Last week I ran a LinkedIn poll suggested by my Creativity professor, Dr. Shelley Carson (2026), asking what best explains the gender gap in big-C creativity. 50% of you said sociocultural, 37% said a mix of all three, 12% said personality, and 0% said biological (good job). I think the wisdom of the crowd is (mostly) correct. Studying under Dr. Carson, one of the foremost scholars in the field of creativity, is a priviledge of a lifetime, and each week she finds a new way to reshape how I think about who achieves creative greatness, and why.

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That question she posed feels more urgent in the age of AI. We’re generating new things at an unprecedented pace, but AI learns from what history has already recognized as creative, a record written overwhelmingly by men. If we want genuinely new ideas rather than anodyne slop, it helps to understand who was left out of that record, and why.

Here’s what I’ve learned about gender and creativity. Explanations generally fall into nature or nurture. The nature view holds that evolution favored men as creators and leaders. The nurture view holds that society assigned men those roles and steered women toward domestic ones. Both have been used to argue that men are “superior.” Only one holds up well.

Dr. Carson shared 3 arguments that have been suggested that explain this gap.

Biology: the weakest explanation

The oldest claim is that men are simply more capable: stronger, smarter, more driven. Men are physically stronger on average, but that’s where the evidence stops. Average IQ is the same for men and women, and there’s no male advantage in divergent thinking, the ability to generate many original ideas that are closely tied to creative potential.

A more serious version of the argument is variability. Men’s IQ scores are more spread out than women’s, so more men land at both the very top and the very bottom. That could put more men in the extreme upper tail. But threshold theory weakens this: above an IQ of roughly 120, extra intelligence has little relationship to creative achievement. And whether men show the same extra variability on creativity measures is much less clear.

Brain research shows some small sex differences, but none that come close to explaining a creative gap of this size. There is no conclusive evidence of female inferiority in intellect or creative ability. At most, men may be overrepresented in the extreme tails of a few contributing factors.

Verdict: To borrow the verdicts from one of my kids’ favorite science shows, this claim is “busted.”

Personality: real differences, modest effects

Here the research finds genuine average differences in traits that matter for creative output:

• Risk taking. Women take fewer risks than men on average (Byrnes et al., 1999; Harris & Jenkins, 2006). But the overall difference is small, with heavily overlapping distributions.

• Agreeableness. Women score higher, with a stronger drive to please others (Weisberg et al., 2011). Highly creative people tend to be less agreeable, willing to reject consensus and frustrate people.

• Self-perception. Women are more self-effacing, while men are more confident and self-assertive (Barron, 1972).

These differences are real. But each is modest, and it’s worth asking how many are themselves products of socialization. Small average differences in personality cannot plausibly produce a 97-to-3 split.

Verdict: plausible. The differences are real, but too small to explain the gap on their own.

Sociocultural factors: where most of the gap lives

This is where Dr. Carson suggests the evidence is strongest, and there are many factors driving it.

How we raise children. Boys are socialized toward independence and achievement, while girls are socialized toward caring for family and relationships. Many talented women don’t pursue goals outside the home until family needs are met. When family resources are limited, they’ve tended to flow to sons. Helson’s (1990) longitudinal research on Mills College women traced how these expectations shaped women’s creative careers.

The cost of family. Highly creative women have historically tended to avoid family responsibilities. Women in Who’s Who are about four times more likely than men to be unmarried and successful women who marry are less likely to have children than equally successful men (Hopcraft, 2024). Only women have been forced to choose between productive and reproductive success.

Oversocialization. Some researchers argue women are “oversocialized” to prioritize the well-being of the group over individual ambition (Helson, 1990). Notably, gender-raising practices vary across cultures, which is hard to square with a purely biological explanation.

Gatekeeping. Creative fields are judged by gatekeepers who decide what gets in, and historically those gatekeepers were men. Marie Curie won the Nobel Prize in Physics in 1903, yet in 1911 the French Academy of Sciences rejected her for membership. That same year, she won her second Nobel, in Chemistry.

Women have historically fared better in literature, and for a telling reason. Unlike science or art, writing required no lab, studio, or block of marble, and so no funding or sponsor. A woman could also publish under a pen name, so the field never knew her gender. Even then, recognition often came late. Fewer than a dozen of Emily Dickinson’s poems were published in her lifetime. She wrote nearly 1,800, and today she’s considered one of the most important American poets (Carson, 2026).

The zeitgeist. The political and religious climate of an era can bar women outright. Across history, many cultures and traditions have restricted women’s education, required their obedience to husbands, or treated them as dependents.

Verdict: confirmed

So is it a mix of all three?

In a sense, yes, and that’s a fair answer. But the three don’t carry equal weight. Biology explains very little. Personality explains some, and part of that may be learned rather than innate. Most of the gap is explained by differences in parental treatment, societal expectations, the demands of family life, discrimination within fields, and the cultural climate of the time.

Why this matters at work

The creative luminaries who made history and the executives who run companies today got there through the same doors: someone opened a gate, forgave a risk, sponsored an unproven idea, or simply invited them to the golf course. Those forces still shape who reaches the top. Women still only hold 29% of C-suite roles, a share that has stopped climbing (McKinsey & Company & LeanIn.Org, 2025), and even worse, just about 11% of Fortune 500 CEO seats (Fortune, 2026).

The pattern is even sharper in the startup world. Startups with at least one female founder received just 19.9% of U.S. venture capital in 2024 (PitchBook, 2025). Those founded only by women received about 2% in 2023 (SSTI, 2024). Investors are gatekeepers too, and their choices shape which ideas get built and which never leave the whiteboard.

We’ve come a long way but the sociocultural mechanisms have not disappeared. They moved inside organizations, and today’s gatekeepers are often people who would never think of themselves that way. Who gets the stretch assignment? Whose failed bet is forgiven? Whose unconventional idea is called visionary and whose is called risky? Who carries the caregiving load that quietly caps their output? The research suggests creative capacity is evenly spread. What isn’t spread evenly is access through the gate. And as AI increasingly shapes what gets made, every talented person left outside it is a cost that compounds.

Who are the gatekeepers in your organization, and who are they letting in? I’d love to hear in the comments.

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References

Barron, F. (1972). Artists in the making. Seminar Press.

Byrnes, J. P., Miller, D. C., & Schafer, W. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367–383.

Carson, S. (2026, September 30). Gender differences in creativity [Course presentation]. Psychology E-1704, Harvard Extension School.

Fortune. (2026, June 3). Women run a record 11.2% of Fortune 500 companies in 2026. https://fortune.com/2026/06/03/how-many-women-are-fortune-500-ceos/

Harris, C. R., & Jenkins, M. (2006). Gender differences in risk assessment: Why do women take fewer risks than men? Judgment and Decision Making, 1(1), 48–63.

Helson, R. (1990). Creativity in women: Outer and inner views over time. In M. A. Runco & R. S. Albert (Eds.), Theories of creativity (pp. 46–58). Sage.

Hopcroft, R. L., Fieder, M., & Huber, S. (2024). Not so weird after all: The changing relationship between status and fertility. Routledge. https://doi.org/10.4324/9781003463320

McKinsey & Company & LeanIn.Org. (2025). Women in the workplace 2025.

PitchBook. (2025). 2024 US all in: Female founders in the VC ecosystem. https://files.pitchbook.com/website/files/pdf/2024_US_All_In_Female_Founders_in_the_VC_Ecosystem.pdf

Simonton, D. K. (1994). Greatness: Who makes history and why. Guilford Press.

SSTI. (2024). Useful stats: Female founders and VC, an overview. https://ssti.org/blog/useful-stats-female-founders-and-vc-overview

Weisberg, Y. J., DeYoung, C. G., & Hirsh, J. B. (2011). Gender differences in personality across the ten aspects of the Big Five. Frontiers in Psychology, 2, 178.

Somewhere along the way, writing about it stopped being enough.

Every piece on burnout, layoffs, AI anxiety, or leaders promoted past their competence reminded me that I wanted to do more than write about these problems. I wanted to put the research to work in the real world and drive real change, one company at a time.

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So I joined forces with a classmate who shared my view of the workplace and was tired of watching from the sidelines. Danielle Kaufman and I recently co-founded The Antidotes, a people strategy firm that diagnoses and treats the root causes keeping organizations from reaching their goals. We’re being incubated at the Harvard Innovation Labs, and we’re both seasoned operators who’ve owned P&Ls and led teams of our own.

We’ve seen what works, what doesn’t, and how much gets lost in between. We know what it’s like to bang our heads against the wall when leadership won’t listen. And we know what it’s like when they do follow through, and the change actually sticks: teams get energized and performance follows.

Which brings me to this newsletter.

Starting today, iopsychmarketer becomes Second Opinion and now lives within The Antidotes’ family as insights.antidotes.io. Here’s what that means for you.

What’s staying the same

• Me. Same research-first approach, same bad jokes, same occasional sailing yarns.

• Your subscription. You don’t need to do anything.

• The topics: AI and the workplace, leadership blind spots, org design, motivation and burnout, creativity and innovation, and how people actually learn.

What’s new

• Occasional guest perspectives from Danielle and others who’ve been in the room when culture breaks (and when it gets fixed).

• More focus on interventions that work, plus early access to the tools we’re building. First up: our free Culture Self-Checkup, which is grounded in validated psychometric instrumentation. If you want to see how your own organization is doing click here to get started.

• A new look. Our brand takes a clinical approach to building healthy organizations, and our colors come from the purples and greens you find in nature. (Design nerds, here’s the image that inspired the palette).

Why “Second Opinion”?
Second Opinion captures our goal of taking a systematic, scientific approach to understanding what’s really going on. Many leaders think they already know what’s wrong: low engagement, change fatigue, a “talent problem.” But those are symptoms, not a diagnosis. My goal with this Substack is to help you look again, research in hand, to find the root causes behind those symptoms and the treatments that actually work.

Thanks for reading this far, and for being here from the start. If you know someone who’d find this useful, I’d be grateful if you passed it along. I’m excited about what comes next, and I hope you are too.

Julie

Julie Legrand is co-founder of The Antidotes. Learn more at antidotes.io.

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But unlike the booms of the bast, this one comes with a side of impending gloom. Specifically, P(doom): the odds, as AI insiders put it, that this technology ends badly for humanity. Estimates from AI leaders run from basically zero to near-certain, with many prominent voices landing around 5 to 10%. At the Axios session on data governance I attended, several speakers put it at 0 to 2%, closer to where VC backers like Marc Andreessen sit.

Of course, the people with the lowest estimates can also afford the nicest bunkers. The rest of us will be “negotiating” with the neighbors over the last can of beans. (Maybe the Preppers have been onto something this whole time.)

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So it’s no wonder motivation and mental health at work are in rough shape. People are being asked to enthusiastically adopt a technology whose own builders can’t agree on whether it ends the world.

Inside companies racing to adopt AI, I keep seeing three types of people: AI Optimists, AI Pessimists, and Ostriches. Self-Determination Theory (SDT) explains why each one behaves the way they do. People thrive at work when three basic psychological needs are met: autonomy (some control over how I work), competence (I’m good at this and getting better), and relatedness (I belong here). Meet those needs and motivation becomes your most powerful adoption tool. Thwart them and you get something else entirely.

Let me start with a story about thwarting them.

Token quotas destroy autonomy

At Tech Week I spent a long time talking with an AI product manager at a global industrial electronics manufacturer. Her company makes the parts inside a lot of the tech the rest of us build, and her team integrates AI across engineering: code development, testing, DevOps.

She was thrilled about the use cases. The company is growing so fast there simply aren’t enough qualified engineers in the world to keep up. Testing is the perfect target: highly technical, deeply boring, and loved by approximately no one.

She’s excited about the promise of AI and deeply frustrated by how her organization is rolling it out. You see, her company sets an AI token quota. Every engineer must burn a set number of tokens each month, and anyone who comes in under is assumed to be slacking. Same quota for everyone, regardless of role or team.

She was blunt: that’s not how the work works. Some of her best engineers spend their days in design sessions. Others live deep in the weeds and blow past the quota by mid-month. Not all roles are the same.

I understand how companies get here. Traditional performance reviews are notoriously unreliable (Buckingham and Goodall make the case in Nine Lies About Work), so leaders reach for something they can count. Token consumption is countable.

But here’s what the quota actually does. These engineers are some of the most intrinsically motivated people in the building. They want to use the tools. Slapping an external target on them doesn’t add motivation. It swaps their autonomy for compliance, and that is DEmotivating.

It’s also expensive. Engineers I speak with keep telling me the same thing: under quotas, people start pouring tokens down the drain, running the priciest models on the simplest tasks just to hit the number. You’re paying more for worse motivation.

The fix: measure outcomes, not inputs. Nobody ever got promoted for how much electricity they used

.

The three people on your AI team

Over the past month on my 100 Conversations tour, I’ve talked with many employees and leaders about work, and AI almost always comes up as a core theme they want to discuss. Most people fall into one of three camps: AI Optimists, AI Pessimists, and Ostriches.

AI Optimists

Optimists are intrinsically motivated to build cool things. They figure the doomsayers are mostly trying to hype the technology to sell more tokens. They have the competence to learn the tech fast and love putting it to the test.

Their blind spot is the business. They’re often not experts in the processes they’re automating, so they can build beautiful solutions to the wrong problems.

Their other risk is quieter. I talked with a young AI developer, let’s call her Meera, who knows that if her project succeeds, roughly 1,000 people will lose their jobs. She loves the work. And yet every morning she thinks about the people on the other side of her success metric, which is impacting her mental health.

For Meera, the professional P(doom) for those 1,000 people isn’t a probability. It’s a certainty. Being the job killer is a real burden for AI developers, and for the leaders and HR managers responsible for carrying out mass layoffs.

Individuals associated with layoffs can experience moral injury: psychological distress that comes from doing, or failing to prevent, something that violates your own moral beliefs. The concept is most often studied in the military and healthcare (Litz, 2009). I’d argue it belongs in tech too.

Even your most enthusiastic Optimists can only take so much. Moral injury wears people down, and it shows up in what I/O psychologists call withdrawal behaviors: absenteeism, presenteeism (showing up but checking out), and eventually turnover. Your best builders are the ones you can least afford to lose. Protect their mental health like you’d protect any other critical asset.

AI Pessimists

Pessimists believe AI is coming for their jobs, and some of them are actively working against your rollout. This isn’t hypothetical. In a 2026 survey by Writer and Workplace Intelligence, 29% of employees admitted to sabotaging their company’s AI strategy, from refusing to use the tools to feeding company data into unapproved ones (Fortune).

Here’s the part leaders should sit with. Among the saboteurs, 30% cited fear of losing their job. But 26% blamed a poorly executed AI strategy. Token quotas, anyone?

Through an motivational theory lens, Pessimists have all three needs under threat. Competence: they feel behind. Autonomy: the tools are being dictated to them. Relatedness: it’s starting to feel like human versus machine (and they resent the Meera’s of the world building them).

