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 | Jan 11, 2026 | Leading Through Uncertainty, Strategy
We’re two full weeks into the new year and I’m curious, how is the strategy and operating plan you spent all Q3 and Q4 working on progressing? You nailed it, right? Everything is just as you expected and things are moving forward just as you planned.
I didn’t think so.
So, like many others, you feel tempted to double down on what worked before or chase every opportunity with the hope that it will “future-proof” your business.
Stop.
Remember the Cheshire Cat, “If you don’t know where you’re going, any road will get you there.”
You DO know where you’re going because your goals didn’t change. You still need to grow revenue and cut costs with fewer resources than last year.
The map changed. So you need to find a new road.
You’re not going to find it by looking at old playbooks or by following every path available.
You will find it by following these three steps (and don’t require months or millions to complete).
Return to First Principles
When old maps fail and new roads are uncertain, the most successful leaders return to first principles, the fundamental, irreducible truths of a subject:
- Organizations are systems
- Systems seek equilibrium and resist change when elements are misaligned
- People in the system do what the system allows, models, and rewards
Returning to these principles is the root of success because it forces you to pause and ask the right questions before (re)acting.
Ask Questions to Find the Root Cause
Based on the first principles, think of your organization as a lock. All the tumblers need to align to unlock the organization’s potential to get to where you need to go. When the tumblers don’t align, you stay stuck in the dying status quo.
Every organization has three tumblers – Architecture (how you’re organized), Behavior (what leaders actually do), and Culture (what gets rewarded) – that must align to develop and execute a strategy in an environment of uncertainty and constant change.
But ensuring that you’ve aligned all three tumblers, and not just one or two, requires asking questions to get to the root cause of the challenges.
Is your leadership team struggling to align on a decision because they don’t have enough data or can’t agree on what it means? The Behavior and Culture tumblers are misaligned with the structure and incentives of Architecture
Are people resisting the new AI tools you rolled out? Architectural incentives and metrics, and leadership communications and behaviors are preventing buy-in.
Struggling to squeeze growth out of a stagnant business? Structures and systems combined with organization culture are reinforcing safety and a fixed mindset rather than encouraging curiosity and learning.
Align the Tumblers
When you diagnose the root causes you find the misaligned tumbler. And, in the process of bringing it into alignment, it will likely pull the others in, too.
By role modeling leadership behaviors that encourage transparent communication (no hiding behind buzzwords), quantifying confidence, and smart risk taking, you’ll also influence culture and may reveal a needed change in Architecture.
Modifying the metrics and rewards in Architecture and making sure that your communications and behavior encourage buy-in to new AI tools, will start to establish an AI-friendly culture.
Overhauling Architecture to encourage and reward actions that expand that stagnant business into new markets or brings new solutions to your existing customers, will build new leadership Behaviors will drive culture change.
Get to your Goals
It’s a VUCA/BANI world AND It’s only going to accelerate. That means that the strategy you developed last quarter and the operational plans you set last month will be obsolete by the end of the week.
But the strategy and the plan were never the goal. They were the road you planned based on the map you had. When the map changes, the road does, too. But you can still get to the goal if you’re willing to fiddle with a lock.
by Robyn Bolton | Oct 28, 2025 | Leadership, Strategy
Last week, I shared that 74% of executives believe that their organizations will cease to exist in ten years. They believe that strategic transformation is required, but cite the obvious problem of organizational inertia and the easy scapegoat of people’s resistance to change.
Great. Now we know the problem. What’s the solution?
The Obvious: Put the Right People in Leadership Roles
Flipping through the report, the obvious answers (especially from an executive search firm) were front and center:
- Build a top team with relevant experience, competencies, and diverse backgrounds
- Develop the team and don’t be afraid to make changes along the way
- Set a common purpose and clear objectives, then actively manage the team
The Easy: Do Your Job as a Leader
OK, these may not be easy but it’s not that hard, either:
- Relentlessly and clearly communicate the why behind the change
- Change one thing at a time
- Align incentives to desired outcomes and behaviors
- Be a role model
- Understand and manage culture (remember, it’s reflected in the worst behaviors you tolerate)
The Not-Obvious-or-Easy-But-Still-Make-or-Break: Deputize the Next Generation
Buried amongst the obvious and easy was a rarely discussed, let alone implemented, choice – actively engaging the next generation of leaders.
