’ve found, presented in no particular order because this isn’t a ranking… it’s a resource.

📚 Best Teamwork Books

1. The Five Dysfunctions of a Team by Patrick Lencioni

Probably the first one you thought of too. This is a business fable that somehow nails real team dysfunctions with precision. Lencioni’s model—from lack of trust to inattention to results—offers a practical, memorable way to diagnose and address breakdowns. I’ve referenced this book with dozens of leaders because it gets past the surface and straight to the relational heart of team performance.

2. The Culture Code by Daniel Coyle

Coyle makes the case that talent alone doesn’t create great teams—culture does. He distills team culture into three key behaviors: build safety, share vulnerability, and establish purpose. What stood out to me is how much of team excellence is invisible, built in the small moments. It’s a great reminder that culture is less about slogans and more about habits.

3. Dream Teams by Shane Snow

This one turns a lot of conventional wisdom upside down. Shane Snow argues that the best teams aren’t the most harmonious—they’re the ones that learn how to disagree productively. With examples from science, sports, and even organized crime, he shows that friction (when handled well) makes teams smarter. A great read for leaders dealing with complexity and cognitive diversity.

4. Team of Teams by Stanley McChrystal

McChrystal’s story of transforming Joint Special Operations Command is a masterclass in breaking down silos. His team couldn’t win modern battles using traditional hierarchy. So they built a “team of teams” built on shared consciousness and empowered execution. It’s a great reminder that agility isn’t just for startups—it’s a requirement in any complex environment.

5. Collaboration by Morten Hansen

Here’s the uncomfortable truth: not all collaboration is good. Hansen shows that ineffective collaboration can actually make performance worse. His concept of disciplined collaboration—knowing when and how to collaborate—helped me see the difference between helpful alignment and wasted effort. Especially valuable for leaders in large or matrixed organizations.

6. Tribal Leadership by Dave Logan, John King & Halee Fischer-Wright

This book maps out five stages of team culture, from toxic to world-changing. What makes it stand out is the focus on language—how the words people use reveal the tribe they belong to and the performance they can unlock. It gave me a new lens for diagnosing team dynamics and helping leaders upgrade their team’s shared narrative.

7. Teaming by Amy Edmondson

Unlike most books that treat teams as fixed entities, Teaming focuses on teamwork as a dynamic, ever-evolving process. Edmondson shows how people must learn to collaborate quickly across boundaries, roles, and expertise areas—especially in fast-moving environments. It reframed for me how learning and collaboration go hand in hand, especially when teams are temporary or fluid.

8. Best Team Ever by David Burkus

Yes, it’s mine. But if you noticed, a lot of these other books are pretty old. They’ve stood the test of time, but research is always evolving. And so I wanted to understand what consistently sets high-performing teams apart—based on the latest evidence. What I found were three repeatable habits: common understanding, psychological safety, and prosocial purpose. Best Team Ever is a blueprint for building teams where people do their best work—and genuinely want to.

Final Thoughts

You don’t have to read every book on teams to lead a great one. But you do need to rethink how you approach teamwork—what you reward, what you reinforce, and how you respond when things go sideways. These are the best teamwork books that helped me do that. They changed how I build, lead, and coach teams—and they might do the same for you.

Because great teams aren’t just born.

They’re built — habit by habit, choice by choice, leader by leader.

Image credit: David Burkus

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Leading to the Future of Work

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GUEST POST from David Burkus

If you led a team through 2025, you probably felt like you were trapped in a never-ending game of workplace buzzword bingo. Coffee badging. Quiet quitting. Quiet firing. Corporate catfishing. Every week came with a new term, a new “trend,” and a new reason to wonder whether you were falling behind in the future of work—or just drowning in noise.

That’s the challenge for leaders right now: not “keeping up,” but getting clear on what actually changed. Because some of what we saw in 2025 wasn’t a fad. It was a preview. And 2026 won’t be a clean break from the past; it’ll be the year those shifts harden into the new defaults.

Here’s what I mean. In hindsight, 2025 wasn’t a year of brand-new problems. It was a year when familiar tensions finally became impossible to ignore: autonomy versus control, speed versus security, loyalty versus flexibility, experience versus reinvention. The labels made it feel new. The underlying issues weren’t.

