Lessons Learned Archives

3 Deaths. 3 Lessons. 3 Questions to Survive (and Thrive)

by Robyn Bolton | May 5, 2026 | Leadership, Leading Through Uncertainty, Stories & Examples, Strategy

Sunday morning, my phone blew up. Thirty-three text messages. Most mornings, I have zero, so my first thought was “who died?”

The texts were about a death. Sort of.

Sloan Management Review died (ceased publication) and a group chat filled with academics, thought leaders, and consultants were having an absolute meltdown.

Knowing that my husband, an actual Sloan graduate, hadn’t yet seen the news, I broke it to him gently. “Okay,” he shrugged, not even glancing up from his phone.

This was in stark contrast to his reactions to the demise of Spirit Airlines (howling with laughter at the memes) and the resurrection of Allbirds as an AI company (thoughtful and incredibly technical analysis).

Lesson 1: The Race to the Bottom Never Ends Well

CNN’s headline said it all, “Why did Spirit fail? Too many passengers hated flying it.” To prove the point, the article opens,

“Lousy service, not the Iran war, killed Spirit Airlines. Spirit was doomed to fail because of mismanagement, deep financial problems, and – crucially – its reputation for poor customer service. The spike in jet fuel prices during the war just accelerated Spirit’s inevitable demise.”

If that can be written about your business, you don’t deserve to be in business.

It’s only a matter of time until you’re not.

Lesson 2: Be Patient for Growth and Impatient for Profit

Allbirds raised $348 million when it IPOed in 2021 and, at one point, was valued at $4.1 billion despite never turning a profit. Six years later, its stock price had fallen 95% and it sold its business and IP to a brand management company for $39 million.

How did this happen? There are plenty of theories – it expanded too aggressively into bricks and mortar retail, it made ugly shoes but operated like a fashion brand, its Tech Bro image is no longer aspirational for Gen Z customers – but the fact is that it prioritized growth over profit and that ultimately bit them in the balance sheet.

Lesson 3: Some Businesses are Butterflies

While my colleagues’ alarm was understandable, it missed the bigger picture.

Sloan Management Review (SMR) didn’t die. It metamorphosed.

Yes, the SMR brand is going away, but future ideas, research and findings will continue to be shared through digital newsletters, short-form videos, podcasts, and social-first content.

In effect, SMR is metamorphosing to better reflect how its subscribers consume information. Busy executives don’t have the time to read long-form, dense research articles. They grab information in snippets and soundbites. This change ensures the people who need the ideas the most get them.

3 Questions to Find Your Fate

Do you treat your customers like they exist for your benefit? In other words, are you more focused on value extraction than value creation and delivery? If yes, start planning your business’ funeral and don’t expect anyone to attend.

Do you have a financially and operationally sustainable business model? If no, start planning your funeral but take comfort in the fact that people will attend and may even say nice things about you.

Do you know the unique, relevant, valuable, and hard to imitate reason why you exist? Can you articulate the rare and essential Job to be Done you do for your customers? If no, you’re on life support. When you can answer yes, you’ll be ready to be a butterfly.

One quick caveat

When businesses die, people lose their jobs and that is incredibly tragic. The psychological, financial, and relational impacts of job loss are tremendous, impacting people far beyond the individual laid off. It can take months, even years for people and families to recover and, for some, it never happens.

Creative destruction is real and necessary for long-term economic, technological, and societal growth. But the short-term impact has human consequences that should never be ignored.

Uncertainty, Overwhelm, and the Wisdom of Bull Durham

by Robyn Bolton | Mar 30, 2026 | Just for Fun, Leading Through Uncertainty

We survived the first quarter of the year. Congratulations everyone, job well done.

Did we hope for more than just survival? Of course we did! But hey, sometimes just living to fight another day is a victory and we still have nine more months to hit our KPIs, deliver our OKRs, and nail this fiscal’s BHAG.

So, let’s take a moment to focus on what really matters: Baseball is back!

Along with the hope of the new season, and the warm weather that comes with it, comes an excuse to revisit the wisdom of classic baseball moves. In 2021, I wrote about Moneyball’s lessons in innovation and it continues to be one of the top read posts on my blog.

If you feel overwhelmed by Q1, fear not! There’s no greater source of advice on finding simplicity, solving problems, and leading people than Bull Durham.

When you’re overwhelmed, go back to the basics.

Skip: This… is a simple game. You throw the ball. You hit the ball. You catch the ball.

