A vision may point towards a future, but it cannot guide every decision we make along the journey. After all, changing conditions and emerging paths continuously shape our decisions.

What’s more, we can share the same destination while disagreeing about how to reach it. If a vision alone cannot take us to where we need to go, then what’s missing?

Values help fill that gap.

While vision tells us where we hope to go, values influence how we choose to travel. They provide a sense of orientation as we navigate the decisions we encounter along the way. Sometimes, those values become most visible when the journey itself is under threat.

We Shall Fight on the Beaches

“…we shall fight on the beaches, we shall fight on the landing grounds, we shall fight in the fields and in the streets, we shall fight in the hills; we shall never surrender…”

Those were the famous lines from Winston Churchill’s “We Shall Fight on the Beaches” speech, delivered to the House of Commons on 4th of June 1940 and later broadcast to the nation. His words still echo through the 21st century.

Before Churchill spoke those very words, Britain and its allies faced a perilous situation. Nazi Germany had already executed a devastatingly rapid military campaign, capturing Poland, Belgium, the Netherlands, and much of France. British and Allied forces had just been evacuated from Dunkirk, France was on the brink of defeat, and the threat of a German invasion of Britain was becoming frighteningly real. At the same time, Churchill was fighting a battle within his own War Cabinet.

Foreign Secretary Lord Halifax urged the government to explore whether Italy might broker a negotiated peace with Hitler. With Britain’s military position deteriorating by the day, Halifax believed the possibility should at least be considered. Churchill fought against it, fearing that entering negotiations from such a weak position could ultimately compromise Britain’s independence. However, knowing that Halifax had considerable influence within the five-man War Cabinet, Churchill needed wider political support.

The Turning Point

Churchill strengthened his position by addressing ministers from outside the War Cabinet. With twenty-five around the table, he delivered a brutal message: it would be better to “fight it out,” and “If this long island story of ours is to end at last, let it end only when each one of us lies choking in his own blood upon the ground.” His refusal to negotiate was met with overwhelming support. Churchill then returned to the War Cabinet knowing that he had the backing of ministers beyond the five men sitting around its table.

Days later, Churchill delivered his iconic speech to Parliament. It did not win the war or immediately change Britain’s military reality. But his words made the government’s direction unmistakable: Britain intended to keep fighting.

Churchill stripped away any lingering illusion of the conflict being a distant “Phoney War”. The evacuation at Dunkirk had demonstrated just how serious the situation had become, and Britain now faced the prospect of invasion. The country responded accordingly by expanding the Home Guard, intensifying aircraft production, and having workers endure round-the-clock shifts to support the war effort.

Churchill’s message also resonated across the Atlantic Ocean. By committing Britain and its Royal Navy to continue fighting, even if the country itself were overwhelmed, he signalled to the United States that Britain intended to remain in the war. His reference to “the New World, with all its power and might, steps forth to the rescue and the liberation of the old” also looked towards an expanding alliance that would eventually transform the war.

The speech itself may not have provided Britain with extra firepower or won any battles. What it helped provide was something less tangible: political and social resolve. Britain continued fighting, survived the Battle of Britain, and Hitler’s planned invasion was eventually postponed indefinitely.1

Words can carry a powerful message when they reflect values people already hold. Churchill’s warnings and speeches expressed resilience, patriotism, unity, courage, and defiance – values that resonated with ministers and much of the public. Together, they helped create the creative tension needed to pull a vision of preserving Britain’s culture, independence, and way of life closer to reality.

Sometimes, we fight for what’s worth fighting for not because we resist change, but because we resist losing what we value most. Churchill understood how much Britain stood to lose and appealed to values that people were prepared to defend.

Sometimes, what we fear losing gives us a reason to move.

And that is often how cultures survive.

Values Behave Like a Compass

Throughout Journeys to Value, we’ve largely viewed value as an expression of something we find meaningful, useful, or important. While that remains true, values – what we consider worth valuing – are slightly different. They reflect what matters to us and what we consider important, desirable, or worth protecting, shaped by social norms, culture, relationships, and lived experience.

Values become integral to our belief systems because they help coordinate our movement through an uncertain world. In this sense, values behave a little like a compass. They help us judge what is good or bad, fair or unjust, virtuous or vicious, acceptable or unacceptable – even what’s worth fighting for. Those underlying judgements influence our decisions in the present while helping us navigate toward a new or familiar future.

But values are not universal navigation rules.

What one person considers fair, another might consider unjust. What one culture celebrates, another might reject. Values emerge from different histories, experiences, relationships, cultures, and belief systems. And that means not all of us carry the same compass.

When Values Become Shared

We all live by values. Some are personal, others shared. We can name the obvious ones like trust, loyalty, honesty, respect, maybe monogamy. But there are also quieter values, embedded so deeply that they become intuitive.

Politeness was one of my dad’s. No matter the situation, it was best to show civility and respect, even if you hated the bastard.

Another was to constantly apply alternative perspectives to a problem or argument. That probably explains why he often took things apart, much to people’s annoyance, or appeared to awkwardly gainsay what someone had said. Really, he was just trying to get to the core of something.

But there’s one value that always stuck with me: don’t take yourself too seriously. I remember my dad whispering those words from his hospice bed. Terminally ill, he didn’t make much sense at times. But this was actually a piece of golden advice – and it wasn’t the first time he’d shared it.

While it’s not exactly the kind of ultimate wisdom you can use to change the Universe, its underlying message is simple. Despite all our worries, sometimes we have to step back and see the bigger picture. We can’t worry too much about everything we do or say. And sometimes, we just need to laugh at ourselves and the situation. That probably explains my humour, which is mostly terrible. But, hey, like I care.

Looking back, none of these values needed to be written down. They materialised through behaviour, and through repetition, some rubbed off on the people around my dad – including me. Perhaps that’s how personal values begin becoming shared ones.

Seen this way, values often require something intimate to become shared. Children naturally mirror the behaviour of parents and others around them, absorbing values they may eventually pass on themselves.

Values can also emerge from life experience. A father learns something about parenthood and instinctively weaves those values into the company he runs. Others take notice and may eventually adopt those values themselves.

Of course, values don’t only spread from one individual to another – the reverse also happens. Personal values are continually shaped by the social systems around us. Families, neighbourhoods, communities, cultures, and religions foster shared ideas about how we should behave and what we should consider important.

Religion is perhaps one of the clearest examples. People can adopt religious values during childhood or encounter them much later in life, sometimes following periods of hardship, loss, or personal upheaval. In doing so, they find established frameworks for interpreting their experiences and navigating life differently.

Values then become more than something personal; they become social tools for creating meaning, coordinating behaviour, and connecting people around shared beliefs.

Yuval Noah Harari describes religion in Sapiens: A Brief History of Humankind as a system of human norms and values, founded on belief in what he calls a “superhuman order”.

Harari also explains that religions that unite large groups tend to possess universal and missionary qualities. Since they are socially contagious, their values can easily cross cultural and geographical boundaries, spreading far beyond the communities where they originated.2

Importantly, those systems do not necessarily require belief in a god. Take Buddhism, for example. Its traditions trace back to Siddhartha Gautama, who became known as the Buddha, meaning the “awakened one.” Buddhism focuses on understanding suffering, craving, conduct, and the nature of experience. Over centuries, these teachings developed into traditions practised by millions of people worldwide.

One expression of those teachings is the Five Precepts, which clearly show how guiding values become shared behaviour. They encourage Buddhists to refrain from killing, stealing, sexual misconduct, false speech, and intoxicants that lead to heedlessness. Rather than solving every situation in advance, they guide how someone might respond appropriately in the moment.3

Values Don’t Just Shape Us – We Shape Them

Thinking about guiding values this way, we can begin to recognise a feedback loop. Whenever we encounter a situation, we interpret it partly based on the values we already hold. These values shape our responses, and the outcomes of our actions provide us with new experiences to interpret. Over time, these experiences can strengthen, weaken, or even change our existing values.

That’s an important distinction:

As values become shared, repeated, and culturally embedded, they gradually become part of a system’s language. From there, they can spread through movements almost like waves gathering force. Shared belief systems then help sustain those movements, binding values together into something that people, organisations, institutions, and communities collectively recognise and reinforce.

As with religion, beliefs become organised around shared values, practices, stories, symbols, and principles that can survive for generations. Ideologies work in similar ways. Their values become embedded in artefacts such as sacred texts, constitutions, manifestos, symbols, rituals, and traditions, allowing ideas to persist across generations and far beyond their origins.

Organisations do much the same thing. You probably walk past one of these artefacts every day: a beautifully designed poster hanging somewhere near the water cooler, reminding everyone to Be Bold, Think Different, or The Customer Is Always Right. Whether anyone actually believes the whole thing is another matter.

But sharing values is only part of the story.

Shared values can help bind a culture together, but a strongly bound culture isn’t necessarily healthy. What matters is how those values shape behaviour. And when shared values become organised into wider systems of belief, ideology often enters the picture.

When Values Become Ideology

We could think of ideologies as belief systems operating at scale. They develop as groups of people share values, assumptions, stories, and ideas about how the world works.

In this sense, ideologies can behave like social glue. They strengthen relationships between people and groups that share similar values. This bonding can connect people across some boundaries, making it easier for them to assemble around a shared belief system. By contrast, it can also reinforce other boundaries, weakening relationships with those outside it.

Belief systems rarely emerge overnight. Instead, they develop over time through culture, experience, movements, and countless interactions. These systems are often reinforced by the stories and narratives people tell about themselves and others. As time passes, values that start among individuals can become ingrained in communities, organisations, and even entire societies.

History shows us exactly this through humanity’s journey from hunter-gatherers to farmers. According to Harari, the Agricultural Revolution coincided with the development of increasingly complex religious and social orders, each capable of coordinating much larger populations. These shared beliefs, myths, norms, and values ultimately helped bind together people who otherwise had little reason to trust one another.4

Human societies have been building belief systems ever since. Over time, ideologies have developed outside of religion across politics, economics, education, science, and countless other domains. Each carries different values about how society should work, what matters, and what a better future should look like. In this way, values became social benchmarks.

Some values eventually become embedded in the systems around us.

The Magna Carta, for example, formalised important values that limited the power of the English monarch and later influenced ideas about lawful judgement and individual rights.5

Centuries later, across the Atlantic Ocean, the Constitution of the United States embedded ideas about political freedom and limited government that are now rooted in American political culture.6

Neither artefact created a perfect society, nor did their values remain fixed. Both, however, demonstrate how shared beliefs can become institutionalised and survive for generations beyond their founders.

And there’s another reason shared values can become so powerful: they don’t always require people to sacrifice their personal interests.

When Personal and Collective Interests Align

About two centuries ago, French diplomat and political thinker Alexis de Tocqueville travelled across the United States to study its democracy and social life. During his journey, he noticed an interesting pattern. Americans were fiercely protective of their independence, yet they often formed associations to solve problems collectively.

Tocqueville called this phenomenon “self-interest, rightly understood,” meaning that helping others and contributing to the common good can also serve the individual’s interests. If it benefits the community, it can benefit the individual.7

We can see this idea through reciprocity and the commons. Both help explain how people, species, or parts originating from a decentralised system can coordinate around something shared. When everything gravitates towards a shared core, the environment becomes almost atomic.

In The Upswing: How America Came Together a Century Ago and How We Can Do It Again, Robert Putnam and Shaylyn Romney Garrett explore the same concept as an altruistic act that can contain an element of longer-term self-interest. If it benefits the community, it can benefit the individual – indefinitely.

Perhaps this is where shared and personal values become especially powerful. When individual and community needs align, altruism and self-interest stop pulling in opposite directions. Cooperation then reinforces trust, and trust makes further cooperation easier. Over time, repeated acts of reciprocity strengthen the social relationships that hold a community together. Indeed, this creates a community growth loop.

Values, then, don’t just bind people because everyone suddenly becomes selfless. Sometimes they bind us because personal and collective interests become complementary.

When Ideology Becomes Identity

Putnam and Garrett’s analysis of 125 years of American history offers an interesting lens on what can happen when that social glue begins to change. Their famous “I–We–I” curve describes a cultural shift from the rapidly industrialising, highly individualistic, and deeply unequal America of the Gilded Age towards a more communal ethos around the middle of the twentieth century. From there, the pattern gradually swung back toward individualism and inequality again.

That movement appeared across multiple parts of American life. Civic organisations, clubs, unions, religious participation, and other forms of community involvement expanded during much of the upswing before declining again during the latter half of the century. But something interesting happened at the same time.

America didn’t simply become less collective. The collectives themselves began changing. And Putnam and Garrett’s analysis suggests that growing partisanship played a major role.

From the 1960s into the 1970s, partisanship gradually became a stronger source of social affiliation in American life, even surpassing religion. Political identities also became increasingly sorted, with fewer liberal Republicans and conservative Democrats. As a result, the ideological distance between the two camps grew – a pattern we now refer to as polarisation.8

Political disagreement has even crossed into personal relationships. Resistance to cross-party marriages has grown, while racial and religious intermarriage has become more accepted. In this sense, political affiliation is increasingly becoming an intimate checkbox rather than simply a preference at the ballot box.9 Perhaps on Tinder, swiping left should literally mean politically left.

It’s no secret that politics in America – and increasingly across the pond in Britain and Europe – can feel less collaborative and more tribal. Political parties naturally represent different interests and values, but those differences can begin shaping how people interpret reality itself.

Political science research suggests that voters are increasingly adjusting their policy positions to fit their party loyalties. Simply put, Margaret might change her stance on a policy because her political tribe’s values matter more than the policy itself.

In that sense, pragmatism becomes secondary. What matters is whether our position feels consistent with who we are and, increasingly, who we are not. Indeed, ideology becomes identity.

This complicates Putnam and Garrett’s “I–We–I” pattern. Western culture may have become more individualistic, but as social psychologist Jonathan Haidt would put it, people remain inherently “groupish” and are often “sucked into tribal moral communities.”10

Those choices often reflect the values embedded in our belief systems. That explains why Margaret eventually left her husband Graham after he switched political sides.

Interestingly, opposing political ideologies can share similar values, even though they interpret them differently. Liberals and conservatives might both care deeply about fairness, freedom, responsibility, security, or human wellbeing, yet disagree about what those values mean in practice or how to prioritise them.

This is where polarisation can become misleading. People can share the same underlying values while taking very different journeys. Maybe there was hope for Margaret and Graham after all. Sometimes, it’s simply a matter of understanding where our compasses align.

When we pan out to view the gap between reality and vision, we can now see how values guide action towards different objectives, goals, missions, and visions.

In that same picture, we can also see different ideologies undergoing their own journeys. Sometimes those journeys converge around shared meaning. Other times, opposing values and interpretations pull them apart, hardening boundaries and turning disagreement into moral conflict.

The same values that help bind one group together can therefore become the very things that separate it from another.

When People Become Symbols of Ideology

Humanity has a habit of turning people into symbols, even after death. These people often deliberately led movements, expressed values, and became living symbols of those movements. Over time, versions of them are remembered through reconstructed stories and narratives – from history books and media footage to Hollywood.

Perhaps “I have a dream” is one of the defining moments in modern history that still resonates today.

Martin Luther King Jr. remains a global symbol of peace and freedom. During his lifetime, he relentlessly championed civil rights and inspired millions with his dream of a more equal society. What made him particularly symbolic were the personal values he embodied.

One of King’s primary values was nonviolent resistance. Instead of using hate or violence to fight segregation, he organised peaceful marches, sit-ins, and boycotts. Racial equality and justice also captured his ethos. Not only did he fight to end legal segregation and discrimination against the Black community, but he also advocated equal access to voting, employment, and education. In effect, these values shaped his vision of a “beloved community” in which all people could live together without racial barriers.11

King is also remembered for his moral courage and faith. During trying times, he drew deep strength from his Christian faith and the church, often speaking with calm, steady bravery. In fact, he drew inspiration from another symbol: Mahatma Gandhi.

Between 1915 and 1947, Gandhi became a leading figure in India’s nonviolent movement for independence from British colonial rule. Perhaps his standout campaign came in 1930, when he walked roughly 240 miles to the sea to protest against the British salt monopoly. At the time, Indians were prohibited from producing salt themselves and forced to pay taxes on something they needed every day. Knowing that salt was a necessity for every human being – rich or poor – Gandhi used it as a symbol to expose the injustice of colonial rule.12

Despite that injustice, he refused to advocate violence. Instead, he stood by his values of nonviolence, which became more powerful than brute force when the world began to notice.

Years later, King openly referred to Gandhi as an important influence on his philosophy of nonviolence, explaining that Christianity gave him the motivation while Gandhi gave him the method.

Today, we can see the connection between King and Gandhi’s values – both fought for what they believed in while demonstrating the very behaviours they advocated. To promote change, sometimes you must become a living symbol of that change.

Because their guiding values were so powerful, society could absorb and compress them into something culturally transmissible – whether it be a memorable march, an iconic speech, or a symbolic act. Each became something much larger than the moment itself.

Values are mostly learned and accepted over time. They guide action, whether within current reality or towards a greater purpose. And while we often see them as communal and political, organisations also operationalise them.

When Values Become Operational

As personal mastery becomes collective, organisations need ways to coordinate people without prescribing every decision. Guiding values help provide that orientation. They establish what matters and influence how people behave, make decisions, and work together while pursuing a broader vision.

Often called core or behavioural values, they help employees understand what the organisation considers important. Such values are sometimes used as cultural benchmarks, allowing leadership and HR to determine how aligned people are with them. More importantly, they can strengthen capabilities, stimulate learning, and empower people to make decisions.

Values, however, are easily confused with principles. The two are closely related, but they perform slightly different roles. If guiding values tell us what matters as we travel, principles help translate those values into ways of thinking and behaving.

Design principles, economic principles, scientific principles, and countless others guide decisions or help us understand how something works. Unlike values, they don’t necessarily tell us what we should ultimately care about or where we should go. They’re more practical: laws, rules, propositions, or guidelines that can be applied repeatedly across different situations. The problem is, we often end up with hundreds of principles to keep track of.

In organisations, principles become useful artefacts that turn values into something people put into practice. For example, a team might value simplicity while adopting a principle like removing unnecessary complexity. The value provides orientation; the principle helps translate it into behaviour.

Values Have to Be Practised

But values only become useful when they influence everyday decisions. Leadership can declare sustainability, integrity, inclusion, or excellence as a guiding value, but putting the words on a poster doesn’t directly change behaviour – nor the system. Those values have to influence how people make decisions, resolve trade-offs, allocate resources, and respond when reality becomes uncomfortable.

Some values, however, are imposed. This is where leadership can fall into the trap of using empty buzzwords and printing generic words on walls for employees to act out. But scripts rarely reflect reality.

I remember one company director who genuinely tried to boost morale and productivity by introducing a list of new core values. Some focused on individual growth, while others reflected broader organisational ambitions for equality and environmentally friendly practices. After months of anticipation, he finally announced them at a company gathering with all the bells and whistles – music, free merch, guest speakers. The stage was set to energise the crowd and rally everyone behind the changes.

During these announcements, people initially show interest. They engage with the presentations and discuss the values amongst themselves. But over time, those values begin to fade, and people soon fall back into old habits.

The deeper lesson is that if people cannot easily recall or naturally demonstrate the core values leadership sets, those values will do very little for culture. Broader group ambitions are also unlikely to resonate when they were never part of people’s visions to begin with.

That’s not to say leadership should simply abandon ideas for introducing new values. Rather, employees and leadership need to explore these ideas together – see what resonates, where their values align, and what they can contribute to the wider vision.

It takes time, patience, and dialogue to familiarise ourselves with each other’s worldviews and ideals. We may not necessarily discover the “perfect values,” but we can at least find common ground to work from.

Like headwaters and rivers, genuine culture emerges when individual values begin flowing towards something shared.

Organisational values can then help shape employee behaviour towards specific objectives, goals, missions, and a shared vision. A small business or startup might communicate its values relatively easily, but as it scales across multiple locations and distributed networks, integration becomes more challenging. With less direct control, communication alone becomes less effective.

Jamie Buttigieg, a leader in franchising, explains that companies such as Patagonia, Starbucks, and LEGO succeed by operationalising their ethos rather than relying on abstract posters or memos. “You can’t enforce values,” he explains, “you have to embed them into the ecosystem in ways that make them feel essential, achievable, and beneficial to the day-to-day operations of each business.”

Rather than simply hoping values will stick, leaders can make culture easier to learn through experience, not just aspirational mission statements. During onboarding, for example, employees might practise those values through role-play conversations and everyday service behaviours. Repeated over time, those behaviours become increasingly embedded, almost like learning a language.

Values also become easier to understand and apply through what Buttigieg calls culture-aligned tools and support systems. Ultimately, when organisational values are repeatedly shared and practised, “culture becomes part of a business rhythm, not just a side note.”13

But what if values are not enough?

Values Need Capability

We’ve established that guiding values help coordinate behaviour, but values alone cannot move a system. An organisation, or perhaps an entire nation, might share the same purpose, vision, and values, yet still fail to preserve any of them.

Something else is required: capability.

Even though Churchill’s speeches and warnings brought his cabinet and the public closer to the perilous reality they were facing, values were simply not enough. If values were the catalyst, then the armed forces, factory workers, and general public were the engine. Together, their capabilities helped turn Churchill’s words into reality through Britain’s continued resistance.

But capability can matter more than achieving a vision. Sometimes, it’s what allows the vision and its values to survive. Let me tell you a story about it.

When a Company Becomes a Legacy

Imagine someone wanting to sell his company. He has numerous offers on the table, but none gives him enough certainty that the things he values will be protected – job security, customer care, product quality, and supplier relationships. His core innovation philosophy is especially integral to the company’s DNA. Having invested nearly twenty years building the business, he’s understandably reluctant to let it go – even to the highest bidder. His company is his legacy.

Of course, there are no guarantees that whoever acquires the business will preserve its vision and values. A management buyout, however, presents an interesting option. If he can sell the business to directors already familiar with its people, customers, products, and values, he may be more certain that he’s leaving the company in the right hands.

Over time, however, the directors struggle to secure funding for the MBO. Issues arise, communication breaks down, and all the while, the owner is terminally ill. He passes away.

Shortly afterwards, the owner’s children inherit the business and follow their father’s instructions to honour the MBO. After further negotiations, the buyout finally completes. Everyone is relieved that the company will remain in familiar hands and that the founder’s vision and values will live on. But that’s not where the story ends.

Several years later, the directors sell the company to a competitor. While little is known about what happens to the products, customers, and suppliers, jobs are lost through relocation. With key employees also gone, an uncomfortable question emerges: who now preserves the company’s values and the founder’s vision?

There’s a missing piece to the story I’ve just told. The founder was my father. I was one of the children who inherited the business.

I could easily tell this story as one about what happened after my dad died, but that would miss the more useful lesson. The directors who eventually took ownership through the MBO weren’t necessarily incapable or acting against his wishes. They inherited a system whose most important capabilities had, over nearly two decades, become deeply embedded in its founder.

There’s an old saying I’ve come across: “the business owner is the business.” There’s some truth in that. Founders often understand every nook and cranny – even the skeletons in the cupboards. They intuitively know how to deal with awkward customers, resolve supply-chain problems, interpret subtle market changes, and make decisions when the available information isn’t enough. Years of experience become relationships, judgement, intuition, and tacit knowledge. And that’s difficult to transfer.

My dad could communicate his values. He could choose people he trusted. He could leave instructions about what he hoped would happen next. What he couldn’t do was simply hand over nearly twenty years of accumulated judgement and experience. Nor could he control what conditions his successors would eventually face.

Seen this way, the problem wasn’t necessarily that the values disappeared. The deeper vulnerability was that too much of the capability required to interpret and sustain those values may have remained concentrated in one person. When that person was no longer there, part of the system’s ability to navigate uncertainty was gone too.

That’s an important distinction. Values might tell us to protect employees, maintain product quality, or preserve long-standing customer relationships. But what happens when those values conflict? What if protecting jobs threatens the business’s survival? What if maintaining quality makes a product uncompetitive? What if preserving an old customer relationship prevents investment somewhere new?

That’s where capability becomes essential, helping us navigate all the awkward trade-offs and compromises.

This is perhaps one of the greatest challenges founders face when considering their legacy. Passing one journey to another person isn’t simply a matter of finding someone who shares the same values. The next person must also possess – or develop – the capability to navigate the system as conditions inevitably change.

When Values Outlive Their Leaders

Steve Jobs faced a version of this problem before his death. He chose Tim Cook as his successor, not because Cook could become another Steve Jobs, but because Apple needed someone capable of taking the company into whatever came next.

Cook inherited an organisation shaped by values around product excellence, simplicity, user experience, and challenging convention. But preserving those values didn’t mean preserving Apple exactly as Jobs had left it.

Under Cook, Apple expanded further into areas including services, health, payments, wearables, artificial intelligence, and spatial computing. Whether every decision reflects what Jobs himself would have done is almost beside the point. Jobs wasn’t there to make those decisions anymore. The organisation had to learn to navigate without him.14

On 1st of September 2026, Cook handed the CEO baton to John Ternus. In Cook’s final memo as CEO, he focused on the company’s culture and core values: “This place is proof that culture triumphs over everything.” He also acknowledged that those values had once again helped Apple leave a “dent in the universe” because of “who we are and what we believe.”15

Even after 50 years, Apple’s CEOs, including Ternus, continue to reflect on the company’s values while standing on the shoulders of giants. In an interview, Ternus recalls Jobs’ furniture story, in which he admired how a carpenter had finished a hidden back panel with the same care as the visible front. Ternus uses the story to reflect Apple’s present philosophy: “It perfectly exemplifies what we do here.”16

Ternus tells a fascinating story about leadership, capability, and growth. His journey at Apple began in 2001, when he joined the product design team and worked on the Apple Cinema Display. By 2021, he was leading hardware engineering, then took responsibility for Apple’s industrial design team in 2026 and eventually succeeded Cook as CEO.

Following Ternus’ journey, we can see personal mastery at work: as people grow, their capabilities can become organisational capabilities. Over 25 years, his personal growth became part of Apple’s organisational growth. Perhaps that journey also helped carry Apple’s values into a new generation of leadership.17

Looking at Apple through the Atomic Innovation model, different capabilities feed into its culture, while values flow through the organisation like its lifeblood. When people learn and grow, so do organisational capabilities. Together with values that endure beyond any one person, those capabilities help sustain the culture.

The Deeper Warning

Perhaps that’s the deeper warning. When a business or organisation gravitates around its founder, it inadvertently creates systemic fragility.

If the vision, values, relationships, judgement, and knowledge required to navigate uncertainty remain concentrated in one person, then removing that person takes away far more than a leader. It’s like ripping out the heart and soul.

Organisations can embed values through culture, behaviour, and capability. But what becomes of those values when institutions set them?

Something to think about: When your values point in different directions, how do you decide which ones matter most?

Feel free to share your thoughts in the comments. 👇

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A vision provides direction, not correctness.

That sounds like an anti-vision statement. You won’t see that as a poster hanging over an office water cooler. But there’s an uncomfortable truth in it. Leaders can set a compelling vision for a better future, but the future they imagine doesn’t always match reality.

Ron Johnson learned this the hard way when he tried to apply his previous success at Apple to his vision for a boutique-style JCPenney. What worked in one system didn’t necessarily work in another.

In other words, a vision provides us with a sense of direction. It raises the bar, sometimes as high as the Moon. But as we move towards it, things may not turn out as we expected. Reality may have other ideas.

So, what do we do then? That’s one question I’ll answer.

A Vision Gives Us Somewhere to Go

If purpose is the inner energy that drives change, then that change needs direction. That’s precisely how a vision works. It coordinates commitment and inspires individuals and collectives to move towards something together.

The Wright brothers’ dream of flight helped revolutionise transportation. Steve Jobs and Steve Wozniak imagined computers becoming more personal and accessible. Walt Disney simply wanted to make people happy.

Whatever the vision, it represents a compelling picture of a different future. It might involve civil rights, technological innovation, or something never previously imagined. Perhaps one of the boldest examples was John F. Kennedy’s moonshot.

“We Choose to Go to the Moon”

In 1961, Kennedy announced the audacious goal of landing a man on the Moon and returning him safely to Earth before the end of the decade. While travelling to the Moon had long inspired fiction and imagination, this was more than aspiration; it was a statement of intent. But convincing Congress and the American public to commit billions of dollars to NASA required more than a bold statement.1

Kennedy was renowned for rallying public support through inspiring speeches. “Ask not what your country can do for you – ask what you can do for your country” remains one of his most memorable lines. Delivered during his 1961 inaugural address at the height of the Cold War, the wider speech called for collective action against tyranny, poverty, disease, and war.

The following year, Kennedy needed to rally support around another extraordinary ambition. “We choose to go to the Moon...” he announced during his speech at Rice University in 1962. The words were simple yet powerful; they helped turn an ambitious national goal into something people could collectively imagine.

A statement, however, was not enough. Kennedy also needed to construct a value narrative that could sustain the vision.

Therefore, Kennedy made the challenge personal to the United States: America would compete with the Soviet Union in space exploration, with a crewed lunar landing becoming the ultimate prize. At the same time, he framed the endeavour as a test of national leadership, technological capability, and collective effort.

In 1969, Apollo 11 astronauts Neil Armstrong and Buzz Aldrin took humanity’s first steps on the lunar surface, making, as Armstrong famously put it, one giant leap for mankind. Kennedy had not lived to see it, but the vision he articulated less than a decade earlier had been realised.

For a short while, NASA continued its lunar expeditions, advancing with each mission. A rover in one, golf in another. It’s a shame they didn’t send any dogs to play fetch. Along the way came setbacks, including the Apollo 13 crisis, yet the programme persisted. By 1972, Apollo 17 marked the end of an era as the last crewed mission to land on the Moon.

Every mission eventually ends, making way for another. But without a new mission, a vision can become increasingly difficult to sustain, and its purpose can gradually fade. That’s partly what happened after NASA stopped sending people to the Moon.

Once the United States accomplished its primary Cold War objective, the narrative supporting Apollo began to weaken. Political priorities shifted, budgets tightened, and attention moved towards other programmes, including the Space Shuttle. Eventually, public interest in lunar exploration faded, and the Moon landings gradually became history – even becoming the subject of conspiracy theories.

More than five decades have passed since an astronaut last stood on the lunar surface – and, indeed, played golf there. Yet when we pan out, the Moon landings appear to have been just one part of a much broader human journey into space.

The International Space Station, the James Webb Space Telescope, and reusable rockets are among the achievements keeping that journey very much alive and kicking – or firing. The United States and Russia are no longer alone.

China and India have developed increasingly ambitious space programmes. At the same time, private companies such as SpaceX and Blue Origin have introduced new commercial and operational capabilities. One of the boldest contemporary ambitions is Elon Musk’s enduring vision to send humans to Mars.

To illustrate our progress on this space journey, we’ve reached a point similar to where commercial aviation was at the beginning of its flight. The Wright brothers’ early prototypes, followed by countless advancements in aircraft and propulsion, were milestones within a much larger movement. Likewise, satellites, telescopes, lunar landings, space stations, reusable rockets, and future missions represent many journeys converging into something larger.

From Destinations to Directions

A vision, therefore, is not necessarily a destination, but a directional force that influences movement. One way to see that movement is through a river system.

Individual journeys are much like headwater streams at the top of a mountain, each following its own path. In this context, imagine different space agencies and private companies, each pursuing separate goals. As their journeys begin to align around a shared vision, they flow together like tributaries joining larger rivers, converging at points where a broader movement emerges. Different players in the space race recognise their common ambitions and increasingly contribute to something greater.

Rather than ending at a fixed destination, the movement keeps flowing, gathering strength as more journeys join. In space exploration, companies, institutions, and entire industries increasingly contribute towards a broader vision. Over time, their individual journeys combine into something greater, much like rivers eventually flowing into the same ocean. Together, they create possibilities that none could achieve alone. The space revolution is on.

Seen this way, a vision doesn’t begin as a single idea or suddenly announce itself. Much like a river system, it takes time for individual journeys to converge, gather momentum, and eventually become a movement.

If we take a leaf out of nature’s book, however, we’ll quickly realise that a shared vision has to evolve organically – and that always starts with people.

A Shared Vision Can’t Be Imposed

A vision is something deeply embedded in a person’s or an organisation’s DNA. That’s why it’s difficult for people to adopt one after reading a textbook or watching a keynote presentation. A shared vision can only truly emerge through individual visions, which brings us back to personal mastery.

People with high levels of personal mastery tend to focus on a personal vision. Such a vision is personal because it comes from within.

Systems thinker Peter Senge describes people with high levels of mastery in learning organisations as taking greater initiative, possessing a deeper sense of responsibility, and learning faster. He also notes that many organisations encourage personal growth because it ultimately makes the organisation stronger as a whole.2

Seen this way, a shared vision simply cannot be imposed from the top down.

Suppose a company CEO sets a new vision. In a company announcement, they say all the right things and paint a compelling picture of the future. It all sounds rather inspiring, but one thing is missing: nobody believes in it.

Instead, people politely nod and comply, treating the vision more like a goal to achieve than a direction to travel. Ironically, a personal vision delivered as a top-down mandate can create the wrong behaviour entirely. Ron Johnson at JCPenney learned this lesson the hard way.

Ron Johnson’s Expensive Lesson

In 2011, JCPenney appointed Johnson as its new CEO after successfully leading Apple’s retail stores and developing the concept of the Genius Bar.3 He clearly demonstrated competence, but his attempt to transfer assumptions from one system to another without adapting them proved costly.

Johnson had a personal vision to transform the ageing department store into a modern, boutique-style shopping experience, heavily influenced by his time at Apple. Central to that vision was his “Fair and Square” pricing strategy, which replaced the coupons, clearance events, and seemingly endless promotions that JCPenney customers knew well.

Adamant that his vision would work, Johnson pushed ahead despite warnings from people who understood the business and its customers. He replaced experienced executives, distanced the company from parts of its traditional retail model, and attempted to reshape what JCPenney represented. But without the thrill of the bargain, customers suddenly had less reason to visit. In Johnson’s first full year, sales fell by around 25%, wiping billions of dollars from annual revenue.4

JCPenney customers didn’t necessarily want a “fair price”; many enjoyed the psychological thrill of a bargain, even when those promotions were partly manufactured through the pricing model itself. Internal teams understood how important coupons and promotions were to customer behaviour. Frontline employees also knew their customers intimately.