And the way most organizations responded? Predictable. Also, mostly wrong.

When leaders face uncertainty, they usually reach for what worked before. They tighten policies. They standardize schedules. They add approvals. They try to “fix” culture with perks. It’s a natural reflex—especially when performance pressure is high. But it assumes the problem is that people need more rules, more oversight, or more incentives.

In reality, the lesson of 2025 is simpler: the rules of work didn’t just bend. They rewired. And if you keep trying to manage 2026 with a 2016 playbook, your team won’t just feel frustrated—they’ll quietly build workarounds. That’s where the real risk lives.

The Future of Work Is Structured Flexibility, Not a Return to the Old Office

Take the return-to-office story. Early 2025 looked like a full-scale push back to “normal,” with big-name companies raising the stakes and making attendance a mandate instead of a suggestion. Plenty of leaders braced for a rebellion.

But the more interesting story was what happened after the headlines: most people returned. Not necessarily happily. Not necessarily five days a week. But they showed up — often because they felt they didn’t have a better option.

And then something else happened. Leaders started realizing that office time isn’t a strategy. It’s a setting. You don’t get collaboration just because you share a zip code.

In the data, the pattern has been consistent: the best outcomes show up when people have flexibility—and when that flexibility is designed with intention. Hybrid can work. Remote can work. In-office can work. What doesn’t work is forcing one model without explaining the purpose or giving people any control.

That’s why I don’t think 2026 will be the year “RTO wins” or “remote wins.” I think 2026 will be the year structured flexibility becomes the default. You’ll see more anchor days, where teams coordinate time together for the work that benefits from face-to-face interaction. You’ll see more meeting-free focus time. You’ll see more experiments that look like “summer Fridays,” only year-round.

The real debate was never about office chairs. It was always about autonomy.

And autonomy doesn’t mean chaos. It means leaders stop managing presence and start managing performance.

AI Didn’t Replace Your Team. It Joined It.

The second shift is happening just as fast, but with more confusion: AI stopped being a novelty and started becoming a coworker.

In 2025, a lot of organizations rolled out enterprise AI tools — often with the best of intentions. But leaders ran straight into a new kind of friction: security guardrails that made the tools less useful than the consumer versions people were already using.

So employees did what humans always do when systems slow them down: they routed around them. They used personal accounts. They used personal devices. They found ways to keep moving.

From a productivity standpoint, that makes sense. From a risk standpoint, it’s terrifying.

And it creates a trust problem on both sides. Leaders worry about data leakage and compliance. Employees feel like the company is handing them a power tool…then wrapping it in bubble wrap and asking why the job isn’t done faster.

Here’s what 2026 is likely to bring: less debate about whether AI belongs at work, and more expectation that everyone knows how to use it responsibly. Senior leaders will lean on it for strategic thinking and competitive analysis. Frontline employees will use it to automate the “gray work” that clogs calendars—summaries, drafts, templates, first passes—so they can spend more time doing what humans still do best: judgment, creativity, and problem-solving.

The winners won’t be the companies with the fanciest AI license. They’ll be the ones that treat AI like a teammate who needs onboarding, training, and clear norms.

Your Team Is Becoming a Network

Meanwhile, another major shift has been quietly becoming permanent: freelancing is no longer a side hustle. It’s becoming infrastructure.

Layoffs, hiring freezes, and reorganizations pushed a lot of talented people out of traditional roles. At the same time, organizations started pulling contractors in—not just for gig work, but for high-skill roles: finance, HR, operations, even fractional executives.

This blurs the line between “employee” and “teammate.” And in 2026, that line will blur even more.

That creates a leadership challenge most managers weren’t trained for. Traditional management assumes stable teams: the same people, the same roles, the same reporting lines. But the emerging reality looks more like a project-based network, where talent plugs in, contributes, and moves on—sometimes to your competitor, sometimes back to you, sometimes to three other clients at the same time.

If you keep treating contractors like “temporary labor,” you’ll get temporary commitment. But if you start treating them like part of the mission, you’ll get better work, better collaboration, and—over time—a stronger talent ecosystem around your team.

