Category Archives: Entrepreneurship

How Compensation Reveals Culture

Five Questions with Kate Dixon

How Compensation Reveals Culture

GUEST POST from Robyn Bolton

It’s time for your company’s All-Hands meeting. Your CEO stands on stage and announces ambitious innovation goals, talking passionately about the importance of long-term thinking and breakthrough results. Everyone nods enthusiastically, applauds politely, and returns to their desks to focus on hitting this quarter’s numbers. After all, that’s what their bonuses depend on.

Kate Dixon, compensation expert and founder of Dixon Consulting, has watched this contradiction play out across Fortune 500 companies, B Corps, and startups. Her insight cuts to the heart of why so many innovation initiatives fail: we’re asking people to think long-term while paying them to deliver short-term.

In our conversation, Kate revealed why most companies are inadvertently sabotaging their own innovation efforts through their compensation structures—and what the smartest organizations are doing differently.

Robyn Bolton: Kate, when I first heard you say, “compensation is the expression of a company’s culture,” it blew my mind. What do you mean by that?

Kate Dixon: If you want to understand what an organization values, look at how they pay their people: Who gets paid more? Who gets paid less? Who gets bigger bonuses? Who moves up in the organization and who doesn’t? Who gets long-term incentives?

The answers to these questions, and a million others, express the culture of the organization. How we reward people’s performance, either directly or indirectly, establishes and reinforces cultural norms. Compensation is usually the biggest, if not the biggest, expenses that a company has so they’re very thoughtful and deliberate about how it is used. Which is why it tells you what the company actually does value.

RB: What’s the biggest mistake companies make when trying to incentivize innovation?

KD: Let’s start by what companies are good at when it comes to compensations and incentives. They’re really good about base pay, because that’s the biggest part of pay for most people in an organization. Then they spend the next amount of time and effort trying to figure out the annual bonus structure. After that comes other benefits, like long term incentives, assuming they don’t fall by the wayside.

As you know, innovation can take a long time to payout, so long-term incentives are key to encouraging that kind of investment. Stock options and restricted shares are probably the most common long-term incentives but cash bonuses, phantom stock, and ESOP shares in employee-owned companies are also considered long term incentives.

Large companies are pretty good using some equity as an incentive, but they tie it t long term revenue goals, not innovation. As you often remind us, “innovation is a means to the end, which is growth,” so tying incentives to growth isn’t bad but I believe that we can do better. Tying incentives to the growth goals and how they’re achieved will go a long way towards driving innovation.

RB: I’ve worked in and with big companies and I’ve noticed that while they say, “innovation is everyone’s job,” the people who get long-term incentives are typically senior execs. What gives?

Long-term incentives are definitely underutilized, below the executive level, and maybe below the director level. Assuming that most companies’ innovation efforts aren’t moonshots that take decades to realize, it makes a ton of sense to use long-term incentives throughout the organization and its ecosystem. However, when this idea is proposed, people often pushback because “it’s too complex” for folks lower in the organization, “they wouldn’t understand.” or “they won’t appreciate it”. That stance is both arrogant and untrue. I’ve consistently seen that when you explain long-term incentives to people, they do get it, it does motivate them, and the company does see results.

RB: Are there any examples of organizations that are getting this right?

We’re seeing a lot more innovative and interesting risk-taking behaviors in companies that are not primarily focused on profit.

Our B Corp clients are doing some crazy, cool stuff. We have an employee-owned company that is a consulting firm, but they had an idea for a software product. They launched it and now it’s becoming a bigger and bigger part of their business.

Family-owned or public companies that have a single giganto shareholder are also hotbeds of long-term thinking and, therefore, innovation. They don’t have that same quarter to quarter pressure that drives a relentless focus on what’s happening right now and allows people to focus on the future.

What’s the most important thing leaders need to understand about compensation and innovation?