Yet Johnson repeatedly discounted those signals because they conflicted with a model heavily influenced by his experience at Apple. He famously resisted extensive testing of the new strategy, reasoning that Apple hadn’t needed it either.

Johnson’s personal vision failed because it became detached from reality. He tried to transfer lessons from Apple without sufficiently adapting them to JCPenney’s context. As evidence mounted against his strategy, he remained committed to the path. Rather than allowing dissent to reshape his thinking, he repeatedly defended his assumptions. In the end, one person’s vision placed an entire organisation at risk.

When leaders impose a vision, people are more likely to see it as a goal to achieve than as a direction they genuinely want to follow. Some will challenge it. Others will simply comply because they lack the energy to resist or fear the consequences. Neither response creates genuine commitment.

People Need to See Themselves in the Vision

A vision, then, is more than a goal. It needs to resonate with something already present within people’s own belief systems. Personal aspirations somehow need to connect with something greater than the individual, the leader, or even the organisation itself. Kennedy’s famous “...ask what you can do for your country” line comes to mind.

In The Upswing, Robert Putnam identifies Kennedy’s sentiment as reflecting America’s shift from an individualistic “I” ethos to a more collective “we” around the mid-twentieth century. In many ways, his words captured what a shared vision can achieve: connecting individual aspirations to something greater than the self.5

Had Johnson understood JCPenney and its wider system like a river network, he might have adapted his personal vision into something more widely shared.

Senior executives, frontline employees, suppliers, and customers were already travelling their own journeys, carrying knowledge about how the system worked and what people valued. Listening to those headwaters might have revealed where individual activities, motivations, and strategies were already flowing in similar directions. Those streams could then converge into tributaries, eventually forming a much larger organisational movement.

Simply put, when smaller streams merge into rivers and rivers eventually reach the sea, many different journeys have contributed to the flow. In this sense, the ocean becomes the ultimate expression of a shared vision. It is where employees, customers, partners, and others begin to recognise what an organisation represents and why they might want to participate.

As Simon Sinek famously puts it in Start with Why, “People don’t buy what you do; they buy why you do it.”6

Johnson effectively tried to force his own river. He imposed what he believed people should value. But his river of dreams eventually dried up because he created conditions for participation that too many people simply rejected.

Not everyone needs to see exactly the same picture, nor will their personal aspirations align perfectly. But something has to resonate. It’s almost as though people are saying, “The vision is different from mine, but there’s something about it that matters to me, and I know I can contribute to it.”

Seen this way, an organisation or community functions much like an organic puzzle. Leadership’s role is not to manufacture every piece, but to understand how those pieces might fit together.

That means understanding what motivates people: why they want to work within the organisation or contribute to a particular cause; what excites them; what gives them energy to push beyond existing limits; and what kind of journey they’re already travelling. A common cause is far more likely to resonate when people recognise themselves within it. And when something resonates, people become more willing to contribute to the whole.

This collective behaviour is what I often call Atomic Innovation: a shared vision continually fed by surrounding capabilities.7 People contribute different knowledge, skills, experiences, and aspirations, gradually strengthening the movement towards something they could not create alone.

Whether we’re talking about retail, space exploration, or social movements, no shared vision begins as a single, perfectly formed idea.

People, organisations, institutions, and communities pursue separate journeys towards their own concepts of value. Over time, those journeys cross boundaries. People interact, build relationships, form partnerships, and gradually discover areas of common meaning. Their different visions can then converge into something more widely shared.

Perhaps that’s the deeper lesson: a vision becomes truly shared when people can connect it to their own goals and aspirations. No single person drives it. The collective does.

Listening at Scale

Aligning different people, companies, or institutions around such a vision usually begins with a smaller group of representatives. Some hold formal leadership positions, while others lead informally because they are willing to step forward.

Informal leadership can take many forms, from community representatives to company “champions”. These leaders advocate for needs and perspectives across a variety of contexts, from local issues to organisational change. In doing so, they open dialogue around purposes, goals, and visions that might otherwise remain unheard or unseen.

Once councils, governments, or organisational leaders better understand what people are striving for, they can begin exploring how broader purposes and visions might better reflect those aspirations.

International diplomacy requires greater formality. Countries appoint ambassadors and other representatives to interact with one another. After the routine handshakes and waves in front of the cameras, much of the real work takes place behind closed doors. Through dialogue, representatives try to find ways for nations with different interests to coordinate and navigate uncertainty together. Diplomacy requires careful sense-making, translation, and compromise because representatives must balance their country’s interests with the realities and interests of others.

Aligning dozens, hundreds, or even thousands of people around a shared vision, however, is considerably more difficult.

Through ongoing interactions, people can better understand the belief systems surrounding them – their needs, values, assumptions, biases, paradigms, and worldviews. While this is practical between individuals or small groups, doing it at scale is often perceived as time-consuming and costly. Can an organisation genuinely listen to every employee?

Actually, it can. Or at least, it can get much closer than we might assume in at least three possible ways:

Structured: Listen Through the Organisation

Line managers speak with their direct reports and feed insights upwards to heads of department. Weekly or monthly conversations help managers understand people’s development, motivations, and how their personal aspirations relate to the organisation’s direction. Department heads can then identify recurring patterns and carry those insights further through the organisation.

Decentralised: Create Opportunities to Connect

Team-building events, field days, social gatherings, and other informal settings allow people from different levels of an organisation to interact directly. An employee might speak with a director and share an idea or challenge without that insight travelling through several layers of hierarchy first. Though they might want to do this before taking advantage of the free bar. Then again, alcohol does have a habit of freeing the tongue. With or without inhibitions, directors and board members gain first-hand exposure to what really motivates people and how they understand the wider vision.

Asynchronous: Let People Respond in Their Own Time

Surveys, suggestion boxes, internal platforms, and email make it possible to gather insight at scale. This approach is relatively easy, although often more ambiguous. People may provide vague – even angry – answers, avoid uncomfortable truths, or simply say what they think leadership wants to hear. But these signals can still reveal patterns and create opportunities for deeper follow-up conversations.

These are only a handful of ways leadership can tune into people’s thinking, as organisations, in different contexts, will discover their own methods. Pixar introduced Dailies and the Braintrust, for example. But what works for one company doesn’t necessarily work for another. In one team, I tried to gather candid feedback through a Braintrust format; the method simply didn’t match our environment. (Plus, the fact that we didn’t produce movies was probably a big giveaway – in hindsight.)

The point isn’t simply to align capabilities, roles, and responsibilities. Leadership’s role is also to continually understand and coordinate personal visions so that the shared one remains relevant.

Sometimes, we just need to step back and imagine observing the headwaters, noticing where springs emerge, where streams begin flowing, and where they start converging. When we see how everything interconnects, the vision becomes clearer.

But seeing where we want to go is one thing. Turning that vision into something we can actually move towards requires structure.

Turning Vision into Movement

A vision realistically materialises once we start taking action. Early ideas only truly take form once we act on them, and innovation can turn concepts into something tangible. Likewise, moving towards an imagined future state requires a venture – indeed, a journey.

Whether intentional or not, our activity often consists of purpose, vision, missions, goals, objectives, and the smallest of actions. These can be understood as a hierarchy of flow, moving from the broadest to the most specific:

• Purpose – Why we exist

• Vision – What future we’re trying to create

• Mission – What we undertake

• Goals – What we aim to achieve

• Objectives – What makes progress specific or measurable

• Action – What we do.

They may appear sequential, yet in reality, they interconnect as part of a living system.

Purpose is deeply intrinsic and linked to personal mastery; it gives us that ultimate sense of “why”. It’s the inner energy that drives us every day, whether towards a vision or not. This distinction matters because not everyone has a clear vision. Some people simply go with the flow.

Vision gives that energy direction, while missions turn it into something we can undertake. A mission can contain multiple goals, objectives, and actions, each supporting a wider vision. NASA’s Apollo programme, for example, consisted of multiple missions, each contributing towards the broader vision of human space exploration.

Goals give those missions something more specific to aim for. During a spacewalk, astronauts might have several goals, from installing new equipment to carrying out repairs or scientific experiments. Back on Earth, a product team might pursue goals around launching a feature, improving an experience, or solving a particular customer problem.

Breaking those goals down gives us objectives. These make progress more specific and, where appropriate, measurable. Product teams might use KPIs or OKRs to understand whether they’re moving in the intended direction.

But not everything worth understanding can be easily measured. User research, for example, provides insight into how people interact with products and services. We can assign metrics to aspects of behaviour, but human needs, emotions, and motivations are far more difficult to squeeze into a number.

Finally, action is where everything meets reality. These are the individual tasks and daily activities that contribute towards our objectives, goals, missions, and ultimately the wider vision.

Structure Only Takes Us So Far

Of course, not everyone works this way. Some people prefer to focus on the task at hand. This is especially true for many artists who “feel” their way through a process of curiosity and play. For some, objectives and goals might simply drain their energy. Others set themselves challenges and timeframes, but even then, deadline pressure can compromise quality and mastery itself.

In more structured environments – from product development to spaceflight operations – goals, objectives, and actions become vital for large-scale coordination and execution.

A project or product manager might guide a team through a programme of work, bringing together the right capabilities and helping everyone coordinate around shared goals. Much higher up, an astronaut has to follow a rigorous sequence of steps and checks to ensure absolute precision – accidentally uncoupling a tether is probably the last thing anyone wants to do during a spacewalk.

In both environments, however, people sometimes need to take the initiative by adjusting or even abandoning objectives and goals. One unexpected problem can introduce an entirely new set of priorities. A product team might bring different capabilities into dialogue to explore ideas, workarounds, and trade-offs. Astronauts might coordinate with their crew and mission control to assess a situation and its possibilities.

At any moment, new problems, challenges, and situations can arise, potentially jeopardising the wider mission.

For example, an oxygen tank exploded while the Apollo 13 crew were travelling towards the Moon. Ernest Shackleton faced something similar when Endurance became trapped in Antarctic pack ice.8

In both situations, the original mission could no longer proceed as planned. Crews had to reassess reality, explore their options, and establish new goals, objectives, and actions. Sometimes we have to move backwards to move forward again.

When Success Sends Us in Circles

Sometimes, objectives, goals, and even missions can stand in the way of our vision. The optimisation trap reminds us what happens when we keep experimenting without pausing to question whether we’re solving the right problem.

When chasing targets and metrics becomes habitual, we begin to lose sight of what we’re actually aiming for. We can happily chase higher conversion rates or watch customer satisfaction scores rise – even NPS 🫢 – but these are signals of success against criteria we’ve already defined.

Without comparing those signals with the direction we’re actually travelling, we might simply be moving around in circles like a dog chasing its own tail.

Seen this way, vision and success look in opposite directions; one looks forward, the other looks backward. We imagine a vision before anything happens. Afterwards, we seek signals of success by comparing what happened with a definition of success. Goals and objectives sit somewhere between reality and a vision, continually signalling whether we’re making progress.

Together, this forms the planning-analysis loop: we plan or aim for a future state, action creates signals, and retrospective analysis helps us interpret those signals into something meaningful. But those signals do not always provide immediate evidence that value is genuinely being realised.

Attach ourselves too tightly to one, and we can lose sight of the wider mission, become blind to the vision, and eventually forget the purpose behind what we’re creating in the first place.

Plans, objectives, goals, and missions give structure to our movement, but none of these guarantees that reality will cooperate, almost like a stubborn mule unwilling to budge. Sometimes we have to change the route. Sometimes we have to change the goal. Sometimes we may even have to abandon the mission altogether.

What matters is whether our actions continue moving reality towards the future we imagine. And then, maybe, the mule might start moving after all.

The Gap Between Vision and Reality

Some visions are hard to describe. Even when we’re clear about where we want to be in the next five years, our awareness of reality can make that future state appear increasingly distant.

Senge describes the gap between current reality and a vision as creative tension, like two hands stretching a rubber band in opposite directions.9 The greater the distance, the greater the tension.

Creative tension isn’t necessarily emotional, like stress or anxiety. Rather, it’s what Senge describes as a source of “creative energy”. The more we act, observe, and adapt, the more likely we are to pull reality toward our vision.

However, the loftier the vision, the greater the perceived challenge. For some, if a vision appears too distant, they’ll deem it impossible, give up, and move on. For others, that same distance becomes a challenge and a source of motivation, no matter how far away it is.

In many ways, stretching a vision raises our ambitions and intensifies our purpose. It makes us question the status quo and even what we accept as objective reality.

Before human flight, the Wright brothers pursued a vision that seemed far removed from reality. The moonshot gets its name from setting an ambition as high as reaching the Moon. Emmeline Pankhurst, Martin Luther King Jr., and Mahatma Gandhi must also have seen civil rights and independence as a far cry from the reality they experienced at the time.

Where many might have given up or accepted the social norm, these individuals persisted in closing the gap. Doing so meant embracing creative tension through resistance, rejection, and setbacks. Through continual action, they brought others onto their journeys, gradually generating enough momentum to sustain a movement.

We can also see how this kind of action is embedded in purpose and personal mastery. People are not simply improving a craft; they are developing collective intelligence and advancing a shared purpose.

Where creative tension can provide energy to move toward a vision, emotional tension can pull us in the opposite direction.

Rather than changing reality, we relieve any discomfort by lowering our expectations and ambitions. Under pressure, targets become smaller, movements slow down, journeys lose momentum, and ultimately the entire system for change begins to shrink.

It’s almost like Michael Phelps changing his ambition from becoming the best swimmer in the world to simply becoming a good one, then significantly relaxing his training.

The deeper lesson is that when we lower our ambitions, our behaviour, psychology, and effort often follow. In this way, a virtuous cycle can gradually become a vicious one. Leading class becomes standard class. Excellence becomes good enough. Moonshots become safe bets. We eventually stop pushing the boundaries and even start protecting them.

Creative tension helps explain the distance between where we are and where we want to be. But agreeing on where we want to be doesn’t mean we’ll agree on how to get there. Moving consistently in the same direction requires something that helps guide our choices along the way.

We call these guiding values. We’ll visit that next.

Something to think about: When reality pushes back against your vision, what do you change: the route, the goal, or the vision itself?

Feel free to share your thoughts in the comments. 👇

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Extraordinary movements often have surprisingly small beginnings. They challenge the flow, the status quo, the outcome, and sometimes even the entire system. Over time, one small, ordinary push can become an extraordinary force. We often call these revolutions.

The Wright brothers kept experimenting until flight became possible.

John F. Kennedy’s Moon speech transformed an ambition into a movement.

Martin Luther King Jr., Emmeline Pankhurst, and Mahatma Gandhi all began with ideas that many people resisted at the time.

Each began with a question of what a future might look like. But reaching that state required something deeply human.

First Flight

In the early 1900s, Orville Wright and Wilbur Wright pioneered the first successful aeroplane. Their persistence created a movement that gave rise to an entire aviation industry.

Soon after, President John F. Kennedy announced the Apollo program that would land humans on the Moon. Once again, persistence unlocked a new chapter. However, these movements did not begin suddenly. They gathered momentum through extraordinary vigour and determination.

Seen this way, change is often born from aspiration. Yet aspiration can also begin with adversity.

Emmeline Pankhurst rallied a movement to win voting rights for women.

Mahatma Gandhi mobilised one to secure India’s independence from British rule.

Martin Luther King Jr. inspired one to build a fairer society.

At the time, each was viewed differently: a hero to some, a rebel to others, an inconvenience to those in power. Yet through determination, they forged enough momentum to create lasting change.

Sometimes, change doesn’t just happen from the edge of a system; it can also happen within it.

Take Winston Churchill. He helped a nation move in the same direction during World War II. His commitment, determination, and speeches inspired people to pull together to overcome one of history’s greatest adversaries.

Some individuals never live to see the full impact of their efforts. But when enough people believe in an idea or cause, they amplify its movement.

Today, billions of people benefit from civil rights secured by those who came before them. While many believe much work remains, the movement continues because ordinary people are capable of creating extraordinary change.

Each of these examples reminds us that change usually begins with an individual or small group of people. Whether we label them heroes or not, they serve as catalysts for new movements.

We often remember the speeches, protests, and defining moments, but we must recognise that these are supported by months – sometimes years – of persistence, sacrifice, and determination that typically go unseen and unheard.

There is a simpler way of looking at it: purpose.

Purpose provides energy and direction to our journeys, and gives entire movements a reason to exist.

Whether we call it a vision, an aspiration, or simply a sense of why, movements emerge because we are all searching for something we believe is worth moving towards: value.

And change often begins with mastery.

Mastering Change

Mastering a craft, skill, or practice has kept us humans busy throughout history. Driven by curiosity, we’ve continually sought better ways to build, improve, and refine our tools, resources, activities, and knowledge. Let’s consider one of humanity’s oldest bushcrafts: fire building.

Building a fire might seem trivial compared with building a large language model. Yet, the ability to control fire became one of humankind’s greatest leverage points.

Sometime during the Palaeolithic Age, our hairy ancestors spent much of their time striking flint against dry tinder. At first, starting a fire wasn’t easy. But through observing cause and effect, they gradually discovered the best materials, structures, techniques, and conditions for creating and sustaining a fire. Over time, they simply became better at it.

Our ancestors didn’t build fires for the fun of it – although pyromaniacs probably existed back then too. Once they realised the flickering orange flame provided warmth, they extended its use to cooking, breaking down tough meat and plants to unlock more calories. One discovery led to another. Fire became useful for producing glue, heat-treating stone into more durable tools, lighting dark shelters, keeping predators at bay, and illuminating evenings of storytelling and ceremony.

Yet every discovery also revealed new dangers. Our ancestors learned that fire could clear land, flush out prey, and even become a weapon against rival tribes.

As tribes – and later societies – became increasingly dependent upon fire, building it reliably became a survival necessity.

A tribe couldn’t simply rely on Fire Striker Joe (whose name has been interpreted from a series of enthusiastic grunts) to keep everyone warm.1 More cave dwellers needed to learn the craft. As communities grew and daily life became more complex, fires needed to burn larger, longer, and more consistently. Perhaps that’s why fire building gradually evolved from a simple task into a craft worth mastering. In many ways, we might even consider it one of humanity’s earliest examples of personal mastery.

Looking back, our ancestors continually improved their fire-building techniques by observing cause and effect. Whether they consciously thought of this as personal mastery is a question best answered after somebody invents a time machine.

Today, however, personal mastery helps explain why some people devote endless energy to improving their craft. It explains why some willingly invest more time, practise longer, and push themselves further than others. Mastery, however, can create system tension.

When a manager faces a deadline, an employee pursuing mastery sees unfulfilled potential in the project. They continue experimenting and refining, while the manager winces painfully at the sight of their burndown chart. When it comes to personal mastery, nothing ever feels truly finished.

However, people who continually transform their capability can also raise the standard for everyone who follows. This is the spirit of innovation: a relentless commitment to learning, refining, and advancing.

For some, mastery is rewarding because they simply enjoy discovering new possibilities. Others are driven by the desire to achieve something that has never been achieved before or to become a better version of themselves.

But when I think about our ancestors, I struggle to imagine Fire Striker Joe proudly declaring, “I must improve my upholstery skills. I am more than a fire builder. I am not Fire Striker Joe. I am Joe.” More likely, Joe simply kept experimenting with mammoth skins because the tribe needed warmer clothing, and because every improvement made life a little easier.

For modern humans, personal mastery remains an ongoing journey of individual value. Whether we’re painting, playing music, coding, or philosophising, we continually ask questions. How can I improve this? What happens if I take it apart? How can I become better than I am today? In effect, personal mastery is continual inquiry. But there’s more to mastery than we think.

Peter Senge describes personal mastery as “the discipline of continually clarifying and deepening our personal vision, of focusing our energies, of developing patience, and of seeing reality objectively.”2

Adam Grant sees mastery as a way to “transform the daily grind into a source of daily joy.”3

James Clear describes mastery as “the process of narrowing your focus to a tiny element of success, repeating it until you have internalised the skill, and then using this new habit as the foundation to advance to the next frontier of your development.”4

Together, these perspectives suggest that mastery emerges through deliberate practice, structured repetition, clear goals, feedback, and the continual refinement of habit.

Personal mastery only becomes possible when we engage with feedback loops, using outputs and outcomes to continually improve future inputs. Over time, mastery itself becomes a reinforcing loop. The more progress or reward we experience, the more motivated we become to continue.

This reinforcing cycle helps explain why our ancestors kept refining fire-building alongside countless other crafts. It also explains why teams continually optimise, businesses pursue new opportunities, scientists search for cures, inventors keep experimenting, and activists continue campaigning.

Even failure becomes a source of motivation. For every failed prototype, every unsuccessful sales pitch, or every rejection, we learn, adapt, and find the motivation to keep pushing.

Change, however, does not always begin with a grand ambition or an epiphany. More often, it begins with habit.

Turning up at the gym each morning, tweaking a favourite recipe, learning a new language, or practising a musical instrument are all forms of personal mastery. Small improvements accumulate slowly over time, just as the tortoise made its way to the finish line. However, those habits can sometimes grow into something much larger, like Facebook.

While studying at Harvard University, Mark Zuckerberg built a simple social networking site connecting students across campus. Originally called TheFacebook, what began as a small side project eventually became one of the world’s largest technology companies.5

The Pokémon franchise began just as modestly. As a child, Satoshi Tajiri – nicknamed “Dr Bug” – loved collecting insects. Years later, he combined that childhood fascination with a passion for video game design. He eventually pitched his idea to Nintendo. Since then, children – and adults – have spent hours on their screens trying to “catch them all.”6

At the time of writing Journeys to Value, my eldest son is obsessed with trains. Every day he sketches locomotives, carefully capturing every mechanical detail. One day, he hopes to see the legendary Union Pacific Big Boy steam locomotive in America. My youngest shares a similar curiosity. Almost every day, he builds increasingly complicated train tracks and marble runs.

Learning through play adds another dimension to personal mastery.

Children naturally immerse themselves in whatever captures their imagination. Whether trains, sport, music, or drawing, they practise because they enjoy the process. Sometimes those interests become lifelong skills. Sometimes they simply shape the way we think. Occasionally, they become something far more personal.

Having been diagnosed with receptive aphasia (that explains why I confuse people – and myself) at around the age of five, my own learning journey followed a less conventional path.7

Speech and language therapy, together with specialist education support, helped me develop, but ironically, learning itself gradually became my craft. As a child, sketching ideas became a way of expressing thoughts that words often struggled to convey. I often had to work harder than others, yet continual improvement gradually became a habit. I’ve always enjoyed writing, but never expected it to become one of the defining ways I express myself today. Learning, however, never really ends.

Even today, I still struggle with some ideas, but I’ve developed ways of working through those moments. AI especially helps me with clarity and articulation, although I’m increasingly conscious of not becoming overly dependent on it. Like many others, I may seem confident, but I am still deeply aware of how much more I have to learn. Even after years of work, I still discover ideas that reshape my thinking.

Generally speaking, the more our understanding grows, the more we recognise how much remains unknown. Mastery, then, is not certainty, but the discipline of remaining curious.

Once personal mastery becomes deeply embedded, we stop looking back at where we began. Our attention naturally shifts towards where we want to go.

But what keeps us mastering?

Theory of Human Motivation

Near the peak of Maslow’s Hierarchy of Needs lies self-actualisation: the drive to become who we are capable of being. For one person, that may mean being a devoted parent. For another, it could involve launching rockets into space and landing them again. Maslow summed up the idea memorably:

“A musician must make music, an artist must paint, a poet must write, if he is to be ultimately at peace with himself. What a man can be, he must be.” – Abraham Maslow.8

Beneath that simple observation lies something deeply human: purpose. Sometimes we struggle to put it into words, but I’d simply say it’s that quiet feeling of knowing that nudges us out of bed while others are still sleeping. Through years of studying organisations, societies, and even Indigenous communities, Maslow developed this idea into what became known as self-actualisation.

Since then, self-actualisation – and Maslow’s Hierarchy of Needs – has been both celebrated and challenged. I suspect Maslow himself would have welcomed that scrutiny. After all, he spent much of his life questioning accepted ideas in search of deeper understanding.

In many ways, we appear to continually organise ourselves around meaning. We package one idea, then later decide it belongs in another box. It’s almost like obsessively rearranging a garage, storeroom, or attic, convinced that this time everything is finally in the right place.

Maslow also acknowledged that our needs do not unfold in a strict sequence.9 Had video games existed in his day, he might have agreed that we don’t simply level up until we eventually unlock self-actualisation – or transcendence – as though they were the final goal.

In reality, our needs overlap, reappear, and sometimes reverse altogether. Some people pursue status ahead of friendship. Others sacrifice comfort – or even survival – for an ideal. What we believe we need may also disguise something deeper.

Viewed this way, Maslow’s hierarchy is more like a circus act. Higher needs, including esteem, cognitive, and aesthetic, continually work in tandem as we pursue our aspirations.

Esteem shapes confidence, recognition, agency, and self-respect.

Cognitive needs drive curiosity, learning, and understanding.

Aesthetic needs influence our appreciation of beauty, form, and harmony.

Together, they influence how we observe, adapt, and respond as we continually balance our needs along our journeys towards value.

Rather than seeing Maslow’s hierarchy as a journey towards one destination, we might instead see it as an ongoing process of value discovery.

That process is itself a learning discipline. We continually refine our understanding because meaning never truly reaches a final state.

Searching for one definitive answer is a little like Douglas Adams’ famous joke in The Hitchhiker’s Guide to the Galaxy, where the answer to Life, the Universe, and Everything turns out to be “42”. As Adams humorously reminds us, an answer is meaningless if we don’t first understand the question.10

Perhaps that’s our greatest challenge. We spend so much time searching for answers that we sometimes forget to improve the questions themselves.

There is, ultimately, no definition of done. That’s bad news for project managers hoping to reduce a product backlog, but excellent news for philosophers, who can continue asking questions – and questioning those very questions.

More importantly, continually asking more questions expands our understanding and deepens our wisdom. In many ways, that continual pursuit of understanding is another form of personal mastery.

By now, we can begin to see how purpose inspires movement – and those hero moments – from Churchill to Martin Luther King Jr, or even Game of Thrones’ Jon Snow or reality queen Kim Kardashian, depending on what truly inspires you.

Yet purpose alone is not enough.

It’s like the Duracell Bunny, endlessly full of energy but running in circles until the batteries die. His cheery face always beamed optimism, but the lithium-manganese dioxide up his arsehole never gave him real direction.11

In other words, purpose gives movement a reason to exist; it still needs direction.

Reflecting on my own journey, determination helped me overcome the expectation that I would never progress beyond the cognitive ability of a twelve-year-old. Yes, read that again.12

But determination alone would never have been enough. My energy needed somewhere to go. Perhaps that’s why I never really stop. I can be a little stubborn – yes, I admit that – but I’ve always wanted to keep moving forwards.

Once we have something worth moving towards, we begin directing our energy towards it. Purpose, then, needs direction towards an imagined future state: a vision.

What Keeps Us Moving?

History reveals a pattern in humankind’s search for meaning that extends beyond the individual. These journeys often begin small and eventually grow into movements. Some happen on the edge of systems, challenging social norms. Others occur within the system itself, asking groups – even an entire nation – to move in the same direction.

The remarkable individuals we often remember provide a deeper lesson:

Hero moments aren’t some mystical phenomenon. They are the visible expressions of years of hard work, determination, sacrifice, and, ultimately, purpose. Beneath them are countless smaller moments of learning, experimentation, feedback, failure, and improvement that typically go unseen.

That’s personal mastery. It isn’t perfection, nor does it have a definition of done. We master through necessity, curiosity, play, practice, success, and failure. The more we learn, the more we discover there is still left to learn.

The driving forces behind personal mastery are deeply human. We’re not merely climbing a ladder towards some final state. Rather, we’re continually discovering what matters to us.

Each time we reframe meaning, we shape the very systems around us. Our individual search then becomes collective, extending into teams, organisations, institutions, communities, and even humanity. Together, we continually redefine what we consider meaningful, fulfilling, and worth moving towards.

But what keeps us moving? Purpose may supply us with energy, but that energy still needs direction. That’s where the next article will take us.

Something to think about: What keeps you moving? Is it curiosity, purpose, personal mastery, or simply the belief that change is possible?

Feel free to share your thoughts in the comments. 👇

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In 1970, Apollo 13 faced a life-threatening crisis while some 200,000 miles from Earth. The crew were on the brink of disaster. Without a solution, they were destined to drift away into the darkness. There was no room for panic. Time was ticking. Fast.

The events that unfolded have been well documented, particularly in Ron Howard’s 1995 movie adaptation. We remember the scenes in which NASA engineers had to improvise an ingenious solution. But there’s something else that stands out: composure under pressure.

Under pressure, behaviour changes – for better or worse. Having the right structure helps, but composure is what brings everything together.

Systems Under Pressure

An explosion severely damaged the spacecraft’s oxygen tank and vital fuel cells, triggering a sequence of emergency responses. One particular response involved astronauts James Lovell, Jack Swigert, and Fred Haise powering down the Command Module Odyssey to conserve its battery.

Consequently, the crew had to rely entirely on the Lunar Module Aquarius as a makeshift lifeboat. Cramped inside the small cabin for four days, they faced dangerous levels of toxic carbon dioxide.

Meanwhile on Earth, NASA’s engineers needed to innovate a solution under extreme time pressure. Working only with the materials available onboard, they devised what later became known as the “mailbox” fix. Using duct tape, plastic bags, cardboard, and instruction manuals, they adapted square carbon dioxide canisters to fit into a round opening.

The solution was ingenious, but it only succeeded because the astronauts executed it precisely. Managing carbon dioxide, however, was only one part of the journey.

Without power, the cabin temperature plunged to near-freezing levels. Condensation formed throughout the spacecraft, creating extreme discomfort, fatigue, and the risk of hypothermia.

Under these conditions, the crew also had to perform multiple untested manual engine burns to place the spacecraft on a precise trajectory back to Earth.

Against extraordinary odds, Apollo 13 safely splashed down in the Pacific Ocean, becoming one of history’s most remarkable survival stories.1

It is tempting to credit the crew’s survival to clever engineering, technical expertise, and disciplined execution. Yet none of these happened in isolation. Every decision had to be made under changing conditions, incomplete information, and relentless uncertainty.

Although astronauts train extensively for emergencies, no training programme can anticipate every possible situation. No one expected the Apollo 13 crew to follow spoken instructions over the radio to build a carbon dioxide filter. Technical skill alone was not enough.

Something else enabled the crew, engineers, and mission control to maintain learning, coordination, and adaptation together: composure.

Up until now, we’ve explored how journeys move through changing conditions. But movement alone isn’t enough.

Under pressure, people often stop observing, stop adapting, and fall back on familiar responses.

Fear narrows attention, time compresses decision-making, and uncertainty grows beyond our comfort levels.

We can train for countless scenarios, prepare endless contingency plans, and surround ourselves with exceptional people and resources. But composure is what allows those capabilities to function when conditions become more uncertain.

Composure creates the space to observe the situation before reacting, adapt to changes before committing, and respond with intention rather than panic. In many ways, composure is the quiet regulator that allows observation, adaptation, and response to work together.

The old wartime saying reminds us: Keep Calm and Carry On. But composure is more than a slogan. It emerges through the environments we create together.

Leadership Create the Conditions for Composure

The Apollo 13 mission reminds us that composure creates the conditions for measured decision-making. That’s equally true in organisations.

Organisations experience problems far more frequently, albeit on a smaller scale. Cybersecurity breaches, critical system failures, supply chain disruption, reputational damage, and unexpected market shocks all place enormous pressure on people to act quickly.

Under pressure, people often retreat to what feels most familiar. Put simply, they fall back on old habits. The challenge, then, is preserving enough clarity to observe the situation before deciding how best to respond.

This is where leadership plays one of its most important roles.

Psychological safety, clear communication, shared understanding, and trust give people the confidence to think clearly under pressure. The goal is not for leaders to become the hero with the perfect answer. It is to create the conditions for people to observe together, adapt together, and respond together.

Like every journey, the paths we choose do not always lead where we expect. Some reveal unexpected forks, while others become dead ends.

In healthy cultures, people resist the urge to panic. Instead, they pause, observe the changing conditions, adapt their understanding, and continue moving together.

Apollo 13 is remembered not because its crew possessed every answer, but because they remained composed and coordinated enough to keep learning. Through that process, the right answers gradually emerged.

Eventually, however, every journey reaches a point where someone must decide which path to take.

This raises another question. If composure matters so much, where does it actually come from?

From Followers to Independent Leaders

Decision-making in high-risk environments – from military operations and emergency response to aviation, healthcare, and space exploration – often follows a clear chain of authority. Yet effective decisions cannot rely on authority alone. They must be grounded in observations drawn from current conditions rather than personal opinion or hierarchy.

In high-performing teams, leaders create the conditions for people at every level to ask questions, challenge assumptions, and investigate problems without waiting for instruction. This cultivates a culture of curiosity and inquiry. Within these conditions, people develop the confidence to act with composure under pressure.

By contrast, command-and-control cultures often produce the opposite. As people become increasingly dependent on authority, they gradually lose the confidence to think and act independently.

Former US Navy captain L. David Marquet explores this challenge in Turn the Ship Around!. When he took command of the USS Santa Fe – then the Navy’s worst-performing nuclear submarine – he recognised how the traditional leader–follower model had conditioned the crew’s behaviour.

Rather than thinking for themselves, crew members waited for permission. Command-and-control leadership had unintentionally weakened accountability, eroded trust, and discouraged initiative. Instead of learning how to respond to changing conditions, they had learned how to comply.

At the time, Marquet’s approach was unusual. Instead of reinforcing the traditional leader–follower model, he cultivated a learning philosophy. Within this environment, crew members used their initiative to assess situations, explore possible solutions, and present intended actions before a final decision was made.

Doing so lifted much of the burden from leadership, allowing senior officers to spend less time directing individual tasks and more time evaluating informed proposals. Authority remained, but thinking became distributed throughout the system.

In effect, Marquet transformed followers into independent leaders who remained aligned to a shared mission.2

But what happens when there is no leader to consult? Dr Christopher Kayes’ analysis of the 1996 Mount Everest disaster offers a compelling contrast. Once climbers became separated from their expedition guides, the leadership structure effectively collapsed.

According to Kayes, climbers who had become accustomed to following instructions suddenly found themselves facing rapidly changing conditions without anyone to guide them. Their vulnerability did not arise from a lack of technical skill, but from a dependence on leadership that no longer existed.