The Durham Bulls are 8-16 and Skip (the manager) has had enough. He’s tried every tool in his coaching toolkit and the team continues to perform poorly, display a poor attitude, and deliver a halfhearted performance. Overwhelmed and frustrated, he turns to veteran player Crash Davis for advice. “Scare ‘em,” Crash offers and what comes next is one of the greatest tirades on film.

But the greatest lesson here is what comes towards the end of the tirade: a description of the utter simplicity of baseball. There’s no strategy, no competitor analysis, no number-crunching, just a simple explanation of the most basic elements of the job. Throw. Hit. Catch.

It’s easy to get overwhelmed by news, technology, corporate politics, the list goes on. That overwhelm causes us to worry, lollygag, and obsess about what could happen. But when we cut through all that to find the essence of what we do and why we do it, things become remarkably clear and the next steps feel obvious.

Fall in love with the problem. Not the solution.

Zeke: We need a night off just to stop our losing streak. We need a rainout.

Crash: I can get us a rainout.

The Bulls are on another losing streak but this time on the road. As the team bus pulls into another motel and the players gather their bags, they complain about their problem (losing streak), propose an approach (night off) and propose a specific solution (rainout).

When Crash promises a rainout, it’s not because he knows something about the forecast the others don’t. It’s because he understands that there’s more than one way to get a night off. Like breaking into the ballpark, turning on the sprinklers, and flooding the field.

When we fall in love with a solution (rainout) we get stuck. We focus on making one thing happen, when critical dependencies are beyond our control. But when we fall in love with the problem (need a night off to stop a losing streak), we’re able to see less obvious but more likely and effective solutions.

People first. Problem solving second

Larry: [Jogs out to the mound to break up a players’ conference] Excuse me, but what the hell’s going on out here?

Crash Davis: Well, Nuke’s scared because his eyelids are jammed and his old man’s here. We need a live rooster to take the curse off Jose’s glove and nobody seems to know what to get Millie or Jimmy for their wedding present. We’re dealing with a lot of sh*t.

Larry: Okay, well, uh… candlesticks always make a nice gift, and uh, maybe you could find out where she’s registered and maybe a place-setting or maybe a silverware pattern. Okay, let’s get two! Go get ’em.

The Bulls are finally on a winning streak, but off-the-field issue are affecting on-the-filed play and things aren’t looking good. As the players gather on the mound, the team’s Assistant Manager trots out to figure out what’s going on and get the game going again.

After Crash sums up the personal issues, instead of telling the players to be professional, leave their problems at home, and get on with things, Larry focuses on solving the single issue affecting the most people first. It’s only when the players start nodding that he shifts everyone back into work-mode.

Only on Severance can we separate ourselves into work and life modes. Pretending that isn’t the case is counterproductive and toxic. But we can’t let one consume the other because it will ultimately degrade both our professional and personal lives.

As leaders, we need to find the balance between helping the humans grapple with real and personal issues and getting the team (back) on track and doing great work.

Ready to keep playing?

Baseball is a game of survival. A foul tip keeps the at bat alive. A walk keeps the inning alive. A bloop single to score a runner send the game into extra innings.

Winning takes patience and perseverance because the game is rarely won or lost in a single at-bat or inning. Just like you don’t win or lose your KPIs, OKRs, or BHAGs in a quarter.

As we start a new quarter, let’s keep it simple, focus on solving problems, and put people first.

Go get ‘em.

You’re Addicted to AI. That’s by Design.

by Robyn Bolton | Mar 25, 2026 | AI, Leadership, Strategy

“AI is the new cigarette.”

When a colleague said this in the waning days of 2022, days after ChatGPT burst on the scene, she took my breath away. The idea that this miracle would kill us seemed confined to hysterical handwringing foretelling the birth of Skynet.

She was right.

But neither of us knew it was designed to be that way.

Designed for addiction

My friend predicted that ChatGPT would stay free and helpful until usage reached “critical mass,” and then we’d have to pay. Less than three months after its November launch, OpenAI introduced its $20 per month service.

But it’s not the “first one’s free, the next one will cost you” aspect of drugs that makes AI addictive. It’s the design decisions at its core that keeps you coming back:

Purchase Decoupling in which you convert real money into tokens, creating psychological distance between you and your actual spending
Difficulty Curve where skills and benefits accumulate quickly giving you the sense that you’re becoming more capable over time and therefore more committed after progress slows.
Skill Atrophy where every skill you stop practicing because the machine does it for you, quietly disappears.