If you’re serious about innovation, you should be incentivizing people all over the organization. If you want innovation to be a more regular piece of the culture so you get better results, you’ve got to look at long term incentives. Yes, you should reward people for revenue and short-term goals. But you also need to consider what else is a precursor to our innovation. What else is makes the conditions for innovating better for people, and reward that, too.

Kate’s insight reveals the fundamental contradiction at the heart of most companies’ innovation struggles: you can’t build long-term value with short-term thinking, especially when your compensation system rewards only the latter.

What does your company’s approach to compensation say about its culture and values?

Image credit: Pexels

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Three Steps from Stuck to Success

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Managing Uncertainty

Three Steps from Stuck to Success

GUEST POST from Robyn Bolton

When a project is stuck and your team is trying to manage uncertainty, what do you hear most often:

“We’re so afraid of making the wrong decision that we don’t make any decisions.”
“We don’t have time to explore a bunch of stuff. We need to make decisions and go.”
“The problem is so multi-faceted, and everything affects everything else that we don’t know where to start.”

I’ve heard all three this week, each spoken by teams leads who cared deeply about their projects and teams.

Differentiating between risk and uncertainty and accepting that uncertainty would never go away, just change focus helped relieve their overwhelm and self-doubt.

But without a way to resolve the fear, time-pressure, and complexity, the project would stay stuck with little change of progressing to success.

Turn Uncertainty Into an Asset

It’s a truism in the field of innovation that you must fall in love with the problem, not the solution. Falling in love with the problem ensures that you remain focused on creating value and agnostic about the solution.

While this sounds great and logically makes sense, most struggle to do it. As a result, it takes incredible strength and leadership to wrestle with the problem long enough to find a solution.

Uncertainty requires the same strength and leadership because the only way out of it is through it. And, research shows, the process of getting through it, turns it into an asset.

Three Steps to Turn Uncertainty Into an Asset

Research in the music and pharmaceutical industries reveals that teams that embraced uncertainty engaged in three specific practices:

Embrace It: Start by acknowledging the uncertainty and that things will change, go wrong, and maybe even fail. Then stay open to surprise and unpredictability, delving into the unknown “by being playful, explorative, and purposefully engaging in ventures with indeterminate outcome.”
Fix It: Especially when dealing with Unknowable Uncertainty, which occurs when more info supports several different meanings rather than pointing to one conclusion, teams that succeed make provisional decisions to “fix” an uncertain dimension so they can move forward while also documenting the rationale for the fix, setting a date to revisit it, and criteria for changing it.
Ignore It: It’s impossible to embrace every uncertainty at once and unwise to fix too many uncertainties at the same time. As a result, some uncertainties, you just need to ignore. Successful teams adopt “strategic ignorance” “not primarily for purposes of avoiding responsibility [but to] allow postponing decisions until better ideas emerge during the collaborative process.

This practice is iterative, often leading to new knowledge, re-examined fixes, and fresh uncertainties. It sounds overwhelming but the teams that are explicit and intentional about what they’re embracing, fixing, and ignoring are not only more likely to be successful, but they also tend to move faster.

Put It Into Practice

Let’s return to NatureComp, a pharmaceutical company developing natural treatments for heart disease.

Throughout the drug development process, they oscillated between addressing What, Who, How, and Where Uncertainties. They did that by changing whether they embraced, fixed, or ignored each type of uncertainty at a given point:

As you can see, they embraced only one type of uncertainty to ensure focus and rapid progress. To avoid the fear of making mistakes, they fixed uncertainties throughout the process and returned to them as more information came available, either changing or reaffirming the fix. Ignoring uncertainties helped relieve feelings of being overwhelmed because the team had a plan and timeframe for when they would shift from ignoring to embracing or fixing.

Uncertainty is Dynamic – You Need to Be Dynamic, Too

You’ll never eliminate uncertainty. It’s too dynamic to every fully resolve. But by dynamically embracing, fixing, and ignore it in all its dimensions, you can accelerate your path to success.