Others, however, responded differently. Rather than waiting for their leaders to return, they began learning directly from the conditions around them. They continually assessed their oxygen supplies, the weather, the remaining daylight, and their own physical condition before deciding what to do next.

Rather than pursuing the original objective, climbers entered what Kayes describes as a learning cycle: experience the situation, reflect on what is happening, make sense of it, and act. For Kayes, it is learning – not the goal itself – that enables people to survive novel situations.3

Marquet and Kayes ultimately arrive at the same conclusion from different environments:

This is where composure begins. But it doesn’t emerge overnight. Rather, it emerges through years of learning, practice, trust, and experience.

NASA astronauts rehearse relentlessly so they can remain composed under extraordinary pressure.

Submarine crews develop the confidence to act because they are trusted to think independently.

Mountaineers improve their chances of survival by learning from the conditions unfolding around them.

Learning restores movement within systems because it replaces dependence with agency. People no longer wait to be told what to do. Instead, they observe the conditions, adapt their thinking, and respond with intent.

In this sense, learning becomes the opposite of a recurring behaviour called Path Fixation – the tendency to continue following familiar directions despite changing conditions.

It transforms the archetype Response Without Adaptation – repeated familiar behaviours – into a continual cycle of observation, adaptation, and response.

Perhaps that is the deeper lesson. The strongest organisations are not those led by a handful of exceptional individuals. They are those that cultivate the confidence, curiosity, and composure for leadership to emerge wherever it is needed.

But what gives people the confidence to act?

Trust the Training

Confidence is rarely built alone. It emerges from trusting our preparation and trusting those around us. Few people demonstrate this better than Olympic swimmer Michael Phelps.

Ahead of the 2008 Beijing Olympics, Phelps followed one of the most demanding training programmes in sporting history. The American former professional swimmer famously trained every single day for six consecutive years without missing a session. Birthdays, Sundays, and even Christmas mornings were treated no differently.

His longtime coach, Bob Bowman, estimated that by never taking Sundays off, Phelps accumulated the equivalent of an additional 52 days of training every year compared with many of his competitors.

Yet physical conditioning alone was not what made Phelps exceptional. His greatest preparation happened in his mind. Every day, he visualised the perfect race, mentally rehearsing every detail: the smell of chlorine, the feel of the water, each turn, every stroke, and even the finishing time.

But he also rehearsed failure. He imagined broken goggles, torn swimsuits, and unexpected setbacks so that if they occurred, they would feel familiar.

Bowman reinforced this preparation by occasionally cracking or flooding Phelps’ goggles during practice, forcing him to complete races effectively blind. Over time, Phelps learned to count every stroke so precisely that he could touch the wall without ever seeing it.

Years of relentless physical training combined with deliberate mental rehearsal prepared Phelps for his defining moment. At the Beijing Olympics, he won a record-breaking eight gold medals. By the end of his Olympic career, he had accumulated twenty-eight medals, more than any athlete in history.4

Phelps did not simply trust his talent. He trusted his preparation. Training transformed uncertainty into familiarity. When unexpected situations arose, he no longer needed to panic because he had already experienced many of them in his mind.

The same principle extends beyond individuals. Within organisations, people depend upon one another. At that point, trust shifts from confidence in ourselves to confidence in the wider system.

In The Culture Code, Daniel Coyle describes trust as the glue that binds individuals into highly cohesive teams. His observations span organisations as diverse as the US Navy SEALs and Pixar Animation Studios. Although very different, both deliberately create environments where trust is continually strengthened through healthy friction.

Coyle observes that Navy SEAL training exposes recruits to relentless physical and psychological pressure, developing deep confidence in one another. In doing so, they build the trust needed to operate in hostile conditions.5

Pixar, by contrast, cultivates trust through its famous Braintrust meetings, where directors, writers, and producers openly critique one another’s work with remarkable honesty.

While one environment builds trust through physical hardship and the other through creative vulnerability, both share the same underlying principle: trust grows through repeated experiences of healthy friction.

Healthy friction reveals another important pattern.

Uncomfortable interactions are the opposite of smooth cooperation. In reality, they create the highly cohesive relationships that make cooperation possible under intense pressure. Skill and expertise remain important, but trust ultimately determines whether individuals can coordinate under uncertainty.

Seen this way, trust becomes another condition for composure. The more we trust our preparation, our teammates, and the system, the less uncertainty overwhelms our thinking.

Composure then becomes less about suppressing emotion and more about relying on relationships that have already been tested.

Whether preparing for an Olympic final, a business decision, or a military operation, success begins with preparation. But composure still has to be maintained.

Regulating Composure

Composure is not something we achieve once and then permanently possess. Like balance within a living system, it requires continual regulation. Every journey introduces new conditions, and each demands fresh observation, adaptation, and response.

Ecosystems are remarkable regulators. Bacteria, fungi, plants, insects, mammals, and entire forests self-regulate to conserve energy, maintain stability, and adapt to changing conditions. Every species contributes to the wider balance of the ecosystem.

Importantly, these behaviours are not improvised; they emerge from biological structures refined over millions of years. A tree does not consciously decide how to respond to drought. A migrating bird does not ponder whether to fly south. Like clockwork, they respond through deeply embedded biological systems.

Human systems work rather differently. We don’t inherit most of our responses – we learn them. I certainly have to shout my boys’ names more times for dinner than I’d like. Then again, word has it that men are born with selective hearing.

The point is that families, teams, communities, and organisations also depend on shared ways of working. But unlike nature, much of that has to be learned rather than inherited. As conditions change, people must consciously regulate themselves.

That is often more difficult than it sounds because new ways of working rarely feel natural at first.

You might read a book on running workshops, only to stumble the first time you facilitate one. Under pressure, people usually fall back on what is most familiar.

Thinking about it this way, it’s as though your vocabulary suddenly shrinks, and old routines become the easiest words to reach for.

As you struggle to recall what you learned, the collaborative workshop becomes the old meeting. The loudest voices dominate the discussion while everyone else retreats into the same awkward silence. What’s missing is a mental library of responses to draw upon. We call that library experience.

Experience is built through continual practice. Airline pilots clock thousands of hours of training before taking command of an aircraft. Even then, experienced captains continue learning throughout their careers.

Like evolution, our responses are continually refined rather than completed. Each experience expands that mental library, leaving us better prepared for future uncertainty.

Learning, then, is much like acquiring a language. Sport makes this easier to see because teams either share that language, or they don’t.

Learning the Language

Navigating a World Cup is less like sprinting and more like running a marathon. Across seven matches, teams travel between cities, experience different climates, recover from injuries, manage fatigue, and continually adjust to unfamiliar opponents.

Even seemingly minor events – a delayed flight, disrupted sleep, illness, or extreme weather – can affect performance. Throughout the tournament, teams must continually regulate how they play because every match presents a different challenge.

The more they experience together, the more fluent they become. Over time, that experience becomes a shared language. Few teams embody that language better than Spain.

At the start of the 2026 World Cup, Spain and head coach Luis de la Fuente were heavily criticised after a 0–0 draw against the island nation Cape Verde. To put the result into perspective, it was like David battling Goliath on green turf.

But Spain didn’t abandon their philosophy. Instead, they kept playing the same way, making small adjustments from game to game while staying true to the same underlying principles. They trusted their process, learned from each match, and continued to adapt. Spain ultimately won the World Cup, conceding just one goal. But this was not an isolated event.

Since 2008, Spain has cultivated a footballing culture that has repeatedly produced world and European champions across both the men’s and women’s game.

Radical reform of the Royal Spanish Football Federation’s grassroots pathways, coaching, training facilities, and relationship with La Liga helped establish the foundations of this philosophy. From these reforms emerged a footballing language built around rhythm and possession.6

Over time, it became embedded throughout the national teams. Slowly, the principles became so familiar that they no longer required conscious thought.

Like a spoken language, they became habit. That ultimately materialised as Spain’s identity. The footballing world eventually gave that language a name: tiki-taka (or tiqui-taca in Spanish).

With a mature footballing language, Spain can adapt instinctively as conditions change. Players do not panic or abandon their principles when possession is lost. Instead, they rely on positional play, patience, pressing, and trust.

What’s remarkable is how instinctively they understand one another’s movements. Although the coach provides direction, players continually solve problems together until opportunities emerge.

Even though Spain went almost a decade without winning a major trophy, their language didn’t disappear. They just required the right person to unlock it once more.

Seen this way, Spain has remained recognisably Spain across different managers. While their system is far from perfect, it enables players to express themselves with a deeply embedded language. This familiarity then enables them to play as a team, adapt as a team, and respond as a team.

More importantly, when the opposition asks questions, Spain can answer with composure. Through shared language, they have become one of football’s best regulators.

Football might seem like a special case. It isn’t.

Regulation, then, is about the continual process of collective learning in changing conditions. Shared language ultimately allows people to coordinate that learning. And composure is what enables them to continue doing it under pressure.

Seen this way, composure becomes another form of regulation. The more effectively a team regulates its emotions, communication, and coordination, the more clearly it observes changing conditions.

Better observation of changing conditions improves adaptation. Better adaptation improves response. Together, these movements continually reinforce one another throughout the journey.

The same principle extends far beyond football. Every organisation, project, expedition, and community experiences moments when conditions suddenly change. The question is rarely whether pressure will intensify, but how effectively people regulate themselves when it does.

Every culture depends on a shared language. When people can collectively express a system’s rules, goals, and structure, they develop a shared identity.

Pixar has its Braintrust. The US Navy SEALs share a deeply embedded culture of trust. Apple and Tesla each developed distinctive ways of thinking about design, innovation, and execution. Although these organisations look very different, they all rely on the same principle.

Whatever the organisation, a shared language helps answer questions like:

How do we respond when conditions change?

What emotions do those conditions create?

How quickly can we adapt?

How do we restore composure when uncertainty begins to overwhelm us?

Over time, shared experiences become a shared mental library that helps people regulate uncertainty together. They know how to respond, whom to trust, and how to recover when conditions suddenly change.

In other words, they develop composure together.

By now, a pattern should be starting to emerge. Composure isn’t another capability. It’s the condition that allows many other capabilities to work together.

From Composure to Purpose

If composure depends upon trust, shared understanding, and coordinated learning, it naturally creates the conditions for psychological safety. People feel able to ask questions, challenge assumptions, admit uncertainty, and learn from mistakes. The goal is no longer to protect ourselves, but to help one another learn.

As a result, movements become more observant, more adaptive, and more responsive because people are no longer defending themselves – they are learning together.

Over the past three Journeys to Value posts, movement within systems has been a recurring theme. We can now see why. Healthy movement isn’t simply about changing direction; it’s about creating the conditions for collective learning

As people learn together, something deeper starts to emerge: a shared vision. Beneath that lies a sense of purpose that gives us a reason to keep moving, even when conditions appear to work against us.

When these qualities align, many individual journeys begin moving as one. Teams become more coordinated. Organisations become more resilient. Communities become more cohesive. People no longer respond as isolated individuals, but as participants in something greater than themselves.

Yet change rarely begins with everyone. More often, it begins with one person – or a small group – who choose to learn together before others do.

Perhaps we could call that a hero moment. Not because extraordinary people suddenly appear, but because ordinary people remain curious, composed, and willing to learn when uncertainty is at its greatest.

Something to think about: Which movements are shaping your thinking today? Are they helping you observe, adapt, and respond – or pulling you towards familiarity and old habits?

Feel free to share your thoughts in the comments. 👇

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We naturally seek explanations that justify our actions.

A politician may use moral arguments to strengthen their point of view.

A company CEO might insist that management double down on strategies that were previously successful.

A team may struggle to see beyond the ideas they generated in a workshop.

These behaviours reveal something fundamental about human psychology. We tend to use reasoning to defend what is familiar or what we are unwilling to question.

Our explanations seem rational, yet they rarely emerge from a complete understanding of the situation. More often, they arise from the narratives we already hold.

This is where another movement archetype comes into play.

Movement Archetype 3: Defensive Reasoning

We often use blame when we cannot clearly explain an outcome, or when the explanation threatens something we value. Blame often becomes the first explanation we reach for.

“You’re not executing the framework properly,” a manager might claim.

“The previous government left us with a £21 million black hole.”1

“It’s them, not us.”

Each explanation seems rational to the person providing it. More importantly, it offers an immediate answer before we fully understand what’s happening. Whether we truly believe what we say or not, blame often serves as a psychological defence mechanism; it allows us to shift responsibility elsewhere.

Correlation is another intuitive tool. We instinctively join the dots, creating explanations that feel coherent even when the evidence is still lacking.

“Customer complaints increased because we introduced home working.”

“Sales dropped because we changed the strategy.”

“I didn’t get the promotion because I’m different.”

Although blame and correlation are different, they often work together to reinforce the worldviews through which we interpret reality. After all, few of us enjoy realising that we might be wrong.

This recurring pattern is what I refer to as Defensive Reasoning.

Rather than understand how our assumptions, decisions, or behaviour might contribute to the problems we face, we tend to focus outward. We place blame elsewhere and correlate ideas even when we lack evidence.

As a result, we gradually push responsibility away from ourselves until the explanation becomes, “It’s not us, it’s them.”

Defensive Reasoning, then, is less about finding the right explanation than protecting the one we already have.

Protecting What We Believe

At the heart of Defensive Reasoning lies protection. The explanations and justifications we defend are not inherently valuable. They matter because they protect something much deeper – our beliefs, identities, relationships, or sense of certainty. When situations become uncertain, protecting those things often feels less risky than questioning them.

However, this defensiveness has consequences. Instead of adapting our understanding as circumstances change, we tend to focus on protecting our existing beliefs and explanations.

The challenge is that we react to what we see without considering the broader context. When faced with uncertainty, our intuition seeks the quickest explanation. We join the dots, draw conclusions, and begin to take action long before we truly understand the situation.

Defensive Reasoning appears in every kind of human system:

• Within families, when individuals cling to long-held beliefs.

• Throughout communities when groups defend shared identities.

• In businesses, when departments blame one another for diminishing returns.

• Across institutions as crises escalate and economies weaken.

Whatever the context, Defensive Reasoning sets in because, like Fear of Loss, it protects the beliefs, identities, and explanations we already hold.

And nowhere is the pattern more visible than politics.

Defensive Reasoning in Public Life

Political debate often resembles theatre rather than dialogue. Politicians spend less time accepting responsibility and more time defending their own positions by attacking others. It leaves me wondering who I should trust.

More worryingly, I begin to wonder whether they are becoming increasingly difficult to tell apart. Seen this way, it’s difficult not to think of George Orwell’s Animal Farm. One scene that comes to mind is when the ruling pigs became so indistinguishable from the humans they had overthrown that it was “impossible to say which was which”.2

Especially during election campaigns, politicians compete for public support by highlighting the failures of the “other side”. Failures vary from economics to public health, but whatever the issue, parties use them as leverage to justify their positions. Meanwhile, activists, campaigners, commentators, and media outlets reinforce one political view while attacking another.

The objective is rarely for opposing sides to work together to solve social and economic problems. More often, it is about persuading people that responsibility lies elsewhere. These narratives then reinforce explanations throughout our hyper-media world.

Advertisers, political campaigns, media outlets, and online creators amplify this dynamic by producing provocative content designed to induce emotional responses.

It might be an Argentina fan deliberately wearing a jersey in London after defeating England in the 2026 World Cup.3

It may be a marketing campaign featuring a hydraulic press crushing musical instruments.4

It could even be an intentionally absurd way of cooking paella.5

Whatever the topic, provocation drives engagement. In an attention economy, attention is often rewarded over understanding.

Rage-baiting6, then, has become a kind of online currency. The strongest emotional reactions often receive the greatest reward. As these narratives spread, they reinforce existing beliefs, deepen division, and make Defensive Reasoning seem increasingly rational.

But it’s not something that we adopt overnight.

The Psychology of Defence

Beneath these public behaviours lies a familiar psychological pattern. Organisational theorist Chris Argyris argued that we often protect ourselves from questioning the validity of our own reasoning.7 Instead of challenging our assumptions, we instinctively defend them.

When we fear losing a method, identity, relationship, or belief that once brought success or acceptance, we become more resistant to change.

As a result, we often avoid feedback, criticism, or dissent – even when we claim to welcome them. We may even dismiss both the people who challenge our thinking and the evidence that threatens our beliefs.

In high-pressure environments, people often end up being viewed as the problem. Whether sales decline, performance stalls, or schedules drift, management frequently concludes that the workforce is at fault for poor execution.

“They didn’t follow our instructions.”

“They don’t fully understand the methods.”

“They didn’t execute the strategy as planned.”

Yet those explanations rarely question the underlying conditions that shaped the outcome. Instead, the focus remains on the people rather than on the system shaping it.

With Defensive Reasoning in play, management is likely to demand that teams work harder, optimise further, or undergo additional training to preserve what has worked before.

Seen this way, Defensive Reasoning blinds those who refuse to challenge their mental models, paradigms, and belief systems. Consequently, blame and correlation overshadow the very signals that should stimulate learning.

The same tendency also extends into our personal lives. In The Subtle Art of Not Giving a F*ck, Mark Manson observes:

“What is objectively true about your situation is not as important as how you come to see the situation, how you choose to measure it and value it. Problems may be inevitable, but the meaning of each problem is not. We get to control what our problems mean based on how we choose to think about them, the standard by which we choose to measure them.”8

In other words, we interpret events through our existing standards, values, and belief systems. Those interpretations often influence our responses far more than the objective reality itself. When those interpretations become shared, they begin to amplify. Almost contagiously.

When Narratives Compete as Instruments of Influence

As these interpretations spread among groups, they start to shape collective narratives – shared stories that influence what people come to accept as true.

Communities, organisations, and institutions reinforce particular worldviews, making some explanations seem more rational than others. The social rules, corporate practices, and cultural habits we repeat are not necessarily correct. They simply become embedded over time because we keep repeating them.

As those ideas become more widely accepted, opposing narratives become easier to dismiss. Rather than helping us question reality, competing narratives increasingly reinforce what we accept as true. In effect, they become instruments of influence.

Unfortunately, competing narratives often do little to bring people together. As people become increasingly divided over almost anything – wealth, economics, education, politics, culture, Apple versus Android, Marmite, or even whether pineapple belongs on pizza – the systems we create often reinforce those divisions rather than reduce them.

Political campaigns often emphasise division. Media outlets amplify it. And marketing campaigns frequently leverage it. Because, after all, difference itself attracts attention. Once you begin noticing the pattern, it becomes remarkably difficult to ignore.

Narratives that reinforce differences appear everywhere. They are amplified and intensified across television, newspapers, podcasts, and social media because conflict naturally captures attention.

Bad news, after all, usually makes the biggest headlines.

Repeated exposure reinforces the belief that our problems lie elsewhere. Over time, trust erodes, curiosity fades, boundaries harden, and cooperation becomes increasingly difficult.

Perhaps that's why Margaret no longer talks to her neighbour. Not because either of them suddenly changed overnight. But because they gradually came to see the world through increasingly different stories and, ultimately, different movements.9

As those movements drift further apart, defending existing positions often becomes more important than exploring alternative explanations. Evidence that challenges an existing worldview is easily dismissed, no matter how well supported it is. By this point, Margaret isn’t simply defending an opinion. She’s defending the story that gave rise to it.

Once we accept one explanation for a situation, our belief system begins to reinforce it. At this stage, it becomes harder to consider different viewpoints.

What’s more, beliefs become harder to challenge once they are shared among others and become part of a movement. Disagreements then become struggles over competing interpretations of reality.

Nowhere is that struggle more visible than on social media.

Social Media and the Story Gap

Social media was originally designed to connect friends and communities. Today, it increasingly resembles a battleground of competing ideologies. Disagreement is not inherently the problem since healthy cultures depend on it. The issue lies in how disagreement is handled.

Too often, online conversations become less about the issues at hand and more about defending identities, allegiances, and beliefs. Every post reflects a particular interpretation of the world. Sometimes it is designed to spark outrage. Other times, it is intended to inform. Either way, people choose to support or attack the narrative, often making the town square feel more Medieval than 21st Century.

The danger is that debate gradually drifts away from dialogue and towards defence. This is when political disagreement evolves into moral disagreement; curiosity is replaced by certainty, and understanding gives way to accusation.

The more we defend our reasoning by placing blame, the wider the divisions become. In many ways, the friction between the different waves of human movement continues to intensify.

One thing appears increasingly clear: society is fragmenting into many different movements as people search for change, certainty, belonging, and meaning.

Perhaps the ocean itself is becoming more turbulent, and it may be some time before the waves settle again. Ironically, as society becomes more fragmented, it becomes easier for each movement to believe it is on the right path while everyone else has lost their way.

Dealing with Defensive Reasoning

Movement itself is not the problem.

The challenge is whether movement leads us towards learning or towards defence. Human history, after all, is a history of movement.

Our hunter-gatherer ancestors travelled in search of food, shelter, and safety. As societies settled following the Agricultural Revolution, movement gradually expanded into trade, exploration, and opportunity.

Today, movement often takes different forms: changing careers, moving home, building a business, joining a new community, or perhaps deciding to write a book – though quite why anyone would willingly choose that particular journey remains open to debate.

The point is that as our basic needs become more secure, movement increasingly becomes a search for meaning rather than survival.

Perhaps it is here that learning begins to replace defence.

Our search for meaning also creates opportunities for coordination. People unite despite holding different political views, religions, cultures, or identities.

For example, during natural disasters, communities rapidly organise to help one another. When oppression, inequality, or injustice become too severe, people also look to one another to bring about collective change. Throughout history, people have rallied around civil rights, democratic reform, and workers’ rights.

Yet coordination is not driven by adversity alone. Others have united in pursuit of scientific discovery, medical breakthroughs, and space exploration. For a time, separate waves begin moving in the same direction. In that moment, movement becomes shared purpose.

From Defence to Learning

Shared purpose has a remarkable way of taming Defensive Reasoning. During emergencies, people rarely stop to ask who is to blame before helping one another. Responsibility shifts from accusation to contribution, competition gives way to coordination, and differences become secondary to a greater cause.

Perhaps that is when humanity is at its very best.

Whether people come together through adversity or aspiration, their behaviour changes. As they develop a shared purpose and understanding, the Story Gap – the gap between competing narratives – begins to narrow. The narrative becomes less about defending positions and more about understanding the conditions together.

As the Story Gap narrows, people become more willing to question assumptions rather than defend them. By then, other behaviours begin to change.

Path Fixation – the tendency to keep following familiar directions – loosens as people become more willing to change direction.

Value Mirage – the tendency to mistake familiar signals for genuine value – begins to fade as familiar signals give way to deeper forms of meaning.

We’re no longer focused on winning arguments or preserving familiarity; we’re learning together and realising value together. Over time, culture itself becomes one of continuous learning, where curiosity replaces certainty, and learning becomes the primary form of coordination.

Perhaps this happens because, beneath all our differences, lie remarkably similar human needs. Familiarity creates trust. Shared experiences create relationships. Relationships enable coordination.

Like neurons reaching towards one another, people naturally connect when they discover common meaning. As understanding deepens, Defensive Reasoning gradually gives way to collective learning.

Eventually, however, those shared movements begin to diverge once again. As missions conclude and conditions change, people return to pursuing different needs, values, and priorities. Some continue riding the same wave. Others search for another.

Healthy movements, therefore, are not those that never disagree. Rather, they are those that remain willing to learn together as conditions continue to change.

Seeing the Pattern

Having explored how healthy movements emerge, we can now step back and recognise the broader pattern. By now, we can begin to see movement for what it truly is. It is not just change; it reflects journeys unfolding within systems.

Everything we observe, interpret, decide, and do subtly influences the direction we take. As conditions evolve, we observe, adapt, and respond. Together, these movements shape not only our personal journeys, but also the wider systems in which they occur.

There’s also another pattern: each movement archetype has its own dominant diagnostic signal.

Response Without Adaptation centres on repeating familiar behaviours. Its primary signal is Path Fixation – the tendency to continue following familiar directions despite changing conditions.

Fear of Loss stems from the psychology of distorted value. Value Mirage – the tendency to mistake familiar signals for genuine value – reveals why people become emotionally attached to familiar behaviours, identities, or definitions of success.

Defensive Reasoning arises from fragmented understanding. Story Gap – the widening gap between competing interpretations of reality – emerges as people build explanations that justify their interpretations, values, and ultimately, their behaviour.

These signals do not operate independently. Together, they reveal how movements gradually drift over time.

• Behaviour – what people do.

• Psychology – why they do it.

• Reasoning – how they come to defend it.

In many ways, the diagnostic signals function like a medical scan, helping to reveal the underlying movement archetype. A scan rarely tells a doctor everything they need to know, but it can reveal patterns that warrant closer investigation.

Likewise, Path Fixation, Value Mirage, and Story Gap do not tell us exactly what is wrong with a person, organisation, institution, or society. Instead, they indicate that something within the wider system may be drifting out of alignment. The movement archetypes then help us understand why.

The earlier we recognise these signals, the greater our opportunity to adapt. Detecting Path Fixation early allows us to question familiar behaviours before they become habits.

Recognising Value Mirage helps us distinguish genuine value from emotional attachment.

Together, they reduce the likelihood of the Story Gap widening and people becoming trapped in fragmented interpretations of reality.

Left unchecked, however, the three signals begin reinforcing one another until learning gradually gives way to escalating patterns of behaviour. That’s when movement becomes increasingly difficult to change, and we become trapped in vicious cycles.

We can never eliminate these archetypes entirely since they are deeply human. We can, however, learn to recognise them sooner and work with them more deliberately.

In doing so, our journeys become healthier, and so too do the systems they help shape. The ocean never becomes entirely calm because new waves always emerge. Yet by learning to read the conditions more carefully, we become better navigators of whatever waters lie ahead.

So far in Journeys to Value, we have explored how journeys drift through changing conditions, why movements emerge, and how familiar patterns of behaviour, psychology, and reasoning shape the direction we take.

We have also seen that healthier journeys depend upon adaptation, curiosity, and learning.

But adaptation itself depends upon something else.

It depends upon composure.

Under pressure, composure creates the space for observation, adaptation, coordination, and ultimately, shared purpose.

Something to think about: Which movements are shaping your thinking today? Are they encouraging curiosity and learning – or certainty and defence?

Feel free to share your thoughts in the comments 👇

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Every movement begins with energy. People test, play, and explore. In doing so, they discover, adapt, and learn. But over time, something quietly changes.

Familiar behaviours become habits. Success becomes something to protect. And what once helped people adapt slowly becomes something they defend.

Across psychology, behavioural economics, systems thinking, and organisational learning, these recurring patterns appear remarkably consistently. I think of them as movement archetypes.

Movement Archetype 1: Response Without Adaptation

One of the most common movement archetypes is what I call Response Without Adaptation. Faced with changing conditions, people often respond quickly by adjusting what they do. Yet the assumptions, beliefs, and mental models guiding those actions remain untouched.

In other words, behaviour changes, but thinking does not.

Individuals, organisations, institutions, markets, and even nations frequently respond to changing conditions without first adapting their understanding of them.

Sport simply provides one of the clearest illustrations.

Reaction Isn't Adaptation

My dad often reminded me of an old saying: “Football is a gentleman’s game played by hooligans, and rugby is a hooligan’s game played by gentlemen.”

The famous sporting maxim captures the banter and contrasting cultures surrounding the two sports.

Yet appearances can be deceptive.

Interestingly, while rugby appears far messier, it is actually built around highly coordinated phases of play. Once you understand its structure, rules, and objectives, you begin to appreciate the constant adaptation taking place beneath the surface.

American football follows a similar principle, albeit with armour, specialised roles, and carefully timed interruptions.

Association football (the one played with feet), by contrast, often appears more elegant, emotional, and free-flowing. Apply a systems lens, however, and another pattern begins to emerge.

Football teams typically organise themselves through formations, defensive blocks, and attacking triangles. Yet much of the game still revolves around individual responses to changing conditions. Legendary moments – a Cruyff turn, a nutmeg, a defence-splitting dribble – often emerge instinctively through years of practice.

Yet not every response produces brilliance. Under pressure, players frequently lose composure. As their cognitive bandwidth narrows, they panic. They force ambitious passes, dive into tackles, or simply launch the ball upfield. Together, these reactions closely resemble the Shifting the Burden system archetype.1

Understanding the distinction between reaction and adaptation matters because they often look remarkably similar. Both involve movement and decisions. Yet reaction tends to repeat familiar patterns, whereas adaptation updates the thinking guiding those patterns.

Smashing the ball clear may feel like the safest option. Yet doing so often hands possession straight back to the opposition. It’s a symptomatic approach that often boomerangs back. Responding solves the immediate problem. Adapting, however, seeks to understand the wider situation before acting.

When a team plays with patience and composure, something different begins to happen. Rather than chasing the ball, players collectively reshape the conditions surrounding it.

Wingers stretch defenders across the width of the pitch. Midfielders create overloads. Defenders patiently recycle possession. Gradually, defensive lines become disorganised, spaces begin to appear, and opportunities naturally open.

What these movements reveal is something fascinating.

Patient movement slowly drains the opposition’s energy while disrupting its structure.

This reminds me of Germany over many decades.

On paper, many of their teams appeared ordinary compared with their rivals. Yet tournament after tournament, they consistently progressed further than expected.

Their strength rarely came from individual flair alone. Instead, it came from selecting players who understood how to function within a coordinated system.

They remained patient, disciplined, and focused on the long game – qualities that often matter more in tournament football than spectacular moments.

When played well, football becomes less reactive and more adaptive. Teams continually move between the two, which perhaps explains why the game remains so wonderfully unpredictable.

Response Without Adaptation is a recurring movement that happens across many domains, especially in organisations and institutions where short-termism takes hold.

In these environments, people jump straight into responding to problems – launching initiatives, restructuring, increasing effort – without first adapting their understanding of the system.

The result is activity without leverage.

But football isn’t unique. The same pattern appears inside organisations every day.

When Organisations Stop Learning

Artificial intelligence provides a contemporary example. Many organisations are rushing to adopt AI, hoping it will solve longstanding problems. Yet AI cannot compensate for fragmented processes, outdated infrastructure, poor collaboration, or weak organisational learning.

When underlying assumptions, structures, and ways of working remain untouched, AI simply becomes another response. It risks becoming an overcorrection rather than a genuine adaptation. Outputs may become faster, yet all the while, learning slows.

Signs of this archetype appear everywhere.

Teams optimise locally around short-term goals and fixed targets. Familiar success creates a false sense of certainty. Reactive decisions become normal practice. Symptomatic interventions gradually evolve into overcorrections that unintentionally create new problems elsewhere.

Not every organisation responds with confidence, however. Some respond by waiting. Ironically, waiting for certainty is itself a response.

Project-based organisations often illustrate this particularly well.

Teams follow a rigid sequence of planning, execution, measurement, and iteration. Months – or even years – later, the market has already moved. Products launch too late. Customer needs have changed. Competitive conditions have evolved.

At that point, teams either begin iterating as a form of correction rather than enhancement, or quietly abandon the project altogether.

The behaviour changes. Thinking does not.

Dealing with Response Without Adaptation

Rather than observe, react, and hope, people in healthier systems tend to follow a different sequence:

• Observe the conditions.

• Adapt the system.

• Respond to opportunities.

As a football match unfolds, players naturally respond to immediate events. The coach, however, observes the wider system. When no clear tactical framework exists, players instinctively default to familiar interventions – clearing the ball, passing sideways, or chasing possession.

Yet when players understand the system they are working within, their responses become increasingly adaptive rather than merely reactive. Few philosophies demonstrated this better than Ajax’s famous Total Football.

Total Football

Between 1965 and 1973, Ajax developed a revolutionary style in which players possessed the tactical intelligence and technical ability to interchange positions seamlessly while maintaining the team’s overall structure.

In this philosophy, positions became less important than relationships.

Rather than thinking in terms of fixed positions, players continually adapted to the movement unfolding around them while preserving the wider system.

The philosophy later evolved once again under Louis van Gaal during the 1990s. A youthful Ajax side built around academy graduates – including Edgar Davids, Clarence Seedorf, Marc Overmars, and Patrick Kluivert – won the UEFA Champions League while remaining unbeaten throughout the competition.

Ajax did not succeed through individual brilliance alone. Players learned to observe, adapt, and ultimately respond together.2

Yet, no philosophy remains permanently effective. Eventually, the wider system adapts. Opponents learned to neutralise Total Football through tactical innovations such as zonal marking, greater athleticism, and faster transition play. 3

The philosophy itself did not suddenly become flawed. Rather, the surrounding conditions changed. In other words, successful adaptations eventually become part of the environment that others learn to overcome. Every successful philosophy reshapes the wider system until the wider system adapts in return.

Question the Paradigm

Beyond football, overcoming Response Without Adaptation begins by questioning the paradigms through which we interpret reality.

Philosophies, models, and ways of working rarely become ineffective overnight. More often than not, the conditions surrounding them change while our thinking remains the same.

True adaptation begins the moment we become willing to question the assumptions we once believed were true.

When Response Without Adaptation appears, Path Fixation – the tendency to keep following familiar approaches after conditions change – is usually the first diagnostic signal to emerge. Familiar responses gradually replace learning as people continue repeating what once worked.

If left unchecked, activity itself begins to feel like progress. That is when Value Mirage – the illusion that activity is creating value – starts to appear.

Eventually, Story Gap – the fragmentation of shared understanding – emerges as understanding fragments.

People continue responding, yet no longer share the same picture of reality. By this point, Response Without Adaptation has become deeply embedded within the wider system.

What Adaptation Looks Like in Practice

In organisational settings, leadership plays an important role. Leaders set the vision and create the conditions for curiosity, while teams make the day-to-day adjustments.

When people feel safe questioning assumptions rather than defending them, they adapt to small changes rather than just respond to them. In doing so, they prevent small problems from escalating into bigger ones.

On a personal level, rethinking our paradigms and belief systems is particularly challenging under pressure. While we cannot change how we think overnight, having a more curious, open mindset is the first of many steps towards adaptation.

When I changed my career, my initial reaction was to show people what I was working on. My instinct was to build a product.

After months at home, I felt pressure to show people something tangible.

Yet I hadn’t first questioned my own assumptions or defined the philosophy behind what I was trying to achieve. Instead, I was following the familiar path of many first-time founders chasing immediate outcomes.

Fortunately, I was able to detect the early signs of Path Fixation and Value Mirage. That prompted me to pause the project.

I rethought my assumptions.

I reminded myself why I had changed careers.

That’s when I began Journeys to Value.