In the future of work, leadership is less about supervising a roster and more about stewarding a network.

Generational Change Isn’t a Culture War. It’s a Coordination Problem.

Finally, 2025 made one more shift impossible to ignore: the workforce mix is changing fast.

Millennials have moved into the largest share of management roles, Gen Z is stepping into leadership earlier than many expected, and boomers are retiring—but unevenly, and often later than planned. That means many teams now include people in radically different life stages, with different expectations about careers, technology, and what work is “for.”

A lot of leaders respond to this by stereotyping. “Gen Z doesn’t want to work.” “Millennials are entitled.” “Boomers won’t let go.” That framing is easy…and lazy.

The better framing is this: cross-generational teams aren’t doomed. They’re just harder to coordinate. And coordination improves with curiosity.

If you want the brilliance without the conflict, you can’t lead by assumption. You have to lead by inquiry.

What to Do Next: 5 Moves to Lead the Future of Work

The point of all these trends isn’t to predict the next buzzword. It’s to build a team that can adapt when the next shift arrives — because it will.

Start here.

First, design autonomy on purpose. Don’t “allow flexibility” as a perk; build it as a system. Get clear on which work truly benefits from synchronous time together — onboarding, creative collisions, complex problem-solving—and which work benefits from uninterrupted focus. Then build schedules around those moments. When people understand the “why,” they’ll stop treating policies like arbitrary rules and start treating them like shared commitments.

Second, upgrade accountability from monitoring to check-ins. If your instinct is to measure hours, logins, or keystrokes, you’re solving the wrong problem. Accountability works best when it’s social and meaningful: clear goals, frequent progress conversations, and regular moments where people can ask for help before they’re stuck. When teammates feel counted on—not watched—they show up differently.

Third, onboard AI like you would a new hire. Make training normal, not optional and not reserved for “the tech people.” Give your team safe ways to experiment. Define guardrails in plain language: what data can be used, what outputs must be verified, what decisions require human judgment. And partner with IT and compliance to make policies usable in real work, not just defensible in audits.

Fourth, lead your contractors like they belong. Invite them into the rhythms that create cohesion: the kickoff, the retro, the celebration, the shared language of “what good looks like.” Show them how their work connects to outcomes, not just tasks. You don’t have to pretend they’re full-time. But you do need them to feel like insiders while they’re with you—or you’ll pay the tax later in misalignment and rework.

Fifth, build reverse mentoring into the culture. Don’t wait for it to happen organically. Create opportunities where Gen Z can teach tools and trends, while more experienced employees share context, judgment, and the “why” behind how the organization works. The goal isn’t to make everyone the same. The goal is to help people value what the others bring.

If 2025 taught us anything, it’s that change isn’t a season anymore. It’s the operating environment. High-performing teams aren’t the ones that finally “figure it out.” They’re the ones that keep learning faster than the world keeps shifting.

That’s what the future of work will reward in 2026: leaders who can replace control with clarity, replace policies with purpose, and replace rigid teams with resilient networks.

Image credit: Pixabay

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Compelling Narratives

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Compelling Narratives

GUEST POST from Geoffrey Moore

As human beings we cling to two misconceptions of life. The first is that life is fragile. That is not quite right. Living things are certainly fragile — we are all subject to injury and will eventually die. Even whole species can go extinct. But life itself is anything but fragile. It originated some 3.5 billion years ago and has subsequently taken over the entire planet — land, water, sky, even deep within the earth — and shows no signs of loosening its grip. Life per se, in other words, may be the most powerful force we can experience.

Our second misconception is that, when it comes to our own lives, we are the ones in charge. There is some truth in this, but there is also truth in the notion that life is in charge of us. That is, life per se has an agenda that is independent of us, an agenda in which we are inexorably embedded, one that is grounded in the two universal functions that have enabled it to withstand the test of time — metabolism and reproduction.

We know a lot about these two functions from our study of the microbiology of the cell. Both entail a mindboggling number of chemical reactions chained together by a myriad of cascading pathways that are in turn governed by a byzantine array of positive and negative feedback loops. What is truly astounding is that, working in tandem, they have, from their very inception, been both dynamic — ever-changing—and persistent — continuity-maintaining. Life per se, in other words, is characterized by sustained dynamic equilibrium.