Image credit: Pexels

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Don’t Fall for the Design Squiggle Lie

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Don't Fall for the Design Squiggle Lie

GUEST POST from Robyn Bolton

Last night, I lied to a room full of MBA students. I showed them the Design Squiggle, and explained that innovation starts with (what feels like) chaos and ends with certainty.

The chaos part? Absolutely true.

The certainty part? A complete lie.

Nothing is Ever Certain (including death and taxes)

Last week I wrote about the different between risk and uncertainty. Uncertainty occurs when we cannot predict what will happen when acting or not acting. It can also be broken down into Unknown uncertainty (resolved with more data) and Unknowable uncertainty (which persists despite more data).

But no matter how we slice, dice, and define uncertainty, it never goes away.

It may be higher or lower at different times,

More importantly, it changes focus.

Four Dimensions of Uncertainty

Something new that creates value (i.e. an innovation) is multi-faceted and dynamic. Treating uncertainty as a single “thing” therefore clouds our understanding and ability to find and addresses root causes.

That’s why we need to look at different dimensions of uncertainty.

Thankfully, the ivory tower gives us a starting point.

WHAT: Content uncertainty relates to the outcome or goal of the innovation process. To minimize it, we must address what we want to make, what we want the results to be, and what our goals are for the endeavor.

WHO: Participation uncertainty relates to the people, partners, and relationships active at various points in the process. It requires constant re-assessment of expertise and capabilities required and the people who need to be involved.

HOW: Procedure uncertainty focuses on the process, methods, and tools required to make progress. Again, it requires constant re-assessment of how we progress towards our goals.

WHERE: Time-space uncertainty focuses on the fact that the work may need to occur in different locations and on different timelines, requiring us to figure out when to start and where to work.

It’s tempting to think each of these are resolved in an orderly fashion, by clear decisions made at the start of a project, but when has a decision made on Day 1 ever held to launch day?

Uncertainty in Pharmaceutical Development

Let’s take the case of NatureComp, a mid-sized company pharmaceutical company and the uncertainties they navigated while working to replicate, develop, and commercialize a natural substance to target and treat heart disease.

What molecule should the biochemists research?
How should the molecule be produced?
Who has the expertise and capability to synthetically poduce the selected molecule because NatureComp doesn’t have the experience required internally?
Where to produce that meets the synthesization criteria and could produce cost-effectively at low volume?
What target disease specifically should the molecule target so that initial clincial trials can be developed and run?
Who will finance the initial trials and, hopefully, become a commercialization partner?
Where would the final commercial entity exist (e.g. stay in NatureComp, move to partner, stand-alone startup) and the molecule produced?

And those are just the highlights.

It’s all a bit squiggly

The knotty, scribbly mess at the start of the Design Squiggle is true. The line at the end is a lie because uncertainty never goes away. Instead, we learn and adapt until it feels manageable.

Next week, you’ll learn how.

Image credit: The Process of Design Squiggle by Damien Newman, thedesignsquiggle.com

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Mismanaging Uncertainty & Risk is Killing Our Businesses

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Mismanaging Uncertainty & Risk is Killing Our Businesses

GUEST POST from Robyn Bolton

During 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.

Image credit: Pixabay

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McKinsey is Wrong That 80% Companies Fail to Generate AI ROI

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McKinsey is Wrong That 80% Companies Fail to Generate AI ROI

GUEST POST from Robyn Bolton

Sometimes, you see a headline and just have to shake your head. Sometimes, you see a bunch of headlines and need to scream into a pillow. This week’s headlines on AI ROI were the latter:

Companies are Pouring Billions Into A.I. It Has Yet to Pay Off – NYT
MIT report: 95% of generative AI pilots at companies are failing – Forbes
Nearly 8 in 10 companies report using gen AI – yet just as many report no significant bottom-line impact – McKinsey

AI has slipped into what Gartner calls the Trough of Disillusionment. But, for people working on pilots, it might as well be the Pit of Despair because executives are beginning to declare AI a fad and deny ever having fallen victim to its siren song.