The deeper lesson is:

Understandably, people who lose their jobs need to find work. Others launch businesses, write blogs, or pursue new careers, only to abandon them when immediate results fail to appear. Yet meaningful change rarely emerges that quickly. Most worthwhile journeys require patience, reflection, and continual learning.

Ultimately, Response Without Adaptation reminds us that movement alone is never enough. Before changing what we do, we must first question how we see the world. Only then can we adapt our thinking before responding through our actions.

Yet questioning our assumptions is rarely enough on its own. Sometimes the greatest obstacle to adaptation is not a lack of knowledge or ability, but the fear of letting go of something familiar.

The more we value an identity, a belief, a method, or even an idea of success, the harder it often becomes to let go of it.

Movement Archetype 2: Fear of Loss

Movement is not always driven by hope. Sometimes it is driven by fear. We cling to familiar waves not because they continue carrying us forward, but because letting go feels even more uncertain.

We choose familiarity over curiosity, certainty over exploration, and defence over adaptation.

This is the second movement archetype: Fear of Loss.

Fear Changes What We See

Daniel Kahneman and his long-time collaborator, behavioural economist Amos Tversky, demonstrated that people generally experience losses more intensely than equivalent gains. Losing £100 typically feels far worse than gaining £100 feels good.4

Abraham Maslow approached the same phenomenon from another direction. When our safety, belonging, esteem, or identity feels threatened, our attention naturally shifts away from exploration and towards protection.5

Johnathan Haidt makes a similar observation in moral psychology. He argues that people instinctively defend the groups, identities, and moral frameworks they belong to. Those groups provide certainty and a sense of belonging.6

Fear does not necessarily change the world around us, but it can profoundly change how we perceive it. The greater the perceived loss, the narrower our interpretation of the situation becomes.

In everyday life, fear applies to many familiar things we cling to. We fear losing status, belonging, reputation, identity, careers, relationships, certainty, and even familiar ways of thinking. In many ways, people protect what they fear losing more than they pursue what they could gain.

We often interpret present uncertainty through the lens of past experience. Fear of Loss helps explain why.

Protecting Yesterday

Organisations, institutions, and individuals frequently commit themselves to familiar ways of working because the alternative feels too risky.

They may proudly adopt slogans such as “fail fast”, yet the work still unfolds under relentless pressure to produce immediate results.

Rather than embracing uncertainty, they simply find new ways to pursue familiar outcomes. In effect, they remain riding the same wave.

The same happens when organisations refuse to let go of products, services, or strategies that no longer fit changing conditions. Phrases such as “We’ve come too far” or “We’ve invested too much” quietly reveal Fear of Loss at work.

Admitting failure threatens more than financial investment. It threatens reputation, confidence, status, identity, and sometimes relevance itself. Curiosity gradually gives way to preservation.

Politics provides another illustration.

Governments often continue defending policies long after evidence suggests they require rethinking. Time, political capital, public reputation, and electoral confidence all become investments worth protecting.

Admitting that a policy has drifted can appear more threatening than continuing along the same path.

Perhaps Mao Zedong experienced something similar during the Great Leap Forward. Rather than reassessing changing conditions, governments and political leaders sometimes double down on what they already believe will work.7

What we fear losing, we reinforce. The more invested we become, the harder it often becomes to question ourselves.

When Identity Becomes the Investment

Fear of Loss also helps explain behaviours far beyond organisations and politics.

In Louis Theroux: Inside the Manosphere (2026), UK journalist Theroux explores online communities centred around hyper-masculinity and modern gender roles.8

Throughout his conversations, a recurring pattern emerges. Many of the young men describe growing up without strong male role models or stable sources of identity.

Every story is different. Yet several appear drawn towards communities that provide certainty, belonging, and structure. Letting go of those communities, therefore, risks losing more than opinions. It can feel like losing part of themselves.

I was fortunate enough to grow up with a strong male role model. Like many people, I often wondered how I would cope when I eventually lost my father. When that day came, I was naturally devastated. Yet over time, I gradually adapted to a different world.

Looking back, perhaps having a positive role model gave me the confidence to continue growing rather than defending who I already was. Today, I try to provide that same sense of stability for my own children.

The point is not that I have nothing left to lose. My identity no longer depends upon appearing right or remaining in control. Feedback, criticism, and disagreement can still feel uncomfortable, but they also provide opportunities to learn.

By questioning who I am and how I think, I do not lose part of myself. I gain another perspective.

The same principle applies across organisations.

Employees improve when feedback becomes a tool for learning rather than judgement. Managers become more effective when they acknowledge setbacks rather than hide them. Leaders create healthier organisations when they challenge yesterday’s definition of success rather than defend it.

In every case, curiosity gradually replaces protection.

Fear of Loss also explains why organisations quietly underinvest in their future. Rather than investing in learning, capability, education, wellbeing, or innovation, they protect existing performance and goals. In doing so, they slowly raise the floor of familiarity while lowering the ceiling of possibility.

The safer today’s decisions become, the harder tomorrow’s adaptation becomes.

Over time, this resembles the boiling frog metaphor. Because conditions change gradually, people rarely notice what they are slowly losing. The familiar becomes normal, and the comfortable becomes expected. By the time reality forces change upon them, the opportunity to adapt has often become far more difficult.

The same pattern appears throughout life.

People remain in unhealthy jobs because uncertainty feels frightening. Leaders hide uncomfortable truths to preserve confidence. Political parties continue pursuing familiar policies despite changing conditions. Individuals defend identities that no longer serve them because letting go feels like losing themselves.

Yet fear itself is not the problem.

Why Fear Isn't the Enemy

Fear has always helped humanity survive. Our hunter-gatherer ancestors relied upon it when entering unfamiliar valleys or approaching unknown dangers. Fear slows impulsive behaviour. It encourages observation. It creates space to pause before acting. In that sense, fear remains one of humanity’s oldest risk-detection systems.

Problems emerge only when fear becomes the story rather than the signal.

Modern life presents different uncertainties, yet the principle remains the same. We fear economic instability, illness, technological change, political uncertainty, climate risks, rejection, failure, and irrelevance.

Many of these fears arise from genuine conditions. Others, however, emerge through how we perceive reality.

This is where Fear of Loss connects closely with Kahneman and Tversky’s Availability Heuristic. Events we repeatedly see, hear, or discuss gradually come to feel more probable than they really are.9

Continuous exposure through television, newspapers, political messaging, or social media slowly shapes our interpretation of reality. And what we come to interpret as reality often becomes the source of our fears.

Working With Fear

Fear rarely disappears. Nor should it. The challenge is not eliminating fear but learning from it. Rather than asking, “How do I stop being afraid?”, healthier systems ask different questions:

• What exactly am I afraid of losing?

• What conditions created that fear?

• What evidence supports it?

• What evidence challenges it?

• If the feared outcome happened, how might I adapt?

These questions widen our perspective rather than narrowing it.

Project managers routinely build contingency into plans because they recognise that uncertainty is inevitable and that not every milestone will unfold as expected.

Families purchase insurance not because disaster is inevitable, but because preparation reduces vulnerability when the unexpected happens.

Businesses maintain financial reserves to absorb economic shocks without compromising their long-term direction.

Governments create fiscal headroom to respond to crises such as recessions, natural disasters, or geopolitical conflict.

None of these eliminates uncertainty. Rather, these simply improve our capacity to adapt as conditions change.

The same principle applies personally.

Careers change. Markets shift. Relationships evolve. Technologies emerge. Conditions rarely remain still. Rather than anchoring ourselves to a single definition of success, we must continually reassess the landscape. We must also remain willing to question what we think we know.

Perhaps that is the deeper lesson.

As we loosen our grip on what we fear losing, Value Mirage gradually fades. We no longer confuse preservation with progress.

Path Fixation also softens as familiar assumptions become easier to question rather than defend.

In time, Story Gap narrows because we become more willing to see the world through different lenses rather than a single narrative. Only then can adaptation begin, as certainty gradually gives way to curiosity.

Fear, then, is best understood as a tool rather than a story. We can learn to work with fear rather than allowing it to work on us. Only in doing so, we become better observers, better adapters, and ultimately better navigators of uncertainty.

Fear rarely ends with preservation alone. Left unexamined, it gradually reshapes how we interpret reality itself. The things we fear losing become the very things we begin defending. In time, protecting what we value quietly becomes protecting the stories we tell ourselves about it.

That, however, is where the next movement begins. Once we become invested in our stories, we don’t just protect them – we start explaining them.

And that is where movements begin to drift.

Something to think about: Which movements are shaping your decisions today? Are they helping you adapt to changing conditions – or simply encouraging you to protect familiar ways of thinking?

Feel free to share your thoughts in the comments 👇

Leave a comment

UK journalist and TV presenter Jeremy Clarkson has certainly had his fair share of success, most notably presenting one of the world’s most-loved motoring programmes, Top Gear. For 25 years, he travelled the world driving fast cars, often through absurd and comical challenges.

Clarkson’s career took an unexpected turn when he punched a producer, resulting in his eventual departure from the BBC.1 Alongside co-presenters Richard Hammond and James May, he moved to Amazon Prime Video’s The Grand Tour.

These days, however, he’s doing something entirely different. He’s driving tractors.

Learning to Navigate

In 2008, Clarkson bought a 1,000-acre farm in Oxfordshire. Having lost his farm manager, he decided to manage the farm himself. What could possibly be so difficult about farming, he thought.

In 2021, Amazon helped answer that question by documenting Clarkson’s farming journey in Clarkson’s Farm.2 Almost immediately, he discovered the harsh realities of modern agriculture.

What’s now known as Diddly Squat Farm has produced no shortage of interesting and often comical challenges, most noticeably:

• Lamborghini R8 tractor. Assuming that horsepower would give Clarkson the advantage, it quickly became apparent that the machine was simply too large for the farm.

• The barking “sheep” drone. Too impatient to use a traditional sheepdog, Clarkson attempted to herd his flock using a drone equipped with a loudspeaker playing barking noises.

• Hot chilli chutney. While making a lucrative batch of hot chilli chutney, Clarkson accidentally created something resembling a chemical hazard. Boiling chilli fumes filled the kitchen, leaving the entire crew coughing and fleeing the building in tears.

To his credit, Clarkson asks plenty of questions and learns quickly (well, mostly) why farming follows certain conventions. By the end of season five, he and his trusted agricultural adviser, Charlie Ireland, conclude that, in many ways, farming is a gamble.

Living with Uncertainty

Farmers must decide what to plant months in advance, investing heavily in seeds, fertiliser, fuel, equipment, and labour. Yet British weather is notoriously unpredictable.

Too much rain can destroy crops. Too little rain can be equally devastating. In Clarkson’s case, too little rain meant his harvest wasn’t large enough to make the farm profitable. He lost several thousand pounds.

While those losses barely affect someone whose wealth comes primarily from Amazon, the same losses can be catastrophic for the average farmer. One bad year can bankrupt a farm.

Without sufficient capital, farmers may struggle to invest in the next season. But as farming contractor Kaleb Cooper frequently reminds audiences, farming is not simply about earning a living. It’s a lifestyle.

Seen through a systems lens, that lifestyle is one of continual movement and navigation. Perhaps agriculture provides one of the clearest, yet least appreciated, examples of how changing conditions shape interconnected systems.

Farmers are the unsung participants constantly battling waves of uncertainty. They experience oscillations in the weather. They lose livestock to predators, disease, and difficult births. They face pressures from markets, industry, and government regulations.

Together, these pressures make farming increasingly difficult to sustain.

Throughout Journeys to Value, we’ve explored systems as structures. We’ve also seen how balance, coordination, and uncertainty shape the conditions within them.

Where there is movement, there are paths, branches, delays, intersections, and unintended consequences. Every journey is a path through a system. When enough journeys begin moving in the same direction, they become a movement.

Every journey unfolds within conditions we rarely control. Markets shift. The weather changes. Policies evolve. Relationships strengthen or weaken. As those conditions change, we adapt – and the system adapts with us. That’s why friction is almost inevitable.

Movement Creates Friction

Market forces, industry pressures, and government intervention are all conditions that shape farming. Sometimes for the better. Sometimes for the worse. While regulation exists to maintain standards and protect animal health, interventions can also create unintended consequences elsewhere.

In season five, during routine testing for bovine tuberculosis (bTB), one of Clarkson’s cows returned an inconclusive result. Neither positive nor negative, the result classified the animal as high risk and required it to be isolated from the rest of the herd. The news was especially distressing because the cow was pregnant with twins.

Under these regulations, the wider herd also faced restrictions while further testing took place. For farmers already operating on narrow margins, delays and uncertainty can be both financially and emotionally exhausting.

When the cow later returned another inconclusive result, it was slaughtered before giving birth. Subsequent tests later showed that the animal had not carried the disease. Three healthy cows had died unnecessarily.

Understandably, Clarkson was furious. He questioned the reliability of the testing process and why a disease that has existed for generations remains so difficult to control.

Yet the wider challenge is far more complex than any single test or policy. Disease control, animal welfare, environmental protection, and farmers’ livelihoods are all interconnected. Each has different goals and constraints.

Balancing Competing Needs

Farming involves difficult balancing acts. Efforts to protect one part of the system can create vulnerability elsewhere. Attempts to preserve wildlife, protect livestock, reduce disease, and maintain rural livelihoods often pull in competing directions. There are no perfect solutions, only continual trade-offs requiring coordination and adaptation.

In many ways, this is dynamic balance in practice. Stability never emerges from permanent equilibrium but from continual adjustment as conditions change. Farmers, regulators, veterinarians, environmental groups, markets, and consumers are all responding to different pressures, often with incomplete information.

As one part of the system adapts, others must adapt too. The goal isn’t to find perfect solutions. Rather, it’s to keep navigating competing forces without allowing the wider system to drift too far in one direction.

Clarkson, of course, has experienced many other challenges that reveal how fragile farming can be. Weather, disease, regulation, costs, and markets all interact together. Without sufficient support across the wider system, farming can quickly become unsustainable.

And yet, many farmers continue.

When Systems Change

For many, farming is not simply a business. It’s a way of life, often passed down through generations.

Fields, livestock, and machinery shape the countryside that fascinates people from an early age. Agriculture itself lies at the roots of human civilisation.

Farms feed communities, support jobs, and shape the landscapes around us. Depending on how they are managed, they can also restore habitats and improve the environment.

But farming often struggles to build upon success. Conditions change. Finances evaporate. Eventually, many farmers have no choice but to sell their land. What happens afterwards is a question I often ponder.

Where there is movement, there is also tension.

One system may gradually give way to another. Farms are absorbed into larger operations. Land is repurposed for housing, renewable energy, or alternative uses. New priorities emerge while older ways of life slowly weaken. Whether this represents decline, adaptation, or transformation depends largely on the perspective from which we view it.

What seems clear, however, is that movement rarely happens without friction. Without adequate support, farming remains vulnerable to shocks that are often difficult to avoid.

Those personal stories don’t exist in isolation. They reflect pressures unfolding across the wider system. Governments, industries, markets, technologies, and environmental pressures continually reshape the landscape.

Many argue that society is moving away from traditional farming. Whether true or not, the tensions themselves reveal something deeper.

Increasingly, people, organisations, industries, and institutions are zig-zagging across an ever more complex system, each pursuing different goals, values, and visions.

Some Zig, Others Zag

Not everyone moves in the same direction. If that were the case, we’d all share the same tastes, preferences, identities, and cultures.

In effect, we’d become a sterile monoculture, as humorously depicted by the Goodness Gracious Me sketch in which a group of Indian friends demand the “blandest thing on the menu” at an English restaurant. After all, who wants food as bland as boiled bread?3

Ironically, England itself tells a different story. Travel to Spain, and you expect paella. In Italy, pasta. Yet many English restaurants happily serve Indian, Chinese, Italian, Spanish, and French dishes all from the same menu.

Venture further into the countryside, however, and you’ll discover something else entirely. Traditional pubs, seasonal vegetables, artisan breads, local cheeses, cider, game, and Sunday roasts all reflect cultures shaped by history, geography, and local produce.

English, Welsh, and Scottish towns and villages often preserve much of their charm and character. From Stamford to Totnes, communities still gather around churches, pubs, and weekly markets. Beyond them lie rolling hills, stone cottages, grazing sheep, and winding country roads where life moves at a gentler pace.

Well... apart from the tractor holding up traffic or the suicidal pheasant waiting to test your reflexes.

Cities and metropolises, by contrast, trade fields and hedgerows for steel towers, crawling traffic, and constant movement. Yet urban culture often reveals itself in smaller pockets, such as Covent Garden or Camden Town. Street performers, independent cafés, food markets, and bohemian fashion give these places their distinctive character.

Similar structures exist across both environments, yet the movement within them differs. In many ways, culture emerges through the interaction between people and the environments they inhabit.

The same applies to transport systems. Tokyo’s rail network is famous not simply for its infrastructure, but for how millions of people coordinate their habits and expectations every day.

Meanwhile, anyone who has squeezed onto the London Underground during rush hour will experience something entirely different.

Perhaps this reveals something deeper.

Structures matter, but movement matters too. Similar systems can produce very different outcomes because people navigate them differently.

Journeys Become Interdependent

Within these environments, countless journeys unfold simultaneously. Some people zig, others zag, yet their lives frequently intertwine like threads within a moving tapestry. Families, friendships, businesses, communities, and institutions all depend upon one another.

People consume goods and services while others provide them. Teachers educate future workers. Farmers feed communities. Hospitals care for the sick. Businesses employ people who, in turn, become customers themselves. In this sense, society is built upon reciprocal movement.

At larger scales, these journeys extend across communities, organisations, industries, institutions, and markets.

Populations migrate. Technologies emerge. Companies rise and fall. Political parties drift. As they do, cultures evolve through changing values, rebellion, migration, and new ideas.

Some movements become increasingly coordinated and influential. Others fragment into competing directions or gradually lose momentum.

Where movement exists, interdependence follows. And where interdependence exists, tensions inevitably emerge.

This becomes especially visible when individuals pursue their own interests at the expense of the wider system. Ecologist Garrett Hardin described this pattern as the Tragedy of the Commons.4

Simply put, shared resources begin to degrade because no one is fully responsible for maintaining them. Questions of fairness, inequality, and responsibility soon follow.

Perhaps social imbalance does not always emerge from structures alone. Sometimes it emerges because people, groups, and institutions begin moving in different directions. And as movements diverge, so too do the assumptions, values, and belief systems guiding them.

How Movements Become Belief Systems

In ancient Rome, millions of people across Europe, North Africa, and the Middle East united under a common political and institutional system. Within it, hierarchy and centralised control enabled large-scale coordination.

Many people shared assumptions, values, laws, stories, and customs that made them feel part of something larger. Yet humanity has never stood still. As conditions change, so do the movements within belief systems.

I don’t believe humanity woke up one day and collectively decided, “We need more than one belief system.” Rather, belief systems evolve much as paradigms drift. New ideas emerge, old assumptions weaken, and shared meanings fragment and reorganise.

Some people eventually organise those beliefs into more explicit forms, especially when concerned with how society should be structured or changed. If belief systems help us interpret the world, then ideologies help us organise and reshape it.

Coined in 1796 by the French philosopher Antoine Destutt de Tracy, the term ideology derives from the Greek words idéā (notion or pattern) and -logíā (the study of). Proposed as a “science of ideas”, it was intended as a rational and objective study of the human mind and the origins of thought.5

In other words, in Destutt de Tracy’s view, ideology was about inquiry. Today, however, the term has evolved into something quite different. We often use it to describe organised values, customs, and beliefs – constructs that are generally more subjective than objective.

History provides a useful illustration.

Remarkably Roman

Back in the third century AD, the Romans defined themselves through a collection of political and cultural concepts often described as Romanitas.6 Through this shared identity, millions coordinated around assumptions and values that made them feel remarkably... Roman.

Back then, you weren’t simply human; you were Roman. Yet even within that wider belief system, multiple ideologies and philosophies existed, including republicanism, imperial rule, Stoicism, Christianity, military expansion, and civic virtue.7

As the empire expanded, it also absorbed new knowledge, skills, technologies, and cultural influences from the societies it encountered. In many ways, movement itself strengthened Rome’s capacity to innovate, govern, and build at a remarkable scale.

These ideas not only sustained the wider Roman belief system but also helped embed elements of it into Western civilisation. Even after the empire collapsed, its shared meaning continued to thrive through laws, roads, Christianity, Latin, and concepts of citizenship.

Perhaps the Romans never truly disappeared; they simply transcended their institutions and found new expressions in another age.

Institutions, like the Roman Empire itself, are expressions of belief systems. They emerge from them, reinforce them, and eventually decline as those beliefs begin to drift. In that sense, the Roman Empire was not the belief system itself. It was one expression of a much larger system of shared meaning.

Modern Expressions

We can observe something similar today. Apple, Nike, and Ben & Jerry’s are expressions of broader systems of meaning surrounding technology, sport, and social values.

Long after Steve Jobs, Tim Cook and employees continue building products that focus on individual empowerment, simplicity, and challenging the status quo.

The “Just do it” philosophy, too, continues to evolve around human potential and the drive to overcome.

Meanwhile, Ben & Jerry’s is renowned for its stance on social justice and progressive activism, actively supporting the communities around it.

In each of these cases, one word stands out: ethos. Derived from the Greek word for “character”, ethos describes the guiding beliefs and ideals that give an ideology its distinctive identity.8

Apple has an ethos of empowerment. Nike celebrates human potential. Ben & Jerry’s champions justice.

Seen this way, the Roman world contained multiple movements, each shaped by its own ethos and guided by different ideologies. Ultimately, ethos and ideology were connected through a broader belief system.

Ideas in Motion

Movements do not necessarily emerge from nowhere. Rather, they emerge from shared meanings that help people interpret the world and coordinate around what they collectively believe matters.

Today, we witness similar movements. Environmental, scientific, religious, cultural, political, and economic movements all offer different ways of interpreting and organising reality.

Some movements reinforce existing belief systems, while others attempt to reshape them through new ideologies. It is within these movements that societies continually decentralise, fragment, and reorganise themselves.

Activism provides a particular example. Throughout history, movements have questioned assumptions surrounding rights, laws, equality, and social responsibility.

The Suffragettes campaigned for women’s voting rights. Martin Luther King Jr. challenged assumptions surrounding racial equality and justice. Today, thousands of movements seek change across environmental, political, economic, technological, and humanitarian issues.

In many ways, belief systems themselves are journeys. They evolve, branch, compete, merge, and occasionally transform into entirely new ways of seeing the world. Yet where different movements exist, tensions inevitably emerge. After all, not every movement shares the same vision of progress.

Some beliefs simply help us make sense of reality, while others seek to reshape it. Perhaps that’s why so many arguments miss the underlying point. People are not always defending an ideology. Sometimes they are simply defending the lens through which they understand the world.

With so many movements emerging, friction across society is perhaps inevitable.

When Waves Collide

With so many emerging movements, there is increasing friction across society. Friction does not necessarily arise from movement alone, but from the interaction between competing belief systems and ideologies.

We can imagine humanity as a vast ocean. Throughout much of history, great civilisations resembled powerful swells moving millions of people in broadly the same direction.

The Romans, the Ottomans, and many others each generated movements that, while imperfect, remained relatively coherent for long periods. Smaller waves still existed, but they rarely challenged the wider current.

Today, however, the sea feels very different. Instead of a handful of dominant swells, countless waves form, split, merge, and collide. Some quickly disappear. Others gather momentum. The result is a far more turbulent ocean, increasingly shaped by uncertainty and competing interpretations of the future.

Those waves are clearly visible across UK politics.

For decades, the public largely followed a familiar rhythm, swinging between Labour and the Conservatives in most election cycles. Perhaps those on the other side of the pond can relate; elections usually swing between the Democrats and the Republicans.

Today, that rhythm appears to be changing. As confidence in long-established institutions weakens, more people are migrating towards parties such as Reform and the Green Party. The political landscape is indeed becoming increasingly fragmented.

Interestingly, fragmentation is now emerging within both the political left and right. Politicians and voters alike are moving towards groups that better reflect their values and beliefs.

Some seek fairness and equality, while others prioritise security, stability, or national identity. In many ways, political narratives become less about individual policies and more about morality, identity, and certainty.

Simply put, people are riding the waves they feel they belong to.

Why We Follow Certain Waves

Jonathan Haidt describes this tendency as being “groupish”. As social creatures, we naturally seek belonging. The same instinct shapes friendships, workplaces, sporting loyalties, religions, and political movements.

In The Righteous Mind, Haidt argues that liberals and conservatives often pursue similar moral goals, such as fairness, care, and justice. They simply interpret those goals through different moral lenses.

Liberals generally look outward, embracing change and reform, while conservatives often look inward, preserving tradition, continuity, and social order. Yet neither side has a monopoly on compassion, generosity, or public service.

Being groupish also shapes identity. People often remain loyal to a party, movement, or cause because it reflects how they see themselves.

As Haidt observes, political opinions frequently function as “badges of social membership”. Sometimes people genuinely support the policies their group proposes. At other times, belonging itself becomes the stronger force. Supporting the movement becomes just as important as supporting its ideas.9

This groupish nature closely mirrors Abraham Maslow’s Love and Belonging need. In his paper, A Theory of Human Motivation, Maslow observes that people possess a deep psychological need to belong to families, communities, and wider social groups. As social creatures, we seek acceptance, connection, and shared identity.

Further up his hierarchy sits another powerful need: esteem. Recognition, respect, achievement, and status often deepen our commitment to the groups we identify with.10

But belonging and esteem are not selfish traits. Rather, as Haidt puts it, they are often about “demonstrating commitment to our team.” After all, most of us want to be team players.

Yet Maslow also reminds us that human needs rarely unfold in a fixed sequence. They overlap, reappear, and sometimes reverse altogether. People change careers. They move countries. They leave organisations. They abandon political parties. Others sacrifice comfort, status, or even safety in pursuit of causes they believe transcend their own interests.

Simply put, we often adjust our movements to survive the world’s ever-changing conditions.

Throughout Journeys to Value, we’ve explored change and innovation as journeys unfolding through time. These include individuals and groups of people travelling through life, work, relationships, organisations, and society, continually responding to changing conditions.

From Journeys to Movements

Every individual follows their own journey. Sometimes those journeys remain separate. Sometimes they begin moving in the same direction. When enough people align around shared needs, values, or beliefs, we recognise the pattern as a movement.

Journeys belong to individuals. Movements emerge when many journeys align, whether briefly or over time.

When conditions beneath them become unstable, they naturally search for another wave that better supports their needs, values, or aspirations.

Sometimes that shift happens gradually. Sometimes a signal – a conversation, an event, a crisis, or an intervention – is enough to trigger an entirely new movement. Almost instantly, people can jump from one wave to another as their priorities, beliefs, or circumstances suddenly change.

Yet movement alone does not guarantee adaptation. People often alter their behaviour while continuing to interpret the world through the same assumptions, mental models, and belief systems that guided them before.

We often imagine that movement itself is progress. But changing direction is not the same as changing understanding.

Something to think about: Which movements are shaping your decisions today – and are they helping you see the world differently, or simply giving old assumptions a new direction?

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When Sir Ernest Shackleton set sail aboard the Endurance in 1914, his goal was clear: to become the first person to cross Antarctica by land. Yet within months, the ship became trapped in ice.1

As the ice slowly crushed the vessel, Shackleton faced a decision that many leaders struggle to make. Should he continue pursuing the original mission, or accept that the conditions had fundamentally changed?

Shackleton chose the latter.

History often remembers Shackleton for his extraordinary leadership under pressure. Yet perhaps his greatest achievement was something more subtle. He recognised that navigating uncertainty sometimes means changing the destination itself.

Where there is movement, there is also uncertainty...

Decisions Under Uncertainty

Where there is movement, there is also uncertainty – especially as systems become increasingly interconnected, delayed, and complex. Even decisions we consider good do not guarantee positive outcomes.

Since the future can never be known with complete certainty, decision-making becomes inherently probabilistic. We estimate what might happen, weigh competing possibilities, and act without ever seeing the full picture.

Every decision is a bet on a possible future. Like any bet, it carries risk because systems reveal their consequences over time.

Shackleton couldn’t know whether abandoning the expedition would save his crew. He simply recognised that the conditions had changed, making the original plan the greater risk.

Risk, therefore, becomes less about predicting outcomes and more about understanding how change unfolds across the wider system.

Annie Duke approaches the same challenge from a different perspective. In Thinking in Bets, she compares probability to a game of poker. As a former World Series of Poker champion, she contrasts poker with chess.2

Chess rewards calculation because every piece is visible. Poker, on the other hand, rewards decision-making despite incomplete information. Nobody knows what cards another player holds until they are revealed.

The distinction matters because innovation – and life itself – resembles poker far more than chess. While we can’t control the future or eliminate uncertainty, we can continually reduce uncertainty by making better decisions.

To do that, we often need to think both backwards and forwards.

Back to the Future, and Back Again

Duke describes probability as a form of mental time travel: the ability to imagine multiple possible futures before deciding what to do next.

Yet sometimes the most practical way to navigate uncertainty is not to start at the beginning. Instead, we work backwards from the future we hope to create.

Steve Jobs captured this idea when he encouraged Apple’s teams to begin with the customer experience and work backwards to the technology. Instead of asking where to start, they first considered the future they wanted people to experience.

Many organisations begin with technology, process, or method. Apple reversed that logic, making technology a consequence of the vision rather than the starting point.

But real systems rarely unfold in neat, linear sequences. Instead, they are shaped by relationships, feedback, delays, and complexity. Every decision ripples throughout the wider system, eventually returning as new information.

For that reason, every decision must take both the past and the future into account. We anticipate possible futures while continually learning from what has already happened. This brings us back to the planning-analysis loop, where planning and learning continually inform one another.

It was this ongoing movement that gave rise to the Journeys to Value Model (JVM).

When we first introduced the JVM, we saw how systems shape our journeys to value. Yet those same journeys also reshape the system itself. Like the familiar question of the chicken and the egg, each continually influences the other.

Seen this way, the JVM also becomes a decision loop. Previous learning informs every intervention, and every intervention creates new conditions from which we continue learning. As those conditions change, so too does our understanding of risk.

Without certainty about the future, probability helps us navigate that uncertainty. In many ways, it becomes another expression of dynamic balance, continually adjusting our decisions as new information emerges.

Just as dynamic balance depends on continually responding to changing conditions, probability depends on continually updating our understanding.

We act, observe, learn, and adapt as conditions change. We may not control the future, but we can listen to the signals that emerge. Some are obvious. Others only become visible when we question our assumptions.

But understanding uncertainty also requires us to avoid one of our most persistent cognitive traps.

Resulting: Learning the Wrong Lessons

Duke describes resulting as judging the quality of a decision primarily by its outcome rather than by the thinking behind it.

Viewed through a systems lens, however, resulting becomes more than a cognitive bias. It becomes a reinforcing feedback loop.

When short-term results appear positive, we naturally assume our thinking, strategy, or intervention must have been correct. Beneath the surface, however, a reinforcing loop is quietly taking shape:

• Success reinforces confidence.

• Confidence reduces questioning.

• Reduced questioning limits learning.

Eventually, assumptions become embedded within the system itself. What began as a way of thinking gradually becomes the way the system behaves.

Success, however, can cast a shadow. Yesterday’s strengths often become tomorrow’s vulnerabilities.

Rather than continuing to question why something worked, we simply repeat the actions that produced the desired result. Behaviour becomes routine while understanding gradually fades.

It’s much like an organisation that keeps applying the same strategy because it once delivered exceptional results. The outcomes may seem convincing for a while, but without understanding why the strategy worked in the first place, adapting to changing conditions becomes increasingly difficult.

Kodak did this. So did Nokia. Blockbuster became one of the clearest examples. Each organisation continued relying on a strategy that had once delivered remarkable success. Yet as conditions changed and reality shifted, yesterday’s strengths gradually became today’s constraints.

Initially, a tweak here and an adjustment there may improve performance. Eventually, however, those same interventions begin narrowing future possibilities. Metaphorically speaking, we lift the floor while gradually lowering the ceiling.

Seen this way, judging decisions primarily by their outcomes can create resistance throughout the wider system. That’s how successful patterns harden into assumptions. Assumptions harden into paradigms. And paradigms are reinforced through the stories we tell ourselves.

“I know this strategy works because it worked before.”

The reasoning feels perfectly rational because it is grounded in genuine past success. The danger isn’t the success itself. It’s assuming tomorrow will behave like yesterday.

This mirrors the poker player whose early winning streak gradually gives way to repeated losses. Instead of questioning whether the conditions have changed, they simply blame bad luck. Their confidence rests not on their current understanding, but on yesterday’s outcomes.

The difficulty is that systems rarely reveal change immediately. What looks stable on the surface may already be shifting beneath it.

The challenge, then, is not to eliminate uncertainty, but to navigate it. That often depends on recognising where the greatest opportunities for intervention actually lie – or hang. In other words, where leverage is greatest.

Low- and High-Hanging Fruit

One way to think about leverage is through the metaphor of low- and high-hanging fruit. Some opportunities hang within easy reach. Others require us to climb.

We typically aim for the opportunities that appear within easy reach. After all, low-leverage interventions often produce immediate outcomes, short-term stability, or symptomatic relief. Simply put, they’re painkillers.

We’re also aware of the bigger opportunities hanging higher up. Reaching them, however, takes greater effort, patience, and persistence. High-leverage interventions are no painkiller, but they have the potential to create more lasting change.

The difficulty is that we cannot always tell which fruit will prove most valuable before we begin climbing. Focus only on the low-hanging fruit, and we risk treating symptoms rather than causes. Reach too high, and we risk overinvesting our time, energy, and resources.

The challenge, then, isn’t choosing low or high leverage. It’s choosing the appropriate level of leverage for the situation – recognising which opportunities genuinely deserve the climb.

Under pressure, however, we respond to uncertainty differently.

Instead of asking where the appropriate leverage lies, we naturally gravitate towards what appears easier, quicker, or more certain. We reach for the quick fix, the obvious metric, or the familiar solution. In effect, we begin solving the problem we can see rather than the one creating it.

Sometimes that’s entirely appropriate. A temporary intervention can buy valuable time, stabilise a situation, or reduce immediate harm. The problem isn’t the painkiller. It’s forgetting it was only ever meant to be temporary.

What begins as a sensible response to immediate pressure can become the strategy itself. Before long, we stop trying to change the system and start adapting ourselves to its symptoms.