Even casual AI users have experienced one or more of these:

You get a message mid-chat telling you you’ve used all your tokens and need to come back in three hours even though you’ve paid your monthly $20 fee
You’re prompting in all caps because it’s the only way you can think of to get the LLM to stop hallucinating, while reminiscing about the days when it was a brilliant thought-partner
You’ve relied on AI to outline articles for the last several months, but you need to write in a different style and have no idea how to get started.

And yet, we keep going back.

But it’s not just individuals who are addicted. It’s entire organizations.

Signs that your organization is addicted to AI

Your CFO asks for the total AI spend across the organization. Three weeks and four departments later, the number is three times what anyone expected because the licenses are buried in IT infrastructure budgets, the pilots are expensed as innovation projects, and half the tools were purchased by business units on corporate cards.

The board approved the AI transformation initiative based on the pilot results. Eighteen months later, the pilot case study slide hasn’t changed, headcount has been reduced in anticipation of productivity gains that haven’t materialized, and the team running the pilot has quietly moved on to other work.

You eliminated the analyst pool two years ago because AI could do in minutes what they did in days. Now you need to evaluate whether the AI’s output is actually correct, and you’ve just realized there’s nobody left in the organization to check it because everyone who’s done it is gone.

Sound familiar? Your organization is an addict.

Recovery is possible

Addiction can’t be cured, only managed. The same is true for AI.

The road to recovery starts in a similar place: Visibility

Centralize AI spending the way you centralize other business processes AND allow some flexibility by setting strict spending limits and clear decision-making criteria and ownership.
Start pilots with the end in mind by establishing success metrics and scaling plans at the start of the pilot, not when it’s already in process.
Treat certain human capabilities as strategic reserves the same way you’d treat any critical operational dependency. Before automating a function, explicitly document what judgment and expertise currently lives there, who holds it, and what it would cost to rebuild it if needed.

Unlike cigarettes or gambling, we’ve reached a point where we can’t quit AI.

But we can be aware of our addiction and we must manage it.

The first step is admitting that it’s real. And by design.

You Got Buy-In So Why Is Execution Stalling?

by Robyn Bolton | Feb 23, 2026 | Leadership, Stories & Examples, Strategy

Congratulations, you’ve done the hard part required to get buy-in! You asked instead of told, said “I don’t know” out loud, and got genuine buy-in. Your team believes, is engaged, and ready to go. And yet execution is stalling.

What gives?

Activity without Achievement

There’s no doubt that people are working hard. You can see it in their schedules and you hear it in your one-on-ones. But projects are moving slower than they should, decisions that seem straightforward take weeks, and agreements made in meetings are quietly undone. Strategies, buy-in, timelines are powerless against an invisible and unnamed force.

So, you consider your options. A team offsite can provide a helpful rest but there’s no guarantee it sticks when you’re back in the office. Training can help shore up skill gaps, but your team is already capable, so this doesn’t feel like a skill problem. You could reorg but that creates new problems.

Your People Aren’t the Problem

The problem isn’t your people, your team, or even your culture. The problem is the hidden seams between people, teams, and cultures, that create friction.

Because of friction, people hesitate to share information across functional or hierarchical seams. They make assumptions about other generations. They work to achieve individual or functional, rather than collective, goals.

These friction points have been part of your organization for so long that they are accepted as normal. As immoveable and unchangeable as your company’s mission and vision. And because they’re so ingrained, you shift your efforts to things that feel changeable: skills, org charts, and communication plans.

You’re addressing symptoms because the root cause seems impossible to fix.

It’s not impossible.

How One Company Resolved the Friction and Tightened the Seams Without Extra Work

When a K-5 curriculum company decided to expand into the Middle School market, they knew they were asking the project team to do something new that was complex, ambiguous, and fraught with high-stakes decisions.

Six months in, the project was breaking down. Decisions that should have taken a day took weeks or months. Work got stuck as different functions weighed in at different times with different mandatory requirements. People hid problems and gave optimistic updates.

The executive who owned the project had seen this before. In fact, she was seeing it in every project team across the entire company. So, she knew that the problem wasn’t the project or the people, it was something much deeper, something that was such a part of the company’s standard operating process that it had become invisible.

So, she brought in someone (me) who could see things differently and together we sought out the seams, naming the moments when friction occurred, and engaging the team in developing and experimenting with solutions.