Because they’re listening to the NYT, Forbes, and McKinsey.

And they’re wrong.

ROI Reality Check

In 20205, private investment in generative AI is expected to increase 94% to an estimated $62 billion. When you’re throwing that kind of money around, it’s natural to expect ROI ASAP.

But is it realistic?

Let’s assume Gen AI “started” (became sufficiently available to set buyer expectations and warrant allocating resources to) in late 2022/early 2023. That means that we’re expecting ROI within 2 years.

That’s not realistic. It’s delusional.

ERP systems “started” in the early 1990s, yet providers like SAP still recommend five-year ROI timeframes. Cloud Computing“started” in the early 2000s, and yet, in 2025, “48% of CEOs lack confidence in their ability to measure cloud ROI.” CRM systems’ claims of 1-3 years to ROI must be considered in the context of their 50-70% implementation failure rate.

That’s not to say we shouldn’t expect rapid results. We just need to set realistic expectations around results and timing.

Measure ROI by Speed and Magnitude of Learning

In the early days of any new technology or initiative, we don’t know what we don’t know. It takes time to experiment and learn our way to meaningful and sustainable financial ROI. And the learnings are coming fast and furious:

Trust, not tech, is your biggest challenge: MIT research across 9,000+ workers shows automation success depends more on whether your team feels valued and believes you’re invested in their growth than which AI platform you choose.

Workers who experience AI’s benefits first-hand are more likely to champion automation than those told, “trust us, you’ll love it.” Job satisfaction emerged as the second strongest indicator of technology acceptance, followed by feeling valued. If you don’t invest in earning your people’s trust, don’t invest in shiny new tech.

More users don’t lead to more impact: Companies assume that making AI available to everyone guarantees ROI. Yet of the 70% of Fortune 500 companies deploying Microsoft 365 Copilot and similar “horizontal” tools (enterprise-wide copilots and chatbots), none have seen any financial impact.

The opposite approach of deploying “vertical” function-specific tools doesn’t fare much better. In fact, less than 10% make it past the pilot stage, despite having higher potential for economic impact.

Better results require reinvention, not optimization: McKinsey found that call centers that gave agents access to passive AI tools for finding articles, summarizing tickets, and drafting emails resulted in only a 5-10% call time reduction. Centers using AI tools to automate tasks without agent initiation reduced call time by 20-40%.

Centers reinventing processes around AI agents? 60-90% reduction in call time, with 80% automatically resolved.

How to Climb Out of the Pit

Make no mistake, despite these learnings, we are in the pit of AI despair. 42% of companies are abandoning their AI initiatives. That’s up from 17% just a year ago.

But we can escape if we set the right expectations and measure ROI on learning speed and quality.

Because the real concern isn’t AI’s lack of ROI today. It’s whether you’re willing to invest in the learning process long enough to be successful tomorrow.

Image credit: Microsoft CoPilot

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This AI Creativity Trap is Gutting Your Growth

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This AI Creativity Trap is Gutting Your Growth

GUEST POST from Robyn Bolton

“We have to do more with less” has become an inescapable mantra, and goodness, are you trying. You’ve slashed projects and budgets, “right-sized” teams, and tried any technology that promised efficiency and a free trial. Now, all that’s left is to replace the people you still have with AI creativity tools. Welcome to the era of the AI Innovation Team.

It sounds like a great idea. Now, everyone can be an innovator with access to an LLM. Heck, even innovation firms are “outsourcing” their traditional work to AI, promising the same radical results with less time and for far less money.

It sounds almost too good to be true.

Because it is too good to be true.

AI is eliminating the very brain processes that produce breakthrough innovations.

This isn’t hyperbole, and it’s not just one study.

MIT researchers split 54 people into three groups (ChatGPT users, search engine users, and no online/AI tools using ChatGPT) and asked them to write a series of essays. Using EEG brain monitoring, they found that the brain connectivity in networks crucial for creativity and analogous thinking dropped by 55%.