Shifting the Burden

As we explore the tree’s possibilities, it’s natural to begin with the low-hanging fruit. Sometimes we’ll stretch a little higher, balancing effort against potential value. More often, however, we postpone the harder interventions until another day.

That isn’t necessarily a mistake.

In many situations, the easiest intervention is also the most appropriate one. For example, in an emergency department, a doctor may stabilise a patient before fully understanding the underlying illness. The immediate goal is not to solve the problem permanently, but to buy time.

Systems often require exactly the same kind of thinking. Short-term interventions can reduce pressure, prevent further harm, or create space to understand what is really happening. The problem begins when temporary responses gradually become permanent strategies.

Over time, our attention shifts from addressing underlying causes to continually managing symptoms.

Peter Senge describes this recurring pattern as Shifting the Burden.3 Donella Meadows calls it a Dependence Trap.4 As people repeatedly rely on symptomatic solutions, the system gradually loses its capacity to recover.

The pattern appears in countless forms.

Someone drinks because they feel unhappy. The drinking temporarily relieves the discomfort, yet gradually creates new problems that deepen the unhappiness they were trying to escape.

As Fat Bastard, played by Mike Myers in Austin Powers: The Spy Who Shagged Me, memorably puts it: “I eat because I’m unhappy, and I’m unhappy because I eat.”5

Humorous though it is, the quote captures an important systems principle. The intervention provides temporary relief while quietly reinforcing the very conditions that created the problem in the first place.

The same pattern appears far beyond addiction:

• Organisations repeatedly rely on consultants rather than strengthening internal capabilities.

• Governments postpone structural reform through continual short-term intervention.

• Managers solve problems for their teams instead of helping people develop the confidence and skills to solve them independently.

But none of these interventions is inherently wrong. Just as emergency treatment may save a patient’s life, short-term solutions often play an essential role within healthy systems. The danger begins when symptom relief replaces structural learning.

As Meadows warns, “The trouble is that the states created by interventions don’t last.”

In other words, the temporary conditions created by an intervention eventually fade. Over time, consultants leave, temporary funding comes to an end, and managers have less time to coach their teams. The intervention disappears, but the underlying capability has never been strengthened.

Ultimately, the problems return because neither people nor the system have adapted. Dependence has grown while resilience has declined.

The danger doesn’t end there. Eventually, people begin adjusting their expectations to match the system’s declining performance.

Eroding Goals

Senge identifies this subtle shift as Eroding Goals.

Whenever a gap emerges between where we are and where we want to be, we face two choices. We can either work to close the gap or gradually lower the goal. One seeks to improve reality, while the other redefines success.

George Orwell captured this beautifully in Nineteen Eighty-Four. One day, chocolate rations are reduced from thirty grams to twenty. The following day, the government proudly announces that chocolate rations have been “raised” to twenty grams.6

Nothing improved. Only the story changed.

You can see a similar pattern during Prime Minister’s Questions in the UK. The Opposition challenges the government’s record. The Prime Minister responds by pointing to the previous government’s performance instead. Rather than asking whether today’s situation is good enough, the debate often becomes about who performed worse than the other.

It’s a familiar pattern. One government lowers the floor. The next raises it only slightly, but presents it as meaningful progress. The benchmark shifts, yet the underlying problem often remains. In other words, the story changes more than the system.

That leaves ordinary people watching from their living rooms, cup of tea in hand, wondering: “Are we actually better off?”

This is what makes goal erosion so deceptive. Systems rarely drift because people stop caring. More often, people gradually adjust their expectations to match deteriorating conditions. What once felt unacceptable slowly becomes normal.

Perhaps this helps explain why different generations often disagree about standards of work, manufacturing quality, or public services. Each generation inherits a slightly different version of what “normal” looks like.

Both Shifting the Burden and Eroding Goals reveal the same underlying lesson. When people repeatedly favour short-term adaptation over long-term learning, systems gradually lose their capacity to correct themselves.

The challenge, therefore, is not to avoid temporary interventions altogether. Rather, it is to ensure they remain temporary.

As Meadows suggests, escaping the trap begins by strengthening the system’s own ability to carry its burdens once again. Rather than asking only how to relieve immediate symptoms, we might ask deeper questions:

• Why do people stop learning from feedback?

• What obstacles prevent them from adapting?

• How can people become better at recovering without continual intervention?

When people learn, they make better interventions. And when those interventions address the underlying conditions, the system gradually becomes more capable of sustaining itself.

More often than not, the people closest to the problem already hold many of the answers. Listening to their experiences often reveals not only what is broken, but also the signals the system has been generating all along.

Expressing Uncertainty

Recognising those signals, however, is only part of the challenge. Acting on them often requires people to question assumptions, admit uncertainty, and explore alternatives together. That is usually far more difficult than applying another quick fix.

Effective decision-making, therefore, depends on something surprisingly human: creating the conditions in which people feel safe enough to say, “I don’t know.”

Duke describes this as expressing uncertainty. Rather than presenting opinions as certainty, people openly acknowledge probabilities, assumptions, and alternative possibilities. The goal is no longer to appear certain, but to increase clarity over time.

This shifts decision-making away from seeking validation and towards seeking understanding. Instead of defending positions, people coordinate around discovering what is true.

Thinking about it this way brings us back to one of the simplest, yet most overlooked, forms of systems learning: listening.

Most people don’t raise concerns to be difficult or obstructive. More often, they want their experiences to be recognised and the problems they see to be taken seriously. Equally, many remain silent because they fear criticism, judgement, or the consequences of being wrong.

This is where psychological safety becomes essential.

When people feel able to question assumptions without embarrassment or retaliation, uncertainty becomes something to explore rather than something to hide.

Of course, psychological safety alone doesn’t erase our past experiences. As previous failures become part of our mental model, we naturally begin interpreting present uncertainty through the lens of past disappointments.

A football supporter may struggle to believe their team can succeed after years of heartbreak. Someone at work may remain silent out of fear of being wrong or of lacking authority. Sometimes those memories provide valuable warning signs. At other times, they encourage us to interpret a new situation as though it were the old one.

Disagreement, then, stops being a threat and instead becomes another source of learning.

Earlier, we explored the importance of boundary work in creating shared understanding across teams, organisations, and disciplines. Psychological safety provides the conditions that make those conversations possible. Without it, people protect certainty. With it, they begin exploring uncertainty together.

But exploring uncertainty together doesn’t mean everyone has to agree. The result isn’t agreement; it’s a shared understanding.

Daniel Coyle describes a similar pattern in The Culture Code through the idea of concordance. As trust, listening, and vulnerability increase, people gradually begin operating on the same wavelength. They don’t necessarily think alike, but they become better at understanding one another.7

Vulnerability, then, becomes another way of expressing uncertainty. It emerges whenever people openly acknowledge limitations, mistakes, incomplete understanding, or simply the possibility that they may be wrong.

Paradoxically, this kind of openness often strengthens coordination rather than weakening it. Transparency builds trust, encourages honest contribution, and invites others to lower their own defences. Rather than pretending that uncertainty doesn’t exist, people begin to navigate it together.

Navigation as Intervention

Shackleton’s greatest achievement wasn’t simply bringing his crew home safely. It was recognising that the journey itself had changed. Rather than forcing reality to fit the original plan, he continually adapted his decisions to the conditions unfolding around him.

Perhaps that’s what navigation really means.

Expressing uncertainty and embracing vulnerability strengthen both coordination and decision-making. Together, they create the conditions for people to move beyond immediate problems, superficial success, and familiar assumptions. Only then can they better understand what is happening across the wider system.

Perhaps this is how dynamic balance is sustained.

Balance, then, is not something we engineer through rigid control or perfect prediction. It emerges through continually understanding and responding to systems that never stop moving.

Within this environment, decision-making takes on a different meaning. We prioritise understanding the system over being correct. That’s why navigation becomes a form of intervention in its own right. Like Shackleton, we don’t overcome uncertainty by forcing our way through it. We navigate it by responding to the conditions as they unfold.

But responding also reminds us of something important: systems shape our choices, yet they don’t make them for us.

Systems provide the conditions within which change becomes possible. They influence behaviour, create opportunities, establish constraints, and shape the feedback we receive. Yet systems do not move on their own.

People do.

Understanding how systems behave is only half the story. We must also understand how people move within them.

Something to think about: Where in your work or everyday life might balance be quietly drifting? What signals suggest it’s time to adapt rather than push harder?

Feel free to share your thoughts in the comments 👇

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Perhaps Man vs Bee is one of the closest portrayals of overcorrection. Trevor, played by Rowan Atkinson (yes, that’s Mr Bean), takes his annoyance to absurd – and cringeworthy – extremes. What begins as an attempt to remove an unwanted bee gradually spirals into chaos.1

Over time, the conflict escalates, ending in property destruction and arson. Small corrections were supposed to cover up the house sitter’s mistakes, yet each intervention landed him in even bigger trouble.

We all exhibit characteristics of Trevor. In many cases, we believe we are solving a problem right in front of us. Yet, each solution often creates new problems, demanding further corrections.

Organisations, institutions, and even societies can behave in remarkably similar ways. Eventually, attempts to solve one problem can create new problems elsewhere.

The problem is, one small correction can escalate into something extremely costly. The challenge then is to understand where and how to intervene before our attempts to restore balance create new forms of instability.

Simply put, we need to be less Trevor and more aware of the surrounding conditions and possible futures.

Finding the Goldilocks Zone

Trevor’s interventions always led to chaos. While he had no intention of destroying a multi-million-pound smart home, he was unaware of how each correction impacted the wider system.

The same applies to the basic balancing mechanisms in everyday things. When using a shower, we gradually adjust the temperature to maintain an ideal setting: neither too cold nor too warm. It’s a workable equilibrium that’s often referred to as a Goldilocks zone.

Workable equilibrium operates within certain thresholds. Yet, they never remain stable forever. At some point, the temperature fluctuates because someone inconveniently uses the hot water elsewhere. So, what does one do? Turn the tap to increase the heat.

As you struggle to rediscover the Goldilocks shower zone, something elsewhere in the system is distorting your perception. Once the mischievous intervention ceases, your correction then results in a scalding overcorrection.

Interventions can also create resistance elsewhere. Someone rushing to use the hot water in another room may have no idea they’re disrupting your shower. Yet local actions often create consequences beyond their immediate boundaries. Organisations behave in much the same way.

As we’ve seen with leverage points, interventions can be as small as adjusting a number or turning a tap, or as significant as transcending a paradigm. Yet their consequences often become visible only much later.

Some interventions produce long-term, life-saving benefits. Seatbelt laws gradually reduced road fatalities. Smoking restrictions eventually protected public health. Wastewater treatment regulations slowly reduced pollution and improved environmental quality.

These interventions were clearly worth the risk. However, not all corrections work out as we expect – something Trevor would confirm.

The Paradox of Overcorrection

Balance can drift into overcorrection. What begins as an adaptive response may gradually become maladaptive. Adjusting or removing one part of a system may initially appear beneficial, only for behaviours and pressures to become displaced elsewhere.

Teams, organisations, and institutions often overcorrect, creating new forms of imbalance in the process. But these overcorrections are rarely deliberate. More often, they emerge through delayed consequences.

For example:

• A team might react to a failed product launch by adding more layers of approval. Yet over time, these changes hinder innovation.

• A recruitment initiative might focus so heavily on one imbalance that other forms of diversity become neglected.

• An institution might tighten safeguarding procedures so extensively that trust and personal responsibility gradually weaken.

In each case, the original intention remains understandable. Yet correcting one imbalance can unintentionally create another. The search for balance can sometimes become a source of imbalance itself.

Sometimes, however, overcorrections emerge from attempts to preserve the paradigms and belief systems that people hold. In many ways, this pattern is most clearly revealed through efforts to centralise control.

Throughout history, excessive censorship, taxation, and bureaucratic controls have often provoked resistance, rejection, and, at times, rebellion. Perhaps the French have best demonstrated this pattern, having undergone multiple revolutions.

In many ways, overcorrection can create the very behaviours it seeks to suppress. Rather than restoring balance, interventions can unintentionally generate new forms of instability.

Take social media platforms, for example. In response to misinformation, abuse, or harmful content, moderation policies often become stricter. While these interventions aim to protect users, excessive moderation can create new tensions around trust, censorship, and freedom of expression.

Equilibrium, therefore, exists only within certain limits. As interventions create new forms of resistance, balance must evolve with changing conditions. It must remain dynamic.

From Linear to Dynamic Balance

Peter Senge described dynamic complexity as situations where cause and effect are delayed or difficult to observe.2 Dynamic balance works in much the same way. Rather than a fixed state, balance must continually adapt to changing conditions.

This means balance is not something we achieve once and preserve forever. After all, as conditions change, so do the forces that support or resist growth.

When resisting forces emerge, we need to understand how they slow growth. Only then can we better recognise which forms of leverage are becoming more or less effective over time.

Changing numbers, structures, or goals then become more relevant to the world we’re navigating. Product teams can build more confidently around actual or emerging needs. Governments can adapt policies to changing social and economic pressures. And organisations can strengthen talent pipelines before skills shortages begin to constrain growth.

Crucially, this approach often requires stepping back to recognise changing conditions. After all, a wider perspective reveals pressures, relationships, and patterns that are easy to miss when we’re too close to the problem.

That way, we avoid resorting to quick fixes or redesigning everything from the ground up. Instead, we spend more time understanding the wider environment surrounding the problem and how different parts of the system influence one another.

Seeing the wider landscape changes the questions we ask. Why are talent pipelines weakening? Why are funding priorities shifting? Why is trust beginning to erode? Answers to these questions can reveal the wider pressures constraining growth.

Of course, none of this guarantees success. It does, however, reflect a dynamic balancing mindset. Such a perspective continually adapts to changing conditions instead of treating any framework, philosophy, or source of value as absolute truth.

Yet dynamic balance becomes much harder when our ways of thinking become fixed. Whatever framework we adopt, we should avoid treating it as a permanent paradigm. Otherwise, it risks becoming deeply embedded within organisational or societal culture.

Whatever we change, balance, and repeat today can eventually become tomorrow’s normal. Over time, even the mechanisms designed to maintain balance can become barriers to adaptation.

Fortunately, systems rarely keep these tensions hidden forever. Feedback often leaves clues.

Reading the Signals

Seen this way, the diagnostic system signals we explored earlier become even more relevant. Through feedback, behaviours such as Path Fixation, Value Mirage, and Story Gap reveal where assumptions, values, or meanings may be drifting.

Some common signals include:

• Teams repeat the same patterns despite little meaningful progress.

• Rising frustration, fatigue, and changing behaviours amongst staff under pressure.

• Leaders protect decisions rather than question assumptions.

Ultimately, organisations reveal deeper patterns through how they respond to pressure and change, not through what they say. A leader might present an inspiring vision, but what people experience day to day often tells a different story.

Rising frustration, defensive behaviour, and repeated patterns often point to a deeper issue. They suggest that local corrections are no longer aligned with wider conditions.

In many cases, teams genuinely believe they are optimising their way to success. Leadership often celebrates visible metrics and outcomes, but the underlying diagnostic signals reveal tensions that those measures fail to capture. Without recognising these signals, organisations can gradually drift into optimisation traps.

Value Mirage reveals when teams become overly invested in familiar measures of success.

Path Fixation reveals an increasing commitment to rigid paths or visions that people no longer truly believe in.

Story Gap reveals how those decisions become justified, even when little evidence or alternative perspectives are considered.

Understanding these tensions, therefore, requires more than isolated fixes. It requires coordination across the wider system.

Corrections then become less about defending paradigms and more about understanding behaviour and culture. In this sense, our journeys to value become ongoing processes of learning and adaptation.

Over time, those behaviours shape culture itself. Healthy cultures behave less like machines to be fixed and more like living environments. They continually learn, coordinate, and adapt to changing conditions.

In many ways, balance is not about perfection. It is about maintaining movement within a world that is always changing.

Movement is one thing. Moving together is another.

Staying in Sync

If stability is temporary and adaptive, coherence depends on continual coordination around shared goals, meaning, and movement. After all, no wider system remains coherent when its subsystems respond only to their own local pressures, needs, or objectives.

Coordinating many parts of a system is a little like leading a group on a long journey. Different people have different needs, priorities, and perspectives. Yet everyone still needs to keep moving in the same direction. Coordination, therefore, becomes less about control and more about helping people move together.

Yet attempts to improve coordination can also create new forms of imbalance. When people overreact to perceived problems, interventions may overcompensate, unintentionally creating new distortions elsewhere.

Just imagine oversteering a vehicle on an icy road. Your efforts to regain control cause the car to spin further, creating greater instability. The harder you fight it, the further you drift from balance.

Dynamic balance is not simply about correcting movement. It also means understanding how much change a system can absorb before it pushes back. When driving in winter conditions, we constantly judge the surface beneath us and adjust our movement accordingly.

But systems rarely absorb change in isolation. Dynamic balance depends on shared awareness and coordination. Just as drivers remain aware of the road, the surface, and the traffic around them, people within subsystems rely on healthy relationships to maintain wider coherence.

Coherence Through Wider Systems Awareness

No single person, team, capability, or process produces success independently. Rather, performance emerges through many specialised capabilities converging around a common purpose.

In many ways, this reflects atomic innovation: progress that emerges through coordinated relationships among interconnected parts. The real test comes when those relationships begin to weaken. British Cycling offers an interesting example.

When British Cycling’s wider support structure weakened, its marginal gains philosophy became increasingly difficult to sustain.

A common misconception is that marginal gains alone were responsible for British Cycling’s success. In reality, they depended on a much wider support structure.

Over time, grassroots racing became increasingly underfunded. Institutional pressures grew, and development pathways weakened. Together, these changes eroded the talent and resources supporting elite performance. In effect, marginal gains lost its scaffolding.3

While British Cycling remains highly successful, it no longer appears to enjoy the same dominance it once did. Over time, fragmentation within the wider system gradually made sustained success harder to maintain.

Reducing fragmentation requires coordination across the wider system. In British Cycling’s case, grassroots development, coaching, governing institutions, funding, and elite performance all needed to remain aligned around shared goals and standards.

Doing so helps balance local needs with wider system coherence. Otherwise, individual subsystems may shift burdens elsewhere or become anchors that slow the wider system’s movement.

The same principle applies elsewhere. Families, project teams, hospitals, businesses, and governments all face similar tensions. In each context, different people and groups naturally focus on different priorities.

These tensions are much like members of a rowing crew pulling with slightly different rhythms. Left unchecked, the boat begins to drift.

Continual communication and coordination help keep everyone moving in the same direction. Shared goals, values, and meaning provide the rhythm that reduces fragmentation and systemic drift over time.

When Coordination Breaks Down

However, not every person, team, department, or institution remains receptive to coordination. That’s largely because of the boundaries they operate within. By boundaries, I mean the groups, disciplines, and organisations that shape how people think, work, and collaborate.

Some boundaries remain open, making collaboration and adaptation easier. In contrast, others become harder to cross as incentives, pressures, and power structures take hold. This helps explain why coordination often becomes more difficult in larger organisations.

Sometimes people genuinely pull together around a shared purpose. At other times, they simply go along with decisions because local priorities, incentives, or power structures make alternative paths more difficult.

This is often described as organisational politics. Yet politics is not always about manipulation or hidden agendas. More often, it reflects people trying to balance competing goals, priorities, relationships, and influence while keeping the wider system moving.

Dissent, therefore, may appear disruptive because it challenges the direction the wider group is attempting to reinforce. Just imagine half the rowing crew refusing to follow the same rhythm.

Progress then becomes less about rowing harder and more about restoring coordination. This is where innovation heroes play their most important role.

Innovation Heroes and Systems Convening

Restoring coordination rarely happens by accident. It often depends on people who can reconnect fragmented parts of a team, organisation, or wider system.

This is where innovation heroes – Pathfinders, Sensemakers, and Translators become especially important.

Some naturally navigate boundaries, relationships, and organisational politics. Others help different groups understand one another, reconnect shared meaning, or identify opportunities that might otherwise remain hidden.

Pathfinders explore the wider terrain. They move between boundaries to identify changing conditions, overlooked relationships, or new opportunities. They tend to ask, “What are we missing?” or “Where else should we be looking?”

Sensemakers help different groups interpret one another across a complex environment. They ask, “What does this mean?” or “How do these perspectives fit together?”

Translators become influential through communication. They bring clarity, reconnecting language, meaning, and understanding across different boundaries. Their questions are, “How do we explain this?” and “How do we help others understand?”

Together, these roles help convene the wider system. Over time, they strengthen coordination, adaptability, and coherence. Yet coherence does not always eliminate uncertainty.

If you're unfamiliar with these roles, you can learn more about them in my earlier post, "Innovation Heroes." Crucially, these roles are not defined by skill, job title, or rank. They are human traits that can emerge in any of us

Balance Is a Moving Target

Conditions continue to change, feedback remains imperfect, and every intervention carries consequences that cannot be fully predicted.

Balance itself is a moving target.

Unfortunately, Trevor learned the hard way that trying too hard to restore order can create even greater disorder.

This raises another challenge. If outcomes are uncertain, how do we decide which risks are worth taking? And why do systems often shift burdens elsewhere rather than confront difficult trade-offs directly?

Something to think about: where in your work or everyday life might balance be quietly drifting? What clues are telling you it’s time to adapt rather than push harder?

Feel free to share your thoughts in the comments 👇

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It’s no secret that in 2000, Netflix founder Reed Hastings reportedly offered to sell his company to Blockbuster. He asked for around $50 million. Blockbuster declined.1

At the time, $50 million probably seemed like an eye-watering amount. In retrospect, it was quite the bargain.

That said, Blockbuster’s decision likely seemed perfectly reasonable. After all, the company dominated the market. Thousands of stores, millions of customers, and a business model that had delivered years of success hardly suggested a company under threat.

Yet while Blockbuster focused on reinforcing what had worked before, the wider landscape quietly changed. As streaming emerged and consumer habits evolved, the strengths that had once made Blockbuster successful gradually became vulnerabilities.

Perhaps this is the shadow of success.

We all know how the story ends. There’s probably a documentary about it on, you know, that popular streaming platform, Netflix.

When Success Casts a Shadow

A familiar innovation story often begins in a normal garage in an ordinary suburb. Experimentation is rapid, customers respond positively, and before long, investors arrive with promises of growth. Teams expand, budgets increase, and the company establishes itself as a market leader.

Then one day, growth begins to slow.

Investors grow restless. Teams release more features, increase production, and accelerate optimisation. Competitors become the benchmark, while research and deeper understanding gradually lose influence. Surely whatever everyone else is doing must hold the answer.

At first, the interventions appear to work. Momentum returns and confidence rises. Yet over time, products become bloated, customer complaints increase, and morale declines. Under mounting pressure and diminishing returns, layoffs follow, and leadership eventually changes.

Meanwhile, competitors once dismissed as minor threats have quietly moved ahead.

In many ways, the story resembles the tortoise and the hare. Early success reinforces confidence, and confidence reinforces familiar patterns. When growth slows, organisations often respond by doubling down on what worked before.

Yet all the while, the wider landscape continues adapting, much like the tortoise that quietly and steadily won the race. The deeper lesson is that the very forms of leverage that once accelerated growth can gradually begin creating resistance elsewhere.

Systems thinkers often describe this pattern as escalation. Success reinforces familiar behaviours, which in turn create new pressures and unintended consequences elsewhere.

What once appeared to be a strength gradually casts a longer shadow.

Seen this way, escalation becomes a long-term outcome of reinforcing success. People gradually stop reassessing the conditions that made that success possible in the first place. As familiar patterns recur, new pressures and vulnerabilities quietly build elsewhere, creating blind spots that become increasingly difficult to see.

Customers move on, competitors adapt, and the conditions that supported success begin to weaken. However, attention often remains focused on restoring previous forms of success instead of understanding how the wider landscape has changed.

Success can gradually create complacency, rigidity, or overconfidence in familiar ways of thinking. Many organisations have thrived through approaches such as Lean Manufacturing, MVP thinking, or marginal gains. Yet, competitors adapt, customers change, and conditions shift, making yesterday’s advantages harder to sustain.

Over time, pressures that once seemed distant become harder to ignore. As competitors adapt and limits are tested, unintended outcomes emerge. The momentum that once drove success begins to slow, and strengths reveal new vulnerabilities, often in places that initially seemed unrelated.

This is where interconnectedness becomes essential.

Escalation Through Interconnectedness

Since systems rarely operate independently, isolated interventions rarely work – at least not indefinitely.

A change in one part of a wider environment influences another, sooner or later. As the Poached Egg model suggests, everything is connected through relationships, dependencies, and feedback across multiple layers.2

Over time, these interactions compound and intensify. Much like a tornado gathering strength, systems can escalate through interconnectedness.

Therefore, improving one part of a system is rarely straightforward. In many ways, it’s like a family decorating a house.

One person paints the walls, another sands the skirting boards. Then the dog runs through the wet paint, and a child leans against the freshly finished wall. Nobody means to cause problems – everyone is trying to help. Yet each action creates new conditions for everyone else.

Systems behave in much the same way. As we reinforce one process, counteracting forces may arise that hinder, slow, redirect, or compromise progress. Nobody expected the dog to race through the room.

Often, the challenge is not overcoming a single obstacle, but recognising how multiple people, goals, and interventions continually influence one another. Systems thinker Peter Senge captures this pattern through the Limits to Growth archetype.3

Early reinforcing processes – from optimisation to word-of-mouth recommendations – often accelerate success. In effect, what appears to be a winning formula creates the impression that growth can continue indefinitely.

Yet systems rarely stand still. Competitors adapt, resources become constrained, and unintended consequences emerge. Like the hare racing ahead while the tortoise patiently maintains its pace, what once accelerated progress gradually encounters resistance.

Growth slows not because effort disappears, but because other forces begin to influence the journey.

When Growth Meets Resistance

British Cycling and Team Sky strongly mirror this dynamic. From Beijing to Rio, Team GB dominated Olympic cycling. Around the same time, Team Sky achieved similar success in elite road racing, winning multiple Tour de France titles.

Looking at their success as a line graph, the trajectory resembles a rocket launching upwards. But eventually, the curve levels off. As competitors adopted similar approaches, the same optimisation strategies that once conferred a major advantage began to produce diminishing returns.

The marginal gains philosophy, of course, did not suddenly stop working. Rather, the wider landscape adapted around it. In many ways, British Cycling and Team Sky became vulnerable to the very success patterns they had helped create.4

This is where Senge’s archetype becomes especially relevant. The harder people push to reinforce growth, the more pressure gradually emerges elsewhere.

As Senge observes in The Fifth Discipline: “... the more successful the changes become, the more threatening they can also become, and those threatened begin to undermine the change implementation.

In other words, people often double down on what previously worked. Yet the more familiar patterns are reinforced, the harder it becomes to reinterpret changing conditions and adapt accordingly.

Thinking about change this way, why does progress often become so difficult?

When Leverage Encounters Resistance

This line of thinking brings us to compression as a behavioural force. Simply put, under pressure, individual, organisational, and institutional perspectives narrow around familiar ways of thinking.

These compressed mental models reinforce existing patterns. Meanwhile, people find themselves repeating familiar ways of thinking while expecting different outcomes.

Over time, these patterns can become deeply embedded. The assumptions and ways of thinking that once brought success gradually become accepted as “the way things work.”

The marginal gains philosophy, of course, remained valuable. Yet the wider conditions supporting it gradually changed. While British Cycling and Team Sky continued refining performance at elite levels, important foundations elsewhere were beginning to weaken.

Over time, grassroots participation declined, funding pressures increased, sponsorship became less certain, and development pathways weakened. In retrospect, marginal gains were never simply an optimisation philosophy. Their success depended upon a much wider ecosystem of talent, coaching, institutions, and competition.

As that ecosystem weakened, the conditions that had once sustained British Cycling’s success gradually eroded.

From Virtuous to Vicious

Seen this way, virtuous cycles can slowly evolve into vicious cycles as the wider system drifts. Conditions change, competing pressures intensify, and coordination fragments.

This collapse, however, rarely happens overnight. More often, it unfolds gradually – one compromise, one funding decision, one race, and one Olympic cycle at a time.

Senge draws a parallel with Boxer, the loyal workhorse in Animal Farm, whose answer to every setback is simple: “I will work harder.” Yet effort alone cannot sustain success indefinitely.

Over time, even successful forms of leverage can encounter resistance. Simply working harder produces diminishing returns. The lesson is that leverage depends on the health, adaptability, and interconnectedness of the conditions that support it.

It’s much like trying to force a horse to run faster while ignoring the quality of its feed, the condition of the track, and the strain already placed upon its body. Eventually, more pressure no longer produces more speed.

Perhaps the deeper challenge is not the system itself, but how people come to understand, justify, and reinforce the patterns operating within it.

Something to think about: where might the shadow of success be appearing in your own work, organisation, or everyday life? What familiar patterns are you reinforcing – and what changing conditions might you be overlooking?

Feel free to share your thoughts in the comments 👇

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Mr Goodkat sits opposite a young Nick Fisher in a bus station waiting room. Rows of bright blue plastic seats stretch into the distance beneath harsh fluorescent lights. The atmosphere feels oddly quiet and ordinary as he calmly explains the workings of a confidence trick.

Introducing himself simply as Mr Smith, his voice remains quiet yet certain.

“The reason I’m in town, in case you’re wondering, is because of a Kansas City Shuffle,” he explains.

Confused, Fisher asks, “What’s a Kansas City Shuffle?”

“A Kansas City Shuffle is when everybody looks right, you go left,” Goodkat replies.

After telling Fisher a story about a horse race, he asks him to look to the right. Fisher does. Then he turns to the left.

Goodkat has vanished.

Then snap goes his neck.

The trick wasn’t merely explained. It had just been performed.

That scene comes from the film Lucky Number Slevin.1 Throughout the film, Mr Goodkat, played by Bruce Willis, uses the Kansas City Shuffle to keep both the audience and the characters focused on one story while another quietly unfolds.

In many ways, life works the same way. People often look exactly where they expect to find the answer. Their confidence becomes part of the deception. While attention follows the obvious story, slower changes unfold somewhere else.

The Kansas City Shuffle

The Kansas City Shuffle2 emerged from the world of gamblers and confidence men. The mark (victim) believes they understand what’s happening. Their attention follows the obvious move. All the while, the real action unfolds elsewhere. In effect, the mark deceives itself.

Perhaps the deeper lesson is that we all carry paradigms – assumptions about how the world works. These shared ways of seeing shape how we interpret problems, define success, and recognise what we believe to be true.

The stronger these shared frameworks become, the easier it becomes to overlook slower changes unfolding beneath the surface.

Thomas Kuhn showed how paradigms change in his work on scientific revolutions.3 But not all change arrives suddenly. Sometimes paradigms drift quietly long before dramatic shifts become visible.

Everybody Looks Right

We encounter paradigm drift all the time.

A political party gradually drifts from one set of priorities to another. “They used to represent working people.” Some might say.

A brand shifts from prioritising product quality towards production efficiency. “They don’t build washing machines like they used to.”

An organisation slowly moves away from flexible working and increases office attendance. “Things have changed around here.”

As paradigms drift, assumptions harden, habits form, and familiar ways of thinking become harder to question.

The problem is not necessarily that people look in the wrong direction. Rather, they often look exactly where they expect to find the answer. The more certain people become about what they believe to be true, the easier it becomes to overlook the slower changes unfolding elsewhere.

But paradigm drift not only occurs through reinforcing existing beliefs. It also emerges through reaction. In trying to escape one paradigm, people sometimes drift into another.

From One Paradigm to Another

Consider the growing backlash against startup hustle culture and the optimisation movement.4

For many, relentless self-improvement, productivity obsession, biohacking, and the pursuit of ever-greater efficiency became excessive. As a result, people increasingly associated them with burnout, pseudoscience, unrealistic expectations, and unhealthy lifestyles.

Yet in rejecting these excesses, some have also begun rejecting optimisation itself. In trying to avoid one paradigm, people risk drifting into another.

This is one of the subtler ways paradigms evolve. What was once celebrated becomes ridiculed. What was once considered virtuous becomes viewed with suspicion. Everybody focuses on the visible failures while the underlying shift quietly unfolds somewhere else.

In this sense, paradigm drift resembles a Kansas City Shuffle.

Everybody looks right, and we go left.

Drift Happens Quietly

Paradigm drift rarely happens suddenly, whether through reinforcement or reaction. Similar to escalation – or the snowball effect – it typically unfolds slowly and quietly.

People gradually shift how they interpret the world around them. Familiar assumptions become reinforced as confidence grows. Success patterns harden into habits, and behaviour becomes encoded in identity.

All the while, the underlying conditions continue to change. Over time, paradigms drift out of balance, making them increasingly difficult to reinterpret, challenge, or adapt.

That’s how political parties drift from one set of values to another. Brands drift away from what once made them distinctive. And organisations gradually adopt ways of working that would have once seemed unfamiliar.

What begins as a small shift in interpretation can gradually compound into something much larger.

Because this drift happens so easily yet quietly, we need a way to recognise it before it becomes reinforced.

Diagnostic System Signals

Paradigm drift does not happen by chance. It emerges through three recurring human behaviours:

• Path Fixation is the tendency to become locked into a direction.

• Value Mirage is the tendency to mistake signals for value.

• Story Gap is the tendency for narratives – the stories people tell to make sense of the world – to protect assumptions rather than help people learn.

As we’ve explored throughout Journeys to Value so far, these behaviours are inherent in any social organisation – from business to politics. They quietly reinforce themselves, gradually shaping how people interpret problems, define success, and respond to change.

Over time, these behaviours influence how the wider system learns, adapts, and evolves. Left unchecked, they become increasingly difficult to question and correct.

Yet these behaviours can serve another purpose. They function like indicators on a living dashboard.

Rather than measuring performance alone, they reveal where learning, interpretation, and coordination may be drifting out of balance. In effect, they become diagnostic system signals.

Path Fixation becomes a signal for increasing rigidity around a direction or paradigm. “We’ve always done it this way.”

Value Mirage becomes a signal that metrics, optimisation patterns, or other signals are being mistaken for genuine value. “The numbers look good, so we must be succeeding.”

Story Gap becomes a signal that narratives have stopped helping people learn and have instead begun protecting assumptions, identity, or existing paradigms. “Anyone who disagrees just doesn’t understand.”

In many ways, the dashboard performs a kind of Kansas City Shuffle. It redirects our attention away from the obvious and towards the slower changes unfolding elsewhere.