Leadership’s instinct is carrots and sticks. In the same survey, 60% of executives said they’re considering cutting employees who refuse to adopt AI. SDT predicts how that goes. Rewards and threats can buy compliance, but not commitment. You’ll get people logging in, not people leaning in.

Ostriches

Ostriches haven’t thought much about AI at all. Their heads are in the sand, either because tech doesn’t interest them or because they’re too busy doing their actual jobs to study it.

They’re not anti-AI. They’re usually deep in the very processes that most need automating, and they’re secure enough in their roles that AI doesn’t scare them. Give them a technical partner who frees up some time, and they’ll welcome the help. They just don’t want to build the models themselves.

So what do you do?

1. Integrate your teams

Stop leaving these groups in separate corners. Put them on integrated teams solving real problems together.

Optimists and Ostriches are a natural pair. The Optimists bring the tech. The Ostriches bring the process knowledge that keeps Optimists from solving the wrong problem. And the time the Optimists free up gives Ostriches room to finally pull their heads out of the sand and try the tools themselves.

Integrated teams help Pessimists too. Working closely alongside people builds relatedness, and over time, psychological safety: the belief that you can ask a dumb question or admit you’re lost without paying for it. That safety is the foundation motivation grows from. Nobody experiments with a tool they’re afraid to be seen fumbling.

2. Grow the top line, not just cut costs

To avoid organizational P(doom), point your AI initiatives at growth, not only at cost cutting.

IKEA is the go-to example. In 2021 IKEA launched Billie, an AI customer service bot that now handles 74% of the customers who use it. Instead of laying off the call center workers whose jobs Billie absorbed, IKEA spent two years retraining roughly 8,500 of them to resolve complex issues or work as interior design sales advisors.

The payoff: IKEA’s remote-sales centers are now the company’s fastest-growing sales channel, bringing in €1.25 billion last fiscal year, up from €1.08 billion. Its customer happiness score rose to 89%, from 60% before Billie (Fortune).

While the design consultations are free; the money comes from what customers buy afterward. And IKEA isn’t a no-layoffs utopia. Its two parent companies, Ingka and Inter IKEA, each cut hundreds of corporate roles this spring. None of those cuts touched the remote-sales centers, and none were attributed to AI. Ingka’s chief digital officer also didn’t rule out future cuts.

That’s actually the lesson. IKEA’s reskilled workers are protected because they’re attached to a revenue line, not because the company is sentimental. Reskilling that shows up as goodwill gets cut in the next downturn. Reskilling that shows up as booked sales has someone fighting for its budget.

AI will reshape your organization either way. Whether it lands as a growth story or a P(doom) story depends far less on the technology than on whether your people feel autonomous, competent, and connected while it happens.

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Sources

Inside Ikea’s big bet on humans in the age of AI, Fortune, July 30, 2026 (all IKEA figures and the spring layoffs)

Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout, Fortune, April 8, 2026 (Writer and Workplace Intelligence survey)

Marcus Buckingham and Ashley Goodall, Nine Lies About Work (2019)

Litz, B. T., Stein, N., Delaney, E., Lebowitz, L., Nash, W. P., Silva, C., and Maguen, S. (2009). Moral injury and moral repair in war veterans: A preliminary model and intervention strategy. Clinical Psychology Review, 29(8), 695–706.

The stadium wasn’t full. Honestly, it had the feel of a high school game, just with a jumbotron and a full cheer and dance team. I was there with a big group, including a friend who works for the NFL and knows more about football than anyone I know. By the final minute, we were mesmerized. It felt like we were watching history.

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If you don’t follow football, here’s the setup: Harvard had the lead late in the fourth quarter when Colgate scored a touchdown to go up by 3 with 27 seconds left. I turned to my NFL friend: “Okay, this is over.” She said crazier things have happened. She did not look hopeful.

Then Harvard marched down the field to the 33-yard line, close enough for a field goal to tie with 4 seconds left. And then: a false start. The penalty pushed Harvard back out of field goal range. The crowd was deflated. The guy next to me predicted that the player would be riding the bench for weeks.

But Harvard didn’t give up. From 44 yards out, they threw a Hail Mary, caught it in a crowd, and pitched a lateral to a freshman who dove into the end zone. Final: Harvard 20, Colgate 17. ESPN played it all weekend and it was picked up by the New York Times.

“This is why football is so exciting,” my friend said. “You never know what’s going to happen.”

Except, it turns out, the Crimson coach did.

The miracle was on the practice schedule

The Wall Street Journal followed up and found the play was by design, not by accident.

Head coach Andrew Aurich, 43, played at Princeton and worked his way up as an assistant from Division III to the NFL. Under Greg Schiano (who learned it from Bill Belichick), he absorbed the gospel of “situational football”: a game lasts 60 minutes, but a handful of seconds at the crucial moments decides the outcome.

So every week, Aurich turns part of practice into a lab for the worst case. He puts 60 seconds on the clock, takes away every timeout, and makes the offense drive the length of the field to win. He’s built a specialized playbook just for covering a lot of ground with almost no time. In his three seasons in Cambridge, Harvard has won five games with scores in the final minute, three of them with time expired.

The play that beat Colgate is called “Big Ben.” A 6-foot-6 tight end, Teigan Pelletier, catches the ball in a crowd while four teammates circle him in a diamond, ready to grab a deflection or take a lateral. Harvard had run it in practice the day before, and Aurich reminded his players of exactly that before the snap. Freshman receiver Nate Bailey took the lateral, just as he had on so many Fridays, and scored.

Aurich’s explanation for why his team stays calm when the whole stadium has given up: “We do it every week, multiple times a week, so there’s no panic.”

So what does this have to do with I/O psychology?

Training.

Specifically, training for the things that are unlikely to happen but change everything when they do. It’s the difference between a lost cause and a team that has already rehearsed the miracle.

Right now, in the middle of AI-driven transformation, training is often the first thing to go. Or it gets reduced to generic on-demand modules instead of the kind of practice that becomes a strategic advantage. Things are moving so fast that many organizations aren’t building training at all. People are expected to figure out new tools, new workflows, and sometimes entirely new jobs on the fly.

The research is pretty clear about what that does to people.

What happens when people stop feeling competent

Arjan van Dam, Gera Noordzij, and Marise Born (2020) studied a situation that will feel familiar to many readers: an organization mid-downsizing. They surveyed 275 employees at a Dutch youth care organization during a reorganization that ran from 2014 into 2015 and ended with 145 people, about 30% of staff, leaving.

They separated two kinds of job insecurity:

• Quantitative: Will I still have a job?

• Qualitative: Will my job still have the things that make it worth doing? (Career opportunities, stimulating work, pay growth.)

Two findings stand out.

First, it was the qualitative kind that predicted lower flourishing, while fear of losing the job itself did not. Read that in the context of AI. Most employees aren’t only asking whether AI will take their job. They’re asking whether their job will still be something they’re good at, can grow in, and care about. That second question is the one this study ties to lower well-being.

Second, employees oriented toward mastery (learning and building skills) flourished more, even with significant job loss looming, while those focused on avoiding looking incompetent flourished less. Wanting to outperform colleagues had no significant effect either way.

Here’s the part that matters for leaders. The authors argue a mastery orientation can be developed through training, that interventions can shape a team’s mastery climate, and that organizations should reduce qualitative insecurity through job crafting and building career adaptability. In other words, this isn’t a trait you hire for and hope. It’s something you build.

A few caveats: this is one cross-sectional, self-report study, the effects are modest, and participants had opted into career advice. It shows association, not causation. But it lines up with decades of motivation research.

For my I/O nerds out there: here are the correlations van Dam and colleagues found.

Where motivation theory comes in

van Dam’s work comes from achievement goal theory rather than Self-Determination Theory, but the two meet at the same place: competence. Mastery goals are fundamentally about growing competence. In SDT, competence is one of three basic psychological needs (alongside autonomy and relatedness) that fuel high-quality motivation and wellbeing. When competence breaks down, when people don’t believe they can do something well, the result is often amotivation: not just low motivation, but no reason to try at all.

That’s the real risk of rolling out transformation without training. Not just slower adoption, but people who quietly stop trying.

And notice what Coach Aurich’s drill actually does. It doesn’t just build competence. It builds it together, so eleven people know their role when the clock hits zero. That’s competence and relatedness in the same rep.

Meanwhile, L&D budgets are moving the other direction

The Center for Creative Leadership surveyed 325 mid- and senior-level HR and talent leaders in June and July 2025 about leadership development spending under economic pressure. The findings read like a playbook for doing the opposite of what Coach Aurich does.

Everyone agrees it matters. Most will cut it anyway. 82% say leadership development is a competitive advantage in uncertain times, and 84% say it becomes even more critical during disruption. Yet 71% expect to cut those budgets if the economy worsens. Only 2% questioned whether the programs actually work. The cuts are about pressure, not performance.

The cuts land closest to the work. If budgets tighten, 46% would reduce development for individual contributors and 42% for first-level leaders, compared with 30% for executives. By CCL’s math, IC budgets would be cut 42% more than executive budgets, and first-level leader budgets 33% more. Meanwhile, 95% plan to maintain or increase investment in high-potential talent.

The timing couldn’t be worse. The World Economic Forum’s Future of Jobs Report 2025 found employers expect 39% of workers’ core skills to change by 2030, yet organizations are trimming development for the very people whose day-to-day work is about to shift the most.

The drill is being replaced by the portal. In a downturn, 69% would increase digital delivery, 67% would decrease in-person training, and 69% would restrict travel for L&D. The top-prioritized method is online on-demand tools (69%). On-the-job training? Just 33%.

Even CCL, which sells leadership development (worth keeping in mind), concedes in the report that on-demand digital learning can’t fully replicate the peer connection and relationship-building of live learning.

A self-paced module can teach you what a Hail Mary is. It can’t get eleven people to run one in four seconds.

What drilling looks like at work

Bespoke doesn’t have to mean expensive. A few ways to borrow from Aurich:

• Rehearse the bad scenarios. Run the “60 seconds, no timeouts” version of your transformation: the AI tool gives a confidently wrong answer to a client, a key system fails at quarter end, a new workflow collides with an old one. Practice the response before it’s live.

• Practice as a team. Big Ben works because everyone knows where to be. Cross-functional drills build shared mental models a solo course can’t.

• Make mistakes safe in practice. Remember the false start? The guy next to me assumed that player’s season was over. But one player’s mistake didn’t sink the team, because the team had already practiced for worse. That’s the difference between a culture built on not looking bad and one built on getting better. Error management training, which encourages people to make and learn from errors during training, has been shown to improve how well people adapt skills to new situations (Keith & Frese, 2008). That’s a mastery climate in action.

• Protect frontline development. The people closest to the work are the ones whose qualitative job insecurity is highest right now.

The bottom line

Investing in L&D will be critical for the future. But sending people to generic training on the basics isn’t enough. The organizations that come out of this transformation ahead will treat training as a strategic advantage: building curricula no one else can replicate, drilling together, and preparing for the moments that matter before those moments arrive.

That false start should have ended the game. It didn’t, because Harvard had already practiced what to do when things went from bad to worse.

Just ask Colgate.

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Resources

The game

O’Connell, R. (2026, October 6). The Harvard football coach who hacked the Hail Mary. The Wall Street Journal. wsj.com/sports/football/harvard-coach-andrew-aurich-hail-mary-0fa0e3a9

The research

van Dam, A., Noordzij, G., & Born, M. (2020). Thriving under uncertainty: The effect of achievement goal orientation on job insecurity and flourishing. Social Indicators Research. doi.org/10.1007/s11205-020-02337-4 (open access)

Noordzij, G., van Hooft, E. A., van Mierlo, H., van Dam, A., & Born, M. P. (2013). The effects of a learning goal orientation training on self-regulation: A field experiment among unemployed job seekers. Personnel Psychology, 66, 723–755. doi.org/10.1111/peps.12011

Dragoni, L. (2005). Understanding the emergence of state goal orientation in organizational work groups: The role of leadership and multilevel climate perceptions. Journal of Applied Psychology, 90, 1084–1095. doi.org/10.1037/0021-9010.90.6.1084

Keith, N., & Frese, M. (2008). Effectiveness of error management training: A meta-analysis. Journal of Applied Psychology, 93(1), 59–69. doi.org/10.1037/0021-9010.93.1.59

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press. https://doi.org/10.1521/978.14625/28806

The industry data

Center for Creative Leadership. (n.d.). Staying competitive amid economic uncertainty: Trends shaping leadership development budgets [Survey of 325 HR and talent leaders, conducted June–July 2025]. ccl.org/guides/ld-budgets

World Economic Forum. (2025). The future of jobs report 2025. weforum.org/publications/the-future-of-jobs-report-2025

“I couldn’t take it anymore, so I left for the public sector … taking a 50% pay cut.”

– Janet, content marketing whiz

“I left for a startup. For the first time in my life, it felt more secure than a large company.”

– Audrey, sales executive

“I just want to give up and start a doggy daycare.”

– Sam, senior leader, recently promoted

“Half our sales team is about to quit.”

– Derek, sales executive

“As soon as I get my bonus, I’m outta here.”

– numerous people,
most with no replacement job lined up

(Names changed, roles accurate.)

These are a few of the poingnant comments I heard in the first two weeks of my listening tour. I wasn’t sure what to expect from my 100 conversations campaign, but the stories people tell you when you’re just listening and not selling are fascinating.

These aren’t the low performers a company would be happy to lose. They’re all in crucial roles, and they were expected to pick up the pieces after a reorg or layoff (for some, multiple rounds of both).

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When Janet turned in her notice, her leadership was shocked and begged her to stay. She was a key architect of the company’s AI deployment and had demonstrated an 86% in output with no recognition for her contribution only insistance to keep increasing the output. No one came close to her ability to produce, pioneering the use of AI while preserving a human perspective. “No thanks,” she told them. Life is too short for that kind of abuse, and the money isn’t worth it.

Audrey, Sam, and Derek told similar stories. None of this would surprise an organizational psychologist. It all centers on a concept called job insecurity. You’re probably familiar with the first type, but most leaders consistently underestimate the second one, which is much more impactful on the organization.

Quantitative job insecurity is the fear of losing your job.

Qualitative job insecurity is the fear of losing what makes the job worth having: interesting work, fair pay, the colleagues you actually liked working with.

You’d think survivors would simply be grateful to still have a paycheck. The research says otherwise. Qualitative job insecurity is linked to depressive symptoms, diminished self-worth, and a loss of interest in life (Van Dam et al., 2020). This is serious stuff.

Why surviving a layoff doesn’t feel like winning

Three well-established lenses explain it.

1. Survivor syndrome

This is the one you’ve probably heard of. Survivors miss their friends and colleagues and sincerely worry about how they’re doing. The research shows survivors experience reduced trust, lower morale, and guilt. Not exactly the setup for a rapid, celebratory transformation. Survivor syndrome is known to hinder goal achievement and undercut people’s ability to cope with what’s in front of them. It’s especially damaging in team-based organizations, where downsizing leaves teams merely surviving rather than thriving (Patton et al., 2024).

