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.
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.
by Robyn Bolton | Feb 2, 2026 | AI, Leadership, Strategic Foresight, Strategy
It was a race. And the whole world was watching.
In 1911, Captain Robert Scott set out to reach the South Pole. He’d been to Antarctica before and because of his past success, he had more funding, more expertise, and more experience. He had all the equipment needed.
Racing him to fame, fortune and glory was Norwegian Roald Amundsen. Originally heading to the North Pole, he turned around when he learned that Robert Peary had beaten him there. He had dogs and skis, equipment perfect for the Arctic but unproven in Antarctica.
Amundsen won the race, by over a month.
Scott and his crew died 11 miles from the South Pole.
When the Playbook Stops Working
Scott wasn’t guessing. He’d tested motor sledges in the Alps. He’d seen ponies work on a previous Antarctic expedition. He built a plan around the best available equipment and the general playbook that had served British expeditions for decades: horses and motors move heavy loads, so use horses and motors.
It just wasn’t right for Antarctica. The motors broke down in the cold. The ponies sank through the ice. The plan that looked solid on paper fell apart the moment it met the actual environment it had to operate in.
The same thing is happening today with AI.
For decades, when new technologies emerge, executives have followed a similarly familiar playbook: assess the opportunity, build a business case, plan the rollout, execute.
And for decades it worked. Cloud migrations and ERP implementations were architectural changes to known processes with predictable outcomes. As time went on, information grew more solid, timelines became better understood, and the playbook solidified.
AI is different. Executives are so focused on picking the right AI tools and building the right infrastructure that they aren’t thinking about what happens when they hit the ice. Even if the technology works as designed, you have no idea whether it will deliver the intended results or create a ripple of unintended consequences that paralyze your business and put egg on your face.
Diagnose Before You Prescribe
The circumstances of AI are different too, and that requires a new playbook. Make that playbooks. Picking the right playbook requires something my clients and I call Calibrated Decision Design.
We start by asking how long it will take to realize the ultimate goals of the investment. Do we need to break even this year, or is this a multi-year bet where results slowly roll in? Most teams have a sense of this, so it allows us to move quickly to the next, much harder question.
What do we know and what do we believe? This is where most teams and AI implementations fail. To seem confident and indispensable, people present hypotheses as if they are facts resulting in decisions based on a single data points or best guesses. The result is a confident decision destined to crumble.
Where you land on these two axes determines your playbook. Apply the wrong one and you’ll either waste money on over-analysis or burn through budget on premature action.
Pick from the Four Playbooks
Go NOW!: You have the facts and need results now. Stop deliberating. Execute.
Predictable Planning: You have confidence in the outcome, but the payoff takes patience. Build a flexible strategy and operational plan to stay responsive as things progress.
Discovery Planning: You need results fast, but you don’t have proof your plan will work. Run small, fast experiments before scaling anything.
Resilient Strategy: The time horizon is long and you’re short on facts. The worst thing you can do is go all in. Instead, envision multiple futures, identify early warning signs, find commonalities and prepare a strategy that can pivot.
Apply it
Which playbook are you using and which one is best for your circumstance?
by Robyn Bolton | Dec 17, 2025 | Press Mentions
by Robyn Bolton | Nov 1, 2025 | Innovation, Leading Through Uncertainty
“Is this what the dinosaurs did before the asteroid hit?”
That was the first question I was asked at IMPACT, InnoLead’s annual gathering of innovation practitioners, experts, and service providers.
It was also the first of many that provided insight into what’s on innovators and executives’ minds as we prepare for 2026
How can you prevent failure from being weaponized?
This is both a direct quote and a distressing insight into the state of corporate life. The era of “fail fast” is long gone and we’re even nostalgic for the days when we simply feared failure. Now, failure is now a weapon to be used against colleagues.
The answer is neither simple nor quick because it comes down to leadership and culture. Jit Kee Chin, Chief Technology Officer at Suffolk Construction, explained that Suffolk is able to stop the weaponization of failure because its Chairman goes to great lengths to role model a “no fault” culture within the company. “We always ask questions and have conversations before deciding on, judging, or acting on something,” she explained
How do you work with the Core Business to get things launched?
It’s long been innovation gospel that teams focused on anything other than incremental innovation must be separated, managerially and physically, from the core business to avoid being “infected” by the core’s unquestioning adherence to the status quo.
The reality, however, is the creation of Innovation Island, where ideas are created, incubated, and de-risked but remain stuck because they need to be accepted and adopted by the core business to scale.
The answer is as simple as it is effective: get input and feedback during concept development, find a core home and champion as your prototype, and work alongside them as you test and prepare to launch.
How do you organize for innovation?
For most companies, the residents of Innovation Island are a small group of functionally aligned people expected to usher innovations from their earliest stages all the way to launch and revenue-generation.
It may be time to rethink that.
Helen Riley, COO/CFO of Google X, shared that projects start with just one person working part-time until a prototype produces real-world learning. Tom Donaldson, Senior Vice President at the LEGO Group, explained that rather than one team with a large mandate, LEGO uses teams specially created for the type and phase of innovation being worked on.
What are you doing about sustainability?
Honestly, I was surprised by how frequently this question was asked. It could be because companies are combining innovation, sustainability, and other “non-essential” teams under a single umbrella to cut costs while continuing the work. Or it could be because sustainability has become a mandate for innovation teams.
I’m not sure of the reason and the answer is equally murky. While LEGO has been transparent about its sustainability goals and efforts, other speakers were more coy in their responses, for example citing the percentage of returned items that they refurbish or recycle but failing to mention the percentage of all products returned (i.e. 80% of a small number is still a small number).
How can humans thrive in an AI world?
“We’ll double down,” was Rana el Kaliouby’s answer. The co-founder and managing partner of Blue Tulip Ventures and host of Pioneers of AI podcast, showed no hesitation in her belief that humans will continue to thrive in the age of AI.
Citing her experience listening to Radiotopia Presents: Bot Love, she encouraged companies to set guardrails for how, when, and how long different AI services can be used. She also advocated for the need for companies to set metrics that go beyond measuring and maximizing usage time and engagement to considering the impact and value created by their AI-offerings.
What questions do you have?