With that thought in mind, we must reconsider the marginal gains story.

Marginal Gains Under Scrutiny

Previously, we explored the aggregation of marginal gains as a systems leverage story. Initially adopted by Sir Dave Brailsford and British Cycling, the philosophy sought to optimise performance through countless small improvements.5

Over time, repeated success reinforced the approach. What began as a framework for continuous improvement gradually evolved into a dominant paradigm.

When Success Becomes a Paradigm

Interestingly, the more successful the paradigm became, the harder it was to question, almost reflecting Path Fixation. If British Cycling and Team Sky became so dominant, how could anyone challenge marginal gains as an effective framework?

But over time, the philosophy became less of a unique leverage point as the wider cycling landscape adapted. Sports science diffused globally, and the competitive gap gradually narrowed.

As cycling nations adapted and, at times, outperformed British Cycling and Team Sky, critics began to suggest that marginal gains had plateaued.

That’s not to say the philosophy stopped working. But as conditions changed, sustained success made it increasingly difficult to recognise when British Cycling and Team Sky needed to reassess the wider system.

The marginal gains story also became culturally powerful. Success was often explained through optimisation stories about pillows, mattresses, handwashing, nutrition, and countless tiny optimisations.

Yet critics argued that the narrative sometimes overshadowed other important factors. Funding advantages, recruitment, and organisational resources also played important roles within the wider system.

Seen this way, marginal gains risked becoming mistaken for the complete source of value itself, mirroring another behaviour: Value Mirage.

As scrutiny intensified, story gaps also emerged. For years, narratives of scientific precision, clean performance, and ethical innovation remained central to Team Sky’s identity.

Yet doping controversies exposed tensions between those narratives and the realities of the wider system. In turn, critics began questioning whether scientific precision and marginal gains alone could fully explain Team Sky’s success.

When Strength Becomes Vulnerability

British Cycling and Team Sky reveal something important about leverage points. As a philosophy becomes increasingly successful, its underlying paradigm becomes more entrenched. When everyone lives and breathes it as a belief system, it becomes progressively harder to question.

My heart sank when I watched Team GB gradually drop down the medals table. I was equally surprised to see Team Sky become less competitive. But this systems view helps me understand why.

Innovation cannot always depend on one framework, philosophy, or source of value.

Ultimately, British Cycling and Team Sky were the victims of a cruel Kansas City Shuffle. They kept looking in the same direction, believing value still lay there. Their strength gradually became their vulnerability.

Thinking about the marginal gains story this way, Path Fixation, Value Mirage, and Story Gap are not simply problems to eliminate, but signals to interpret. Like indicators on a dashboard, they help reveal where paradigms are drifting.

Leveraging the Signals

If Path Fixation, Value Mirage, and Story Gap function as diagnostic signals, the next question becomes how to use them.

This is where applying a systems lens becomes essential. Rather than treating these behaviours as problems to eliminate, we can use them as clues to where learning, interpretation, coordination, or leverage itself has begun to drift out of balance.

Let’s unpack how each behaviour can be leveraged as a diagnostic system signal.

Diagnostic Signal One: Path Fixation

We can identify when Path Fixation is being reinforced by observing strategies that centre on past success. An excessive focus on familiar patterns or immediate outcomes often reveals a deeper issue. It signals that a dominant paradigm has become increasingly entrenched.

Narrow awareness is another Path Fixation trait. Limited understanding of changing contexts, emerging threats, or alternative opportunities is one of the many symptoms of lock-in.

Nokia’s dominance in mobile phones, for example, likely made it increasingly difficult to adapt to the smartphone era. As familiar patterns became reinforced, adaptive thinking, learning, and diverse perspectives gradually gave way to preserving existing success.

To leverage Path Fixation as a diagnostic signal, we can:

• See the wider landscape.

• Engage different perspectives.

• Question dominant assumptions.

In many ways, these interventions resemble a particular innovation archetype I call a Pathfinder. Rather than remaining trapped within a single route or dominant interpretation, Pathfinders continually scan the landscape for changing conditions and alternative paths.

Diagnostic Signal Two: Value Mirage

We can identify the emerging signals of Value Mirage happening when people begin chasing narrow, misleading, or incomplete measures of success.

Metrics such as NPS, productivity, engagement, or growth provide useful signals. Problems arise when those signals gradually become mistaken for value itself.

For example, organisations that reward call centre staff primarily on handling times may improve efficiency metrics. Yet over time, this incentive can quietly degrade customer experience and trust.

To leverage Value Mirage as a diagnostic signal, we can:

• Reframe what is being measured.

• Think systemically.

• Look beyond single metrics.

These interventions reflect the Sensemaker archetype. Rather than accepting signals at face value, Sensemakers interpret relationships, context, and meaning to better understand what genuinely creates value.

Diagnostic Signal Three: Story Gap

We can often see the first signs of a Story Gap widening through fragmented narratives, conflicting interpretations, or messaging that confuses, excludes, or misleads.

Story gaps often emerge when organisations contradict their own values or culture. Increasing bureaucracy, burnout, or declining trust are often telling signs. Over time, organisations, institutions, or movements begin losing shared understanding, trust, and collective alignment.

To leverage Story Gap as a diagnostic signal, we can:

• Look for missing connections.

• Engage conflicting perspectives.

• Reconnect the broader narrative.

These interventions reflect the role of the Translator archetype. Translators bridge perspectives and reconnect meaning across boundaries, helping people understand how their stories relate to the wider context.

Leverage Emerges Through Recognising Signals

The three behaviours – Path Fixation, Value Mirage, and Story Gap – are not merely problems to solve, but signals to interpret. They reveal where learning, adaptation, and recalibration are most needed.

And perhaps that is the deeper lesson behind the Kansas City Shuffle.

In that sense, the three behaviours help us recognise when everybody looks right.

And we go left.

The challenge, therefore, is not simply recognising the signals, but knowing when to intervene before familiar patterns reinforce themselves and paradigms drift even further.

This story is far from over.

Next, we’ll explore what happens when these patterns reinforce themselves, how systems drift out of dynamic balance, and why small shifts can eventually escalate into consequences far larger than we intended.

Something to think about: What assumptions shape how you interpret success, value, and progress? And where might familiar patterns, metrics, or stories be quietly reinforcing those assumptions? After all, paradigms rarely change overnight. They drift.

Feel free to share your thoughts in the comments 👇

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In the late 1990s, after years of modest performances at the Olympic Games, British Cycling faced a profound question: what meaningful innovation could make change possible?

Groundbreaking technology, equipment, or talent alone could not guarantee more medals. British Cycling needed a different way of thinking about performance itself.

Rather than searching for a single breakthrough, British Cycling began treating performance as a system of many interconnected parts. Over time, this philosophy helped transform the organisation into one of the most successful sporting programmes in modern history.

In many ways, the philosophy became a paradigm in its own right.

The Story of Marginal Gains

British Cycling’s golden era began around the early 2000s. From Beijing to Rio, cycling heroes Chris Hoy, Bradley Wiggins, Victoria Pendleton, and the Kenny duo dominated Olympic track and road cycling.

Yet those gold-medal victories did not emerge from the athletes alone.

Behind them sat a wider system of coaches, funding, technology, facilities, institutions, and culture. Together, they helped sustain elite performance over time.

But Britain wasn’t always a dominant cycling nation. Between 1976 and 2000, British Cycling struggled to achieve consistent success on the world stage. However, a turning point came in 2003 when Sir Dave Brailsford became Performance Director of British Cycling.

Rather than searching for a single breakthrough, Brailsford introduced a different way of thinking about performance. Drawing on physiology, coaching, and data, he focused on the many interconnected factors that influence results.

These improvements went far beyond racing itself. Small changes across many areas, from psychology to team coordination, came together in a philosophy known as the aggregation of marginal gains.1

The benefits became especially visible during the 2008 Beijing Olympics. British cyclists won eight gold medals, topped the cycling medal table, and smashed world records.

More importantly, the philosophy shifted attention towards where change was possible. Every part became a potential opportunity for improvement. Even sleep became a variable.

Thinking about optimisation this way, we can begin to see where opportunities for change exist. Systems thinkers call these leverage points.

Points of Power

Systems thinker Donella Meadows described leverage points as “places within a complex system where a small shift in one thing can produce big changes in everything.”2

Importantly, not all leverage points are equal, nor do they need to be applied at once. Rather, they help us understand where and how change becomes possible.

Strategic adjustment is the key idea. Effective intervention is not always about disruption or replacement. Often, leverage arises through careful adjustment of an existing system – not too much, not too little.

Brailsford, for example, did not introduce a single revolutionary technology to British Cycling. Instead, he improved many interconnected parts within an existing system that already had the necessary structure, people, and capabilities.

But not every adjustment guarantees success. Changes can lead to delayed or unintended outcomes, emphasising the need to understand cause and effect within a system. Delays can be especially deceptive, causing people to mistake early signals for reliable patterns.

This is why Peter Senge’s famous phrase – “Take two aspirin and wait” – matters. Sometimes the most effective intervention is not another immediate reaction, but allowing enough time for the system to respond, stabilise, and reveal its wider patterns.

Once those patterns become visible, the next question becomes where change is most effective.

Meadows spent much of her work exploring that question. Her answer came in the form of a hierarchy of twelve leverage points. She identified twelve in total, ranging from physical structures to beliefs, worldviews, and paradigms.

Let’s briefly unpack them, following Meadows’ order of effectiveness.

12. Numbers

Adjusting parameters such as budgets, taxes, quotas, or targets can influence a system, but they rarely change its overall behaviour. You can’t run an economy simply by moving numbers around.

11. Buffers

Buffers help absorb shocks and stabilise flows. However, too much buffering can reduce flexibility and responsiveness. Excess inventory, for example, can tie up resources, create waste, and increase risk.

10. Stock-and-Flow Structures

Physical structures are powerful but difficult to change. Once roads, factories, or rail networks are built, the challenge is usually to understand their constraints and bottlenecks rather than redesign them.

9. Delays

Delays are among the most deceptive aspects of systems. When results take time to appear, people often mistake temporary signals for lasting patterns and overcorrect in response. Sometimes the most effective intervention is not acting faster, but slowing the rate of change itself.

8. Balancing Feedback Loops

Balancing feedback loops helps stabilise systems. Whether it’s slowing spending or monitoring an electricity meter, leverage comes from responding to important signals before instability emerges.

7. Reinforcing Feedback Loops

Reinforcing loops amplify whatever direction a system is already moving. They can accelerate growth, learning, and innovation, but also escalation and collapse. Understanding when reinforcement becomes excessive – causing people to double down on a failing path – is often a critical leverage point.

6. Information Flows

Meadows argues that restoring missing information is often a cheaper and more effective intervention than rebuilding physical infrastructure. Simply displaying household energy use, for example, can encourage people to reduce consumption.

Yet visibility alone is not enough. Leverage often comes from identifying and acting on the signals that matter most.

5. Rules

Rules define boundaries, incentives, permissions, and constraints, ultimately shaping behaviour. As Meadows observes, “Power over the rules is real power.” Those who shape the rules often shape the system itself. Change the rules, and behaviour often changes with them.

4. Self-Organisation

Self-organisation describes a system’s ability to evolve its own structure and behaviour. Biology provides a clear example. Through adaptation, learning, and feedback, living systems continually reorganise themselves in response to changing conditions, often without central control.

3. Goals

Goals shape the direction of an entire system. Resources, behaviours, priorities, and decisions gradually align around them. As a result, changing a goal often changes the behaviour of the wider system.

A company focused on quarterly profits, for example, will often behave very differently from one focused on long-term resilience.

2. Paradigms

Meadows describes paradigms as “the sources of systems.” They are the assumptions, beliefs, and worldviews that shape how people interpret reality itself. Because paradigms influence meaning, institutions, incentives, and behaviour, they are extraordinarily difficult to change.

Marginal gains, for example, reflected a paradigm that saw performance as a system rather than a collection of isolated factors.

1. Transcending Paradigms

Meadows’ highest leverage point involves recognising that no paradigm represents absolute truth. Rather than becoming trapped within a single worldview, people gain the ability to consider alternative interpretations, systems, and possibilities.

Seen this way, transcending paradigms represents the deepest form of systems learning. It expands our capacity to reinterpret not only systems, but the world itself.

Importantly, Meadows notes that the higher the leverage point, the more resistant systems become to change. Adjusting numbers may be relatively easy. Yet challenging goals, assumptions, or paradigms often require collective shifts in behaviour, culture, and understanding.

This helps explain why paradigms matter so much. Systems are shaped not only by structures, incentives, and rules, but also by the beliefs, narratives, assumptions, and interpretations people collectively carry within them.

If paradigms are so influential, an important question follows: how do they become embedded in the first place?

How Paradigms Become Embedded

Paradigms rarely stay as abstract ideas. Over time, they spread through institutions, professions, cultures, communities, and everyday practices. This is what makes paradigms especially intriguing.

As people repeatedly act on the same assumptions, those assumptions become woven into behaviours, incentives, routines, and expectations.

But the deeper paradigms become embedded, the harder they are to see. They then shape how people interpret problems, define value, coordinate behaviour, and decide what appears normal, rational, or true.

We can observe this in everyday working life. A workplace that rewards high productivity may normalise long hours, quick responses, and overtime. As employees adopt these behaviours to succeed, they reinforce the belief that productivity is the primary measure of progress.

Many of us have experienced the awkward feeling of leaving work on time while the rest of the team works late to meet a deadline. Over time, these behaviours become accepted as normal simply because the surrounding system continually reinforces them.

Seen this way, paradigms do not simply influence systems from above. They become embedded within the very structures, behaviours, and relationships that sustain them.

From Shared Assumptions to Belief Systems

Looking across product, design, innovation, and institutions, I’ve noticed how difficult it can be to think beyond established paradigms.

For example, interns or junior professionals inherit ideas from academia, mentors, and workplace culture. Organisations then reinforce them through incentives, goals, and everyday practice.

Over time, what began as a practical way of doing things can become accepted as the way things should work.

Simply put, people align around what feels normal, effective, and familiar. As these shared assumptions become embedded in everyday behaviour, they can begin functioning much like belief systems.

Here, belief does not necessarily imply ideology or religion. Rather, it describes systems of shared meaning built on values, assumptions, incentives, norms, and interpretations.

The key question is how shared meanings enable large groups to coordinate in the first place.

In Sapiens, Yuval Noah Harari argues that large groups of people cooperate through what he calls “intersubjective realities”. These are shared stories and interpretations that help people coordinate at scale.3

“Like money, limited liability companies and human rights, nations and consumer tribes are intersubjective realities,” Harari writes.

Like Harari’s intersubjective realities, paradigms can function much like belief systems. They provide shared assumptions about how the world works, what matters, and how people should behave.

Harari’s broader point is that large-scale human systems persist because they coordinate around shared meaning. Paradigms, therefore, are not merely abstract ideas – they are mechanisms that help people coordinate, cooperate, and organise collective action.

Drawing from Harari’s examples, these systems can include money, laws, nations, and corporations. They can also appear in everyday rituals, like pretending to enjoy a networking event because everyone else seems to.

Over time, they become so deeply woven into institutions, culture, and behaviour that they feel normal, unquestionable, and often invisible.

When Paradigms Feel Natural

Within organisations, people may unknowingly align around behaviours, targets, frameworks, or metrics that gradually come to feel objective and unquestionable.

Over time, these patterns become reinforced through performance reviews, incentives, governance structures, and even professional identity.

We can observe similar patterns throughout everyday life. Families, schools, communities, and wider society all reinforce shared expectations about behaviour, success, belonging, and status.

Whether we consciously believe in social, cultural, political, corporate, or religious systems or not, we still participate in many of them intuitively.

In doing so, we reinforce systems of shared meaning – even when we claim not to believe in them directly. Participation itself becomes a form of reinforcement.

The idea of intuition closely mirrors Daniel Kahneman’s System 1 thinking: fast, automatic, and deeply conditioned through repetition.4 Over time, assumptions and norms become so deeply embedded that they fade into the background of everyday life.

This concept circles us back to a recurring theme throughout Journeys to Value: Systems provide the structure for repeated behaviour, while human behaviour simultaneously reshapes those very systems.

Yet behaviour is not the only force that reinforces paradigms. Narratives play an important role, too.

Narratives, Identity, and Paradigms

Narratives help carry and reinforce systems of shared meaning. Every group – whether a family, political movement, organisation, or nation – constructs stories about who they are, what they value, and what they seek to achieve. These stories justify, protect, and strengthen what is collectively believed, valued, or pursued.

Whether promoting lifestyles, framing political issues, or reinforcing organisational values, these narratives do more than communicate ideas. They help people coordinate around shared meaning.

Mainstream and independent media also help coordinate shared meaning, often through the lens of underlying paradigms. Two journalists from competing newspapers can report on the same event yet frame it in very different ways.

The facts may remain largely the same, but the interpretation can differ significantly. Readers often gravitate towards the narratives that best align with their existing assumptions, values, and beliefs. Similar dynamics can emerge within organisational thinking.

Organisations often rely on methodologies, frameworks, and operating models to solve problems and coordinate work. These can range from OKRs and KPIs to MVP thinking and Product Management practices.

Initially, these approaches serve a practical purpose. They help teams make decisions, allocate resources, and reduce uncertainty. Over time, however, organisations build narratives around them. Teams begin to identify with the framework and treat it as proof of good practice.

“MVP is our philosophy,” some might say.

“This is how modern Product Management works,” others might insist.

The challenge arises when useful tools become accepted as the only way of working. As a result, repeated success can reinforce shared beliefs, gradually transforming adaptable methods into fixed paradigms.

Once this happens, they become increasingly difficult to question, reinterpret, or evolve. Teams continue operating within familiar patterns, while the framework gradually shapes how they interpret success, value, and progress.

But paradigms do not emerge in isolation. Many of the beliefs that shape organisations are first cultivated by education, industry, government, culture, and society itself.

Organisations, Institutions, and Systemic Reinforcement

While paradigms shape everyday behaviour, wider institutions often shape how organisations think and act.

Educational institutions, professional bodies, governments, regulators, industries, financial systems, and consumers all influence what organisations interpret as rational, valuable, efficient, or legitimate.

In many cases, a company may genuinely believe it is acting rationally. It complies with laws, upholds standards, and meets industry expectations. Yet many of the assumptions guiding those decisions have been inherited from the wider system rather than consciously chosen.

That same system also reinforces competing ideas about success, from growth and performance to ethics, social responsibility, and environmental stewardship. As a result, organisations can become just as shaped by paradigms as the people working within them.

This also helps explain why organisational change is rarely confined to the organisation itself. No matter how hard people push, the wider system will often constrain, resist, or redirect the change they are trying to create.

Customers, investors, regulators, suppliers, competitors, technologies, and social expectations all influence what change is possible. A company prioritising long-term value, for example, may still face pressure from markets, reporting cycles, consumer expectations, or industry norms.

We can now begin to see that paradigms shape far more than belief. They influence how people and organisations interpret signals, define success, reinforce behaviour, and create shared meaning.

Understanding paradigms is one thing. Recognising when they begin to drift is another.

Signals of Paradigm Drift

When we question the paradigms themselves, we begin to see Meadows’ deepest insight. The most powerful leverage points are often not found in the structures we can see, but in the assumptions, interpretations, and shared meanings through which we understand them in the first place.

Yet paradigms do not remain fixed. Over time, they evolve, adapt, and sometimes drift. Shared assumptions become reinforced. Success patterns harden into habits. What once helped people learn and adapt can gradually become difficult to question.

Perhaps the most important shifts are not the ones we immediately notice, but the ones quietly unfolding beneath the surface. Learning to recognise those signals may be one of the most important forms of systems learning.

Recognising when paradigms shift – and how to respond when they do – is where this story will continue next.

Something to think about: What paradigms shape how you interpret success, value, and progress? And how might your everyday behaviours be helping reinforce them in return?

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If learning helps systems build resilience, then who helps make that happen? After all, systems do not run themselves. Even the most elegant systems still require people to interpret signals, coordinate responses, and intervene when needed.

But there is a deeper question: who helps people build resilience in the first place?

Overlooking the Human Element

While leaders and economists debate how to grow or stabilise an economy, one of the most important participants is often treated as secondary: people.

Like the elephant in the room, they are impossible to ignore. Economists such as Amartya Sen argue that development should focus on “advancing the richness of human life, rather than the richness of the economy in which human beings live.”1

At the same time, people, organisations, and systems all have limits. In a world shaped by constant shocks, delays, and uncertainty, resilience becomes increasingly important.

But resilience rarely emerges in isolation. More often, it develops when people come together to learn, adapt, and collectively make sense of problems. This idea sits at the heart of organisational learning.

In Systems Convening: A Crucial Form of Leadership for the 21st Century, Social theorists and Etienne Wenger-Trayner discuss how people learn in complex social settings.2

However, bringing together different roles, disciplines, and perspectives is rarely straightforward. This complexity arises because people often operate within areas shaped by different goals, responsibilities, and experiences.

Wenger-Trayner see these divisions as boundaries. Their research shows that when people collaborate across different groups, teams, departments, and domains, they better understand each other’s perspectives, limitations, and ways of working.

Over time, boundaries become less like barriers and more like opportunities for learning and coordination.

As people cross boundaries, relationships become more reciprocal. Knowledge, experiences, and responsibilities begin flowing in multiple directions. People start giving and taking with a shared understanding that they are contributing toward something larger than themselves.

Seen this way, systems are not only built through structures, processes, and feedback loops. They are also shaped through human relationships, shared learning, and the ability to work across boundaries.

And when people begin recognising one another’s needs and challenges, they start finding ways to converge on a more meaningful journey to value.

A World Divided by Boundaries

While systems thinking helps explain interconnectedness, not all systems interact as we might expect. That’s because systems are often shaped by boundaries with different degrees of permeability.

In physics, permeability describes how easily liquids or gases pass through a material. Boundaries work similarly. Some are relatively open, allowing the flow of information and resources. Others are more rigid, making systems more closed, controlled, and self-contained.

Forest edges, for example, act as transitional zones between woodlands and open land. These ecological boundaries create dynamic microclimates that support biodiversity. In this way, they shield surrounding areas from wind, fire, and environmental change.3

Human systems behave similarly. In hospitals, departments perform highly specialised tasks. Yet, their boundaries often flex to allow information sharing, medical coordination, and resource allocation across the wider healthcare system.

Boundaries are not only physical or organisational; they can also be psychological.

Psychologist Dr Sarah Davies uses the metaphor of a garden fence to explain personal boundaries. A healthy boundary creates space and protection. It includes a gate that allows people to decide when, how, and under what conditions others may enter.4

Seen this way, boundaries help systems maintain identity, structure, and stability. But they can also limit learning, coordination, and adaptation when they become too rigid.

The challenge, therefore, is not simply whether boundaries exist, but how people learn to work across them.

Because every boundary, no matter how open or closed, still has its limits.

Every Boundary Has Its Limits

A forest ecosystem cannot lose more than it can regenerate. A hospital department cannot lend out its resources endlessly. Individuals only have so much mental capacity before they burn out. These examples highlight a key truth: every boundary has its limits.

When one boundary overshoots those limits, the effects often ripple outward across many others. Even systems that appear isolated are usually connected in some way. And wherever systems become tightly coupled, vulnerabilities emerge.

Supply chains illustrate this clearly. They depend on interconnected networks of people, organisations, resources, and activities, all of which remain sufficiently coordinated to keep goods flowing. When one part falls too far out of sync, disruptions spread throughout the wider system.

The COVID-19 pandemic clearly showed how fragile our systems are. Labour shortages, factory shutdowns, and transport disruption exposed how quickly instability can ripple across interconnected networks.

Yet boundary fragility is not unique to global crises. It emerges whenever systems are pushed beyond their capacity to adapt.

Push a workforce too hard, and people burn out. Remove too many predators, and ecosystems destabilise. Overreact to changing demand, and supply chains spiral into backlog and shortage. Each reflects a principle Peter Senge describes clearly:

“The harder you push, the harder the system pushes back.”5

Understanding limits, therefore, becomes essential to resilience across interconnected systems. Without balance, pressures that initially appear manageable can quietly compound over time, reducing a system’s ability to absorb shocks, adapt, and recover.

This is one reason the planetary boundaries framework has become an important focal point in environmental systems thinking. Under the leadership of Johan Rockström, the research identifies environmental thresholds that, when crossed, increase the likelihood of instability.6

As systems thinking suggests, these risks often build gradually over time until systems struggle to recover. At the same time, maintaining those boundaries requires balancing them against human activity and societal needs, each with its own limits and dependencies.

When viewed through this lens, human needs influence how a system behaves. And behaviour, in turn, shapes the boundaries of what the system can absorb, adapt to, and sustain.

As pressures intensify, systems do not simply react internally; their boundaries begin to react as well. This becomes especially visible in human behaviour under stress.

People become defensive, emotionally withdrawn, or resistant to alternative perspectives. In many cases, people often set up strict psychological boundaries to protect themselves from fear, uncertainty, or feeling like they are losing control.

Similar dynamics often emerge across teams and organisations.

Behavioural Boundaries

After many years working across small and large organisations, I began noticing how teams built boundaries around themselves. Some remained relatively open; others became highly closed and protective.

Looking back – and drawing inspiration from Wenger-Trayner – I now realise these boundaries were shaped by many human factors: needs, values, incentives, politics, fear, beliefs, biases, goals, and identity.

In many ways, boundaries can become behavioural incubators. Within groupthink environments, people reinforce the same interpretations, trapping themselves within a shared worldview.

This behaviour is common in organisations that prioritise short-term goals. Under pressure, teams are unlikely to collaborate beyond their immediate priorities, even though broader cooperation could create greater long-term value.

As these patterns become increasingly reinforced, they evolve into narratives about how the world works, who is right or wrong, and what should be protected. Cultures, ideologies, and communities often preserve these interpretations within their own boundaries.

Rather than supporting learning, such narratives can become mechanisms for defending identity, beliefs, and existing assumptions. Boundaries then harden further, reducing openness to alternative perspectives.

In this sense, boundaries do not merely regulate movement; they also protect belief systems, norms, and collective ways of life. But those who cross boundaries often gain access to new perspectives, relationships, and creative possibilities.

Changing deeply entrenched boundaries is rarely easy. Yet Wenger-Trayner’s work suggests that meaningful coordination does not always require removing or controlling them entirely.

Instead, people can learn to cross boundaries more effectively by creating environments where different groups, perspectives, and systems can meet, learn, and collaborate.

In many ways, it is less about forcing people out of the forest and more about encouraging them into the clearing.

Crossing Boundaries

During my years working in design, I often found myself asking difficult questions: Who will fight for the users? Who is allowed to uncover uncomfortable truths? And when will knowledge finally turn into meaningful action?

The organisational landscape I operated within rarely made it easy to answer those questions. Yet that rarely stopped me entirely. I often worked “under the radar” with people outside my boundary to solve problems that extended far beyond the immediate brief.

Over time, I realised that many local problems were symptoms of much wider organisational patterns.

But bringing people into those conversations also required them to step beyond their own boundaries. As we explored earlier, boundaries are often shaped by competing pressures, priorities, values, and constraints that can make people reluctant to move beyond them.

Using Dr Davies’ garden fence analogy, the goal was not to ask people to abandon their responsibilities or identities, but simply to peer over the fence for a moment and see what others were experiencing.

In many ways, learning across systems requires people to temporarily leave the safety of what they already know.

Yet people rarely do this unconditionally. Meaningful collaboration often depends on creating environments where individuals feel safe enough to meet in the middle.

Some step forward out of curiosity or care. Others need a clearer reason to invest their time and energy.

At first, I crossed boundaries mainly to solve what appeared to be local problems. Over time, however, I realised that because many people remain focused on their immediate environment, someone often needs to help connect the wider landscape.

Mapping the Landscape

Across different social contexts, we can imagine individuals and groups spread across a landscape of boundaries. Some perspectives and objectives are shared, while others remain disconnected. Between them are people attempting to connect ideas, experiences, and viewpoints across the wider system.

Over time, some of these individuals begin to take on a more connective role, helping others navigate the wider landscape beyond their immediate boundaries.

In many ways, these individuals behave much like researchers or scientists. They remain open to questioning assumptions, rethinking what they already know, and exploring perspectives beyond their immediate boundary.

As boundaries become more permeable, perspectives move more freely across the wider landscape. People then begin to challenge assumptions and recognise shared concerns that were previously hidden behind isolated boundaries.

The Causal Loop Diagram (CLD) shows how this collaborative learning dynamic can reinforce itself across a system. It works something like this:

A desire for change encourages people to cross boundaries and engage with others across the wider landscape.

Through conversations and shared experiences, people rethink assumptions and see problems differently. This shift in understanding influences how willing they are to engage across boundaries.

Over time, this engagement reinforces a wider culture of collaborative learning throughout the system.

This kind of cross-boundary learning is central to what Wenger-Trayner describe as systems convening.

Systems conveners are people who “work on sustainable change across challenging silos and in complex social landscapes.”

Systems conveners are not necessarily formal leaders. Rather, they help create the conversations, relationships, and learning needed for meaningful coordination across boundaries.

In many ways, systems convening is less a formal role than a way of behaving. Many people already practise it in everyday life – often without realising it.

At the time, I did not realise I might have been operating in this way. But looking back, I came to understand that skill alone rarely solves system-wide problems. Organisations and societies become more resilient when people learn together across boundaries.

Yet asking people to step outside their own corner of the woods is rarely easy.

A Convening Change

People already carry responsibilities, pressures, targets, and competing priorities. Which is why Wenger-Trayner emphasise the importance of what they call a convening call – a compelling reason for people to come together.

Problems often exist across the wider landscape long before most people fully recognise them. A convening call, however, helps frame shared concerns in ways that resonate with people’s needs, values, and motivations. Once people recognise those concerns, conversations can gradually evolve into longer-term collective learning and action.

While a convening call can encourage people to engage, bringing them together requires understanding the pressures, contexts, and perspectives shaping their boundaries in the first place.

Wenger-Trayner describes much of this process as boundary work.

Again, the goal is not to force people to abandon their viewpoints, but to create conditions where they feel safe enough to step beyond them temporarily.

When people meet in shared spaces, they often gain the confidence to challenge assumptions, surface tensions, and better understand how others experience the system. Over time, fragmented perspectives begin forming a more complete picture.

Even then, articulating problems clearly is not always easy. Biases, assumptions, fears, and competing interpretations can remain hidden beneath the surface. This is where boundary objects become especially important.

As forms of shared evidence, they help move conversations beyond opinion by allowing people across different boundaries to build a more grounded understanding of how the wider system behaves.

Boundary objects might include reports, diagrams, videos, maps, prototypes, or shared frameworks. In many ways, they function like story artefacts – helping diverse groups organise around a shared narrative or interpretive framework.

As a designer, I often had to choose which stories, evidence, or artefacts could best help people align. Sometimes that meant data, research, interviews, or prototypes. The goal was not simply persuasion but the creation of a shared framework that people could engage with together.

Once people feel they can meaningfully contribute to something, they become far more likely to help shape it – and that is often where learning across the system begins.

Learning Across the System

Wenger-Trayner describe systems conveners as people who “act as enablers rather than taking credit or seeking the spotlight.” Their influence often comes less from authority and more from enabling learning and coordination across boundaries.

Whenever I brought together people from areas such as marketing, engineering, or customer support, the group rarely held formal authority to drive large-scale organisational change.

Through shared understanding, new insights surfaced that would otherwise have remained isolated. A customer support representative, for example, once identified behavioural patterns that helped explain why certain new features were negatively affecting engagement and sales.

Experiences like these helped me understand what Wenger-Trayner describe as developing a “landscape view.” This is more than simply having a vision or strategy. It’s the realisation that people from different boundaries can come together to strengthen a system’s ability to learn, adapt, and coordinate.

However, power dynamics often stand in the way. Less like trolls guarding bridges and more like people managing budgets, approvals, or resources, they shape movement across the wider landscape.

Recognising these interdependencies becomes essential when trying to influence wider change. Especially in highly centralised organisations, legitimacy often determines whose voices are heard and whose are ignored.

This is why Wenger-Trayner focus on relationships across the wider landscape rather than isolated silos. Over time, relationships create pathways for influence, learning, and coordination across boundaries.

Yet real influence rarely happens through dramatic moments. More often, it emerges slowly through repeated interactions between people across boundaries. Conversations build trust. Shared learning builds alignment. Small changes accumulate. And over time, those shifts become increasingly visible across the wider system.

Coordinating with Shared Purpose

People tend to work together most effectively when they share a sense of purpose. Shared purpose gives people direction, energy, and a reason to keep moving, even when change becomes difficult.

Yet collective movement often begins with individuals willing to step beyond established boundaries first.

As Wenger-Trayner note, “System conveners can be easily seen as mavericks in their organisation. They strategically learn to make the system work for their convening approach to making a difference.”

In many cases, this means working across established norms, challenging assumptions, and navigating boundaries that others may avoid.

These patterns often appear in activists, reformers, entrepreneurs, researchers, and innovators who attempt to shift systems in new directions. Martin Luther King Jr., for example, challenged deeply entrenched social boundaries around civil rights and justice.

Such efforts show how individuals can influence wider systems by questioning existing limits and pursuing alternative possibilities.

This brings us back to the question we began with: who helps people build their own resilience?

If systems cannot fully regulate or care for themselves, then strengthening their human element becomes essential.

Sustaining healthy systems ultimately requires a learning mindset – a willingness to continuously question, adapt, and rethink what we believe we already know.

Once people begin asking difficult questions, challenging conventions, and learning across boundaries, systems gain greater capacity to adapt, coordinate, and evolve over time.

Local perspectives, competing goals, emotional interpretations, organisational tensions, and dynamic relationships all shape the systems we build, maintain, and participate in.

Recognising the human element of systems is ultimately how we create healthier movement across them. And through shared learning, coordination, and purpose, we become better equipped to shape the systems that enable more meaningful journeys to value.

Something to think about: what boundaries, pressures, and systems are shaping the way you think and behave – and how are your own actions helping reinforce them in return?

Feel free to share your thoughts in the comments 👇

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Systems often behave unpredictably. A change in one area can affect another. But we usually don’t see the consequences of our actions until it’s too late.

That is exactly what occurred in Yellowstone National Park when people believed they were trying to address a local issue by driving a natural predator to extinction.

And that’s how it often unfolds in a supply chain management simulation called the Beer Game. While drinking is usually not involved, players often experience consequences of their actions late in the game – and blame each other.