Even worse? When people stopped using AI, their brains stayed stuck in this diminished state.

University of Arkansas researchers tested AI against 3,562 humans on a series of four challenges involving finding new uses for everyday objects, like a brick or paperclip. While AI scored slightly higher on standard tests, when researchers introduced a new context, constraint, or modification to the object, AI’s performance “collapsed.” Humans stayed strong.

Why? AI relies on pattern matching and is unable to transfer its “creativity” to unexpected scenarios. Humans use analogical reasoning so are able to flex quickly and adapt.

University of Strasbourg researchers analyzed 15,000 studies of COVID-19 infections and found that teams that relied heavily on AI experts produced research that got fewer citations and less media attention. However, papers that drew from diverse knowledge sources across multiple fields became widely cited and influential.

The lesson? Breakthroughs require cross-domain thinking, which is precisely what diverse human teams provide, and, according to the MIT study, AI is unable to produce.

How to optimize for efficiency AND impact (and beat your competition)

While this seems like bad news if you’ve already cut your innovation team, the silver lining is that your competition is probably making the same mistake.

Now that you know better, you can do better, and that creates a massive opportunity.

Use AI for what it does well:

Data analysis and synthesis
Rapid testing and iteration to refine an advanced prototype
Process optimization

Use humans for what we do well:

Make meaningful connections across unrelated domains
Recognize when discoveries from one field apply to another
Generate the “aha moments” that redefine industries

Three Questions to Ask This Week

Where did your most recent breakthroughs come from? How many came from connecting insights across different domains? If most of your innovations require analogical leaps, cutting creative teams could kill your pipeline.
How are teams currently using AI tools? Are they using AI for data synthesis and rapid iteration? Good. Are they replacing human ideation entirely? Problem.
How can you see it to believe it? Run a simple experiment: Give two teams an hour to solve a breakthrough challenge. Have one solve it with AI assistance and one without. Which solution is more surprising and potentially breakthrough?

The Hidden Competitive Advantage

As AI commoditizes pattern recognition, human analogical thinking and creativity become a competitive advantage.

The companies that figure out the right balance will eat everyone else’s lunch.

Image credit: Gemini

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Creative Confidence Beats Market Signals

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And How Johnny Cash Used it to Resurrect His Career

Creative Confidence Beats Market Signals

GUEST POST from Robyn Bolton

The best business advice can destroy your business. Especially when you follow it perfectly.

Just ask Johnny Cash.

After bursting onto the scene in the mid-1950s with “Folsom Prison Blues”, Cash enjoyed twenty years of tremendous success. By the 1970s, his authentic, minimalist approach had fallen out of favor.

Eager to sell records, he pivoted to songs backed by lush string arrangements, then to “country pop” to attract mainstream audiences and feed the relentless appetite of 900 radio stations programming country pop full-time.

By late 1992, Johnny Cash’s career was roadkill. Country radio had stopped playing his records, and Columbia Records, his home for 25 years, had shown him the door. At 60, he was marooned in faded casinos, playing to crowds preferring slot machines to songs.

Then he took the stage at Madison Square Garden for Bob Dylan’s 30th anniversary concert.

In the audience sat Rick Rubin, co-founder of Def Jam Recordings and uber producer behind Public Enemy, Run-DMC, and Slayer, amongst others. He watched in awe as Cash performed, seeing not a relic but raw power diluted by smart decisions.

The Stare-Down that Saved a Career

Four months later, Rubin attended Cash’s concert at The Rhythm Café in Santa Anna, California. According to Cash’s son, “When they sat down at the table, they said: ‘Hello.’ But then my dad and Rick just sat there and stared at each other for about two minutes without saying anything, as if they were sizing each other up.”

Eventually, Cash broke the silence, “What’re you gonna do with me that nobody else has done to sell records for me?”

What happened next resurrected his career.