And we did it all as part of the daily work.

We redesigned hand-offs in real time, experimented with decision-making rules until we found what worked for multiple decision types, and rewarded people for saying “I don’t know.”

Within six months, the project was back on track and engagement and morale were sky-high. Other teams took notice and asked for advice. New products began shipping on time, on budget, and to rave reviews.

Now the Real Work Begins

Where are your seams showing up? A cross-functional initiative that’s losing momentum? A decision that never seems to stick? A team that’s aligned on paper but stuck in execution?

That friction has a name. And it’s findable.

If you’re ready to find the seams and resolve the friction, set up a SeamSpotter Session. It’s a 60 to 90-minute conversation, no prep required, and you’ll receive a written summary and recommended next steps within 48 hours.

If your team is bought in, but execution keeps stuttering, you can fix it. Email me at robyn@milezero.io to get started.

Why Four Winning AI Strategies Look Nothing Alike (and How to Create Yours)

by Robyn Bolton | Feb 8, 2026 | AI, Leadership, Leading Through Uncertainty, Strategic Foresight, Strategy

In 2023, Klarna’s CEO proudly announced it had replaced 700 customer service workers with AI and that the chatbot was handling two-thirds of customer queries. Labor costs dropped and victory was declared.

By 2025, Klarna was rehiring. Customer satisfaction had tanked. The CEO admitted they “went too far,” focusing on efficiency over quality.

Like Captain Robert Scott, Klarna misjudged the circumstance it was in, applied the wrong playbook, and lost. It thought it had facts but all it has was technical specs. It made tons of assumptions about chatbots’ ability to replace human judgment and how customers would respond.

Calibrated Decision Design, a process for diagnosing your circumstances before picking a playbook, consistently proves to be a quick and necessary step to ensure success.

When you have the facts and need results ASAP: Go NOW!

General Mills, like its competitors, had been digitizing its supply chain for years and so facts based on experience and a list of the facts it needed.

To close the gap and achieve end-to-end visibility in its supply chain, it worked with Palantir to develop a digital twin of its entire supply chain. Results: 30% waste reduction, $300 million in savings, decisions that took weeks now takes hours. It proves that you don’t need all the answers to make a move, but you need to know more than you don’t.

When you have hypotheses but can’t wait for results: Discovery Planning

Morgan Stanley Wealth Management’s (MSWM) clients expect advisors to bring them bespoke advice based on mountains of analysis, and insights. But it’s impossible for any advisor to process all that data. Confident that AI could help but uncertain whether its would improve relationships or create friction, MSWM partnered with OpenAI.

Within six months, they debuted a GenAI chatbot to help Financial Advisors quickly access the firm’s IP. Document retrieval jumped from 20% to 80% and 98% now use it daily. Two years later, MSWM expanded into a meeting summary tool to summarize meetings into actionable outputs and update the CRM with notes and follow-ups. A perfect example of how a series of experiments leads to a series of successes.

When you have facts and time to achieve results: Patient Planning

Drug discovery requires patience and, while the process may be predictable, the results aren’t. That’s why pharma companies need strategies that are thoughtfully planned as they are responsive.

Lilly is doing just that by investing in its own capabilities and building an ecosystem of partners. It started by launching TuneLab, a platform offering access to AI-enabled drug discovery models based on data that Lilly spent over $1 billion developing. A month later, the pharma giant announced a partnership with NVIDIA to build the pharmaceutical industry’s most powerful AI supercomputer. Two months later, it committed over $6 billion to a new manufacturing facility in Alabama. These aren’t billion-dollar bets, they’re thoughtful investments in a long-term future that allows Lilly to learn now and stay flexible as needs and technology evolve.

When you’re making assumptions and have time to learn: Resilient Strategy

There’s no way of knowing what the global energy system will look like in 40 years. That’s why Shell’s latest scenario planning efforts resulted in three distinct scenarios, Surge, Archipelagos, and Horizon. Multiple scenarios allows the company to “explore trade-offs between energy security, economic growth and addressing carbon emissions” and build resilient strategies to recognize which one is unfolding and pivot before competitors even spot what’s happening.

Stop benchmarking. Start diagnosing.

It’s easy to feel like you’re behind when it comes to AI. But the rush to act before you know the problem and the circumstances is far more likely to make you a cautionary tale than a poster child for success.

So, stop benchmarking what competitors do and start diagnosing the circumstances you’re in, so you use the playbook you need.

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