It reminds me of a coffee I had with one of my old mentors many years ago. I asked how everyone was doing, and he confided how devastated he was by the layoffs that followed an acquisition. As one of the top revenue-generating partners (and a fantastic leader and mentor), he and his wife were invited to Paris to celebrate the deal. He was so gutted by what happened to his team that he attended the meetings but skipped the “celebratory” boondoggle. Then he quietly bided his time until he could retire, no longer giving it his all as he had done for his entire career.

2. The Job Demands-Resources (JD-R) model

JD-R is a big one in the I/O world. It looks at the balance between what a job asks of you and what it gives you to work with. When demands outstrip resources, you get strain and a decline in both psychological and physical health.

Dlouhy and Casper (2021) found that layoffs reliably produce heavier workloads and unfamiliar tasks at the exact moment support drops away, because supervisors are stretched thinner than ever. Again, doesn’t bode well for quality work or innovation.

3. Threat rigidity theory

This one explains why layoffs so often kill innovation. When perceived threat is high (job insecurity) and perceived control is low (you have no say in the matter), people:

• restrict how much information they take in

• conserve resources

• fall back on familiar standard operating procedures

Leaders, meanwhile, tend to tighten control. Fewer ideas get generated. Risk appetite drops.

So you cut headcount in the name of becoming a faster, more AI-native company, and the predictable result is a workforce that stops experimenting. Fernández-Menéndez and colleagues (2020) found evidence of exactly this pattern: innovation suffers in the aftermath of downsizing.

The result: your best people walk

Stack all three together and you have a workforce that is anxious, risk-averse, overloaded, and under-supported. Then you ask them to drive the transformation. Probably not a great idea.

What comes next is the exodus, and it isn’t your average performers leading it. Your top talent, the people with the most options, are first out the door.

You can see it coming. Cameras off. Colleagues going on medical leave or sabbatical and never coming back. People skipping meetings, or showing up with exhausted faces. Then the goodbye emails start, from more and more experienced people, as the demands on whoever’s left keep climbing until something breaks.

Some survivors get a fast track into leadership, but they’re not ready. Without training, runway, or a backfill for their old job, they can’t deliver what’s expected. Soon they’re out the door too.

What to do before you send the RIF notices

If qualitative job insecurity is the fear of losing what makes work worth doing, the fix is to protect those things on purpose. In motivation research terms, that means protecting people’s sense of autonomy, competence, and relatedness.

Give back some control. Threat rigidity thrives on helplessness, and the research is clear that how leaders lead and manage the change shapes how employees come through layoffs, mergers, and closures (Holten et al., 2019). Let survivors shape how the work gets redesigned, even in small ways.

Rebalance demands and resources, and build competence back up. If the work didn’t shrink, the support can’t either. Newly promoted survivors especially need training and a real plan to backfill their old roles. After one downsizing, survivors learned the work left behind largely by leaning on each other. As one case study title put it, “everybody needs everyone” (Miller et al., 2019). Framing the work around learning and mastery helps too. People oriented toward growth are better able to flourish even under job insecurity (Van Dam et al., 2020).

Honor the loss, and run a fair process. A meta-analysis of downsizing research found that fairness is tied to organizational commitment, for survivors and for those let go (Van Dierendonck & Jacobs, 2012). Survivors are watching how their colleagues are treated. Acknowledging what was lost beats pretending it’s a celebration. Empathy, transparency and two-way communication (where people feel safe to express what’s really on their minds) will go a long way.

So before you send out those RIF notices, have a darn good plan to convince the survivors that sticking around, and staying engaged, is worth their while.

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I’m 2 weeks into my “100 conversations” campaign to learn from real people what happens to people when the org changes underneath them. If you’ve lived this, on either side of the RIF, I’d love to hear your story. [Book 30 minutes here.]

References

Dlouhy, K., & Casper, A. (2021). Downsizing and surviving employees’ engagement and strain: The role of job resources and job demands. Human Resource Management, 60(3), 435–454. https://doi.org/10.1002/hrm.22032

Fernández-Menéndez, J., Rodríguez-Ruiz, Ó., López-Sánchez, J.-I., & Delgado-Piña, M. I. (2020). Innovation in the aftermath of downsizing: Evidence from the threat-rigidity perspective. Personnel Review, 49(9), 1859–1877. https://doi.org/10.1108/PR-02-2019-0082

Holten, A.-L., Hancock, G. R., & Bøllingtoft, A. (2019). Studying the importance of change leadership and change management in layoffs, mergers, and closures. Management Decision, 58(3), 393–409. https://doi.org/10.1108/MD-03-2017-0278

Miller, S. M., Kim, J., & Lim, D. H. (2019). “Everybody needs everyone”: A case study of workplace learning after a downsize. European Journal of Training and Development, 44(2/3), 159–170. https://doi.org/10.1108/EJTD-02-2019-0013

Patton, G. K., Neubert, E., Neubert, M. J., & Rees, R. (2024). Surviving, not thriving: The impact of downsizing on team-based organizations. Business Horizons, 67(3), 251–262. https://doi.org/10.1016/j.bushor.2024.02.006

Van Dam, A., Noordzij, G., & Born, M. (2020). Thriving under uncertainty: The effect of achievement goal orientation on job insecurity and flourishing. Social Indicators Research, 150(2), 659–678. https://doi.org/10.1007/s11205-020-02337-4

Van Dierendonck, D., & Jacobs, G. (2012). Survivors and victims, a meta-analytical review of fairness and organizational commitment after downsizing. British Journal of Management, 23(1), 96–109. https://doi.org/10.1111/j.1467-8551.2010.00724.x

How this all started

I went to my first SIOP conference in April. I was not prepared for it.

Room after room of researchers presenting work that answers questions I’d spent twenty-five years guessing at.

Some of what I heard:

• That moral injury is a leadership problem and not just a soldier’s problem, and that the standard playbook for workplace strain doesn’t touch it, because you can’t fix a values violation by adding resources.

• That the accommodations built for neurodivergent employees turn out to be what everybody wanted, the way OXO designed a peeler for arthritic hands and ended up in every kitchen drawer.

• That AI initiatives are failing on organizational readiness rather than technology, and that I/O has had rigorous methods for exactly that problem sitting on the shelf for decades.

• That middle managers are left with no psychological contract and no good reason to stay.

• That executive presence, which nobody can define, is quietly blocking capable people from leadership.

That’s five sessions out of the twenty-five or so I made it to, out of hundreds on the program.

What got me wasn’t any single finding. It was the arithmetic. Decades of evidence about what makes people commit to work, presented to rooms of specialists, while every executive I’ve ever worked with makes these calls on instinct and whatever framework is circulating that year.

As I sat through the conference it became clearer and clearer that the reason so many transformations are failing right now can be explained, and avoided, through the research being presented in those rooms. The problem is that it’s written by academics for other academics. We call this the scientist-practitioner gap.

So I walked out into the French Quarter and decided I was going to commit the remainder of my career to doing something about that: translate this work into something business leaders can actually use with their teams.

So I quit

This is the second time I’ve walked away from a cushy corporate job, so I have some idea what I’m walking into. But this time I’m taking a customer-focused approach to make sure what I build provides the most value to leaders struggling today.

I’m starting by shutting up and listening.

For the next 100 days I’m talking to 100 people about one thing: what actually happens to people when the org changes underneath them. Not the all-hands version. The reorg that went sideways. The rollout everyone was trained on and nobody adopted. The team that didn’t resist anything, exactly, but quietly stopped caring.

I have theories. Twenty-five years of leading teams through reorgs, layoffs, and system implementations, coupled with the I/O research, leads me to one pretty clear conclusion: transformations don’t fail on strategy. They fail because the people asked to execute were never really bought in, and nobody noticed until the numbers came in.

But theories are how you build the wrong thing confidently. So before I build anything, I want to hear what’s real.

If you’re leading through a change right now, or living through one, I’d like 30 minutes. No pitch, no deck, and half the call is yours to ask me anything.

Book Time with Me

I’ll write up what I hear as I go. Patterns, surprises, and the research that explains what people describe. That’s what this Substack is for over the next few months.

Ninety-nine to go.

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Research points to several ways to maximize it: make the training situation as similar as possible to the real job, provide active practice in varied contexts, and create ongoing reinforcement so new behaviors stick. Training is all well and good, but it only accounts for about 10% of learning; the rest comes from coaches, managers, peers, and hands-on experience. In a way, we’re all responsible for L&D in our organizations.

How we train in the corporate world looks very different from how training works when lives are actually on the line. The hours that first responders, military personnel, and medical professionals invest, not just to get deployed, but to stay credentialed, are staggering. With sports and music, training is far more rigorous than anything most of us experience at work. We often hear from iconic athletes or coaches as keynote speakers at conferences discussing leadership, but I’d argue another topic they’re experts in is the fundamentals of building learning cultures.

I’ve seen good examples and bad examples of learning cultures in my career, but to my surprise, one of the best examples I’ve seen in a long time has been aboard a 37-foot sailboat in the middle of the San Francisco Bay.

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Meet Nick “Wildcard”

Living in the Bay Area, my family is surrounded by some of the best sailing (and the best sailors) in the world, and my kids and husband have recently embraced the sport through our new home away from home at the Richmond Yacht Club. Although I’m typically a fair-weather sailor, I sometimes join them on their nautical adventures, particularly for Wednesday night “Beer Can” races during the summer. Beer Can races are designed to help people develop new skills, and they give boat owners a chance to find and develop crew to join them for more competitive regattas. Yes there is a race, but how the winner is determined is somewhat of a mystery, but from what I can tell points are determined more by how many newbies were developed than who came in first over the finish line.

Last year’s winner of the Beer Can series was one of the club’s most popular skippers, Nick Grebe who’s affectionately known to my family as Nick “Wildcard” (so as not to be confused with all the other Nicks at the club). We first met Nick when my oldest was 12, wandering the docks looking for a boat she could crew on. He invited her aboard his boat Wildcard, a wicked fast Santa Cruz 37, and she was hooked. Soon the whole family was begging their dad each week: “Can we sail on Wildcard tonight?”

A certified level-3 sailing instructor, Nick’s coaching approach is a model any manager or L&D professional would do well to study. Everyone wants to sail with Nick, especially the young people, whom he really takes under his wing. Most of the top sailors at our club have spent time on Wildcard, not just because it’s a cool boat, but because sailing with Nick makes you a better sailor, regardless of where you start. Nick exemplifies what it looks like to build a genuine learning culture, one where everyone onboard reaches a new level on every voyage.

When I think of the learning culture Nick exemplifies, three key lessons I think are worth sharing:

1. See One, Do One, Teach One

Nick’s coaching style reminds me a lot of Dr. Robbie on The Pitt, who embodies the classic medical training method: see one, do one, teach one. On the nights I do join Wildcard, I typically find Nick down below studying charts and weather forecasts while the seasoned crew hustle on deck to get the boat ready. They know just what needs to be done to rig the boat and how to assign simpler tasks to newcomers based on their assessed skill sets. While some of these folks have been sailing for decades, others only a year or so, but they all seem to know their way around Wildcard. Once we’re out on the Bay, it’s this experienced crew guiding the rookies like myself through each maneuver.

I watched this come to life during a recent race, when Nick and the team entrusted my husband Eric, who’s still getting the hang of things, with running a complicated maneuver. Nick stayed quiet while his seasoned mate, Brandon Mercer, coached him through it: “Okay Eric, talk me through what you’re going to do when we hit the mark.” Eric explained his plan, with Brandon offering minor adjustments he should make when the time comes. The principle of see, do, teach translates perfectly from the ER to the Bay, and it’s an approach we should all be applying to learning and development in our work.

2. Drill, Baby, Drill

Another cornerstone of Nick’s approach involves drills. Every night, Wildcard sets out early with plenty of time to drill before the start of the race. If the boat includes brand-new sailors, Nick will always do the “safety talk” calmly explaining some of the most important safety measures to be aware of. Although sailing is a wonderful sport there are some inherently dangerous things that can happen, because if things go wrong, they can go seriously wrong, so everyone on board needs to know these rules.

As newcomers learn port from starboard, the seasoned crew is drilling on more complex challenges and how to be ready for anything. From “man overboard” recovery to docking maneuvers, Nick creates learning opportunities that sharpen every member of the crew, especially on tricky moves they don’t use very often but need to be instinctual when it counts. That’s what a learning culture is all about: meeting people where they’re at and offering small, achievable ways to improve each and every day. It doesn’t happen in one fell swoop, but over time, with lots of reinforcement.

In one respect, corporate training actually does pretty well when it comes to the most risky challenges, in the form of annual compliance training. These are skills most employees will never need, but that are highly consequential if you get them wrong, and they need to be refreshed regularly. Harassment, money laundering, and computer hacking are rare, but the cost of failing to identify them can run into the $millions. The lawyers add new topics to annual training each year — typically after something has gone seriously wrong — but how many other small disasters happen that don’t end up in court? What drills should we all be running on a regular basis that will make our teams better?

3. Let Them Figure It Out

The hardest thing for any coach or manager is learning to let people struggle. When we see our teams flailing, every instinct tells us to step in, the L&D equivalent of Jimmy Fallon’s SNL “IT guy” sketch, where he instructs people to “mooove” and just does it himself. But teams don’t learn that way.

During a recent Beer Can race, my son and I were tasked with trimming the spinnaker, which involves constantly pulling in and letting out lines to capture the most wind. It’s a relentless, experience-driven skill that requires a great deal of nuance, and we were, frankly, not doing a great job. What struck me was that Nick’s only intervention wasn’t directed at us. It was aimed at a seasoned crew member who was coaching us too much. “Let them figure it out,” Nick said, and that was that. Giving people the space to learn by doing and make their own mistakes, without constant correction, is often the most powerful thing a coach can offer. Like the drills, by letting people make mistakes when the stakes are low, you prepare them to do it right when the stakes are high.

Bringing It Back on Land

Sailing with Nick is always fun and an opportunity for continual improvement, wherever one starts and a perfect example of how learning happens. Nick does all of this flawlessly, every Wednesday night in the summer. To recap:

1. See one, do one, teach one - Train your trainers and watch them shine as they upskill others. They learn better and have a real sense of pride and ownership.

2. Drill, baby, drill - Always be learning, meet people where they’re at and don’t forget to keep current on uncommon, but high risk skills.

3. Let them figure it out - Give your teams space to make mistakes in low risk environments, and resist the temptation to over-correct.

If you’re ever in Richmond and want to learn from the best, hit me up and I might be able to get you invited aboard.

Reference

McCall, M. W., Lombardo, M. M., & Morrison, A. M. (1988). Lessons of experience: How successful executives develop on the job. Lexington Books.