But this isn’t the usual “invite a bunch of Hi-Pos (high potentials) to preview and upcoming announcement or participate in a focus group to share their opinions” performance most companies engage in.
This is something much different.
Step 1: Align on WHY an “extended leadership team” of Next Gen talent is mission critical
The C-Suite doesn’t see what happens on the front lines. It doesn’t know or understand the details of what’s working and what’s not. Instead, it receives information filtered through dozens of layers, all worried about positioning things just right.
Building a Next Gen extended leadership team puts the day-to-day realities front and center. It brings together capabilities that the C-Suite team may lack and creates the space for people to point out what looks good on paper but will be disastrous in practice.
Instead, leaders must commit to the purpose and value of engaging the next generation, not merely as “sensing mechanisms” (though that’s important, too) but as colleagues with different and equally valuable experiences and insights.
Step 2: Pick WHO is on the team without using the org chart
High-potentials are high potential because they know how to succeed in the current state. But transformation isn’t about replicating the current state. It requires creating a new state. For that, you need new perspectives:
- Super connecters who have wide, diverse, and trusted relationships across the organization so they can tap into a range of perspectives and connect the dots that most can barely see
- Credible experts who are trusted for their knowledge and experience and are known to be genuinely supportive of the changes being made
- Influencers who can rally the troops at the beginning and keep them motivated throughout
Step 3: Give them a clear mandate (WHAT) but don’t dictate HOW to fulfill it
During times of great change, it’s normal to want to control everything possible, including a team of brilliant, creative, and committed leaders. Don’t involve them in the following steps and be open to being surprised by their approaches and insights:
- At the beginning, involve them in understanding and defining the problem and opportunity.
- Throughout, engage them as advisors and influencers in decision-making (
- During and after implementation, empower them to continue to educate and motivate others and to make adaptations in real-time when needed.
Co-creation is the key to survival
Transforming your organization to survive, even thrive, in the future is hard work. Why not increase your odds of success by inviting the people who will inherit what you create to be part of the transformation?
by Robyn Bolton | Sep 30, 2025 | Leading Through Uncertainty, Strategy, Tips, Tricks, & Tools
Just as we got used to VUCA (volatile, uncertain, complex, ambiguous) futurists now claim “the world is BANI now.” BANI (brittle, anxious, nonlinear, incomprehensible) is much worse than VUCA and reflects “the fractured, unpredictable state of the modern world.”
Not to get too Gen X on the futurists who coined and are spreading this term but…shut up.
Is the world fractured and unpredictable? Yes.
Does it feel brittle? Are we more anxious than ever? Are things changing at exponential speed, requiring nonlinear responses? Does the world feel incomprehensible? Yes, to all.
Naming a problem is the first step in solving it. The second step is falling in love with the problem so that we become laser focused on solving it. BANI does the first but fails at the second. It wallows in the problem without proposing a path forward. And as the sign says, “Ain’t nobody got time for this.”
(Re)Introducing the Cynefin Framework
The Cynefin framework recognizes that leadership and problem-solving must be contextual to be effective. Using the Welsh word for “habitat,” the framework is a tool to understand and name the context of a situation and identify the approaches best suited for managing or solving the situation.
It’s grounded in the idea that every context – situation, challenge, problem, opportunity – exists somewhere on a spectrum between Ordered and Unordered. At the Ordered end of the spectrum, cause and affect are obvious and immediate and the path forward is based on objective, immutable facts. Unordered contexts, however, have no obvious or immediate relationship between cause and effect and moving forward requires people to recognize patterns as they emerge.
Both VUCA and BANI point out the obvious – we’re spending more time on the Unordered end of the spectrum than ever. Unlike the acronyms, Cynefin helps leaders decide and act.
5 Contexts. 5 Ways Forward
The Cynefin framework identifies five contexts, each with its own best practices for making decisions and progress.
On the Ordered end of the spectrum:
- Simple contexts are characterized by stability and obvious and undisputed right answers. Here, patterns repeat, and events are consistent. This is where leaders rely on best practices to inform decisions and delegation, and direct communication to move their teams forward.
- Complicated contexts have many possible right answers and the relationship between cause and effect isn’t known but can be discovered. Here, leaders need to rely on diverse expertise and be particularly attuned to conflicting advice and novel ideas to avoid making decisions based on outdated experience.