Rubin didn’t promise record sales. He promised something more valuable: creative control and a return to Cash’s roots.

Ten years later, Cash had a Grammy, his first gold record in thirty years, and CMA Single of the Year for his cover of Nine Inch Nails’ “Hurt,” and millions in record sales.

“I wasn’t prepared for what I saw, what I had written in my diary was now superimposed on the life of this icon and sung so beautifully and emotionally. It was a reminder of what an important medium music is. Goosebumps up the spine. It really made sense. I thought: ‘What a powerful piece of art.’ I never got to meet Johnny, but I’m happy I contributed in the way I did. It wasn’t my song anymore.” — Trent Reznor

When Smart Decisions Become Fatal

Executives do exactly what Cash did. You respond to market signals. You pivot your offering when customer preferences shift and invest in emerging technologies.

All logical. All defensible to your board. All potentially fatal.

Because you risk losing what made you unique and valuable. Just as Cash lost his minimalist authenticity and became a casualty of his effort to stay relevant, your business risks losing sight of its purpose and unique value proposition.

Three Beliefs at the Core of a Comeback

So how do you avoid Cash’s initial mistake while replicating his comeback? The difference lies in three beliefs that determine whether you’ll have the creative courage to double down on what makes you valuable instead of diluting it.

Creative confidence: The belief we can think and act creatively in this moment.
Perceived value of creativity: Our perceived value of thinking and acting in new ways.
Creative risk-taking: The willingness to take the risks necessary for active change.

Cash wanted to sell records, and he:

Believed that he was capable of creativity and change.
Saw the financial and reputational value of change
Was willing to partner with a producer who refused to guarantee record sales but promised creative control and a return to his roots.

Your Answers Determine Your Outcome

Like Cash, what you, your team, and your organization believe determines how you respond to change:

Do I/we believe we can creatively solve this specific challenge we’re facing right now?
Is finding a genuinely new approach to this situation worth the effort versus sticking with proven methods?
Am I/we willing to accept the risks of pursuing a creative solution to our current challenge?”

Where there are “no’s,” there is resistance, even refusal, to change. Acknowledge it. Address it. Do the hard work of turning the No into a Yes because it’s the only way change will happen.

The Comeback Question

Cash proved that authentic change—not frantic pivoting—resurrects careers and disrupts industries. His partnership with Rubin succeeded because he answered “yes” to all three creative beliefs when it mattered most. Where are your “no’s” blocking your comeback?

Image credit: Wikimedia Commons

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Escaping the Fear Trap

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What We Can Learn from Wildfire Fighters About Leading Through Uncertainty

Escaping the Fear Trap

GUEST POST from Robyn Bolton

What does a lightning strike in a Spanish forest have to do with your next leadership meeting? More than you think.

On June 14, 2014, lightning struck a forest on Spain’s northeast coast, only 60 miles from Barcelona. Within hours, flames 16 to 33 feet high raced out of control toward populated areas, threatening 27,000 acres of forest, an area larger than the city of Boston.

Everything – data, instincts, decades of firefighting doctrine – prioritized saving the entire forest and protecting the coastal towns.

Instead, the fire commanders chose to deliberately let 2,057 acres, roughly the size of Manhattan’s Central Park, burn.

The result? They saved the other 25,000 acres (an area the size of San Francisco), protected the coastal communities, and created a natural firebreak that would protect the region for decades. By accepting some losses, they prevented catastrophic ones.

The Fear Trap That’s Strangling Your Business

The Tivissa fire’s triumph happened because firefighters found the courage to escape what researchers call the “fear trap” – the tendency to focus exclusively on defending against known, measurable risks.

Despite research proving that defending against predictable, measurable risks through defensive strategies consistently fails in uncertain and dynamic scenarios, firefighter “best practices” continue to advocate this approach.

Sound familiar? It should. Most executives today are trapped in exactly this pattern.

We’re in the fire right now. Financial markets are yo-yoing, AI threatens to disrupt everything, and consumer behaviors are shifting.