The truth is, it’s hard to keep up with parenting and work — and this isn’t a niche issue. One in three workers in America has a child under 18 (U.S. Bureau of Labor Statistics, as cited in Status of Women in the States, 2015). Despite so many of us struggling with these challenges, most working parents go out of our way to come across as professional and polished even if we’re dying inside, showing up at work each day pretending we have the same capacity as our non-child-rearing colleagues. For years I took great strides to obfuscate my parental responsibilities at work, which I now realize sets a bad example for the teams I’ve led. If I brush off the struggle of raising three kids without ever signaling how it impacts my psyche, what signal does that set for other parents on the team who might be struggling? And what message does it send the non-parents who may not appreciate how challenging it is to raise kids?

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The kids (and parents) are not alright

There’s significant evidence that parenting in today’s society is more challenging than it’s ever been: two-thirds of parents say that parenting today is harder than it was 20 years ago (Pew Research Center, 2020). In August 2024, then–U.S. Surgeon General Dr. Vivek Murthy issued an advisory naming rising stress and declining mental health among parents a critical public health issue.

The advisory cited a 2023 American Psychological Association survey finding that 33% of parents reported high levels of stress in the past month, compared with 20% of other adults (Murthy, 2024).

These data hit home for me. I feel the impact of my kids’ struggles as they transition into middle and high school, and I think about the challenges I’ve faced as a working parent that may not be obvious to colleagues without kids, or those just starting their parenting journey. Many assume the early years are hardest, however I had been well prepared by my “sister from another mister,” Dr. Heidi Sallee, an associate professor of pediatrics at St. Louis University, who warned me early in my parenting journey: “Little kids, little problems. Big kids, big problems.”

Over the past sixteen years, Dr. Sallee and I have talked for many hours about the challenges of raising our own kids, and the those she sees in her clinical work in a hospital Adolescent Clinic, where she focuses on teen behavior and mental health. Her kids are more than a decade older than mine, and I’ve always had her on speed dial for parenting problems. “Parenting little kids is physically exhausting,” she once told me, “but big kids are emotionally exhausting.” For parents of middle and high schoolers, the struggle is real right now: adolescent mental health plunged in the early 2010s, with rates of depression, anxiety, self-harm, and suicide more than doubling on most measures (Haidt, 2024), a trend social psychologists such as NYU's Jonathan Haidt have tied to the rise of smartphones and social media (if you're a parent, I strongly recommend you read his book The Anxious Generation and take heed of his advice).

All of this is to say: parents really aren’t okay. And when a kid is struggling, it impacts the parents’ own health and wellbeing and thus their productivity on the job. That’s a workplace problem, not just a home problem.

It’s not fair — for anyone

Before I had kids, I remember a friend and I commiserating about how unfair it felt that we were expected to work until the end of the day, while colleagues with kids got to leave early for daycare pickup. What slackers, we thought. They’re off having fun with their kids while we were the ones doing the heavy lifting.

We didn’t appreciate what our colleagues were actually going through: hours of work after their kids went to bed, sheer exhaustion, output that never actually dropped. We were annoyed that we had to work around someone else’s schedule — even though no one extended us the same grace to our own lifestyles (i.e., we were still expected at our desks from 8am until 5pm, no matter how many margaritas we had the night before).

It’s frustrating for people without kids to watch colleagues receive benefits they don’t have access to, such as paid family leave, child care, and “take your child to work day.” None of these benefits mean much for the 2/3s of workers who aren’t raising families and it can lead to resentment and real tension between those with kids and those without.

That tension can mean the difference between a family-friendly policy that actually works and one that breeds quiet resentment.

What the research tells us: supervisor & collegial support

Organizations understand that supporting familial responsibilities has a significant impact on employee performance, which is why more and more research into work-family conflict is coming out of the I/O psych community. A 2011 meta-analysis (that’s academic speak for a study summarizing a bunch of other academic studies) by Shockley and Singla found that work-to-family interactions are highly associated with job satisfaction. In a more recent 2025 meta-analysis, Blom et al. found that caregiver support from organizations has a real, measurable impact on the bottom line: family-friendly policies are positively associated with employees’ intent to stay, their perceived career success, and their overall health and wellbeing. As a result, organizations are starting to increase benefits to help, which is a great start.

But benefits and policies are really just a starting point. A critical and often undervalued piece of the puzzle is the culture, which centers around supervisor and co-worker support. In my psychometrics course this summer, my professor Leanne Tortez introduced us to her Family-Supportive Coworker Behavior (FSCB) Scale, which measures the extent to which employees perceive their coworkers as willing to actively support their work-family balance (Tortez & Mills, 2022).

The research is clear on what’s at stake. Collegial support is linked to decreased psychological strain, depression, stress, burnout, and turnover as well as increased wellbeing, job performance, job satisfaction, commitment, and work-family cohesion (Tortez & Mills, 2022). Similar findings hold for supervisor support. But if supervisors or peers carry resentment toward colleagues managing caregiving responsibilities, the reverse is just as possible. That’s bad for the organization, and it’s exactly why family-friendly policies can’t stand alone, they must be backed by a culture that genuinely supports family responsibilities.

The question is: how can you tell whether supervisors or teams are actually supporting colleagues? It starts with understanding. Validated survey instruments such as Professor Tortez’s FSCB scale and Hammer et al.’s (2013) Family Supportive Supervisor Behavior Short-Form (FSSB-SF)* can help organizations assess that support directly.

Once you have a sense on where things stand, you can deploy interventions to address the gaps.

For example:

Gatherings for all. A family-friendly event where colleagues can meet each other’s kids and see how cute — and how challenging — they really are does more for culture than “take your child to work day” alone, which tends to draw only the parents of little kids. Family events need to feel worthwhile for everyone, from babies to teens to colleagues without kids at all.

Making benefits more equitable. As my own kids aged out of day care, I lost the need for many of the benefits built around it — but I was glad to see changes to my employers’ benefits policies that started to extend to older kids. Day care credits that can flex toward tutoring, elder care, or pet care. Fertility treatment coverage is becoming more common. Parenting inclusion networks are great but exclusionary. Supporting opportunities for young people to gather, reduces resentment toward parents because all workers feel they have a fair set of benefits.

Leaders setting examples. The reality is I don’t know a parent out there who doesn’t struggle with parenting. And yet, these conversations mostly stay behind the scenes in a hushed “parent to parent” safe space and thus our non-parental colleagues have no clue how challenging it is to parent. How often do senior executives talk openly about their kids’ existence, much less their struggles? Is it because a nanny or a stay-at-home spouse is quietly managing it all, or because they simply don’t want to appear weak? The stories we do hear tend to be the highlight-reel version showing how much fun they’re having — leaders posting about a Taylor Swift concert with their kid, not the nightmare it involved getting the family through flights and hotels and traffic jams getting there.

The bottom line

In a nutshell, the key to building a successful family-supportive environment is more about building culture that supports ALL families (kids or not) than it is about benefits. Understanding whether you have a problem in the first place is an important first step and there are great tools to measure this. Once you know where you stand from a culture standpoint, only then can you take effective action to make this a great school year for everyone at the company.

Reading the research on scales like the FSCB or FSSB-SF isn’t always intuitive — it took me all summer to get comfortable with it. If you want help interpreting or accessing the research (which may be locked behind academic firewalls), DM me and I’d be happy to walk you through it.

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References

Blom, R., Jaspers, E., Knies, E., & Van Der Lippe, T. (2025). Family-friendly policies and workplace supports: A meta-analysis of their effects on career, job, and work-family outcomes. Journal of Vocational Behavior, 157, 104091. https://doi.org/10.1016/j.jvb.2025.104091

Hammer, L. B., Ernst Kossek, E., Bodner, T., & Crain, T. (2013). Measurement development and validation of the Family Supportive Supervisor Behavior Short-Form (FSSB-SF). Journal of Occupational Health Psychology, 18(3), 285–296. https://doi.org/10.1037/a0032612

Murthy, V. H. (2024). Parents under pressure: The U.S. Surgeon General’s advisory on the mental health and well-being of parents. U.S. Department of Health and Human Services. https://www.hhs.gov/surgeongeneral/priorities/parents/index.html

Pew Research Center. (2020). Parents’ attitudes — and experiences — related to digital technology. https://www.pewresearch.org/internet/2020/07/28/parents-attitudes-and-experiences-related-to-digital-technology/

Shockley, K. M., & Singla, N. (2011). Reconsidering work—family interactions and satisfaction: A meta-analysis. Journal of Management, 37(3), 861–886. https://doi.org/10.1177/0149206310394864

Status of Women in the States. (2015). Work & family. Institute for Women’s Policy Research. https://statusofwomendata.org/explore-the-data/work-family/

Tortez, L. M., & Mills, M. J. (2022). In good company? Development and validation of the Family-Supportive Coworker Behavior Scale. Journal of Vocational Behavior, 136, 103724. https://doi.org/10.1016/j.jvb.2022.103724

My answer was pretty brutal: there really isn’t any. Although her company offers hundreds if not thousands of on-demand modules in its learning portal, not a single person could tell her which ones actually mattered. Her manager’s advice was: “Sorry, I don’t have time to go through the catalog with you. I think you should focus on your project management and leadership skills. Good luck!”

The thing is, Jennifer had already taken a lot of the leadership courses in that portal — they’re required for everyone in the company. But since she never had a chance to apply the skills afterward, they went in one ear and out the other.

I wish I could say that was unusual.

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The reality is there’s almost too much training out there, and not enough development. U.S. training expenditures jumped 4.9% to $102.8 billion in 2025, and the top 125 companies averaged $145.5 million in training budget alone (Training Magazine, 2025). More than 90% of Fortune 500 companies run some kind of formal training program, spending an average of $1,270 per employee annually. While the companies with formal training programs enjoy 2.1x higher revenue per employee than those without do consistently outperform the ones that don’t (Walsh, 2026), however 43% of employees say the training they get is ineffective (Axonify, n.d.). The money is there. The design usually isn’t.

How I learned to learn

Jennifer is proof of that at the individual level. I’m proof of it too — because long before I was coaching people through this problem, I was living it myself, on the other end of a very expensive lesson nobody had bothered to teach me.

I was 28, a year out of business school, all ego and ambition, when I got my first team: three associates and a 30-day deadline to build a competitive analysis that would either win us a multi-year transformation engagement or hand it to a competitor. No pressure.

The team fell apart almost immediately. They didn’t have the skills the work required, and when they couldn’t deliver, I did what a lot of first-time managers do: I stopped delegating and just did the work myself. I soon found myself out the door by 6am and home past midnight — sometimes 1 or 2am — for a month straight. I ran the project into the ground trying to carry it alone, and I ran myself into the ground right along with it.

Somehow I survived that month and pulled off a pretty impressive analysis, which I got to present to the client at their offices in Geneva. Not only did the trip come with a very fun ski ⛷️ detour, it also led to millions of dollars in add-on work. Win-win, in my book. But that’s survivorship bias talking. Had I crashed and burned instead — which was very much the more likely outcome — the firm could have lost millions had I failed to deliver. Nobody had set me up to succeed. I just happened to.

Afterward, in the debrief, I admitted to some of the firm’s senior leaders how close to the edge that project had actually been because I had no clue how to manage my team. That admission got me pulled off client work and handed one of my favorite projects ever: working with the L&D team to build new-manager training program built so other young managers wouldn't be one bad month away from the same disaster. This was back when organizations still had the patience for that type of investment. My new L&D friends and I spent a month building a 3-day in-person curriculum that included best practices and role-plays for the moments no one prepares you for (an employee breaking down about a personal crisis, a teammate quietly checking out, a peer who resents reporting to you now). We didn’t stop at the classroom, either — participants came back together over several months afterward to work through what was actually happening on the job.

That program worked. We got rave reviews from the new managers, and it was rolled out firmwide. What’s remarkable is that the lessons I learned building it have stayed with me my entire career and there are techniques I still use today that trace straight back to that program. Which is really the point: it was a learning program, not a training class, and the difference showed.

What “Learning” Actually Means

Here’s where many people get it wrong: they treat training and learning as the same thing. They are not.

Learning is defined as “a relatively permanent change in behavior that results from experience.”

Training is one input into that — and a small one at that. Treating it like the whole equation wastes money and leaves people like Jennifer sitting through training that goes in one ear and out the other.

Gallup’s (n.d.) research on high-development workplaces backs this up with real numbers: organizations that invest strategically in employee development see 11% greater profitability and are twice as likely to retain their people. But “investment” doesn’t mean a bigger course catalog.

The scale of what’s at stake here is real money, not soft-skills theater.

What Actually Works

L&D Strategy

Before you touch a single module, get the structural non-negotiables right — this is the part of the academic literature most companies skip entirely:

• Diagnose before you build. Don’t design training and then go looking for a problem it solves. Run a real needs analysis first, at four levels: organizational (what does the business need), task (what does the role require), person (who has the gap), and demographic (are certain groups systematically underserved).

• Train to competencies, not topics. Decide what you actually want every employee to be able to do, then build the program around those specific competencies — not around whatever course happened to be trending.

• Time it to the moments that matter. Development isn’t evenly distributed across a career — it’s concentrated at a handful of lifecycle moments: onboarding, ongoing capability building, the follow-up after a hard performance conversation, and promotions or job changes. Miss those windows and the rest of the calendar is mostly noise.

You don’t have to reinvent the wheel here, and you don’t have to build every piece of content from scratch. But you also can’t do what Jennifer’s employer did and just “wish her luck.” There’s a huge amount of good off-the-shelf content out there — the opportunity is building a hybrid approach: take what already exists, sequence and structure it properly, and give learners real opportunities to apply it, under real conditions, over time.

None of this is a complicated. It’s just rarely done on purpose.

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References

Axonify. (n.d.). Axonify finds no improvement in corporate training: Second annual state of workplace training study. https://axonify.com/news/axonify-finds-no-improvement-corporate-training-second-annual-state-workplace-training-study/

CCL. (n.d.). The 70-20-10 rule for leadership development. Center for Creative Leadership. https://www.ccl.org/articles/leading-effectively-articles/70-20-10-rule/

Gallup. (n.d.). What high-performance workplaces do differently. Gallup Workplace. https://www.gallup.com/workplace/269405/high-performance-workplaces-differently.aspx

Kraiger, K., & Ford, J. K. (2021). The Science of Workplace Instruction: Learning and Development Applied to Work. Annual Review of Organizational Psychology and Organizational Behavior, 8(1), 45–72. https://doi.org/10.1146/annurev-orgpsych-012420-060109

Johansson, E. (2026, February 12). Mentorship statistics. WorldMetrics. https://worldmetrics.org/mentorship-statistics/

Training Magazine. (2025). 2025 Training Industry Report. https://trainingmag.com/2025-training-industry-report/

Walsh, T. (2026, February 12). Training statistics. WorldMetrics. https://worldmetrics.org/training-statistics/

So by now you might be thinking: we’re doomed. If unskilled people keep ending up at the top, what can we possibly do about it?

Good news: there are evidence-backed ways to catch this before it costs you. Here are a few I uncovered in my research.

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Recruiting & Selection

The cheapest fix happens before you even hire someone.