To be sure, life has evolved enormously since its cellular inception. After about 2 billion years of single-celled organisms only, cells began to collaborate with one another, leading to the emergence of additional layers of complexity. Over the 1.5 billion years since, they have generated all the variety of living things we see today, as well as a huge variety of species that have passed out of existence. But amidst all that change, over that entire immensity of time, at the level of the cell itself, this absurdly complex concatenation of cascading processes has never ever stopped. Based on this history, I think we must conclude that living things are compelled to live, and that includes us.

Yes, we can end our lives through suicidal interventions, but we cannot will our hearts to stop beating or our lungs to stop breathing. We can’t stop sleeping, and we can’t stop waking up. In short, we are embedded in something that is much larger and more powerful than our conscious selves, and we need to appreciate how this shapes our lived experience.

It turns out there is a whole tradition in philosophy called phenomenology that takes this premise as its starting point. It is organized around the work of Edmund Husserl and Martin Heidegger, but not in a way I am happy with. Like most philosophers, Husserl and Heidegger anchor their work in analytics and then search for narratives to illustrate their concepts. This runs counter to the fundamental premise of The Infinite Staircase, namely that the stairstep of Narrative precedes the stairstep of Analytics, both in evolutionary time and in order of priority when establishing meaning. That is, you need to get your narratives in focus first and then apply analytics to them, not the other way around.

The reason this is so important is that lived experience expresses itself in narratives, not analytics. Analytics abstract from narratives underlying principles which can be used to refine our strategy for living. This is an incredibly important function, one that underlies virtually all the amelioration of the human condition that we have accomplished over the past several centuries. But analytics cannot substitute for narratives. They cannot capture the immediacy of experience nor engage our sensibility with anything like the power of narratives. We are story-telling creatures, first and foremost. That’s how and where we develop our understanding of cause and effect.

Now, if we take the notion that we are compelled to live and we add it to the notion that narrative is our primary mode for processing lived experience, we can reasonably surmise that we are compelled to tell stories. What might that mean?

Well, for those of us in business, this is not a big surprise. We spend the bulk of our time engaged in storytelling and listening. What are you working on? How is it going? What’s the plan? How did the call go? Did you find that bug? What did Harry want? You get the idea. Stories are our lived experience, even more so if we are working remotely.

More formal occasions call for more formal storytelling, be that a proposal, a report, an analysis, an earnings call, or an annual plan. The point is, in all those situations, we are compelled to tell a story. Now, to be sure, our story may well be challenged–that is the function of analytics—but it is not OK not to tell one. The reason is that all our future actions will ultimately be grounded in a story that we agree to accept. Even the most routine bureaucratic approval cycles involve storytelling at some point in the process. We cannot act without a storyline to guide us. Thus, we are compelled to tell stories.

This is even more the case in the realm of politics. Today we are awash in political storytelling, much of which is being labeled misinformation. But the term is misleading. It implies that the teller has got their facts wrong. But that is not what is happening. Instead, they are telling a story that they believe will generate the political response they are seeking, be that to get themselves elected, or to prevent someone else from being elected, or to get legislation passed, or to block legislation from being passed. Our job as responsible citizens is to apply our analytics to their narratives to detect the ones we endorse and those we repudiate.

In both business and politics, pressure-testing the narratives we are presented with requires both judgment and experience. We normally do not have access to an irrefutable body of facts. Instead, we have to assess the character of the storyteller based on how they come across to us, how self-serving their story might be, how plausible it is, and the like, and we often draw on the opinions of professional commentators whom we have found to be trustworthy. There is no guarantee we are going to get things right, but the more due diligence we do, the more likely we will get close.

But what about all the lies? What about all the blatant liars that are just getting away with it? Why aren’t they being held to account? Why do their supporters believe them? The answer, in my view, is because they want to. People are not stupid. They know when other people are lying. The reason they accede to such lies and bully each other into accepting them is because the story being told validates their lived experience. You or I might repudiate the narrative, but we cannot repudiate their lived experience. That is theirs, not ours.