On the Unordered end of the spectrum:
- Complex contexts are filled with unknown unknowns, many competing ideas, and unpredictable cause and effects. The most effective leadership approach in this context is one that is deeply uncomfortable for most leaders but familiar to innovators – letting patterns emerge. Using small-scale experiments and high levels of collaboration, diversity, and dissent, leaders can accelerate pattern-recognition and place smart bets.
- Chaos are contexts fraught with tension. There are no right answers or clear cause and effect. There are too many decisions to make and not enough time. Here, leaders often freeze or make big bold decisions. Neither is wise. Instead, leaders need to think like emergency responders and rapidly response to re-establish order where possible to bring the situation into a Complex state, rather than trying to solve everything at once.
The final context is Disorder. Here leaders argue, multiple perspectives fight for dominance, and the organization is divided into fractions. Resolution requires breaking the context down into smaller parts that fit one of the four previous contexts and addressing them accordingly.
The Only Way Out is Through
Our VUCA/BANI world isn’t going to get any simpler or easier. And fighting it, freezing, or fleeing isn’t going to solve anything. Organizations need leaders with the courage to move forward and the wisdom and flexibility to do so in a way that is contextually appropriate. Cynefin is their map.
by Robyn Bolton | Sep 2, 2025 | Leading Through Uncertainty, Strategy
In September 2011, the English language officially died. That was the month that the Oxford English Dictionary, long regarded as the accepted authority on the English language published an update in which “literally” also meant figuratively. By 2016, every other major dictionary had followed suit.
The justification was simple: “literally” has been used to mean “figuratively” since 1769. Citing examples from Louisa May Alcott’s Little Women, Charles Dickens’ David Copperfield, Charlotte Bronte’s Jane Eyre, and F. Scott Fitzgerald’s The Great Gatsby, they claimed they were simply reflecting the evolution of a living language.
What utter twaddle.
Without a common understanding of a word’s meaning, we create our own definitions which lead to secret expectations, and eventually chaos.
And not just interpersonally. It can affect entire economies.
Maybe the state of the US economy is just a misunderstanding
Uncertainty.
We’re hearing and saying that word a lot lately. Whether it’s in reference to tariffs, interest rates, immigration, or customer spending, it’s hard to go a single day without “uncertainty” popping up somewhere in your life.
But are we really talking about “uncertainty?”
Uncertainty and Risk are not the same.
The notion of risk and uncertainty was first formally introduced into economics in 1921 when Frank Knight, one of the founders of the Chicago school of economics, published his dissertation Risk, Uncertainty and Profit. In the 114 since, economists and academics continued to enhance, refine, and debate his definitions and their implications.
Out here in the real world, most businesspeople use them as synonyms meaning “bad things to be avoided at all costs.”
But they’re not synonyms. They have distinct meanings, different paths to resolution, and dramatically different outcomes.
Risk can be measured and/or calculated.
Uncertainty cannot be measured or calculated
The impact of tariffs, interest rates, changes in visa availability, and customer spending can all be modeled and quantified.
So it’s NOT uncertainty that’s “paralyzing” employers. It’s risk!
Not so fast my friend.
Not all Uncertainties are the same
According to Knight, Uncertainty drives profit because it connects “with the exercise of judgment or the formation of those opinions as to the future course of events, which…actually guide most of our conduct.”
So while we can model, calculate, and measure tariffs, interest rates, and other market dynamics, the probability of each outcome is unknown. Thus, our response requires judgment.
Sometimes.
Because not all uncertainties are the same.
The Unknown (also known as “uncertainty based on ignorance”) exists when there is a “lack of information which would be necessary to make decisions with certain outcomes.”
The Unknowable (“uncertainty based on ambiguity”) exists when “an ongoing stream [of information] supports several different meanings at the same time.”
Put simply, if getting more data makes the answer obvious, we’re facing the Unknown and waiting, learning, or modeling different outcomes can move us closer to resolution. If more data isn’t helpful because it will continue to point to different, equally plausible, solutions, you’re facing the Unknowable.
So what (and why did you drag us through your literally/figuratively rant)?
If you want to get unstuck – whether it’s a project, a proposal, a team, or an entire business, you first need to be clear about what you’re facing.
If it’s a Risk, model it, measure it, make a decision, move forward.
If it’s an uncertainty, what kind is it?
If it’s Unknown, decide when to decide, ask questions, gather data, then, when the time comes, decide and move forward
If it’s Unknowable, decide how to decide then put your big kid pants on, have the honest and tough conversations, negotiate, make a decision, and move on.
I mean that literally.