Instead of trying to manage an unskilled leader after the fact, a good recruiting and selection process lets you screen for skill and behavior instead of vibes. Any I/O psychologist will tell you the single most effective selection tool available is the structured interview in terms of validity and ease of execution. Structured interviews involve pre-set battery of questions that are targeting specific job skills and have a .51 validity estimate* as compared to just .38 for the unstructured, “tell me about yourself” version companies love to use instead (Sackett et al., 2022). Structured interviews are common enough at the entry level. But how many companies are actually running them for their executive hires? Rarely. And even less so for internal candidates who already have the inside track for a promotion.

*TRANSLATION: a “validity estimate” is just a score for how well a hiring method actually predicts whether someone will be good at the job. It runs from 0 (no better than a coin flip) to 1 (a perfect predictor). A .51 for structured interviews means the results reliably lined up with how well people actually performed once hired. A .38 for unstructured interviews means: still somewhat useful, but a lot less reliable — closer to going with your gut.

Here’s the data, if you want receipts:

So if we’re running structured interviews for our leaders, what should we actually be looking for? Alzahawi et al. (2024) suggest recruiting should focus on people with an intrinsic motivation to lead rather than letting the most ambitious candidates dominate the pool. Look for people who are prosocial, collectively minded, and genuinely committed to the group’s success over their own (Alzahawi et al., 2024).

That’s the whole idea behind structured selection: it doesn’t let you coast on vibes, however good yours might be. But if it only predicts 51% of liklihood of success, it’s often not enough. That’s why you need to look at candidates from mutiple perspectives. From there, run a real battery of tests screening for the knowledge, skills, abilities, and personality traits that predict good decision-making instead of looks and charisma. There are dozens of validated assessment tools that can be leveraged to look for specfic personality traits or characteristics you can use to screen for the leadership skills you need.

Training & Coaching

Selection isn’t the only lever. Leaders can also be trained out of their metacognition deficiencies. Or at least to a point.

A 2023 study by Joie-La Marle et al. found that metacognition-focused soft skills training improved self-efficacy and adaptive performance across creative problem-solving, reactivity, interpersonal adaptability, and stress management.

While I wasn’t able to find any examples on training folks out of DKE, I did find an interesting paper by Geringer et al. (2025) who studied ten high-performing physicians exhibiting through imposter syndrome (or phenomenon). This is when people underestimate their abilities instead of overestimating them. The researchers found that through reflection, feedback, and emotional awareness physicians exhibiting imposter syndrome were able to recalibrate their self-assessments. Since imposter syndrome and DKE sit on opposite ends of the same calibration spectrum (Bodislav & Georgescu, 2025), it’s a reasonable bet that training which helps one direction could help the other — though nobody’s tested that directly yet.

While I didn’t go down the coaching rabbit hole (50 academic papers were enough), my TA pointed me toward a body of research showing executive coaching can be effective here too, especially when the organization is actually sponsoring the coach and treating the metacognition gap as a real priority rather than a box to check.

The Real Problem: Nobody Wants to Have This Conversation

Here’s the part nobody wants to say out loud: telling a powerful, possibly narcissistic executive that they might be the problem is a career-limiting move. On paper, these interventions are simple. In practice, almost no one at a company has the standing — or the nerve — to raise it.

That’s why this can’t be left to individual courage. It has to be systemic. At the executive level, that responsibility sits with the Board and Risk/Regulatory functions, who can build selection and training requirements into policy rather than hoping some brave soul speaks up in the room.

Where This Leaves Us

If you’ve read this far, congratulations — you’re deep in the weeds of DKE.

Across this series, we’ve seen that the paths that get someone into a leadership role — ambition, appearance, conversational dominance — have almost nothing to do with whether they’ll actually be good at the job. When leaders exhibiting Dunning-Kruger ignore or dismiss expertise, they erode trust and make overconfident decisions that hurt organizational performance (Nold & Michel, 2023).

The fix isn’t complicated, even if it’s uncomfortable: screen for metacognitive awareness and prosocial traits on the way in, and invest in real training and coaching once people are already in the seat. Direct research on training DKE specifically is still thin, but the imposter syndrome research gives us a solid reason to believe recalibration is possible in both directions.

My take: the organizations that get serious about this and stop treating charisma, appearance, and ambition as proxies for leadership ability are the ones that will avoid becoming the next Enron, Theranos, or WeWork story. The research is there. What’s missing is the will to act on it.

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References

Alzahawi, S., Reit, E. S., & Flynn, F. J. (2024). A legend in one’s own mind: The link between ambition and leadership evaluations. PNAS Nexus, 3(8). https://academic.oup.com/pnasnexus/article/3/8/pgae295/7736721

Bodislav, D. A., & Georgescu, R. I. (2025). New organization heights—The impostor’s impostor syndrome. Encyclopedia, 5(1), 21. https://doi.org/10.3390/encyclopedia5010021

Geringer, J., LaDonna, K., Varpio, L., & Merkebu, J. (2025). Recalibrating self-assessment: Navigating imposter syndrome through metacognitive reflection. The Clinical Teacher, 22(5), e70197. https://doi.org/10.1111/tct.70197

Joie-La Marle, C., Parmentier, F., Weiss, P.-L., Storme, M., Lubart, T., & Borteyrou, X. (2023). Effects of a new soft skills metacognition training program on self-efficacy and adaptive performance. Behavioral Sciences, 13(3), 202. https://doi.org/10.3390/bs13030202

Michel, L. (2013). The performance triangle: Diagnostic mentoring to manage organizations and people for superior performance in turbulent times. LID Publishing.

Nold, H., & Michel, L. (2023). The Dunning-Kruger effect on organizational agility. In V. Bobek & T. Horvat (Eds.), Business, management and economics (Vol. 13). IntechOpen. https://doi.org/10.5772/intechopen.113827

Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection: Addressing systematic overcorrection for restriction of range. Journal of Applied Psychology, 107(11), 2040–2068. https://doi.org/10.1037/apl0000994

Most failures of judgment are pretty low-stakes. But some become the corporate scandals that define an era. Enron’s accounting fraud. Wells Fargo’s fake accounts. Lehman Brothers’ risky mortgage bets. Theranos’s fraudulent blood testing. These didn’t happen only because of ethical lapses and greed — they happened because unqualified people, overconfident in their own judgment, were sitting in the room where it happened. The stakes of getting this wrong are real: today, the economy is teetering on the edge of another tech bubble, with 95% of AI pilots failing to achieve their stated goals (Challapally et al., 2025), and tens of thousands of jobs disappearing due to AI-driven decisions — a possible early sign of leadership overconfidence in yet another emerging technology.

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For your reading & viewing pleasure

At the Society for Industrial-Organizational Psychology annual conference, one of the most popular (standing room only) sessions each year is "From Screen to Science: Finding I-O in TV, Movies, and Games." It's great to see the concepts we study in the field brought to life on screen. While speakers often dissect examples of good leadership on screen, I prefer the dark side. Thrillers, dramas, romcoms, superheroes — fine, whatever. But a good scandal story? I'm all in. Especially when the bad guys lose. Corporate Crime Reporter put together a list of the 100 best corporate crime movies — solid list, but they missed a few of my personal favorites. So here are my top three scandals of the 21st century, and what each one tells us about what happens when we let charisma and confidence outrun actual qualifications and competence.

Theranos

Living in the Bay Area, for a long stretch there, Elizabeth Holmes's story was all anyone could talk about, and I devoured everything I could find on it — John Carreyrou's excellent exposé Bad Blood, Alex Gibney's HBO documentary, or the Hulu docudrama series starring Amanda Seyfried. It's one of the most fascinating case studies of an "unskilled and unaware" leader making catastrophically bad decisions, and getting away with it for a decade.

The math alone is mind-bending: powerful, credentialed people bought into her overconfident speculation to the tune of $700 million, backing a $4.5 billion valuation for technology that never actually worked. How does a college dropout convince people she knows more than PhDs who’ve spent their careers on the exact problem she claims to have solved? Her overconfidence in her own scientific ability met investors’ and advisors’ overconfidence in their own instincts for spotting a winner — and neither side thought to trusts actual experts in the field to validate scientific feasibility of the idea.

WeWork

Oh man, the WeWork story got me too. I remember the buzz in San Francisco when this “innovative” real estate company started convincing everyone it was actually a tech company — one that would somehow “elevate the world’s consciousness,” to use Adam Neumann’s own framing.

Neumann was the platonic ideal of the traits from Part 1 of this series: tall, charismatic, a commanding presence who could talk a room into anything. What he wasn’t was a person with any particular expertise in commercial real estate, corporate governance, or running a business that needed to eventually turn a profit. None of that stopped SoftBank’s Masayoshi Son from pouring in billions after — by his own account — a 12-minute meeting. None of it stopped a board of supposedly sophisticated investors from signing off on related-party deals where Neumann personally profited from leasing his own buildings back to his own company. The IPO prospectus that finally forced a reckoning wasn’t undone by some hidden secret — it was all sitting right there in the filing, waiting for anyone to actually read it with a skeptical eye.

A few good deep dives if you want the details: Reeves Wiedeman's book Billion Dollar Loser, the 2021 Hulu documentary WeWork: Or the Making and Breaking of a $47 Billion Unicorn, and the 2022 Apple TV+ docudrama WeCrashed, with Jared Leto playing Neumann with unsettling accuracy.

Fyre Festival

If Theranos and WeWork are the master class in overconfidence at scale, Fyre Festival is the fast, chaotic, almost cartoonish version of the same story. Billy McFarland sold a luxury music festival on a private Bahamian island — supermodels, gourmet food, five-star villas — and delivered disaster-relief tents and cheese sandwiches in styrofoam containers.

What makes it such a clean DKE case study is how many actual experts tried to stop it. Event planners, caterers, and local officials repeatedly told McFarland’s team the timeline and infrastructure weren’t real — and got overruled or ignored, because McFarland was convinced his vision and his hustle could will the logistics into existence. He wasn’t short on confidence. He was short on literally everything else: potable water, a stage, functioning tents, a working plan.

There are two competing documentaries if you want the full story — Netflix's Fyre: The Greatest Party That Never Happened and Hulu's Fyre Fraud — and it's genuinely worth watching both, since each one got access to different players and they tell slightly different versions of the same collapse.

Conclusion

What do all three of these stories have in common? A good-looking, ambitious, commanding person talks their way into the room, convinces everyone around them to run with an idea, and never brings in the experts who could tell them whether any of it is actually viable. And when experts do show up, they’re rarely as charming or convincing as the leader who got them into that mess in the first place — so they get overruled instead of heeded.

I won’t cry tears for the investors, who arguably should have known better. But the customers, employees, and everyday people who get hurt in the fallout deserve better than leaders who were never equipped to make the calls they were making.

Next week: how to actually screen for and minimize DKE in leadership ranks. It’s not as hard as you’d think — but it does require real governance and commitment from boards and investors to fully vet who they’re granting power

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References

Carreyrou, J. (2018). Bad blood: Secrets and lies in a Silicon Valley startup. Alfred A. Knopf.

Challapally, A., Pease, C., & Raskar, R. (2025). The GenAI divide—State of AI in business 2025 [White paper]. MIT NANDA. https://www.aigl.blog/state-of-ai-in-business-2025/

Corporate Crime Reporter. (n.d.). The top 100 corporate crime movies. Retrieved 2025, from https://www.corporatecrimereporter.com/news/200/the-top-100-corporate-crime-movies/

Crevello, D., & Eisenberg, L. (Creators). (2022). WeCrashed [TV series]. Apple TV+; Zaftig Films; Wondery.

Furst, J., & Willoughby Nason, J. (Directors). (2019). Fyre fraud [Film]. Hulu; Cinemart.

Gibney, A. (Director). (2019). The inventor: Out for blood in Silicon Valley [Film]. HBO Documentary Films; Jigsaw Productions.

Meriwether, E. (Creator). (2022). The Dropout [TV series]. Hulu; 20th Television; Searchlight Television.

Nichols, T. (2024). The death of expertise: The campaign against established knowledge and why it matters (2nd ed., updated and expanded). Oxford University Press. https://doi.org/10.1093/oso/9780197763827.001.0001

Rothstein, J. (Director). (2021). WeWork: Or the making and breaking of a $47 billion unicorn [Film]. Hulu; Campfire; Forbes Entertainment; Olive Hill Media.

Smith, C. (Director). (2019). Fyre: The greatest party that never happened [Film]. Netflix; Jerry Media; Vice Studios.

Wiedeman, R. (2020). Billion dollar loser: The epic rise and spectacular fall of Adam Neumann and WeWork. Little, Brown and Company.

There are a myriad of reasons why some people who reach leadership ranks excel while others fail to rise to the occasion, but I want to zero in on one cognitive bias that trips up leaders if they’re not careful: the Dunning-Kruger Effect, or “DKE” for short.

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What DKE Isn’t

A lot has been written about DKE — and a lot of it is a convoluted or distorted version of the actual research. Here are a few misinterpretations I’ve run into recently:

• “Bad performers wildly overestimate themselves, good performers are more accurate (and often underestimate).” (AI slop.)

• “Dumb people overestimate their intelligence.”

• And whoever came up with the “Peak of Mount Stupid” vs. “Valley of Despair” (see image) chart never actually read the research. Cute gimmick. Tenuous connection to the data at best.

What DKE Really Is

So now we know what DKE isn’t — what is it, really? Let’s go back to the original 1999 research. Justin Kruger and David Dunning at Cornell titled their study “Unskilled and Unaware of It” — a title that says a lot on its own. They found that people with the lowest skills tend to overestimate their performance, people with moderate expertise are more accurate, and people with the highest expertise often underestimate their performance.

The concept underneath all of this is metacognition, which Kruger and Dunning define as “the ability to know how well one is performing, when one is likely to be accurate in judgment, and when one is likely to be in error” (Kruger & Dunning, 1999, p. 1121).

There’s no indication in the research that individuals exhibiting DKE are low performers, feel stupid or have any sense of despair about their expertise. It’s simply that they don’t have a good read on their own ability relative to everyone else’s.

DKE in Decision-Making

Researchers have looked at how DKE shows up specifically in leadership and decision-making — which was the focus of my paper. One of the most interesting studies I found was by Nold and Michel (2023), which found that people with inflated views of their own abilities, once they’re in positions of authority, will make decisions even when they’re (a) ignorant of the subject matter, (b) unaware of important circumstances, or (c) acting like experts when they aren’t. In other words: leaders exhibiting DKE often just wing it, even when they have no idea what they’re talking about. Nold and Michel go further, arguing that this overconfidence damages a leader’s ability to evaluate their team’s performance and shapes their critical thinking and decision-making in ways that hurt the whole organization.

Christopher et al. (2023) looked at DKE alongside high self-efficacy and narcissistic (defined as a lack of empathy plus inflated entitlement, grandiosity, and self-importance) tendencies. They found that people with narcissistic or high-self-efficacy tendencies do tend to overestimate their abilities, though there’s some debate about whether they’re actually unaware of their skill gaps or just unwilling to admit them.