What we can do is share lived experiences with each other with the goal of finding common values. This requires a level of civility that we see openly mocked and that mockery is perhaps the most dangerous current in our present circumstances. It is not the narratives that are the problem. It is the sneering. We can work our way out of the toughest situations if we respect each other’s perspectives. We cannot do so when we demean or demonize our opponents. Stories and storytelling are the currency of our being. We cannot let it be debased.

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

— Image credit: 1 of 1,500+ FREE quotes available at http://misterinnovation.com

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How Human-Centered Leadership Can Reimagine the Aerospace Industry

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Move the Needle

How Human-Centered Leadership Can Reimagine the Aerospace Industry

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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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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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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Never Trust a Guru

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Never Trust a Guru

GUEST POST from Greg Satell

In 2005 W. Chan Kim and Renée published Blue Ocean Strategy, which found that “blue ocean” launches, those in new categories without competition, far outperformed the shark-infested “red ocean” line extensions that are the norm in the corporate world. It was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ published, Profit from the Core, around the same time. They found that firms that focused on their ”core” far outperformed those who strayed. For example, they warned that Amazon was putting itself from peril for expanding its business beyond books and predicted dire results.

Clearly, none of this makes sense. How can you both “focus on your core” and seek out “blue oceans?” It betrays logic that both strategies could outperform one another. Today, Amazon makes most of its money outside of books. Yes, new markets lack competitors, but they also lack customers. The truth is that most business research is surprisingly shoddy.

Cargo Cult Science

When Richard Feynman took the podium to give the commencement speech at CalTech in 1974, he told the strange story of cargo cults. In certain islands in the South Pacific, he explained, tribal societies had seen troops build airfields during World War and were impressed with the valuable cargo that arrived at the bases.

After the troops left, the island societies built their own airfields, complete with mock radios, aircraft and mimicked military drills in the hopes of attracting cargo themselves. It seems more than a little silly, and of course, no cargo ever came. Yet these tribal societies persisted in their strange behaviors.

Feynman’s point was that we can’t merely mimic behaviors and expect to get results. To illustrate what he meant, he told a story about going to a new-age resort where people were learning reflexology. A man was sitting in a hot tub rubbing a woman’s big toe and asking the instructor, “Is this the pituitary?” Unable to contain himself, the great physicist blurted out, “You’re a hell of a long way from the pituitary, man.”

What makes science real is not fancy sounding words or slick charts with numbers on them. Business gurus often boast of their “research” that consists of hundreds of case study interviews and large databases containing data on thousands of firms, but without the proper methods and controls, those things are meaningless.

The Problem With Case Studies

Organizations are often inscrutable and hard to research. That’s why the preferred mode of analysis is case studies in which insiders are interviewed and a particular situation is interpreted by investigators. These can be helpful, but they also have severe limitations.

First, with shareholders and customers to please, managers are rarely eager to talk about failures. So we usually only hear about successes. Those, of course, are important but also subject to survivorship bias. For example, if a risky strategy results in 1% of the firms being wildly successful and 99% going out of business, then we’ll tend to hear glowing accounts of that lucky 1% and we’ll miss the vast majority that flamed out.

Another issue with the case study method is that it is necessarily limited. When researchers did a case study on a company I used to run, to take just one example, they interviewed insiders (including me) and did their best to interpret what they heard and what they could glean from background information regarding the market.

While I don’t think anything was inaccurate, it wasn’t exactly the truth either. Only a handful of people were interviewed, almost all of them were concentrated in a single part of the business and none of them, besides me, were involved in making decisions. The issues presented in the case study simply weren’t the ones we were actually wrestling with.

The problem with case studies is that they offer little to no documentation. In more rigorous fields like, say, sociology or psychology, researchers are expected to share their data so that others can interpret it. Unfortunately, that’s rarely true in business research.

Working Around The Glitches In Our Brains’ Machinery

We tend to imagine that our minds are some sort of machines, recording what we see and hear, then storing those experiences away to be retrieved at a later time, but that’s not how our brains work at all. Humans have a need to build narratives. We like things to fit into neat patterns and fill in the gaps in our knowledge so that everything makes sense.