Most executives are falling into the Fear Trap by doubling down on protecting their existing business and pouring resources into defending against predictable risks. Yet the real threats, the ones you can’t measure or model, continue to pound the business.

While you’re protecting last quarter’s wins, tomorrow’s disruption is spreading unchecked.

Four Principles for Creative Decision-Making Under Fire

The decision to cede certain areas wasn’t hasty but based on four principles enabling leaders in any situation to successfully navigate uncertainty.

1. A Predictable Situation is a Safe Situation.

Stop trying to control the uncontrollable. Standard procedures work in predictable situations but fail in unprecedented challenges.

Put it in Practice: Instead of creating endless contingency plans, build flexibility and agility into operations and decision-making.

2. Build Credibility Through Realistic Expectations.

Reducing uncertainty requires realism about what can be achieved. Fire commanders mapped out precisely which areas around Tivissa would burn and which would be saved, then communicated these hard truths and the considered trade-offs to officials and communities before implementing their strategy, building trust and preventing panic as the selected areas burned.

Put it in practice: Stop promising to protect everything and set realistic expectations about what you can control. Then communicate priorities, expectations, and trade-offs frequently, transparently, and clearly with all key stakeholders.

3. Include the future in your definition of success

Traditional firefighting protects immediate assets at risk. The Tivissa firefighters expanded this to include future resilience, recognizing that saving everything today could jeopardize the region tomorrow.

Put it in practice: Be transparent about how you define the Common Good in your organization, then reinforce it by making hard choices about where to compete and where to retreat. The goal isn’t to avoid all losses – it’s to maximize overall organizational health.

4. Use uncertainty to build for tomorrow.

Firefighters didn’t just accept that 2,057 acres would burn – they strategically chose which acres to let burn to create maximum future advantage, protecting the region for generations.

Put it in practice: Evaluate every response to uncertainty on whether it better positions you for future challenges. Leverage the disruption to build capabilities, market positions, and organizational structures that strengthen you for future uncertainty.

Your Next Move

When the wind shifted and the fire exploded, firefighters had to choose between defending everything (and likely losing it all) or accepting strategic losses to ensure overall wins.

You’re facing the same choice right now.

Like the firefighters, your breakthrough might come not from fighting harder against uncertainty, but from learning to work with it strategically.

What are you willing to let burn to save what matters most?

Image credit: Pexels

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Building a Business with Feelings and Emotions

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Building a Business with Feelings and Emotions

GUEST POST from Mike Shipulski

If you use your sane-and-rational lenses and the situation doesn’t make sense, that’s because the situation is not governed by sanity and rationality. Yet, even though there’s a mismatch between the system’s behavior and sane-and-rational, we still try to understand the system through the cloudy lenses of sanity and rationality.

Computer programs are sane and rational; Algorithms are sane and rational; Machines are sane and rational. Fixed inputs yield predicted outputs; If this, then that; Repeat the experiment and the results are repeated. In the cold domain of machines, computer programs and algorithms you may not like the output, but you’re not surprised by it.

But businesses are not run by computer programs, algorithms and machines. Businesses are run by people. And that’s why things aren’t always sane and rational in business.

Where computer programs blindly follow logic that’s coded into them, people follow their emotions. Where algorithms don’t decide what to do based on their emotional state, people do. And where machines aren’t afraid to try something new, people are.

When something doesn’t make sense to you, it’s because your assumptions about the underlying principles are wrong. If you see things that violate logic, it’s because logic isn’t the guiding principle. And if logic isn’t the guiding principle, the only other things that could be driving the irrationality are feelings and emotions. But if you think the solution is to make the irrational system behave rationally, be prepared to be perplexed and frustrated.

The underpinnings of management and leadership are thoughts, feelings and emotions. And, thoughts are governed by feelings and emotions. In that way, the currency of management and leadership is feelings and emotions.