The researchers also found that DKE was negatively associated with hypervigilance in decision-making. In layman’s terms: narcissistic leaders rely on their own gut over facts or outside information, and are more likely to make impulsive calls driven by a positive self-view. They tend to undervalue other people’s suggestions rather than confront their own gaps. Interestingly, DKE was also negatively correlated with decision-avoidance, buck-passing, procrastination, and rationalization. So while the instinctual, overconfident decision-making of a DKE leader can produce bad outcomes, there’s can be an upside: decisiveness and the ability to move fast.

So What?

How does this play out inside organizations? When leaders exhibiting DKE skip consulting experts because they’re too confident in their own read, decision quality drops. Nold and Michel (2023) found that when executives overestimate their own abilities and underestimate their team’s, trust erodes — and that erosion directly hurts organizational agility. Pair that with the impulsive, fact-averse decision-making Christopher et al. describe, and you’ve got the exact recipe behind the corporate scandals and AI-implementation failures I mentioned in the last post.

So to set the record straigh, DKE isn’t really about intelligence. It’s about calibration. The people who should have the most confidence — the deep experts — often have the least, because expertise is what makes you aware of everything you still don’t know. Often, the people you should be listening to sound the least sure of themselves. The ones radiating the most confidence are exactly the ones worth a second look.

None of this gets fixed by hoping people become self-aware on their own. Next week: what the research says on how to reduce DKE in leadership ranks.

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Resources

Bonner, B. L., Baumann, M. R., & Dalal, R. S. (2002). The effects of member expertise on group decision-making and performance. Organizational Behavior and Human Decision Processes, 88(2), 719–736. https://doi.org/10.1016/S0749-5978(02)00010-9

Christopher, K. I., Padmakumari, P., & Herbert, H. S. (2023). Presence or absence of Dunning-Kruger effect: Differences in narcissism, general self-efficacy and decision-making styles in young adults. Current Psychology, 42(2), 1444–1455. https://doi.org/10.1007/s12144-021-01461-9

Kruger, J., & Dunning, D. (1999). Unskilled and unaware of It: how difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134.

Nold, H., & Michel, L. (2023). The Dunning-Kruger effect on organizational agility. In V. Bobek & T. Horvat (Eds.), Business, Management and Economics (Vol. 13). IntechOpen. https://doi.org/10.5772/intechopen.113827

That reminded me of two leaders I’ve worked with who both fit that description on paper — good looking, polished, magnetic in a room. One of them is also a genuinely great leader. The other, sadly, is not. Let’s meet them.

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Glenn, the Good

When I was running marketing at a boutique consulting firm, I often worked with big tech alliance partners to co-promote our services alongside their products. My first glimpse of Glenn was watching him emcee a stage in front of about 5,000 people at a tech conference. The man was impressive — looked and carried himself like Mitt Romney: tall, handsome, polished, articulate. The full package. (And admittedly incredibly intimidating).

As the alliance developed, I had the opportunity to work with him at many conferences and events and that first impression never wore off. I vividly recall the first webcast we did together. If you’ve ever done a corporate webcast, you know the “green room” chaos — speakers, “producers”, marketing and comms folks all logged in, everyone testing audio and video, double-checking slides, nerves running a little hot. My first green room with Glenn was different. He lowered the tension in the room just by being in it.

“Glenn treats his team as the reason he’s any good at all. Barbara treats hers as scenery.”

I’ll never forget how he made a point of learning the name and role of every single person there. There was a behind-the-scenes “operator” the webcast vendor had assigned to handle technical issues — someone off-camera we’d never met before and would likely never meet again. Glenn took the trouble to ask her name. Peggy. When it came time to go live, he looked at the camera and said, “Okay, Peggy, we’re ready — go ahead and start the broadcast.” He called every one of us by name, because he actually saw us, whether we worked for him or not.

Over the years I had plenty of other chances to work with Glenn, and he was consistently that supportive, that respectful, every time. One memory I’ll never forget was when we were at a small conference in Chicago and one of my consultants was giving a genuinely disastrous presentation — boring, poorly delivered, painful to watch. Glenn caught my eye and gestured toward the hallway. Oh boy, I thought. I didn’t prep this speaker well enough. Here it comes.

I was wrong. Instead of calling me or my speaker out, he merely wanted to tell me how he learned how to own a stage himself — that his polish wasn’t an accident, but the product of intensive training with a former 60 Minutes producer. He shared it with generosity, clearly hoping it might help my speaker improve, and help me become a better coach for my own team. Not a single word of criticism. Just the gift of constructive feedback, offered quietly, in a hallway.

Barbara, the Bad

Now contrast that with another leader I’ve worked with — let’s call her Barbara. Like Glenn, she’s tall, attractive, and owns every room she walks into, with her sights locked on the corner office. Unlike Glenn, her only real interest in the people around her is how well they can make her look good.

When I first met Barbara, she described her leadership philosophy as “people are my number one priority.” I never once saw evidence of it. She never bothered to learn most of the members of her team’s names. She was never available. She didn’t answer emails. She never met with them. She was too busy smoozing with senior execs and sending directives down the food chain to the people actually doing the work. Sometimes at 5pm expecting a turnaround by 8am the next morning.

I watched her walk through a conference in Vegas a team had spent months preparing for — the booth, the materials, the pitch, all of it — without stopping once to find a single one of them. She breezed past her own people to get to the executives she actually wanted to be seen with.

The result was exactly what you’d expect: a team that felt invisible, unsupported, and unseen. Skepticism took root. Trust never had a chance. She made it to the corner office but once she got there the results were mediocre at best. Turnover was off the charts and for those who stuck around, rather than rallying to help her take things to the next level, the team simply collected a paycheck and little else. Nobody was particularly invested in whether she, or the mission, succeeded, and chaos ensued.

The Difference

Glenn understood something Barbara probably never will: that supportive leadership isn’t a nice-to-have, it’s the secret to your success. People perform better for someone who sees them — and that performance is exactly what gets a leader to their own goals faster, not slower. Barbara treats her team as scenery. Glenn treats his as the reason he’s any good at all.

The same traits got them both into the room — good looking, magnetic, hard to ignore. Only one of them figured out what to do once they were in it.

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I got a little carried away. The assignment called for 7 sources. I read over 50, because every paper I opened led me to three more, much to the dismay of my family after hearing me pontificate on the subject over dinner for 2 months straight. But the rabbit hole was worth it, because it answered a question I’ve asked myself frequently over the course of my whole career: why are so many people in leadership positions so darn bad at leading?

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The Path to Power
(Not Paved With What You’d Hope)

What I uncovered in the research is that the traits that get you promoted into leadership and the traits that make you good at leadership barely overlap. Three in particular keep showing up as fast-tracks to the corner office, with approximately zero correlation to whether you should actually be sitting in it.

1. Ambition

Ambition — “a persistent and generalized striving for success, attainment, and accomplishment,” per Alzahawi et al. (2024) — is one of the strongest predictors of who reaches senior leadership. Makes sense on its face: ambitious people chase the fancy degrees, work the longer hours, angle for the visibility. What doesn’t make sense is what happens next. Ambitious leaders rate themselves as effective. Nobody else does. Side note: I resisted the temptation of digging deep into the overlap between ambition and narcissism, but the literature is filled with research on the topic. I’ll just leave it at that (for now).

In fact, Alzahawi and colleagues found zero evidence that ambition predicts third-party ratings of leadership effectiveness. So the drive that gets someone the job tells you nothing about whether they’ll be any good at it — it just tells you they wanted it badly enough to get it.

2. Appearance

Yes, really. Multiple studies have found that how a candidate looks predicts whether they get picked to lead — and tells you nothing about whether they can. Stoker et al. (2016) found facial structure strongly predicts who gets selected as a CEO, with no relationship to actual performance. Re et al. (2012) went further, finding that perceived height, facial maturity, and a “healthy” BMI all correlated with higher leadership ratings from observers who had no information about how these people actually led. Nobody’s abilities were assessed. Just their faces. We like to think we’ve evolved past picking leaders like we’re casting a movie. We have not.

3. Talking a Lot

Unfortunately for the strong, quiet types, I’ve got bad news, but research into the “babble hypothesis” found that the person who talks the most in a room gets perceived as the most dominant and the most leader-like — regardless of whether what they’re saying is any good. Marianne Schmid Mast’s landmark 2002 meta-analysis found a strong relationship (r = .55–.60) between how much airtime someone took up and how much leadership ability observers assigned them. The effect was even stronger for men than women. And in case you were hoping this got debunked over time — MacLaren et al. (2020) ran it back in 2020 and confirmed it: talk time predicts who emerges as the leader, independent of whether the talking was useful. It’s sad to say that quantity beats quality, but if you really want to move up in the world, it’s time to start speaking up more.

So What Do We Do With This?

I don’t know about you, but I’ve always wondered why so many good-looking blowhards end up leading teams they shouldn’t, and the quiet, supportive leaders keep getting passed over for promotion.

Turns out it’s not a misperception — it’s a documented pattern. Not that this means ambitious, attractive, talkative people can’t be great leaders. Plenty are. The point is that none of those three traits are why — and organizations that keep hiring and promoting for them instead of for actual leadership capability are, whether they realize it or not, running a selection process optimized for confidence, not competence.

What happens once one of these unqualified leaders is actually in charge — it’s often not pretty.

We only need to look at the famous stories such as Enron, Wells Fargo, Lehman Brothers, WeWork, Theranos to remind ourselves of some truly spectacular disasters from seemingly competent leaders. One might argue these were ethical challenges, but strip away the fraud and greed headlines and you find the same thing underneath: leaders who rejected expertise because they were too confident to think they needed it. And before you file this under “history,” consider that 95% of AI pilots are currently failing to hit their goals while companies quietly lay off the humans who could’ve told them that (Challapally et al., 2025).

Overconfidence in isn't a 2008 problem. It's a right-now problem, particularly when folks are leading AI initiatives. Tune into my next post where I'll dig deep into what happens when leaders succumb to the Dunning-Kruger effect.

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Sources

Alzahawi, S., Reit, E. S., & Flynn, F. J. (2024). A legend in one’s own mind: the link between ambition and leadership evaluations. PNAS Nexus, 3(8). https://academic.oup.com/pnasnexus/article/3/8/pgae295/7736721

Challapally, A., Pease, C., & Raskar, R. (2025). The GenAI divide—State of AI in business 2025 [White paper]. MIT NANDA. https://www.aigl.blog/state-of-ai-in-business-2025/

Henderson, A. A., Matthews, R. A., McKersie, S. J., & Whitman, M. V. (2022). Leading when overweight: The influence of supervisor body weight on subordinates’ perceptions and citizenship behaviors. Journal of Business and Psychology, 37(3), 615–631. https://doi.org/10.1007/s10869-021-09763-2

Mast, M. S. (2002). Dominance as expressed and inferred through speaking time: a meta-analysis. Human Communication Research, 28(3), 420–450. https://doi.org/10.1111/j.1468-2958.2002.tb00814.x

MacLaren, N. G., Yammarino, F. J., Dionne, S. D., Sayama, H., Mumford, M. D., Connelly, S., Martin, R. W., Mulhearn, T. J., Todd, E. M., Kulkarni, A., Cao, Y., & Ruark, G. A. (2020). Testing the babble hypothesis: Speaking time predicts leader emergence in small groups. The Leadership Quarterly, 31(5), 101409. https://doi.org/10.1016/j.leaqua.2020.101409

Nichols, T. (2024). The death of expertise: The campaign against established knowledge and why it matters (Second edition, Updated and expanded edition). Oxford University Press. https://doi.org/10.1093/oso/9780197763827.001.0001

Re, D. E., Dzhelyova, M., Holzleitner, I. J., Tigue, C. C., Feinberg, D. R., & Perrett, D. I. (2012). Apparent height and body mass index influence perceived leadership ability in three-dimensional faces. Perception, 41(12), 1477–1485. https://doi.org/10.1068/p7342

Sadun, R. (2022). The myth of the brilliant, charismatic leader: Research shows that good management is more profitable than a cult of personality. Harvard Business Review Digital Articles, 1–5.

Stoker, J. I., Garretsen, H., & Spreeuwers, L. J. (2016). The facial appearance of CEOs: faces signal selection but not performance. PLOS ONE, 11(7), e0159950. https://doi.org/10.1371/journal.pone.0159950

Most of us aren’t Alexander Hamilton. But many of us are running his playbook.

We take our one or two weeks, stress out packing and prepping, coordinating the petsitter, sitting in traffic, waiting for airplanes and then compulsively checking Slack from the pool, and come home more depleted than when we left. We call it a vacation. Our nervous systems know better.

As a busy mom of 3, student, and writer with a full-time job leading a large team, I understand the gravitational pull of the grindstone.

I also know, intellectually, that rest is one of the highest-leverage things I can do — not just for my family but for my own health, creativity, and productivity. The research is unambiguous on this. So why is it so hard to do?

I’ve been thinking a lot lately about what real rest actually looks like. And I think most of us — and most organizations — are getting it badly wrong.

The truth about “unlimited” vacation (it’s rather limited)

Anyone who’s been offered unlimited vacation will tell you it sounds better than it is. The policy looks great in a recruiting deck. The reality is something else.

Without a set number of days, there are no guardrails — no HR nudges to “use it or lose it,” no social norm telling you how much time off is actually acceptable. So people default to peer pressure and perceived performance expectations, which almost always point toward working more, not less.

In fact, a study by HR platform Namely found that employees with “unlimited” vacation actually take fewer days off on average (13) than those with a traditional policy (15). The freedom to take any amount of time off quietly becomes permission to take less.

From a purely financial standpoint, unlimited vacation looks like a good deal for companies: they don’t have to pay out accrued time when employees leave. But the increased turnover that results from breach of trust it creates, and the burnout it fails to prevent, erodes whatever savings it generates. Research by de Bloom et al. (2022) found that while unlimited paid time off can increase feelings of accountability and control it just as easily can spark guilt, uncertainty, and self-endangering work behaviors, including chronically long hours and exhaustion. The policy, in other words, can make the very problem it’s supposed to solve significantly worse.

Conversely, there’s compelling data suggesting significant ROI from offering long-term time off that makes a real dent in burnout and associated turnover intentions. And yet few organizations in the U.S. offer anywhere near enough time off for genuine rejuvenation.

What rest actually looks like

The word sabbatical comes from sabbath — the day of rest. I didn’t really understand what that phrase meant until I got to know David, a friend and university professor who practices Orthodox Judaism. Not knowing much about the practice, I asked a lot of questions. I soon found myself in awe of the discipline and intentionality of it — the care he takes to stay kosher, to honor the sabbath, to observe each week’s rhythms. When I got the invite to attend his infamous weekly Shabbat dinner, I accepted immediately. The food was extraordinary. The conversation was warm and unhurried. And when the meal ended, no one reached for a phone. No one pivoted to logistics. People just stayed at the table. Talking. Being together.