Psychologists often point to a halo effect, the tendency for an impression created in one area to influence opinion in another. For example, when someone is physically attractive, we tend to infer other good qualities and when a company is successful, we tend to think other good things about it.

The truth is that our thinking is riddled with subtle yet predictable biases. We are apt to be influenced not by the most rigorous information, but what we can most readily access. We make confounding errors that confuse correlation with causality and then look for information that confirms our judgments while discounting evidence to the contrary.

Unfortunately, so many of the popular management ideas today come from people who never actually operated a business, such as business school professors and consultants. These are often people who’ve never failed. They’ve been told that they’re smart all their lives and expect others to be impressed by their ideas, not to examine them thoroughly.

That’s why it’s so important to not to believe everything you think, there are simply too many ways to get things wrong and so few ways to get things right.

It’s More Important To Be Careful Than Smart

When I lived in Poland, a common aphorism advised that “life is cruel, and full of traps.” From an American perspective, the aphorism can be a bit of a culture shock. We tend to believe in the power of positivity, the American dream and the can-do spirit. Negativity can be seen as something worse than a weakness, both an indulgence and a privation at the same time.

Over the years, however, I came to respect the Poles’ innate suspicion. The truth is that we are far too easily fooled and taken in by those prey on the glitches in our cognitive machinery. Often business gurus have fooled themselves. They believe they have special powers of insight and get taken in by the glitches we all have in our mental machinery.

We get taken in because we want their claims to be true. We’d like to think that there is a secret we’re missing, that there’s a black magic that we’re not privy to and, if we prove our worth and obtain access to a few simple truths, we’ll capture the success that eludes us. Things can seem simple in a PowerPoint deck, but the truth is that the world is a messy place.

That’s why we need to train ourselves to ask the tough questions. What are we not seeing? What data is missing? What are alternative interpretations for the evidence being presented? It’s more important to be careful than smart. We can only make decisions on higher or lower levels of confidence. In the real world, there are no “sure things.”

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

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How to Lead Cross-Functional Teams Without Cracking

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How to Lead Cross-Functional Teams Without Cracking

GUEST POST from David Burkus

You’ve just been asked to lead a new team. But here’s the catch: it’s not really your team. It’s a group pulled together from different departments – sales, marketing, product, maybe even someone from legal whose job seems to be vetoing everything. These aren’t people you hired. They don’t report to you. And they probably don’t report to each other either.

You’ve been handed what might be called a “project committee” or “task force,” but what you really have is a cross-functional team. And while cross-functional teams should be engines of innovation, agility, and organizational alignment, the truth is most of them don’t work very well.

But they can, if you lead them the right way.

The Promise and Problem of Cross-Functional Teams

In theory, cross-functional teams are supposed to break down silos, accelerate execution, and bring diverse perspectives to complex problems. And sometimes they do.

But more often than not, they stall out. One study found that 75% of cross-functional teams are actually dysfunctional—they miss deadlines, blow budgets, or fail to stay aligned with organizational priorities. And it’s not because the individuals aren’t talented. It’s because collaboration across departments requires a different kind of leadership. One that starts with structure, not just speed.

Too many team leaders, especially those new to cross-functional work, start with the work itself. They jump straight into assigning tasks, setting up meetings, and building timelines. That seems logical, it’s a project after all.

But if you don’t pause to clarify goals, define roles, and build new communication norms, your team will default back to the ways of working they know best—the ways of working from their own silos. And that means your team will function more like a loosely affiliated group than a truly collaborative unit.

Why Most Approaches Fail

Cross-functional dysfunction isn’t about poor communication, it’s about misaligned expectations. Everyone brings different priorities, pressures, and mental models into the room. The marketer thinks about brand. The engineer thinks about feasibility. The legal team thinks about risk. And no one is wrong.

But if you don’t create a shared understanding early, those different viewpoints don’t complement each other—they compete. Left unchecked, people stick to their departmental defaults, and the very diversity that was supposed to spark innovation becomes a source of friction.

How Cross-Functional Teams Win

To lead a cross-functional team effectively, you don’t just manage the project, you design the team.

Here’s how.