If your first inclination is to figure out a situation using logic, don’t. Logic is for computers, and even that’s changing with deep learning. Business is about people. When in doubt, assess the feelings and emotions of the people involved. And once you understand their thoughts and feelings, you’ll know what to do.

Business isn’t about algorithms. Business is about people. And people respond based on their emotional state. If you want to be a good manager, focus on people’s feelings and emotions. And if you want to be a good leader, do the same.

Image credit: Pixabay

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3 Secret Saboteurs of Strategic Foresight

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3 Secret Saboteurs of Strategic Foresight

GUEST POST from Robyn Bolton

You’ve done everything to set Strategic Foresight efforts up for success. Executive authority? Check. Challenging inputs? Check. Process integration? Check. Now you just need to flip the switch and you’re off to the races.

Not so fast.

While the wrong set-up is guaranteed to cause failure, the right set-up doesn’t guarantee success. Research shows that strategic foresight initiatives with the right set-up fail because of “organizational pathologies” that sabotage even well-designed efforts.

If you aren’t leading the right people to do the right things in the right way, you’re not going to get the impact you need.

Here’s what to watch out for (and what to do when it happens).

Your Teams Misunderstand Foresight’s Purpose

People naturally assume that strategic foresight predicts the future. When it doesn’t, they abandon it faster than last year’s digital transformation initiative.

Shell learned this the hard way. In 1965, they built the Unified Planning Machinery, a computerized forecasting tool designed to predict cash flow based on trends. It was abandoned because executives feared “it would suppress discussion rather than encourage debate on differing perspectives.”

When they shifted from prediction to preparation, specifically to “modify the mental model of decision-makers faced with an uncertain future,” strategic foresight became an invaluable decision-making tool.

Help your team approach strategic foresight as preparation, not prediction, by measuring success by the improvement in discussion and decision-making, not scenario accuracy. When teams build mental flexibility rather than make predictions, wrong scenarios stop being failed scenarios.

People are Paralyzed by Fear of Being Wrong

Even when your teams understand foresight’s purpose, managers are often unwilling “to use foresight to plan beyond a few quarters, fearing that any decisions today could be wrong tomorrow.”

This is profoundly human. As Webb wrote, “When faced with uncertainty, we become inflexible. We revert to historical patterns, we stick to a predetermined plan, or we simply refuse to adopt a new mental model.” We nod along in scenario sessions, then make decisions exactly like we always have.

Shell’s scenario planning efforts succeeded because it made being wrong acceptable. Even though executives initially scoffed at the idea of oil prices quadrupling, they prepared for the scenario and took near-term “no regrets” decisions to restructure their portfolio.

To help people get past their fear, reward them for making foresight-informed decisions. For example, establish incentives and promotion criteria where exploring “wrong” scenarios leads to career advancement.

Your Culture Confuses Activity with Achievement

Between insight and action, the Tyranny of Now reigns. In even the most committed organizations, the very real and immediate needs of the business call us away from our planning efforts and consume our time and energy, meaning strategic foresight is embraced only when it doesn’t interfere with their “real” jobs.

Disney’s approach made strategic foresight a required element of people’s “real jobs” by integrating foresight activities and insights directly into performance management and strategic planning. When foresight teams identified that traditional media consumption was fracturing in 2012, Disney began preparing for that future by actively exploring and investing in new potential solutions.

Resist the Tyranny of Now’s pull by making strategic foresight activities just as tyrannical – require decisions based on foresight insights to occur in 90 days or less. These decisions should trigger resource allocation reviews, even if the resources are relatively small (e.g., one or a few people, tens or hundreds of thousands of dollars). If strategic foresight doesn’t force hard choices about investments and priorities, it’s activity without achievement.

How You Lead and What People Do Determine Strategic Foresight’s Success

Executive authority, challenging inputs, and process integration are necessary but not sufficient. Success requires conquering the deeper organizational and human behaviors that determine whether strategic foresight is a corporate ritual or a competitive advantage.

Image credit: Pexels

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