What struck me most was how consistent he is. David adheres to his practice regardless of how inconvenient it might be. When it came time to attend my wedding on a rainy Saturday afternoon, he walked 3 miles to our church and another 2 to the reception, because that’s what keeping the sabbath requires. No machinery. No money changing hands. No headphones. No podcasts. No popping into the nearest café along the way to grab a coffee. Just the walk — in silence, or in conversation with a friend. For one day each week, he rests. Fully and without negotiation. And with grace, contemplation, and peace that no doubt fuels his creativity and productivity. What seems like a lot of work to an outsider actually brings true peace. It takes discipline to rest fully, and few of us have the will or opportunity to follow this example — but we could all benefit from the structure.

David doesn’t just fully rest once a week. As a tenured professor, he takes longer rests on a regular cycle too — a full semester-long sabbatical every few years. It’s structured. It’s protected. And it’s long enough to actually matter.

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The case for real sabbaticals

What do universities know about rest that the rest of us could learn from? They don’t offer sabbaticals out of the kindness of their hearts — they do so because it leads to better results.

Universities have long understood that genuine, extended time away improves productivity, sparks creativity and innovation, deepens expertise, and reduces the kind of burnout that drives talented people out the door.

While some companies advertise “sabbaticals” as a benefit, most of what they’re offering isn’t a sabbatical in any meaningful sense. An extra week or two of vacation every five years or so isn’t a sabbatical — it’s a long weekend with better branding. It almost certainly won’t move the needle on burnout or retention, which means the cost isn’t justified by the return. Even four weeks away isn’t enough for genuine psychological recovery.

Companies would be better served by offering real sabbaticals — a minimum of eight weeks, on a predictable schedule, structured so employees can actually disconnect.

The financial case is stronger than most people expect — and the math rewards generosity. A study of burned-out nurses by Schaar & Swenty (2012) explored the cost-benefit of sabbaticals and found that a 12-week sabbatical for five at-risk nurses cost $187,150 — far less than the $320,000 it would cost to replace them all, and still cheaper than replacing just three. In other words, the program paid for itself even when 40% of participants didn't return.

Using Schaar & Swenty’s example, I modeled the value created at different sabbatical lengths for knowledge workers, with modeled retention rates based on recovery research: the longer the leave, the more genuine the restoration, and the more likely people are to return.

While the retention improvements in this model are hypothetical, there's substantial evidence that longer breaks meaningfully increase retention. The financial implications are pretty clear. A 12-week sabbatical creates nearly $170,000 in value per cohort of five employees — almost double what a 4-week program generates. That's because recovery isn't linear. A four-week leave barely scratches the surface of genuine psychological restoration. A twelve-week sabbatical gives people enough time to decompress, remember why they loved their work in the first place, and choose to come back. The counterintuitive conclusion: the companies offering the stingiest sabbaticals are likely leaving the most money on the table.

Finding your own sabbath

I haven’t cracked the code on true rest personally — but I’m trying. Over the years I’ve tried digital-free Sundays, blocking downtime on my calendar, enforced separation from what my family refers to as the “holy rectangle.” I’m intrigued by these Brick devices many college students I know use to protect themselves from the compulsion to check their phones. We’re all, it seems, looking for a little structure to hold us accountable to rest.

For me, building a buffer around family vacations has been essential. Instead of short vacations moving from work to adventure and back to work again, I take longer breaks building in a couple of days on each end of my vacations at home to decompress and get organized.

This week, I’m closing the work laptop. Not for a long weekend. Not for a week. Two full weeks. I’ll spend my time reading and relaxing in my new hammock and then head up to my sister’s house in the Sierras for quality family time where phones don’t work.

Alexander Hamilton never went to the lakehouse. He stayed at his desk, building his legacy, until his legacy — and his marriage, and eventually his life — fell apart.

I’m going to the lake.

Share in the comments what plans you have to disconnect and how you plan to re-energize yourself this summer.

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References

de Bloom, J., Syrek, C. J., Kuehnel, J., & Vahle-Hinz, T. (2022). Unlimited Paid Time Off Policies: Unlocking the Best and Unleashing the Beast. Frontiers in Psychology, 13, Article 812187. https://doi.org/10.3389/fpsyg.2022.812187

Schaar, G. L., Swenty, C. F., Phillips, L. A., Embree, J. L., McCool, I. A., & Shirey, M. R. (2012). Nursing Sabbatical in the Acute Care Hospital Setting: A Cost-Benefit Analysis. JONA: The Journal of Nursing Administration, 42(6), 340–344. https://doi.org/10.1097/NNA.0b013e318257390f

White, J. B. (2024). Sabbatical Leave in the Private Sector: An Employee Benefit That Can Be a Cost Saver. Compensation and Benefits Review, 56(4), 249–260. https://doi.org/10.1177/08863687241259860

If you enjoyed this and know anyone who’s curious about industrial-organizational psychology and wants to understand these concepts in layman’s terms, please share.

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No framework. No training. Just a headcount, a mandate, and the expectation that you’ll know how to structure the work. And most of us do what I did for years — we reach for instinct. We think about who’s good at what, draw a few boxes on a whiteboard, and call it an org chart.

Then something breaks. A reorg. A hypergrowth moment. A layoff that cut the team in half. A team that suddenly doubled in size.

That’s exactly what happened to me. Once after a reorg, I inherited a large team with no obvious structure. And for the first time, my instincts had nothing to say. So I went looking for answers.

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What I found sent me down a rabbit hole so deep it eventually led me to Harvard and a deep dive into organizational behavior, org design, and industrial psychology — fields that as a GTM leader I hadn’t much thought about since business school. Turns out, org design is an entire field — rich, rigorous, and almost completely absent from most leadership developments programs.

We teach leaders how to manage people. How to run a P&L. How to build strategy. But we don’t teach them how to design the very structures to get the work done.

The simulation that humbled a class full of Harvard students

One of the most enlightening (yet humbling) moments of my program thus far was in my Organizational Behavior class with the iconic Professor Lee Bolman. Anyone who’s taken his course will tell you it’s a magical experience. Professor Bolman has been teaching since 1969 and is half of the duo — along with the late Terry Deal — behind the classic textbook Reframing Organizations (2021), now in its eighth edition. The book explores organizations through four lenses, or “frames”: Structural, Human Resource, Political, and Symbolic.

In his class, we participated in a simulation where we had to redesign a fictional org structure as our company scaled. We got three attempts. No one succeeded on the first try. More than half of us never reached the optimal design at all (myself included).

That’s not a failure of intelligence. It’s simple the nature of org design which is difficult, iterative, and full of tradeoffs. No structure is universally right or wrong. But some are far better than others.

So what does good org design actually involve?

Bolman grounded us in a foundational insight from Alfred D. Chandler Jr., the Harvard historian whose landmark 1962 book Strategy and Structure studied General Motors, DuPont, and Standard Oil to reach a deceptively simple conclusion: structure follows strategy. Before you can design the right org, you have to be clear on what you’re trying to accomplish. A structure that served your old strategy may actively work against your new one.

Structure isn’t just one thing. Depending on what you’re trying to accomplish, you might organize by function (what people know), by product (what you make), by customer (who you serve), by geography, by process, or by time. Each model carries different tradeoffs.

At one end of the spectrum, you have direct hierarchical chains of command — efficient in simple, stable environments. At the other, all-channel networks where information flows freely across the whole team — powerful for complex, ambiguous work, but slow when you need fast decisions. Most real organizations need something in between, and the calibration matters enormously.

The table below is a cheat sheet of the typical options.

Can’t reach your boss? You’re not alone.

Another crucial concept in org design centers around span of control — a challenge facing many stretched leaders today who feel something is off but can’t quite name why. You’d think most leaders would be thrilled with bigger teams. More people, more output, right? But most often, bigger teams are harder. And there’s a good reason why, when you look at it through a behavioral science lens.

The WSJ recently reported that the ratio of employees to managers has nearly tripled since 2017 — from 5:1 to 15:1 — and it’s still climbing. The headline said it all: Your Boss Doesn’t Have Time to Talk to You (2025). And yet this contradicts everything we know about team effectiveness.

OB researcher J. Richard Hackman was characteristically blunt about it: “A rule of thumb I relentlessly enforce … a team cannot have more than six members.”

Hackman and many other behavioral scientists have demonstrated again and again that productivity gains from teamwork tend to decline as teams grow too large and cumbersome — yet organizations keep moving in the opposite direction.

What are the consequences of this disconnect? When a manager is stretched too thin, decisions slow down or go sideways. Add a layer of management and you gain bandwidth, but lose access and speed. The right design isn’t a formula — it’s a function of complexity, volatility, and the nature of the work itself.

The messy truth about change

Here’s what Professor Bolman taught us that I keep coming back to: no structure is right for all times and circumstances. When your strategy shifts, your structure needs to shift too — Chandler’s logic playing out in real time.

And yet many leaders treat org design like a one-time event — something you do after a reorg and then don’t touch for three years. Others swing to the opposite extreme, constantly reshuffling structures and leaving people disoriented in the process. Like the simulation, there’s no perfect answer. But there are good ones and bad ones.

Professor Bolman was brutally honest about why this is hard: you can’t fully know if a new structure will work until you try it. Things usually get worse before they get better. And every structural choice involves tradeoffs.

That’s not a reason to avoid the work. It’s a reason to take it seriously — to learn the theory, lean on the models, and bring in org design experts when the stakes are high. There are a lot of great ones out there, and this is exactly the kind of problem they exist to solve.

Leaders deserve better Org Design resources

We’ve spent decades investing in leadership development and almost none of it covers this. We promote people into roles that require them to architect teams, and then leave them to figure it out by feel.

When those teams underperform, we diagnose the people. We rarely diagnose the structure.

Org design isn’t magic, but it’s not someone one should attempt without understanding the models and principles of the field. The leaders who treat it that way build better teams. The ones who rely on instinct alone? Let’s just say they may not pass Professor Bolman’s class.

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Have you ever inherited a team with no roadmap for how to structure it — or watched a well-intentioned reorg make things worse before anyone admitted it wasn’t working? I’d love to hear from you in the comments.

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References

Bolman, L. G. (with Deal, T. E. & ProQuest). (2021). Reframing organizations: Artistry, choice, and leadership (7th edition.). John Wiley & Sons, Inc.

Hackman, J. R. (with Harvard Graduate School of Business Administration). (2006). Leading teams: Setting the stage for great performances (Nachdr.). Harvard Business School Press.

Your Boss Doesn’t Have Time to Talk to You -- WSJ. (2025, August 29). Dow Jones Institutional News.

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I was going through the motions on all fronts.

Then one day, I got curious about an organizational challenge I was facing at work — and my world changed. After falling down a research rabbit hole, I discovered a genuine passion for organizational behavior and psychology, and before I knew it, I was enrolled in a summer statistics course at Harvard, jumping out of bed at 5 a.m. to study until the wee hours. All while staying on top of work and those pesky teenagers and with a much more intentional workout routine in place.

How did adding a massive new responsibility to my plate actually reduce my burnout?

Because burnout isn’t about how much you work. It’s about your relationship to the work itself.

Burnout is described as “a condition that occurs when employees become so stressed that they experience emotional exhaustion, depersonalization, and a sense of reduced personal accomplishment” (Levy, 2025). It shows up as decreased motivation, cognitive weariness, lack of energy, and physical fatigue. And the stakes are not just personal. Workplace stress is linked to serious physical conditions including heart disease, which the CDC identifies as the leading cause of disability in the U.S. workforce — costing companies roughly $240 billion per year in healthcare, medication, and lost productivity.

So how do we get there? And more importantly — how do we get out?

While our jobs generate real stressors, how we face them is largely within our control. In the I/O world, we have specific definitions related to burnout worth understanding:

How individuals respond to stressors impacts the likelihood that stress will lead to strain. Numerous studies have shown that individuals with high levels of strain are more likely to be disengaged or burned out, and to have high turnover intentions — planning to quit quietly or leave the company altogether. In extreme situations, it may lead to self harm or workplace violence (believe it our not the term “going postal” is in the I/O textbooks as toxic work climates contribute to mental health decline of workers).

Below is an adaptation of the key model from a leading I/O Psychology textbook that brings this concept to life. Organizational psychologist have ample evidence showing the negative impact of piling stressors and strains onto workers, and strongly suggest that finding ways to reduce stress and offer coping mechanisms isn’t just nice to have. It’s a business essential.

Turning to clinical psychology for coping mechanisms

Although I’m a budding organizational psychologist and not a clinical therapist, our field draws heavily on core psychology frameworks to help organizations reduce employee strain and burnout. I should preface this recommendation with the fact that if things are really bad, getting help from a licensed therapist is essential — and there are many affordable online services available these days — but if things are still manageable, here’s a tool to help dial it down, drawing from the Cognitive Behavioral Therapy Thought Record template (Nick, 2025).

Here’s a situation most of us have lived: your boss sends a Slack message at 6 p.m. — no greeting, no context — “Can we talk about the timeline tomorrow?”

You know the project is behind. And the spiral begins. You lay in bed thinking: We’re not going to make it. If we don’t make it, that’s on me. If that’s on me, I’m gone. If I’m gone in this economy … Next thing you know, you’re three steps from selling your house and living in your car before the sun comes up.

What if, instead of catastrophizing, you try out this Thought Record exercise to reframe the problem? Here’s how it might look in practice.

See what you did there? The stress is not gone — not even close. The project is still behind. The Slack message is still sitting there. The meeting is still tomorrow.

But 55% stressed is not 95%. And 55% is something you can sleep through.

Exercises like this don’t eliminate the problem. But they are great coping mechanisms to help redirect your energy toward what you can actually control — and away from the stories your brain tells at midnight that bear little resemblance to reality.

That’s the shift that made the difference for me. The stress of work, kids, and the economy isn’t going away. But fixating on what I can’t change is just expensive — it costs time, sleep, and bandwidth I’d rather spend elsewhere (such as taking classes and writing Substack articles translating I/O Psych concepts into layman terms).

One more thing worth noting for anyone in a leadership role: managers are often the first line of defense against team burnout. If you notice someone spiraling, this kind of reframing tool isn’t just for your own use. It’s something you can offer strugging team members.

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Sources

Levy, P. E. (2025). Industrial/organizational psychology: Understanding the workplace (Seventh). Worth Publishers, Macmillan Learning.

Nick, E. (2025, September 11). ChoosingTherapy.com. Thought Record CBT Worksheets. https://www.choosingtherapy.com/therapy-worksheets/thought-record/

And yet. I’ve watched meticulously organized projects die quiet deaths, not because the plan was wrong, but because the people executing it ran out of steam. The Gantt chart was perfect. The motivation was not.

Here’s what I’ve come to understand: project management systems are containers. What fills them — or doesn’t — is human psychology. Organizational psychology has a lot to say about why some people and teams drive through their goals while others stall out before the first milestone. Two theories in particular have changed how I think about getting work done, and a third reframes what leadership even looks like in the context of a project.

When too many goals are the problem: Dual-Goal Expectancy Theory

Schmidt and Dolis’s (2009) dual-goal expectancy theory offers a pretty obvious point: there’s a limit to how many hard things a person can pursue simultaneously before performance on all of them degrades. When the combined demands of multiple difficult goals exceed available cognitive and motivational resources, something has to give — and it usually gives messily, without us quite realizing it’s happening.