1. Clarify Goals and Roles

Before anyone touches a task list, you need to get the team aligned on two foundational questions: What are we trying to achieve? Who is doing what to get us there?

That may sound obvious. But in cross-functional teams, ambiguity reigns. Everyone assumes someone else is handling a task. Or worse, two people assume they’re both in charge.

Start by mapping out the scope of the project together. Identify major deliverables. Then ask the group: “Who here feels best equipped to own this?” Let people step forward. If there’s debate, facilitate it. If someone volunteers for a stretch assignment, support them, perhaps by pairing them with a more experienced teammate.

This approach does more than assign work. It sends a message: this is a team, not a collection of departments. And you’re here not just to execute—but to develop.

2. Set Communication Norms

Every department has its own way of working. Some teams live in Slack. Others still rely on email. Some expect immediate responses. Others have a “48-hour rule.” If you don’t align early, miscommunication is inevitable.

At your kickoff meeting, have the team co-create its communication norms. Ask questions like:

How will we keep each other updated on progress?
What tools should we use, and for what?
How do we request help?
How often should we meet?
How will we make decisions?
How will we give and receive feedback?

Document the answers. Make them visible and accessible. Then refer back to them, especially when things get bumpy.

These shared norms help your team navigate differences in communication style and prevent misunderstandings from becoming major roadblocks.

3. Build Empathy Through Common Understanding

Communication norms help people speak to each other. Empathy helps them listen with each other.

People on a cross-functional team aren’t just bringing different skills—they’re bringing different definitions of success. One team member might be evaluated on speed, another on accuracy, another on cost control. If you don’t understand the pressures your teammates are under, you’ll misunderstand their decisions—and maybe their intentions.

One powerful exercise: ask each team member to explain how their performance is measured back in their “home” department. What does success look like? What’s their boss expecting from them? What’s at stake?

You can even create simple “user manuals” for each team member that explain how they like to work, how they make decisions, and what stresses them out.

The more your team understands each other, the easier it becomes to collaborate, and to resolve conflicts when they arise.

4. Foster Psychological Safety

Here’s something most people miss: a lack of disagreement on a cross-functional team isn’t a sign of alignment. It’s a sign of silence.

In the early days of a new team, people tend to be polite. They nod along. They bite their tongues. They say things like, “That’s interesting,” when they really mean, “That will never work.”

But innovation doesn’t happen through politeness. It happens through candor. And candor requires psychological safety—the belief that you can speak up without fear of rejection or ridicule.

To build that safety, model vulnerability as a leader. Say things like, “What am I missing?” or “This is a rough idea—feel free to poke holes.” When people challenge you, thank them. When disagreements emerge, guide the group to evaluate ideas based on assumptions, not egos. Ask, “What assumptions are we each making?” rather than “Who’s right?”

Psychological safety isn’t about eliminating conflict. It’s about making conflict productive.

5. Celebrate Small Wins

Cross-functional projects often span months or even years. And when the deadline feels distant, motivation can wane, especially when team members are juggling other priorities.

That’s why milestones matter. Break the project into phases. Define what success looks like for each one. Then, when your team hits a milestone, celebrate it. A shout-out in a meeting. A thank-you email. A Slack emoji reaction.

Research shows that even small wins, when recognized, can boost morale and performance. Just make sure your recognition is authentic and specific. People know when you’re faking it.

Final Thought: It’s Never Too Late to Reset

Maybe you’re reading this and thinking, “Great… but I’m already halfway through leading a cross-functional team that’s barely functioning.”

Good news: it’s never too late to pause and reset. Call a meeting. Clarify goals. Align on roles. Set communication norms. Celebrate any progress you’ve made. Then start fresh from there.

Cross-functional teams can be challenging. But when they’re led well, they become more than the sum of their parts. They become engines of innovation and drivers of real change across your organization.

And you? You become the kind of leader who makes collaboration work, even when no one reports to you.

Image credit: Unsplash

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Do Your Innovation Words Match Your Actions?

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Do Your Innovation Words Match Your Actions?

GUEST POST from Mike Shipulski

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

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

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

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

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

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

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

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

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

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

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

Image credits: Pixabay

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