Both cases illustrate an important principle from chaos theory: small changes ripple outward across a wider system, often creating unintended consequences. Changes, however, are often unseen, unheard, and unfelt until they emerge as patterns later on.

That’s when systems can deceive. But systems thinking offers a way to make our systems – and journeys to value – more resilient to shocks and collapse.

The Unexpected Cascades in Yellowstone

In the early 20th century, wolves were nearly wiped out in Yellowstone National Park. Many people considered them a danger to livestock and a threat to hunting.

Without fully understanding their ecological role, governments, ranchers, and hunters worked together to eliminate them. They genuinely believed they were fixing a problem.

The intention was to make the environment safer, more controlled, and more productive for human activity. But the long-term consequences revealed something much deeper: removing one perceived problem from a system created many others.

As the wolf population collapsed, elk numbers surged. At first, this appeared beneficial. Fewer wolves and more elk meant less danger and more game for hunters. The environment seemed far safer and more predictable.

But over time, the ecosystem quietly began to change. The greatest impact was not population growth alone, but behavioural change throughout.

Without wolves as a regulating force, elk grazed for longer around young vegetation and riverbanks. Plant life declined, root systems weakened, and erosion increased.1

What looked like a local solution became a systemic problem.

These events mirror the escalation patterns we often see in organisations, governments, and societies. They frequently start with a single shift in perception – a distortion in how people understand a problem. Over time, that distortion compounds into something far more damaging, often slowly and quietly.

People in Yellowstone thought they were doing the right thing. But doing the right thing can still lead to the wrong outcome when we fail to understand the wider system.

Cause and Effect Aren't Linear

Systems often change in unusual and unexpected ways. Yet understanding why they changed usually only becomes possible in reflection.

When we reflect on the ecological collapse of Yellowstone, the effects appear clearly linked to a single major intervention: the mass removal of wolves. At the time, the long-term consequences were far less obvious.

People only began recognising the wider impacts once they became visible across the ecosystem. What first appeared to be a local solution gradually created wider systemic problems.

Yet reflection does more than explain the past. It also helps us navigate the future. We predict, observe, reflect, and adjust. That is how systems begin to learn from themselves.

Yellowstone authorities eventually used lessons from the past to guide future intervention. In 1995, wild wolves from Canada were carefully reintroduced into the park. Before release, they were temporarily held in acclimatisation pens to help them adjust to their new environment.

Over time, packs formed, populations stabilised, and ecological relationships began to recover. The ecosystem did not instantly “reset,” but natural balance gradually returned.

In this ecosystem, wolves affect elk; elk affect vegetation; vegetation affects riverbanks; and riverbanks, in turn, shape the ecosystem.

When we begin viewing the world through a systems lens, we stop seeing reality as static. Instead, as Donella Meadows explains in Thinking in Systems: A Primer, we begin recognising a world of movement, interaction, adaptation, and feedback.

Rather than asking only “Who caused the problem?”, we begin asking a deeper question:

“What’s the system?”2

Questioning the wider system

When we question the system, the picture starts to shift. Systems are not fixed things. Rather, they are patterns of movement, relationships, behaviour, and feedback.

Systems constantly adjust and regulate themselves. Remove one important balancing force, and instability can spread throughout the wider environment. Keep relationships healthy and adaptive, and systems are more likely to remain resilient over time.

One of the greatest challenges, however, is that systems rarely behave as linearly as we imagine. In The Fifth Discipline: The Art and Practice of the Learning Organization, Peter Senge argues that people tend to perceive cause and effect as being “close in time and space.”3

In other words, there is often a disconnect between how systems actually behave and how we interpret them.

Yellowstone illustrates this clearly. Many locals believed removing wolves would create a safer environment. The immediate effects seemed positive, but the long-term consequences unfolded slowly over the years, affecting relationships, behaviours, and ecosystems.

This is where systems become difficult to interpret. Some forms of complexity are visible: many moving parts, variables, or decisions interacting at once. But in dynamic complexity, cause and effect are delayed, indirect, or difficult to see.

Small changes in one part of a system can quietly influence many others, often with delayed consequences. Interventions inside ecosystems, organisations, markets, technologies, and societies can also ripple outward in ways people fail to anticipate.

And nowhere is this more visible than in one of the most famous systems thinking simulations ever created: the Beer Game.

Complexity in the Supply Chain

In The Fifth Discipline, Senge uses a supply chain management simulation to demonstrate how individuals often struggle to understand their roles within complex systems.

In the game, each participant – a retailer, a wholesaler, and a brewery manager – manages stock and places orders based on incoming demand. At first, the system appears stable, but unexpected delays build between orders, production, and delivery.

A slight increase in sales prompts the retailer to order more stock, which, in turn, prompts the wholesaler to order more from the brewery, thereby increasing beer production.

But because orders, production, and deliveries take time, participants react before fully seeing the consequences of earlier decisions. When demand declines, excess inventory accumulates, causing instability throughout the supply chain.

As in Yellowstone, the simulation shows that systems rarely follow simple linear cause and effect. Delayed feedback and misinterpretation can easily amplify small changes into broader instability.

It also shows how uncertainty and delays trigger emotional reactions. People begin panic ordering, communication weakens, and assumptions replace understanding. Over time, those behaviours reinforce one another, increasing supply chain fragility.

Escalation inside the Beer Game often sounds something like this:

1. “We believe demand is increasing.”

2. “We need to take action.”

3. “These shortages validate our concerns.”

4. “We’re making the right decision.”

5. “Let’s increase our orders even further.”

Seen this way, systems not only produce outcomes, but they also shape behaviour. And behaviour, in turn, reshapes the system itself.

The same pattern appears in organisations, governments, markets, and everyday life. People act locally, but the consequences spread systemically. The challenge, then, is not to eliminate complexity, but to navigate it better.

A Balancing Act

Knowing how to regulate tension between competing needs, goals, and ideas is very much a balancing act. In Yellowstone, that tension was ecological. In the Beer Game, it was economic. But balance is rarely as simple as weighing two sides on a pair of scales.

Systems are constantly adjusting to pressures, constraints, and interventions. We may restore balance in one area, only to introduce instability somewhere else. And as we’ve already seen through dynamic complexity, these imbalances often emerge gradually and quietly.

Whether in business, economics, politics, or society, striking the right balance is rarely straightforward – nor is it a one-off activity.

Balancing a system, therefore, requires more than reacting to isolated problems. It requires understanding the wider relationships between participants and how their behaviours influence one another over time.

One of the biggest balancing acts you’ll encounter – or at least hear about – is sustainability.

Balancing Competing Needs

Sustainability has become an increasingly political and commercial priority. Governments, institutions, and businesses now place significant emphasis on reducing environmental harm, lowering emissions, and improving long-term resilience.

Historically, sustainability was a practical idea: never take more from a system than it can regenerate.

Viewed through a systems lens, sustainability is about maintaining balance between short-term actions and long-term consequences. In many ways, it’s about seeing the wood for the trees.

Today, sustainability is often framed in terms of climate policy and environmental protection. Governments and global institutions, such as the United Nations and the World Economic Forum, promote measures to reduce long-term environmental risk.

Yet in Fossil Future: Why Global Human Flourishing Requires More Oil, Coal, and Natural Gas – Not Less, Alex Epstein argues that climate policies have both short-term and long-term consequences for society.

He explains that such policies ask societies to absorb short-term economic pain now in exchange for reducing longer-term environmental risks later.4

Whether we agree with that argument or not, it raises a useful systems point: policies aimed at long-term environmental goals can also create short-term social and economic pressures.

This is not about rejecting environmental protection or climate policy. Rather, it demonstrates that systems involve many interconnected participants whose needs cannot always be reduced to simple trade-offs.

Finding a Healthier Balance

Perhaps true sustainability, then, is less about optimising one part of a system and more about balancing many forms of value simultaneously.

The challenge, therefore, is to find healthier forms of balance across the wider landscape, allowing value to emerge across the broader system.

Intervention – often through innovation – is one way we attempt to create that balance. Yet intervention can also create unintended consequences, as we observed earlier through cause and effect.

Senge describes this tension as: “The harder you push, the harder the system pushes back.” In other words, the more aggressively we attempt to force outcomes, the more likely we are to create new obstacles ourselves.

But systems thinking is not about avoiding intervention. Rather, it’s about acting more deliberately, reflectively, and systemically. And those actions rarely happen in isolation. They require coordination across people, environments, organisations, and journeys.

Ultimately, balancing systems means balancing multiple forms of value across an interconnected landscape. We may call this sustainability. We may call it resilience, coordination, or long-term thinking.

Whatever we call it, the principle is the same: healthier systems depend on relationships, not straight lines.

A Language of Circles

“Reality is made up of circles, but we see straight lines.” – Peter Senge, The Fifth Discipline.

Understanding cause and effect requires a shift in mindset. And, as Senge puts it, that mindset speaks “a language of circles.”

That’s not to say linear thinking is useless. It remains deeply embedded in how humans navigate everyday life. But when systems become more interconnected and dynamic, linear thinking alone struggles to explain what is really happening beneath the surface.

A language of circles helps us move away from isolated events and toward relationships, loops, and patterns. More importantly, it helps us understand how systems maintain balance – or fall out of it.

Unbalanced systems create instability. Run a bath without checking the water level, and eventually it overflows. (Yes, I’ve managed that plenty of times during my student days.)

As simple as it sounds, a bath is a surprisingly useful metaphor for understanding system behaviour. It introduces one of the most important concepts in systems thinking: feedback.

Feedback Loops

In systems thinking, feedback means a reciprocal flow of influence. Actions shape systems, and systems shape actions in return.

Reinforcing loops amplify change, while balancing loops regulate it. When I flooded the bathroom by leaving the taps running, the water level kept rising in a reinforcing loop.

However, when someone monitors the water level, turning down the taps creates a balancing loop that stabilises the system. But remove the person from the loop, and cause and effect become separated by time. That’s when it often becomes too late to act.

Delays

Delays are one reason systems become deceptive. Cause and effect may be connected, but often separated by time, making it difficult to recognise how actions contribute to wider outcomes.

We saw this in Yellowstone, in the Beer Game, and even in my student bathroom-flooding days. The bath didn’t overflow instantly; the water level rose slowly until the consequences became impossible to ignore. (Imagine water dripping through the kitchen ceiling downstairs.)

Delays appear throughout many systems. Supply chains, ecosystems, and organisations often respond slowly, causing people to react to incomplete or misleading signals. As a result, overreaction and instability can quietly compound over time.

Stocks, Flows, and Accumulation

Flows are simply movements through a system: water from a tap, beer through a supply chain, money through a bank account, or information through an organisation.

Stocks are what accumulate or decline: bath water, warehouse inventory, savings, attention, trust.

Feedback, then, regulates the relationship between stocks and flows. But if people cannot see what is building up, they cannot respond in time. And when delays slow feedback, systems gradually drift out of balance. That’s when deceptive patterns begin to emerge.

When Systems Become Deceptive

Once we begin thinking in loops rather than straight lines, systems start to look very different. Relationships become more important than isolated events. Actions ripple outward across wider environments, feedback shapes behaviour, and delays distort what people can clearly see.

Over time, these interactions reinforce or balance recurring patterns – from Yellowstone to overflowing bathrooms. To help visualise these circular relationships, systems thinkers often use tools called Causal Loop Diagrams (CLDs).

Visualising Feedback Loops

Unlike process diagrams, CLDs do not rely on a fixed starting point. They show circular patterns: vicious cycles that amplify instability, and virtuous cycles that improve conditions over time.

The simplest way to see a CLD in action is through something as ordinary as running a bath. Water flowing from the taps raises the bath level, which, in turn, should signal the participant to regulate the flow. But without someone to adjust the taps, the tub will eventually overflow.

The next CLD shows how the situation changes when the bath is part of a balancing loop. As water flows from the taps, someone is present to monitor the rising level and adjust the taps to prevent overflow. However, there is still a delay in making these adjustments, as the system takes time to respond.

We can extend this thinking to a much larger, more complex system: the Beer Game. Viewed through a CLD, the supply chain no longer behaves like a simple sequence of events, but as a network of interconnected reactions shaped by feedback, delays, and interpretation.

In the Beer Game, as customer demand rises, the retailer’s inventory begins falling, triggering additional orders upstream. The wholesaler responds by placing larger orders with the brewery, while the brewery increases production to compensate.

But because deliveries, production, and replenishment all involve delays, each participant reacts before fully seeing the consequences of their earlier decisions. The result is a reinforcing feedback loop.

What begins as a relatively small fluctuation gradually escalates into instability across the entire supply chain. Yet vicious cycles rarely emerge from a single mistake.

Time delays build between ordering, production, shipping, and delivery. Because feedback arrives slowly, each participant responds to incomplete information. Retailers, wholesalers, and breweries begin reacting not to reality itself, but to their interpretation of what they believe is happening.

This is where systems become deceptive.

Reacting to the Wrong Signals

People often believe they are simply responding rationally to changing conditions. In reality, their reactions amplify the very instability they are trying to avoid. The harder they try to regain control, the more disorder they inadvertently create across the wider system.

Delays are often central to this process. A retailer may wait weeks for a wholesaler to adjust supply. A manufacturer may continue producing inventory long after demand has changed.

In other contexts, governments may not see the consequences of policies for years. Ecosystems, like Yellowstone, may take decades to reveal the effects of intervention.

Delays often emerge through poor communication, missing information, bottlenecks, weak forecasting, and fragmented coordination.

Each delay slows feedback across the wider system, reducing people’s ability to respond effectively. And because people naturally seek immediate explanations, delays often lead to misinterpretation.

In the Beer Game, a temporary increase in demand is misinterpreted as sustained long-term growth. That interpretation then spreads through the wider supply chain, amplifying instability over time.

Seen this way, systems can distort how people interpret reality. They become fixated on visible events and immediate signals while remaining blind to slower, underlying structural patterns.

This connects to path fixation, where short-term signals harden into overcommitment. It also creates story gaps, where people justify decisions or shift blame elsewhere. The catch is that these behaviours reinforce one another, keeping escalation in motion.

Restoring Balance

Many systems eventually face shocks: sudden events that disrupt normal flow. In the Beer Game, the shock was a surge in demand. Participants overreacted, and the system amplified their response.

Shocks, therefore, act as stress tests, revealing whether a system is resilient or fragile.

Under pressure, as feedback slows and coordination breaks down, hidden vulnerabilities begin to surface. This fragility allows small problems to grow into shortages, overproduction, panic buying, or even collapse, as each reaction reinforces the next in a vicious cycle.

People often try to deal with shocks by being “proactive.” In the simulation, participants placed larger orders to avoid shortages. But as Senge points out, this usually makes matters worse.

The more people react aggressively, the more instability they unintentionally create. As the overreactions build gradually, people often fail to recognise the seriousness of the situation until the instability has already escalated.

Building Resilience

Sometimes, vicious cycles can turn into virtuous cycles. In what we might call a rising halo, learning, coordination, and adaptation begin to improve the system rather than destabilise it. That shift only becomes possible when systems learn through feedback.

Simply put, systems that learn become more resilient over time.

Resilience is not purely about maintaining control. More often, it is about building adaptive capacity – the ability to absorb disruption, adjust behaviour, and continue functioning under changing conditions.

Supply chains also build resilience through buffers and flexibility. Inventory levels, alternative suppliers, and coordinated communication can help absorb shocks before they spread throughout the wider system.

But even then, uncertainty never disappears. Systems thinking simply helps us respond with more care. Senge offers two practical lessons from the Beer Game that remain highly relevant for resilience:

1. “Take two aspirin and wait.” In other words, allow time for interventions to take effect before reacting again.

2. “Don’t panic.” Step back from immediate signals and try to understand the wider system before escalating your response.

Both principles reinforce a deeper systems insight: reacting faster does not always mean responding better. Yet resilience does not mean endlessly compensating or overcorrecting.

Senge describes this tendency through what he calls compensating feedback: “The harder you push, the harder the system pushes back.”

Building resilience means balancing stability with flexibility, and action with patience. It requires recognising that causes and effects are rarely isolated or linear, but interconnected, delayed, and circular.

And once we begin seeing systems that way, we stop asking only who caused the problem and start asking a deeper question:

“What’s the system?”

Something to think about: what systems are shaping your behaviour – and how are your actions shaping those systems in return? Where might delayed feedback, repetition, or reinforcement be quietly influencing the paths you follow?

Feel free to share your thoughts in the comments 👇

Leave a comment

We design for systems. We talk about systems. We think in systems. This extraordinary field, which explores how we connect everything as a whole, has grown in popularity. But its origins stretch back nearly a century.

In the 1930s, biologist Ludwig von Bertalanffy developed general systems theory, which was later expanded by thinkers such as Jay Forrester, Donella H. Meadows, and Peter Senge.

When I first read Thinking in Systems1 by Meadows, it changed how I saw the world. It revealed a pattern I’d always sensed but never articulated. Similarly, The Fifth Discipline by Senge reinforced the idea that organisations often focus on symptoms rather than underlying causes.2

Systems thinking, however, isn’t confined to a single discipline. It applies across contexts, far beyond product and service design. From organisations to communities, systems shape relationships, behaviour, and the patterns that emerge over time.

The Brick That Became a System

In 1954, Danish toymaker Godtfred Kirk Christiansen and purchasing manager Troels Petersen made a profound observation about the toy industry.

“What an industry this is – no system of any kind whatsoever!”

At the time, toys were often standalone objects made from wood or metal. Each toy was designed for a specific purpose. You played with it as intended, and when the story ended, so did the play.

But following that conversation with Petersen, Christiansen began to approach toys differently. Instead of creating complete, “cut and dried” toys, he expanded upon an existing idea that had “fired his imagination.”

He noticed something special about a small plastic brick his company was producing. Individually, the bricks were simple. Combined, they became a system.

Today, that system is known as LEGO.

Each LEGO piece is connected through simple rules. But together they create complex structures. Children can build, break, and rebuild endlessly. A house could become a car. A car could become something entirely new. The outcome isn’t predefined; it emerges through play.

What LEGO discovered wasn’t just a new way to design toys. It was a new way to think about creation itself. And what makes LEGO such a powerful system is best described by a LEGO Group employee:

“The LEGO System means that: all elements fit together, can be used in multiple ways, can be built together. This means that bricks bought years ago will fit perfectly with bricks bought in the future… It means that a LEGO element not only has instant value, but will keep its value always… We will always make sure that all bricks – from yesterday, today and tomorrow – fit together.”3

The key takeaway is that LEGO is more than a construction system; it creates long-lasting value. Designers create sets ranging from City to Technic, each offering different forms of play and exploration. Once released, those sets become shared patterns that people repeat, reinterpret, and expand upon through play.

Through participation and reciprocity, new ideas spread across LEGO communities, showing how value resonates outward through interaction.

Beyond LEGO bricks, systems can be found everywhere – either waiting to be realised into something tangible or built from the ground up. Systems hold things together as environments, and each one shapes our journeys toward value.

Systems Are Everywhere

“A system is a set of things – people, cells, molecules, or whatever – interconnected in such a way that they produce their own pattern of behaviour over time.” – Donella H. Meadows.4

Meadows summarises the meaning of a system well. She describes a system as a set of interconnected parts organised through structure and relationships to achieve a goal or serve a particular function or purpose.

Systems exist all around us – and even within us. Your home is a system. Your car is a system. Your body is a system. Your cat is a system.

Products, services, organisations, cities, economies, nations, and cultures are all systems. Booking a doctor’s appointment is part of a system. Even breakfast is part of a system, in which relationships form between equipment, food, energy, and people working toward different outcomes.

But systems can also become dysfunctional when certain parts stop working or disappear altogether. You can’t make coffee without a cup or a working kettle. When one part breaks down, the effects ripple across the wider system.

Seeing the World Differently

Too often, we become trapped in surface-level details and lose sight of the bigger picture, unable to see the wood for the trees. But through a systems thinking lens, we begin to zoom out.

Instead of focusing only on isolated parts, we start to see relationships, dependencies, patterns, and movement across the whole.

Christiansen used systems thinking, whether consciously or not, to recognise a different kind of possibility in the humble LEGO brick. Without that shift in thinking, the LEGO Group may have continued producing standalone toys rather than interconnected systems of play.

But by understanding the relationships among the pieces, the company opened itself to multiple paths to innovation.

Over time, LEGO expanded into new themes, from fantasy to – my personal favourite – Pirates. Yet those themes still required coordination. New bricks had to remain compatible with existing ones, ensuring compatibility across product generations.

Seen this way, LEGO has maintained a remarkably consistent innovation narrative: the right system enables scalability, flexibility, and adaptability. In doing so, it reveals how separate parts connect into larger patterns of value and behaviour.

But LEGO is only one example. Systems exist in many different forms across the world around us.

Systems Take Many Forms

There are many ways of looking at systems.

• Biological: living systems made up of interconnected parts that work together to survive, adapt, and maintain balance.

• Ecological: natural environments where organisms, resources, and conditions interact through cycles of growth, decay, regeneration, and balance.

• Social: groups of people connected through relationships, shared behaviours, rituals, stories, norms, and repeated interaction over time.

• Organisational: structured groups such as businesses, schools, hospitals, and governments that coordinate roles, decisions, services, production, and responsibility.

• Functional: mechanical, technical, or operational systems designed to perform tasks, often with repeatable processes and interdependent parts.

• Conceptual: abstract systems of thought, belief, meaning, values, assumptions, and ideas that shape how we interpret the world and act within it.

Together, these lenses show that systems go beyond organisations or machines. They can be living, social, structural, functional, or conceptual. What connects them is not their form, but the relationships between their parts – and the patterns of behaviour those relationships produce.

And those relationships rarely exist in isolation.

Nothing Exists in Isolation

One of the core ideas behind general systems theory is that every system exists within a larger, interconnected framework. A solar system, for example, exists within a galaxy, which itself exists within the wider Universe. Well, perhaps the more interesting question is: what system might the Universe itself belong to?

“The Poached Egg“ diagram5 illustrates how systems exist within groups, layers, and hierarchies. A Universe is a larger system that houses many galaxies, which act as subsystems. Meanwhile, a system of interest is simply the particular system we choose to focus our attention on.

This is often where systems thinking starts giving people headaches. Complexity quickly expands in every direction. But part of systems thinking is learning how to make those relationships easier to understand in practice.

What a System Looks Like

To see this more clearly, let’s break down a booking service as an example. A system forms when multiple entities interact to achieve a shared objective. In this case, a booking system may include:

1. A website

2. Notifications

3. Digital tickets

4. Payment processing

5. Customer support

The customer sits at the centre of a booking system comprising interconnected subsystems, such as websites, notifications, payment processing, ticketing, and customer support. Together, these form part of larger organisational, technological, economic, and social systems.

The booking service may be part of a larger travel company. That travel company operates within economic, technological, environmental, and social systems. And those systems, in turn, interact with larger global systems.

Looking Beyond the Surface

The deeper we look, the more interconnected everything becomes. Systems can therefore be understood in many ways. Often, we connect different parts together without even realising we are working with a system.

Systems can become incredibly complicated. Yet their value lies in helping us see the interconnected parts shaping a machine, a hospital service, or even human behaviour itself.

In innovation, systems thinking helps us understand journeys not as isolated steps, but as dynamic patterns of causes, effects, feedback, and interaction.

A map may show the static structure of roads and destinations. Still, a systems lens reveals the relationships, movements, and feedback loops flowing through them. And this is where systems begin to move beyond structure alone. They start to influence behaviour itself.

Systems Shape Journeys. Journeys Shape Systems

We can now begin to understand systems as structure and journeys as movement. Systems hold elements together. Journeys, on the other hand, describe how those elements change, interact, and evolve over time.

A system without movement becomes static – like a forest with no life. But a journey without structure becomes chaotic and ungrounded – a living forest growing wildly beyond control.

Together, systems and journeys form a dynamic relationship that gives rise to behaviour. Systems create the conditions for movement, while journeys continuously reshape those conditions.

We can visualise the relationship between systems and journeys through the Journeys to Value Model (JVM). Systems create the conditions that shape journeys through structures, incentives, constraints, and interactions. As people move through those journeys, they produce outcomes and effects that generate feedback across the wider system.

Over time, that feedback can reshape both system conditions and behaviour, creating recurring patterns across organisations, communities, and everyday life. The JVM shows how systems influence movement and behaviour, while participation and experience reshape those systems in return – something LEGO demonstrates particularly well.

A System in Motion

LEGO inspires endless adventures through a system of play. Each journey tells a story of structure, arrangement, experimentation, and imagination. A pirate ship doesn’t have to sail across a carpet ocean; it can become a flying machine, a fortress, or a shipwreck island.

And every new journey created has the potential to challenge or expand the conditions set by the system.

When interacting with a LEGO set, people are effectively moving through journeys – making decisions, interpreting signals, coordinating with others, and experimenting through play.

In doing so, they generate feedback. Ideas are tested, adapted, and reshaped over time as people rebuild, repurpose, and recombine pieces into new possibilities.

When Systems Drift

Not every LEGO journey goes to plan, but most failed builds can simply be broken apart and rebuilt. Outside of play, however, misinterpretation and drift can become far more costly. That is exactly what happened when the LEGO Group came close to bankruptcy in the early 2000s.

Between 2003 and 2004, the company faced a severe financial crisis driven by over-diversification away from its core brick products, rising production costs, and debts reportedly exceeding $800 million.

In many ways, the company appeared to misread signals as it rapidly expanded. Over time, this led to structural drift and a shift away from its original purpose. The journeys within the organisation didn’t stop – they simply began heading in the wrong direction.

LEGO’s near collapse wasn’t caused by the system or the journeys alone. It emerged through the tension between the two. The company’s structures enabled expansion, while its innovation journeys pushed the organisation further away from coherence and sustainability.

Simply put: The system shaped the journeys, and the journeys reshaped the system in return.

LEGO avoided collapse by streamlining its product lines, selling off non-core businesses such as theme parks, and refocusing on profitable partnerships, like Star Wars. In doing so, it staged one of the most remarkable turnarounds in modern corporate history.6

Learning Through Adaptation

Looking across LEGO’s colourful history, we can see how systems thinking not only helped establish one of the world’s most-loved toy brands but also helped save it from catastrophe.

No matter how successful a company becomes, it must continue to learn and adapt. Because nothing truly stands still.

Ultimately, systems come alive through journeys. But those journeys also shape behaviour over time, influencing what becomes normal, what is repeated, what is rewarded, and what is ignored.

How Systems Shape Behaviour

Behaviours such as path fixation (staying on the same path too long), value mirage (mistaking signals for value), and story gap (disconnects between narratives and reality) emerge gradually through reinforcement, feedback, and systemic conditions.

But systems play an important role in shaping what behaviour becomes normal, rewarded, repeated, or suppressed – regardless of whether that behaviour is ultimately right or wrong.

A clear example of repeated and accepted behaviour can be found in desire paths.

Following the Worn Path

Desire paths are unplanned trails created by pedestrians or cyclists taking the route they perceive as the most direct or efficient between two points.

You’ll often see desire paths as dirt tracks cutting across grassy areas, parks, or even crop fields. They reveal how original designs frequently fail to match actual human behaviour and needs. But there is another layer to this interpretation.

When a behaviour – like walking a particular shortcut – is repeated enough times, it begins to feel like the expected behaviour. The worn path eventually starts to look like the “right” path.7

Desire paths don’t just reflect preference, but they also reflect acceptance through repetition. Some people follow these routes out of convenience. But others follow simply because the path already appears normal, proven, or socially validated.

This lesson is important for product and service teams analysing user journeys. If users frequently take a certain path, it doesn’t mean it’s well-designed; it may indicate friction, confusion, or attempts to bypass usability issues or bugs.

In other words, repeated behaviour does not always reveal what people truly want. Sometimes it reveals the conditions they have adapted to.

But the way we interpret those behaviours often exposes another problem entirely: how easily we confuse correlation with causation.

Looking Beyond Blame

When things go wrong, people naturally lean toward blame. We blame poor decisions, bad leadership, or a lack of discipline. But systems thinking asks a different question: What conditions made that behaviour more likely in the first place?

In The Fifth Discipline, Senge argues that organisations struggle to learn because they suffer from various “learning disabilities.” One of them – “The Enemy Is Out There” – describes the tendency to blame external people or forces when problems emerge.

Senge suggests this behaviour stems partly from another learning disability: “I Am My Position.” People become so focused on their specific role, responsibility, or boundary that they fail to see how their actions influence the wider system.

In other words, it becomes the familiar: “It’s them, not us.”

We hear this constantly in politics when current problems are blamed on previous governments. As Senge explains, “the enemy out there” is usually an incomplete story. If we focus only on what appears external, we rarely notice the deeper structural conditions operating internally.8

And those structural conditions often shape behaviour far more than we realise.

How Drift Becomes Normal

Systems regulate behaviour through incentives, constraints, feedback, visibility, and reward. Social media platforms make this especially visible. They shape what people pay attention to, what gets amplified, what gets ignored, and how behaviour becomes reinforced over time.

Much of this regulation occurs quietly, often outside conscious awareness.

It becomes normal to ignore the designated path because convenience feels rewarding. It becomes normal to endlessly scroll, like, and engage because algorithms respond with more of the same content. And as repetition continues, people gradually stop noticing drift.

We can now begin to see why path fixation, value mirage, and story gap become so prevalent within systems:

• A system that rewards consistency over reflection can gradually reinforce path fixation.

• A system dominated by metrics may encourage people to optimise signals rather than meaning.

• And a system that discourages difficult conversations can create gaps between what people say publicly and what they genuinely believe privately.

Once reinforced, these behaviours influence the larger system, and, in turn, the system shapes them. Over time, feedback loops can lead to escalation, with small distortions accumulating and systems drifting from their intended purpose.

In a forest ecosystem, trees, plants, and grass provide habitats for insects, birds, and mammals. These participants, in turn, pollinate plants, spread seeds, and help regenerate the wider environment, creating a balanced relationship.

But when a key part of the system is removed or significantly reduced, that balance can quickly break down.

Remove too many ladybirds, for example, and aphid populations can rapidly explode. Their growing numbers won’t simply reshape the environment; they can begin to destroy it, weaken plants, spread disease, and affect other species throughout the wider ecosystem.

What initially appears to be a small imbalance can eventually ripple across the whole system.

Human systems often struggle to maintain balance unless they intentionally learn and adapt. This is why Senge argues for the importance of learning organisations – systems capable of reflection, coordination, adaptation, and continuous learning.

But systems do not learn on their own. People participate in that learning process, too.

People Shape Systems Too

What we often call culture is frequently the behavioural expression of the system itself.

So whenever we hear someone say, “It’s the system” – blaming wider structures and conditions rather than focusing purely on individual behaviour – there is often truth in that statement.

Systems can absolutely shape what people believe is possible, acceptable, rewarded, or even worth pursuing. They can constrain behaviour, reinforce habits, and create dependency, leading people to feel trapped by the very systems they participate in.

But systems do not operate independently from people either.

Every decision, action, interaction, and repeated behaviour helps reinforce or reshape the wider system over time. In other words, people shape systems, while systems simultaneously shape people.

And that is why everything is connected.

Something to think about: What systems are shaping your behaviour – and how are your actions shaping those systems in return? Where might repetition, reinforcement, or drift be influencing the paths you follow?

Feel free to share your thoughts in the comments 👇

Leave a comment

As with any journey – in life and innovation – we look back on the paths we’ve taken and reflect on what happened along the way.

We ask what happened and what it means.

These reflections help us understand whether we’re making progress or simply moving. But reflection doesn’t happen in isolation. It’s something we share through storytelling. And when we share stories, we reinforce meaning.

In innovation, this becomes essential. It’s not enough to navigate journeys and generate outcomes – we need to communicate them clearly, so others can follow, contribute, and act.

Storytelling Completes the Journey

Theoretical physicist Richard Feynman had a remarkable ability to explain complex ideas simply.

During the investigation into the 1986 NASA Space Shuttle Challenger disaster, he played a crucial role in explaining the technical cause of the accident.

At a televised hearing, he demonstrated the failure of a rubber O-ring seal by placing a small sample into a glass of ice water. When exposed to cold temperatures, the material lost its elasticity.

Rather than relying on abstract engineering language, Feynman made the problem visible, something people could immediately understand.

As Will Storr explains in The Science of Storytelling, we experience life in story mode – instinctively seeking patterns, causes, effects, and resolution. Without these, meaning begins to fragment.1

When stories don’t connect, the narrative breaks down, and confusion sets in. But when they do – linking decisions, detours, and outcomes – journeys become something others can learn from and build upon.

That’s what storytelling does. It turns movement into shared meaning – and stories into narrative structure.

Journeys as Narratives

Our journeys to value aren’t just paths we follow; they’re also stories we construct to make sense of what’s happening.

Stories show what happened, narratives shape what it means, and value narratives guide what we do next. But those connections don’t always hold.

Story gaps begin to form when stories stretch the fabric of reality or fail to connect to a shared narrative. That’s when groups start to drift.

In organisations, alignment depends not just on the stories we tell, but on how well those stories connect.

It’s a bit like improv comedy. Performers can be funny individually, but when they don’t stay in sync, the performance falls apart. Strong coordination creates a shared narrative; too much focus on individual perspectives leads to fragmentation.

The same applies to innovation. Multiple teams contribute to different parts of a journey. But they’re not just building features, they’re also shaping a shared narrative.

Misalignment sets in, often only becoming visible later through inconsistent outputs or undesired outcomes.

These gaps not only emerge when people defend ideas, but also when teams interpret the narrative differently – or when one team stops working from it altogether.

Tools like user stories or Jobs-to-Be-Done (JTBD) help structure work by connecting actions to outcomes. But structure alone doesn’t create alignment – shared meaning does. And that meaning is carried through a narrative.

Journey orchestration and coordination exist to maintain that shared understanding – what’s happening, why it matters, and where things are heading.

When teams align around a shared purpose, stories stop competing and begin reinforcing one another. That’s how narratives hold systems together.

But product design is only one part of the picture. Stories extend far beyond it, shaping how we communicate, influence, and make sense of the world around us.

How We Tell Stories Changes Everything

Communication isn’t just about sharing meaning – it’s about what we do with that meaning. In storytelling, meaning can either resonate more powerfully or become distorted.

Stories can describe something specific – a task, a requirement, a function – or embody something broader, like a principle or value. Over time, these stories connect into narratives that give direction and meaning.