I see this play out constantly in organizational settings. A marketing team running too many campaigns simultaneously. A tech team rolling out too many new systems all at once. A customer success team managing too many client deployments. A sales team chasing too many “hot” leads. In these cases, you end up operating in a resource deficit that no amount of prioritization theater will fix. The dual-goal model tells us that in these situations, leaders need to make genuine trade-offs, not just add another color to the roadmap.

I see it at home too, particularly with my high schooler who has a particular brand of paralysis that sets in around homework: the more she has, the less she can start any of it. When it gets really bad, I have her write each assignment on a Post-It, and we arrange the cards on a 2x2 matrix — high vs. low impact on one axis, high vs. low difficulty on the other. Then we sequence: easy wins with big impact first, harder high-impact work next, with deliberate breaks woven in. Sure enough, what felt like an insurmountable burden at 4pm is a distant memory by bedtime.

The 2x2 isn’t magic. What it does is externalize the cognitive load of prioritization, so she’s not spending her limited resources just figuring out where to start. As I mentioned in my piece on precrastination, the brain likes done. For managers, the lesson is the same: when your team is buried, help them get the goals out of their heads and onto a surface where trade-offs can actually be made. Then protect them from everything that’s not on the short list.

When autonomy and competency is the point: Self-Determination Theory

Deci and Ryan’s Self-Determination Theory (SDT) identifies three core psychological needs that, when met, produce the kind of intrinsic motivation that sustains long-haul work: autonomy (the sense that one’s actions are self-directed), competence (the sense that one is capable and growing), and relatedness (genuine connection to the people around you).

In the workplace, SDT explains a frustrating phenomenon leaders encounter often: you can have a well-designed project with clear milestones and adequate resources, and it still goes sideways because people feel micromanaged, undertrained, or isolated from the work’s larger purpose. External motivators — performance bonuses, social recognition, the implicit threat of a bad review — can drive short-term compliance. What they can’t do is sustain the kind of engaged, discretionary effort that complex, creative work requires.

Deci et al. (2017) found that when people are more autonomously motivated and feel connected to the purpose of their work, they are able to “perform better, learn better, and be better adjusted.” For managers, this translates into some concrete practices: give people room to decide how they achieve a goal, not just what the goal is. Invest in building competence through real skill development, not just performance feedback. And don’t underestimate the relatedness piece — the degree to which people feel connected to their teammates is a stronger predictor of sustained effort than most compensation models would suggest.

From a project management standpoint, sometimes teams get stuck when they aren’t given the autonomy or feel competent enough to make the decision to get the job done. As a manager it’s your job to help them get there.

While we all want things to be 100% to our liking, sometimes 90% there is good enough. Because 90% done is still 100% incomplete.

When leadership style is the variable: Path-Goal Theory

Robert House’s path-goal theory starts with a deceptively simple premise: a leader’s job is to clear the path between an employee and their goal. Not to own the goal. Not to dictate the route. To remove what’s in the way and provide what’s missing — and to recognize that what’s missing looks different depending on the person and the situation.

House identifies four leadership behaviors, and the key insight is that effective leaders move fluidly between them rather than defaulting to a single style. Directive leadership — clear expectations, defined process, regular check-ins — is exactly what a new team member needs when navigating an ambiguous project. Apply the same approach to a seasoned high-performer and you’ve just micromanaged someone who knew what they were doing. That person needs participative leadership: draw on their expertise, involve them in decisions, treat them as a co-author of the plan rather than an executor of yours.

Achievement-oriented leadership — setting high standards, expressing confidence in the team’s ability to meet them, resisting the urge to lower the bar when things get hard — is what stretch goals require. Supportive leadership, by contrast, is what people need when the work is stressful, the stakes are high, or morale has taken a hit. None of these is universally right. All of them are situationally necessary.

In practice, this means paying attention. Not just to the project board, but to the person sitting across from you in the one-on-one. Is he underwater and needs someone to remove three things from his plate? Is she bored and needs a harder problem? Is the team demoralized after a missed deadline and needs acknowledgment before they can regroup? Path-goal theory won’t answer those questions for you — but it gives you the right questions to ask, and a repertoire of responses when you have the answer.

The leader who picks a style and sticks with it regardless of context isn’t being consistent. They’re being inattentive. And on a long project, inattentiveness to what people need is one of the most reliable ways to watch a plan quietly fall apart.

What this has to do with your project plan

The project management industry has given us increasingly sophisticated tools for tracking work. What it’s less good at is explaining why people do — or don’t — do it. The gap between a well-built plan and a completed one is almost always motivational, not methodological.

Dual-goal expectancy theory reminds us that cognitive and motivational resources are finite, and that genuine prioritization — not just a ranked list, but real trade-offs — is a leadership act. Self Determination Theory tells us that autonomy, competence, and relatedness aren’t soft perks; they’re the substrate on which sustained performance is built. And path-goal theory gives us a framework for reading what a person or team actually needs in the moment, and the flexibility to meet them there.

The best plan you’ll ever build is still just a document. What moves work forward is people who are motivated to do it — and leaders who understand what that actually takes.

References

• Deci, E. L., Olafsen, A. H., & Ryan, R. M. (2017). Self-determination theory in work organizations: The state of a science. Annual Review of Organizational Psychology and Organizational Behavior, 4, 19–43.

• House, R. J. (1971). A path-goal theory of leader effectiveness. Administrative Science Quarterly, 16(3), 321–339.

• Schmidt, A. M., & Dolis, C. M. (2009). Something’s got to give: The effects of dual-goal difficulty, goal progress, and expectancies on resource allocation. Journal of Applied Psychology, 94(3), 678–691.

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So there I was on Tuesday, attending to work, ready for my next meeting, excited to spend one last evening with my 15-year-old before she embarked on a school trip to France the next day. Or so I thought.

Then her phone rang. “Where are you guys? We’re all here at the meet-up point.”

You see, her bags had already been packed. Missing Euros located. Documents all in order. She’d been so ahead of schedule she was resting in our new hammock enjoying the sun. When the call came, we were out the door in five minutes, drove to SFO in a record 37, and she was through security by the time I parked — with an hour to spare.

The only thing that wasn’t pre-packed was her toothbrush.

Precrastination and Personality

Precrastination is a relatively new concept, first explored by psychologist David Rosenbaum and colleagues in 2014 — defined as the tendency to complete, or at least begin, tasks as soon as possible, even at the expense of extra physical effort. German psychologist Christopher Gehrig has since produced additional research showing that pre-crastination isn’t simply the opposite of procrastination, but a separate, independent construct.

While there’s a strong negative correlation (~.7) between the two tendencies, the more interesting finding is how they relate to Big 5 personality types. While procrastination is consistently associated with lower conscientiousness and higher neuroticism, pre-crastinators score high on conscientiousness but also high (.10 coorelation) on neuroticsm. As I’ve written before, neuroticism gets a bad rap — there are plenty of valuable attributes that come with it, if you know how to use it.

Pre-crastination also maps neatly onto goal theory — specifically the satisfaction we get from completing subgoals. Checking things off early reduces cognitive load and creates a sense of forward momentum. The brain likes done. It likes it so much it will sometimes do extra work just to feel that way.

But there are downsides. Gehrig distinguishes between functional precrastination — the adaptive kind, rooted in planning and self-regulation — and the fear-based or compulsive forms, which share more with procrastination than they might appear. As he puts it, those latter forms can carry “motivational similarities with procrastination, particularly under emotional pressure.” Add to that: submitting work before it’s fully polished, answering emails too quickly, taking on more than your share, and a meaningful association with anxiety, fatigue, and burnout.

But if you tap into the superpower, it can pay off tremendously. Precrastination isn’t just doing things early — it’s knowing when early preparation creates genuine optionality. Like, say, surviving the discovery that your daughter’s flight to France is in two hours when you thought it was tomorrow.

I say the benefits outweigh the drawbacks — if you keep them in check.

She made it to France. She picked up a toothbrush at the airport, and by the looks of it having the time of her life. I’m calling the system a success.

References

Gehrig, C., Münscher, J.-C., & Herzberg, P. Y. (2023). How do we deal with our daily tasks? Precrastination and its relationship to personality and other constructs. Personality and Individual Differences, 201, Article 111927. https://doi.org/10.1016/j.paid.2022.111927

Gehrig, C., Herzberg, P.Y. The early bird catches the worm, but falls exhausted from the branch at dusk: developing the FIPS – Facets of (Mal)adaptive precrastination scale. Curr Psychol 44, 18831–18840 (2025). https://doi.org/10.1007/s12144-025-08454-y

Rosenbaum, D. A., Gong, L., & Potts, C. A. (2014). Pre-Crastination: Hastening Subgoal Completion at the Expense of Extra Physical Effort. Psychological Science, 25(7), 1487–1496. https://doi.org/10.1177/0956797614532657

This may be a controversial perspective, and I invite all the I/Os, OB, and OD folks to push back on my POV as the literature is far from definitive on the subject. So here goes:

(I)OP - (Industrial) Organizational Psychology

Just to recap what we learned about I/O Psych — it stems from various psychology fields, and at its core it applies the scientific method to the study of people at work. It’s rigorous, evidence-based, and tightly focused on the psychological levers that shape individual and group performance: motivation, cognition, mental ability, wellbeing, and how people adapt (or don’t) to their organizational environment. The key word there is psychological. I/O Psych is always asking: what’s happening inside the person, and how does that interact with work?

Most I/O PhD programs primarily live inside psychology departments and train the researchers and practitioners who generate the field’s evidence base. These programs are rigorous and research-heavy — the kind of training that produces people who go on to publish, consult, or lead people analytics functions.

What’s in a name

For what it’s worth, I’ve never seen I/O Psychology referred to as OP or IOP, it just worked for my headline. Here are the most common ways we see the field referenced in literature (all of which are a mouthful):

• I/O Psychology — the most common shorthand in practitioner and popular writing

• I-O Psychology — preferred by SIOP officially; the hyphen signals it’s one unified field, not two separate ones bolted together

• I/O Psych — casual shorthand, common in academic programs and student contexts (practitioners are frequently referred to as “I/Os”)

• Industrial-Organizational Psychology — the full formal name, used in academic writing and official contexts

• Industrial/Organizational Psychology — same as above, just with a slash; common in older textbooks

• Work Psychology — more common in the UK and Europe; same domain, different branding

• Occupational Psychology — the British Psychological Society’s preferred term; heavily used in the UK and Australia

• Organizational Psychology — sometimes used as shorthand when the “industrial” half feels dated or when the work skews more toward behavior and culture than selection and assessment

• Industrial Psychology — for those purists focused on the job analysis, recruiting, selection, side of the equation

OB - Organizational Behavior

OB, on the other hand, is multidisciplinary. While it also explores many of the themes we study in I/O Psych — motivation, group dynamics, job satisfaction, leadership — it draws from sociology, anthropology, business, and economics too. Think of it as a wider-angle lens on the same subject matter.

The clearest difference I’ve found between my I/O and OB coursework is this: I/O is scientific study-based, while OB is more business-driven. In I/O, you’re generating and testing hypotheses. In OB, you’re learning from real organizational stories and applying frameworks to diagnose what went right or wrong. One is more statistics focused, the other is more field case studies.

OB also tends to operate at more levels simultaneously — it cares as much about org structure, power dynamics, and culture as it does about the individual employee. I/O narrows the frame; OB widens it.

Not coincidentally, the elite OB PhD programs live inside business schools. At the MBA level, OB is almost always a concentration rather than a standalone degree. The home institution tells you a lot: OB is built to serve managers and future faculty, not clinicians or researchers.

OD - Organizational Development

Confused yet? Now lets add Organizational Development to the mix.

If I/O asks why people behave the way they do, and OB asks how behavior shapes organizations, OD asks: what do we do about it?

OD draws its roots from organizational psychology as well as sociology, and change management. Its fundamental premise is that by designing and delivering “interventions” that change social systems, ways of working, and cultures within organizations, it’s possible to both improve their competitiveness and make them better places for people to work.

The term “organizational development” was coined by Douglas McGregor and Richard Beckhard coined in the 1950s while consulting together at General Mills, to describe an innovative bottoms-up change effort that fit no traditional consulting categories. But its intellectual father came earlier: Kurt Lewin, an MIT professor widely recognized as the founding father of OD, worked across organizational psychology, change management, and group dynamics, and in 1944 established the Research Center for Group Dynamics at MIT.

His most enduring contribution? The change management model of “Unfreeze, Change, and Refreeze” — still widely used in today’s business environment. The idea is elegant: you have to loosen the old patterns first, introduce the change, then lock the new ones in. Anyone who has tried to shift a team’s culture mid-quarter knows exactly how true that is.

Fun fact: In the UK there’s a distinction between I/Os and ODs, both using the term psychology.

• Occupational Psychologist — protected title, regulated, credentialed, closer in spirit to the American I/O tradition

• Business Psychologist — broader, more commercially oriented, unregulated, closer in practice to what a lot of OD consultants do in the US

Where I/O Psych and OB tend to describe and explain, OD intervenes. It’s the field most concerned with transformation — restructuring, culture change, leadership development, team effectiveness, and organizational design. Less lab, more operating table.

OD programs reflect this practitioner bent in where they’re housed — continuing education divisions, management schools, education programs. These programs skew mid-career — the students tend to be HR leaders and consultants, not fresh undergrads. It’s also worth noting that many schools offer OD master’s degrees under different names — Leadership and Change, Organizational Leadership — so finding the right fit is partly about reading past the label to see what’s actually in the curriculum.

(I)OP vs. OB vs. OD — Okay, But Really

I know. Even with all that, it still sounds like a lot of the same thing. Looking at academic discussion boards, there doesn’t seem to be clearly agreed upon distinctions.

The way I’ve come to think about it: I/O is the science, OB is the business strategy, and OD is the practice.

I/O Psychology gives you a rigorous, peer-reviewed research base. It asks precise psychological questions and demands controlled answers. OB takes that knowledge and combines it with insights from sociology, anthropology, and political science to build a richer, messier, more realistic picture of how organizations actually function. And OD takes all of it and puts it to work — diagnosing organizational friction, designing interventions, and managing change.

Or, as one researcher put it, OB “develops a much bigger canvas” for understanding phenomena like job satisfaction or motivation, while I/O explains them strictly from the angle of human psychology. Neither approach is wrong — they’re just trying to answer different questions.

The boundaries genuinely do collapse in practice. Most OD consultants draw on I/O research. Most OB courses teach I/O findings. And anyone doing serious I/O work ends up bumping into OB concepts constantly. The fields aren’t rivals — they’re layers. And once you see the layers, you start seeing them everywhere.

The reality is there’s no single term that describes the field in general, and no clear definition for any of this, which might explain why the field has such an identity problem. I think it’s time for us to get a branding consultant to come fix it!

Hope you enjoyed If you agree or disagree with this perspective I’d love to know. Please share in the comments.