We see this clearly in how the same events can be told in different ways.

We can see that there’s not much to this. It’s functional, but a flat list.

Now see the difference between the two. The events haven’t changed, but the meaning has. The second version adds context: time pressure, expectation, and frustration. It helps us understand not just what happened, but why it mattered. That’s where value begins to surface.

The same applies to data. Individual data points rarely create understanding. It’s only when they’re connected into a story that meaning emerges.

Innovation journeys are made up of many stories, but telling them effectively requires shaping them into something others can understand, relate to, and act upon.

Beyond Product: Stories in the Wild

We also see the power of storytelling beyond product teams. In marketing, stories are used to embed brands into everyday life. The most effective campaigns go beyond features and benefits, drawing on humour, emotion, and cultural insight.

Patagonia’s “Don’t Buy This Jacket” campaign, for example, challenged consumption habits to reinforce its environmental values, strengthening both trust and identity.2

In politics, storytelling shapes how policies are understood and how narratives spread. Social media often simplifies and amplifies complex stories, sometimes omitting or distorting key details, which can lead to misinformation.

Whether intentional or not, these stories influence how people interpret reality. And when narratives diverge too far from the underlying truth, gaps begin to form – story gaps.

Value Narratives: What Stories Shape

Narratives don’t just help coordinate groups – they shape how we interpret what’s happening. They influence what we see, what we believe, and how we make sense of the journey.

Value narratives go one step further. They shape direction – what we choose to pursue, protect, or change.

Aligning Multiple Narratives

In organisations, these narratives guide strategy. Teams align around a shared understanding of value, while customers form their own narratives through lived experience.

What’s needed is a way to coordinate multiple narratives and make their relationships visible. Tools like journey maps or service blueprints help do exactly that. They show not just what customers experience, but what happens behind the scenes to enable it.3

But coordination alone isn’t enough. Holding multiple narratives together requires something deeper – a shared cultural narrative that shapes purpose, standards, and values.

We can also see this structure reflected in the Journeys to Value Model (JVM). What organisations describe as a vision or North Star acts as a value narrative, shaping what is explored and pursued. From there, values and principles guide action.

But this value narrative doesn’t simply sit at the beginning or end of the journey – it runs through it. It influences how scenarios are explored, how outcomes are interpreted, and how feedback reshapes the path forward.

In this sense, the JVM isn’t just a model of movement; it reflects how value narratives guide, adapt, and evolve across the entire journey.

When Narratives Harden

When that narrative is clear and shared, it binds people together through meaning and direction. But as Jonathan Haidt describes in The Righteous Mind, what binds us can also blind us.4

In some cases, narratives don’t just shape how we move forward – they’re used to reinterpret what’s already happened. Decisions are reframed, outcomes are justified, and missteps are explained away to preserve coherence.

As Annie Duke highlights in Thinking in Bets, the danger in decision-making lies in turning assumptions into beliefs.5 Left unchallenged, those beliefs shape future choices. The same applies at a collective level. Teams may appear aligned, but aligned to what?

Without reflection, teams can coordinate around the wrong narrative. That’s why learning is crucial to keep the narrative grounded in reality.

Beyond organisations, value narratives operate at a societal level, shaping culture, politics, and belief systems. They align people around shared meaning, but they can also divide.

The stronger the narrative, the more resistant it can become to challenge.

The Power of Storytelling and Value Narratives

The power of storytelling has stayed with me since my university days.

I had a lecturer, Alan Peacock, who had a knack for translating complex ideas into something that resonated. He often used simple analogies – even connecting theory to films like Blade Runner. (Yes, we really did watch movies in class.)

In one project, we were asked to explore whether the T-800 (Arnie) in Terminator 2 was capable of human emotion. We had to present our thesis using a prototype made from any materials we chose.

Many built intricate, almost mechanical models. Some looked like modern art. Mine? It looked like a toddler had made it. Pressed for time, I threw together a 4 x 6 box covered in printed paper, with two small holes on either side, each backed with tinted Perspex.

When I presented my abomination, my peers sniggered. I wouldn’t have blamed them – I probably would have bet against myself too. But I had one thing working in my favour: a story.

As I explained the thinking behind it, the mood shifted. Alan, slightly bemused at first, seemed genuinely engaged. In the end, it was the idea – not the artefact – that carried the work. I can’t remember exactly what he said, but it was something along the lines of “brilliant, but lazy.”6

That moment stuck with me.

You can spend hours perfecting something, but without substance, the story struggles to carry it.

Storytelling, then, is not just about expression. It’s about clarity, depth, and shared understanding.

Bringing It All Together

Up to this point, I’ve explored innovation as a journey – one that unfolds across multiple paths, requiring coordination and constant decision-making under uncertainty.

Storytelling – and the value narratives formed from those stories – bring all of this together. Stories show what happened, narratives shape what it means, and value narratives guide what we do next.

But they don’t just sit at the end of the journey; they help us reflect. They run through it. They shape how we plan, move, coordinate, and decide.

Because if journeys create value, then stories are how that value is understood, shared, and sustained.

Something to think about: What story is guiding your decisions? Are you aligning on shared meaning – or simply moving in parallel? And where might that story be drifting from reality?

Feel free to share your thoughts in the comments 👇

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British weather is predictably unpredictable. But we Brits still bet on whether it’s going to rain or shine anyway.

It might rain later – I’ll take an umbrella.
It looks clear – I’ll leave it at home.
The forecast says sun – I’ll plan the day around it.

These everyday decisions are small bets on the future.

Life and innovation will always involve risk. No matter how much we prepare, we’re bound to encounter unexpected outcomes – some favourable, others not so much.

Learning to Live with Risk

Some of my biggest risks in life have looked like this:

• Quitting my first university course to start another

• Leaving my job to travel the world

• Walking away from my design career to write a book

Quitting, as it turns out, isn’t failure – it’s often how change begins. Without change, we don’t progress. Without taking risks, we don’t discover what’s possible. And each choice carries potential reward and consequence.

Social psychologist Adam Grant describes how successful original thinkers approach risk:

“They are the ones who reluctantly tiptoe to the edge of a cliff, calculate the rate of descent, triple-check their parachutes, and set up a safety net at the bottom just in case.”1

What becomes clear is this: Risk isn’t something we can avoid. Even doing nothing carries risk. And that is what makes it so fundamental to our journeys to value.

The Risk Paradox

In life, risk is personal. In organisations, it becomes systematic.

Whether in finance, healthcare, procurement, or product design, decisions are rarely made without some form of evaluation. Organisations try to reduce uncertainty through structured evaluation, but there are limits to how much risk can be removed.

In the UK, only around 38% of businesses survive five years, meaning over 60% fail, according to the Office for National Statistics.2 Similar patterns can be seen in other economies. Despite careful planning, market research, and strategic intent, outcomes remain unpredictable.

To navigate this, organisations rely on structured approaches. In product design, for example, teams often assess ideas through a set of core risk lenses. In his book INSPIRED, Marty Cagan outlines four that help determine whether a product is worth building:

1. Value risk: Will people actually use or buy it?

2. Usability risk: Can users understand and use it effectively?

3. Feasibility risk: Can we build it with the resources and technology available?

4. Business viability risk: Does it make sense for the organisation?

Cagan also highlights two uncomfortable truths:

1. Half of the product ideas won’t pass these tests.

2. The other half typically requires multiple iterations to succeed.3

In that case, risk doesn’t disappear – it becomes visible.

In trying to reduce risk, organisations can become overly cautious – favouring certainty over exploration. Decisions become slower, ideas are filtered too early, and in some cases, the very mechanisms designed to manage risk begin to suppress opportunity.

Because risk is not just something to minimise – it’s something to work with. Too little risk leads to stagnation, whereas too much leads to instability.

The challenge then is not to eliminate risk entirely, but to engage with it intelligently, understanding where it sits, how it moves, and what it might enable.

This is where the nature of risk begins to shift. It’s no longer just a constraint on decision-making. It becomes a gateway to something else: opportunity.

Decisions as Bets

In the game of life, we’re not just navigating uncertainty – we’re constantly thinking in bets. In the book of the same name, Annie Duke, a former poker champion, explains what a bet really means: a decision about an uncertain future.4

Risk becomes less about outcomes and more about how we decide under uncertainty. The quality of our inputs – and the information that supports them – begins to matter far more.

Duke emphasises that poker isn’t about winning every hand, but about making good decisions over time. Innovation works much the same way.

A good outcome delivers favourable results from our inputs or investments. It can signal that our process is working. But Duke highlights an important catch: correlating the quality of an outcome with that of a decision can be misleading.

Known as resulting, this way of thinking draws us into the trap of judging decisions solely by their outcomes.

In other words, hitting the bullseye with your first throw doesn’t make you a skilled darts player – it might just make you lucky. And luck plays a role in innovation, just as it does in life. The problem arises when we assume our decisions were correct solely on the basis of the outcome.

At that point, we’re no longer learning – we’re resulting.

Hindsight is a Wonderful Thing

Drawing on her experience in high-stakes poker, Duke explains that resulting is a product of hindsight bias. It happens when we work backwards to explain what’s already happened.

We convince ourselves we “knew it all along”. But in reality, nothing in life or innovation is ever certain. With limited information, we’re always making informed guesses – and how we form those guesses shapes the outcomes that follow.

Duke puts it simply:

“What makes a decision great is not that it has a great outcome. A great decision is the result of a good process — and that process must include an attempt to accurately represent our own state of knowledge. That state of knowledge, in turn, is some variation of ‘I’m not sure.’”

To say “I’m not sure” is especially important. Because the moment we move from uncertainty to certainty – from “I’m not sure” to “I knew it” – we stop learning. And that’s exactly where resulting takes hold.

But resulting isn’t just a one-off mistake. It reveals something deeper about how we think. Our brains rely on shortcuts to make decisions quickly. These instincts help us act fast, but they also lead us to misread signals and see patterns that aren’t really there.

When we misread risk, we don’t just make poor decisions – we shape the paths we’re willing to take. Some opportunities are dismissed too early, while others are pursued with false confidence.

Which raises a deeper question:

What if risk isn’t just something to manage, but something we are constantly interpreting – and sometimes misinterpreting?

From Signals to Beliefs

That interpretation is where things begin to drift. Duke explains that the real danger in decision-making lies in turning an assumption into a belief.

When we interpret an outcome as a signal that a decision was good, we begin to treat it as something true. But, as Duke warns, “we would be making a mistake to use that outcome as a signal to repeat that decision in the future.”

We commit to a familiar strategy, gradually fixating on a single path towards illusory value. Over time, those decisions become ingrained as a belief.

This is how escalation begins. A positive outcome is interpreted as proof of a good decision, reinforcing that choice even when it may not be the best. As this pattern repeats, the path hardens, and alternative options fade from sight.

But when we begin to question our beliefs – and allow others to challenge them – something shifts.

We move from trying to be right to trying to understand. Instead of asking “Was that correct?”, we ask “What can we learn?” Whether an outcome is good or bad, it becomes a signal to interpret, not a conclusion to lock in.

This is where feedback becomes critical.

The Learning Loop

To prevent decisions from becoming too entrenched in our beliefs, Duke describes a learning loop in which we use outcomes to update what we know and how to shape future decisions.

In this loop, beliefs drive our bets. Those bets lead to outcomes, which we use to understand what actually drove them. Over time, what we learn reshapes our beliefs and reduces uncertainty.

As this loop repeats, learning compounds. The more we learn, the more opportunities we uncover – and the better equipped we are to navigate future decisions.

Even when outcomes don’t unfold as expected, they still carry value. The learning loop helps us examine what drove those outcomes – whether it was skill, luck, or a combination of the two. And this is where a subtle challenge emerges.

If we attribute success entirely to decision, we risk overlooking flaws in our process. If we attribute it entirely to luck, we miss the opportunity to understand what worked. In reality, most outcomes sit somewhere in between.

To make sense of them, we need different forms of insight that help us understand not just what happened, but why it happened. Doing so gives us stronger signals to recalibrate our beliefs, improve our decisions, and better navigate risk.

In this sense, learning becomes the mechanism through which uncertainty is interpreted – not eliminated. Each outcome feeds back into how we see the world, shaping the bets we make next.

But if learning helps us interpret risk more clearly, it raises another question: how do we act on that understanding?

From Risk to Opportunity

If learning helps us interpret risk more clearly, the next step is to act on that understanding. At its core, experimentation is a form of risk management. It helps teams reduce uncertainty by generating evidence.

However, testing only one idea is a risk – it’s a single bet.

The more we experiment across different variations, the more insight we generate. To counter false positives and false negatives, teams can diversify their experiments – testing multiple hypotheses in parallel.

While this doesn’t guarantee the right answer, it increases the probability of making a better-informed decision when ideas are put into practice.

Even then, quantitative, statistical evidence only tells part of the story. In digital environments, A/B testing and multivariate testing (MVT) help us understand what performs better. But they rarely explain why.

Understanding why is critical. Why do users move towards one outcome over another? Why does one path resonate while others fall away?

This is where qualitative insight becomes essential.

Ethnographic research, for example, immerses teams in real-world contexts – observing behaviours, interactions, and cultures firsthand. Through interviews, observation, and participation, it reveals the underlying drivers behind outcomes.

But no single method is sufficient on its own.

Quantitative data tells us what is happening. Qualitative insight helps us understand why. Together, they give us a clearer signal. By combining methods, we don’t eliminate uncertainty, but we reduce it.

We move from guessing to informed judgment. And that’s where the shift happens. Risk is no longer just something to manage – it becomes something we can explore.

Each experiment, each signal, and each insight opens up new possibilities. Instead of committing to a single path too early, we create space for multiple paths to emerge.

In doing so, we avoid illusory value and the trap of fixation. We don’t just follow a path – we shape it through what we choose to explore.

Breaking the Problem Down

If experimentation is how we act on uncertainty, then how we frame the problem becomes just as important.

Agile methodologies such as MVP and Lean are often used as risk strategies. The intention is to reduce risk, but teams end up focusing on efficiency rather than exploring to validate an idea. It’s like trying to squeeze an elephant through a door by cutting it into pieces, but without ever asking if it’s the right animal.

That’s not agility. That’s reacting.

True agility is about testing viability, not shrinking delivery. Airbnb’s founders didn’t build a full platform in stages; they tested demand by renting out their own apartment. And Dropbox didn’t start with a complex product either; they used a simple video to validate interest.

In both cases, the goal wasn’t to incrementally build a solution, but to learn whether the solution should exist at all.

In this sense, agile becomes a way of generating leading signals – helping teams navigate uncertainty before committing to a path. But as we’ve seen, the moment learning is replaced by commitment, the dynamic shifts.

What begins as an assumption can quickly harden into commitment. Teams invest time, resources, and belief into an idea, making it harder to step away.

This is where escalation begins to take hold, not because the evidence is getting stronger, but because the commitment is. As confidence grows, even without support, teams double down. Then the path becomes harder to question, and before long, they’re no longer exploring value – they’re chasing it.

I’ve seen this pattern play out many times. A team builds confidence in an idea by framing it as a “low-risk” MVP. But…

Faster delivery can generate faster feedback. But if the team is solving the wrong problem, that feedback is either irrelevant or misleading.

In reality, limited understanding increases uncertainty. A team that builds a single MVP without exploring alternatives is effectively placing a large bet on a single outcome. And when that bet doesn’t pay off, they’re left with a difficult choice: double down, or change direction.

Especially under pressure – time, cost, or expectation – many choose to persist, even when the signals suggest otherwise.

That isn’t measured risk. It’s an amplified risk.

By contrast, teams that invest in understanding the problem – exploring multiple possibilities, testing different assumptions – are better equipped to navigate uncertainty. They don’t eliminate risk, but they distribute it more intelligently.

Even with the best planning, uncertainty remains. Whether we’re testing an idea, building an MVP, or navigating an entire journey, we cannot fully predict what will happen. Even validated ideas can fail. Every decision carries risk. The difference lies in how we choose to engage with it.

Love and Excellence

How we engage with risk doesn’t just shape what we explore, but it also shapes what we create. It’s one thing to navigate uncertainty and uncover opportunity. It’s another to turn that opportunity into something meaningful.

We can still manage risk and explore opportunity, but the question becomes: what are we aiming to create?

Love and excellence shift the focus from speed and quantity to quality and depth. Rather than rushing products through a pipeline only to fix them later, we invest time and care into making them reliable, thoughtful, and lasting.

This mindset shows up in systems like the Toyota Production System, where quality isn’t inspected at the end – it’s built in from the start through continuous improvement and care.

Principles like Just-in-Time, Jidoka (automation with a human touch), and continuous improvement (Kaizen) ensure quality is built into the process from the start.

In this sense, quality becomes a powerful leverage point for shaping the value that emerges from our decisions. It reflects not just how something functions, but how it is experienced: how it looks, feels, performs, and endures.

Of course, quality is often associated with higher cost. But as Toyota demonstrates, it doesn’t have to come at the expense of efficiency. By embedding care into processes – and empowering people to act on it – systems can reduce waste while increasing value.

That way, “Love” shows up as care – attention to detail, intention, and quality at every step.

Without it, ideas may function, but they rarely satisfy. Value is diminished, and sometimes lost entirely.

The real risk, then, is not just failure, but creating something that never truly mattered in the first place.

Seen through the lens of risk, the meaning of journeys to value begins to shift. We’re not just navigating towards a single outcome or coordinating multiple journeys to reach it. We’re creating and navigating multiple paths, increasing our chances of discovering the value we’re actually looking for.

Something to think about: How are you making your bets? Are you learning from the outcomes, or mistaking them for proof? And where might you be underestimating risk, or missing opportunity?

Feel free to share your thoughts in the comments 👇

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Innovation involves navigating many journeys. If driving one route is stressful enough, try coordinating several at once.

Without coordination, teams drift, interpretations vary, and coherence is lost – even when people are doing everything the right way.

But coordination doesn’t command. It brings movement into alignment, shaping how decisions connect as journeys unfold.

The Limits of Planning

It makes perfect sense to begin a journey with a plan. In innovation, that often means mapping out the steps required to reach a desired outcome.

We ask:
How do we get there?
What do we need to do?

Project management tools like Gantt charts and roadmaps help align activities with milestones and time constraints. But these planning-first models are built on an assumption of certainty. In reality, nothing ever goes exactly according to plan.

Even when plans succeed, it’s often because timing and context happen to align. Outcomes also mislead us – some signals are delayed, others are difficult to measure, and some turn out to be false positives.

As Matt Watkinson puts it in Mastering Uncertainty:

“If we can’t predict our journeys entirely, then we can’t formulate the perfect plan.”1

But unpredictability isn’t the only challenge.

Errors often stem from situational factors. Poor inputs – like faulty assumptions or flawed design – can lead to unintended outcomes. As Watkinson notes, these effects are often invisible until they combine with certain conditions, triggering negative events.

In other words, results often don’t match our intentions – and we’re not very good at anticipating all possible outcomes.

(Few would have predicted a robot vacuum smearing dog faeces across a carpet while a dog looks on.)

Instead of trying to control the future, we need to prepare for change.

One helpful lens is VUCA – a world shaped by volatility, uncertainty, complexity, and ambiguity. In this kind of environment, planning becomes less about prediction and more about adaptation.

While we can’t predict exactly how the future will unfold, we can still prepare for multiple possibilities. One way of doing this is through scenario planning.

Planning for Possibility and Probability

Planning is not about choosing a single path – it’s about understanding possible paths. In doing so, we reduce the risk of fixation and keep learning alive.

Because the path will change. Planning simply prepares us to adapt when it does.

When we plan ahead, we aim to explore multiple futures, prepare for uncertainty, and keep options open. One framework that enables all three is scenario planning.

As the name suggests, it helps organisations make flexible, long-term decisions by exploring and preparing for possible future scenarios. At its core, scenario planning involves:

1. Identifying driving forces: Spot the major external trends – social, technological, economic, environmental, and political – that could shape the future.

2. Identifying critical uncertainties: Narrow these down to the 2–3 factors that are both highly uncertain and highly impactful (e.g. AI adoption speed, regulatory shifts).

3. Developing plausible scenarios: Create 3–4 distinct and coherent future worlds by combining different outcomes of those uncertainties.

4. Exploring implications and paths: Consider how strategies might play out in each scenario. Identify robust actions, early signals, risks, and opportunities for innovation.

Scenario planning often involves a significant effort to gather data, identify drivers, and construct scenarios. However, by considering multiple potential futures, we can prepare for risks and opportunities rather than just react.

Because conditions change, scenario planning should be treated as a living process – continuously updated as assumptions evolve.

Even when it isn’t applied explicitly, elements of scenario thinking often appear in practice. In product management, for example, OKRs are used to define future goals. Objectives can reflect driving forces, while key results hint at expected outcomes and implications.

If planning involves looking forward, we also need a way of looking back. That’s where analysis comes into play.

Analysis as Sensemaking

If planning explores what might happen, analysis helps us understand what is happening.

Analysis involves examining a sequence of events to understand how our actions lead to outputs, outcomes, and impacts. In doing so, we begin to see what value has been realised – and what has been missed.

One useful technique for guiding this process is cause-and-effect analysis.

We ask:
How did we get here?
What actions led to this result?

These questions help us track progress, interpret signals, and understand relationships. They especially help drive innovation by uncovering root causes and enabling more targeted action.

Cause-and-effect analysis is often visualised as a fishbone diagram, where a central problem is traced back to multiple contributing causes. At its simplest, the process involves:

1. Tracing the effect (or problem) back to multiple possible causes

2. Identifying root causes and taking action to address them

Like scenario planning, cause-and-effect analysis can require significant effort to gather data, identify contributing factors, and map relationships. But the value lies in shifting perspective.

It becomes even more powerful when we combine different forms of analysis. Instead of relying solely on quantitative metrics – such as spreadsheets or traffic data – we also incorporate qualitative insight into behaviours: how people act (and don’t act).

We now have two complementary ways of thinking: one that looks forward, and one that looks back. But journeys to value don’t unfold in a single direction – they move across time.

Through analysis, we begin to make sense of what has happened. We trace actions, uncover relationships, and interpret outcomes. But those outcomes don’t reveal themselves all at once.

Some appear early, offering hints about where a journey is heading. Whereas others emerge later, revealing the deeper consequences of what has already happened.

To navigate effectively, we need to understand not just what we’re seeing – but when it appears, and how those moments connect over time.

Reading Signals Across Time

Outcomes don’t reveal themselves all at once. Some appear immediately – a click here, a drop-off there – while others take time to unfold.

In this sense, outcomes act as both leading and lagging signals.

Leading signals provide early feedback, helping us adjust direction while the journey is still unfolding. Lagging signals, on the other hand, help us understand the longer-term, stronger effects of our decisions.

If we rely only on lagging signals, we risk reacting too late – after patterns have already taken hold. But by paying attention to leading signals, we can begin to adapt earlier, while there is still room to change course.

The challenge, then, is not just collecting signals, but interpreting them – understanding what they mean, how they relate across time, and when they warrant action.

Signals, on their own, are just observations. It is through analysis that they become insight – helping us make sense of what is happening, and what might happen next.

The Planning–Analysis Loop

Many teams make the mistake of separating planning and analysis. Planning without analysis can lead to drifting into assumptions, while analysis without planning can result in observation without action.

The two modes work best when combined as part of a planning-analysis loop:

• Planning explores potential value

• Action creates signals of value

• Analysis interprets those signals

• Insights reshape the path to value

What emerges is a continuous learning loop. As we move between planning and analysis, we uncover new ways to navigate our journeys and adjust direction as we go.

Plans, then, aren’t fixed – they evolve with the journey.

Much like the Double Diamond, we diverge and converge across different paths – analysing progress, then planning new directions.

During planning, we ask:
What steps could we take to reach our desired outcomes?

During analysis, we ask:
What steps led us to where we are now?

Importantly, the loop doesn’t have a fixed starting point. We don’t always plan first and analyse later. Instead, we begin where it makes most sense.

For example, a team addressing customer retention might start by conducting a cause-and-effect analysis to understand historical churn. They can then use scenario planning to see how future market or technological shifts could affect their strategies.

Working backwards is often especially valuable in problems involving customer experience. This approach echoes Steve Jobs’ idea of starting with the customer and working back to the technology.

But even when planning and analysis work together, another challenge remains: the signals we rely on don’t arrive at the same time.

Modelling Journeys to Value

Innovation unfolds in complex and often unpredictable ways, making planning and analysis difficult to navigate in practice.

To make this more actionable, we can combine scenario planning with cause-and-effect analysis into a simple three-column structure:

1. Driving forces: Inputs, activities, or initiatives that shape the direction of scenarios

2. Scenarios: Key points in the journey where actions take place and paths begin to diverge

3. Outcomes: The short- and long-term effects that emerge from those scenarios

I refer to this as the Journeys to Value Model (JVM) – a way of understanding how value is explored, shaped, and realised across multiple, interconnected journeys.

Rather than a fixed process, the model reflects a dynamic system continuously reshaped through feedback and learning.

At a glance, it forms a continuous cycle:

• Planning explores what might happen

• Analysis reflects on what has happened

• Feedback connects the two, informing what happens next

In this way, value is not just discovered – it is navigated, shaped, and continuously redefined over time.

The JVM also helps distinguish between realised value (what has been achieved) and unrealised value (what remains possible). This creates two complementary modes of working:

• Prospective (Planning & Predicting): exploring future paths and anticipating value

• Retrospective (Reviewing & Analysing): reviewing past outcomes to uncover insight

By combining both, we align foresight with reflection – strengthening how decisions are made and adjusted over time. Without this balance, we risk following paths that lead us away from value, with little ability to recognise or correct course.

To keep these elements aligned in motion, we need something that connects them. This is where orchestration comes in.

Orchestration: Coordinating the Journey

Orchestration aligns planning, analysis, feedback, and action into coherence – continuously, and in real time.

Timing is crucial, but how we act on our interpretations matters just as much. A small shift in understanding can distort an escalation loop and send it off course, like one instrument falling out of sync and affecting the entire system.

The JVM then becomes a guiding tool – helping us track movement, interpret signals, and adjust direction as we go.

But this kind of coordination isn’t just theoretical – it shows up in practice in more domain-specific forms.

Orchestration in Practice

In customer experience, this appears as customer journey orchestration (CJO) – a domain-specific application of orchestration focused on coordinating experiences in real time.

Rather than relying on static journey maps or personas, CJO uses real-time data to understand individual needs and preferences.

This enables organisations to deliver the right message, at the right time, through the right channel – creating a more adaptive and responsive experience.

At its core, CJO operates as a continuous loop:

1. Data collection and integration: Signals are gathered across touchpoints and unified into a coherent view.

2. Real-time analysis: Behaviour is monitored as it unfolds, revealing intent, context, and friction points.

3. Orchestration across channels: Signals inform personalised actions across multiple channels and journeys.

These steps reflect the same learning loop we explored earlier, in which signals are interpreted and used to guide action. But the cycle extends further with AI, machine learning, and continuous optimisation:

1. AI and machine learning: Enable prediction, automation, and personalisation at scale, while continuously identifying emerging patterns.

2. Continuous optimisation: Uses feedback to refine actions over time, ensuring journeys remain aligned with changing needs.

Feedback provides insight, but AI and machine learning accelerate our response time. It’s no longer about coordinating a single journey, but many – simultaneously and at scale.2

But orchestration isn’t limited to customer experience – it reveals something more fundamental about how coordination works, especially when multiple participants are adapting at the same time.

When Adaptation Drifts Apart

Orchestration is an active, ongoing process involving many participants. Each continuously adjusts its journey to value – but not always in coordination with others.

As Independent Systems Architect Samir Bico explains, problems don’t just arise from poor coordination, but from how systems adapt over time:

When teams adapt asynchronously, their representations, assumptions, and decision rules begin to diverge – resulting in systemic misalignment.3

Each part of the system may remain locally consistent within its own update cycle, but those cycles are no longer aligned. What appears coherent in isolation begins to drift in combination.

This raises an important question: if adaptation itself can create misalignment, how do we coordinate it?

Journey Management: Putting Orchestration into Practice

If orchestration coordinates journeys in motion, then journey management helps stabilise them over time.

They are closely related, but serve different roles. Management focuses on monitoring and optimising journeys using data, insight, and feedback. Like journey mapping, it typically operates outside of real time.

To understand what journey management embodies, we can turn to a description by Systems Thinker Thomas Wilson:

“[Journey management] operationalizes empathy at scale, builds bridges between insight and execution, and most importantly, centers every decision around the true narrator of the story: the customer or colleague themselves.”4

Wilson’s description highlights an important point: management doesn’t control – it facilitates alignment over time.

“Empathy at scale” suggests insight is shared across the system, enabling teams to better understand needs and context.

“Bridges between insight and execution” reflects how ideas move through journeys – from signal to action, through decision points.

Most importantly, journey management focuses on the storytellers – the individuals experiencing the journey. Customers, colleagues, and partners shape how the journey unfolds. While managers can influence the environment, they cannot control behaviour.

Overall, journey management provides structure and alignment over time, while orchestration builds on this by coordinating multiple journeys in real time.

Together, they form a complementary system:

• Management provides structure, reflection, and alignment – creating the conditions for better decisions.

• Orchestration provides coordination, responsiveness, and adaptation in motion.

Managing Movement in Motion

Journey orchestration is about managing movement in real time – adjusting direction in response to feedback as signals unfold. In doing so, journeys become dynamic, shaped by pace, intensity, and interaction.

It allows us to align teams and signals, navigate trade-offs, and maintain coherence across moving parts.

This movement draws on different capabilities – exploring possibilities, making sense of signals, and translating insight into action – often shifting between them as journeys unfold.

The JVM offers a way to support this. It visualises the planning–analysis loop, whether working prospectively or retrospectively, helping us navigate journeys in a structured yet flexible way.

More than a tool, it reflects a mindset – understanding how value emerges through movement, decisions, and experience over time.

Movement alone isn’t enough.

Every journey carries uncertainty, opens up possibilities, and reflects the care we bring to it. To understand how value is created – and why it sometimes fails to emerge – we need to look more closely at the forces shaping our decisions:

Risk, opportunity, and the role of care in defining quality.

Something to think about: How well are your journeys coordinated – across teams, decisions, and time? Are you adapting in alignment, or drifting out of sync? And where could better planning, analysis, or feedback help you adjust direction earlier?

Feel free to share your thoughts in the comments 👇

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Innovation is a journey full of signals – but we don’t always read them correctly.

Instead, we interpret them through assumptions, metrics, and momentum – often mistaking progress for value.

So how do we make sense of what’s really happening as a journey unfolds?

To navigate that journey, we need a way to read those signals – to understand what they mean as we move.

That’s where four interconnected elements come in.

Four Navigation Lenses

Journeys typically follow a path with a beginning, an end, and some milestones. In innovation, a journey tends to evolve through interconnected elements, including:

1. Inputs: signals, ideas, resources, and intentions

2. Outputs: the actions we take and what we produce along the way

3. Outcomes: the immediate effects of those actions

4. Impacts: the longer-term changes that unfold over time

At first glance, these elements may appear sequential. But in practice, they overlap, loop, and continuously influence one another.

One way to understand them is to see them as navigation lenses.

Wherever we are in the journey, we can shift our perspective to see what’s happening – where we are, what’s changing, and how value is being realised.

Through this lens, we begin to notice how outputs reshape inputs, outcomes alter direction, and impacts reveal meaning long after decisions are made.

A journey, then, is not a straight line from input to impact. Rather, it’s a dynamic system of movement in which each element feeds back into the next – continuously shaping the path as we move.

This is where feedback starts to matter – shaping direction before paths become fixed.

Let’s take a look at each journey element.

Making Sense of the Mess

Just as spaghetti twists, overlaps, and coils in unpredictable ways, the journey elements – inputs, outputs, outcomes, and impacts – rarely sit in a neat order. There is no clear beginning or end – only movement.

Innovation doesn’t follow a fixed sequence. We don’t move cleanly from inputs to outputs, then to outcomes and impacts. Instead, we operate across them simultaneously, often acting before we fully understand what just happened.

These elements are not steps, but states we move between. So rather than asking “What comes next?”, a more useful question is:

“What’s happening now – and how is it influencing everything else?”

Inputs

Inputs are the signals or decisions that initiate movement – ideas, intentions, or interpretations that can quickly accumulate into larger consequences.

Used well, inputs guide discovery. But used poorly, they become noise – superficial changes made for optics rather than understanding. Progress may appear visible, yet learning stalls quietly.

Outputs

Outputs are what inputs produce – tangible actions or artefacts such as insights, prototypes, code, or features.

But outputs don’t create change on their own – they only matter when they influence behaviour. When teams focus on volume instead of meaning, they drift into “feature factory” thinking – producing more, but learning less.

Outcomes

Outcomes reflect the changes that result from what we build. When Steve Jobs said, “Start with the customer experience and work backwards to the technology,” he pointed towards this way of thinking.

Later, product leaders attempted to define outcomes more explicitly. In Outcomes Over Output, Joshua Seiden describes an outcome as:

“A change in human behaviour that drives business results.”1

These shifts can range from improved decision-making to greater trust or accessibility.

But not all outcomes are inherently valuable – even when they appear to be progress. They are immediate effects – and their meaning depends on how we interpret them. The longer-term consequences of these effects are what we call impacts.

Impacts

Impacts reflect the longer-term changes that unfold over time. A poor experience may erode trust, while repeated frustrations can compound into something larger.

Unlike outcomes, impacts rarely come from a single event. They emerge through accumulation – patterns that build and reinforce over time.

This is where journeys truly evolve. While we often optimise for immediate outcomes, it is the long-term impacts that reveal whether value has been sustained – or quietly eroded.

Joining the Dots

Connecting these journey elements is like joining the dots to reveal a bigger picture. Frameworks attempt to do exactly that – helping us understand how actions lead to results.

Two examples illustrate different approaches.

Program Logic Model (PLM)

In 1998, the W.K. Kellogg Foundation introduced the PLM to connect planned work to outcomes. It provides a structured way to identify gaps and adjust direction as learning emerges.

The model consists of interconnected elements:

1. Inputs: People, materials, funding

2. Activities: Actions and processes

3. Outputs: Direct products

4. Outcomes: Changes in behaviour or conditions

5. Impact: Longer-term results

At its core, the PLM connects what teams do with the changes they hope to achieve. Let’s consider how it might work in a school facing high dropout rates that implements a mentoring programme.

Inputs (coordinator, mentors, funding) support activities like mentoring and workshops, producing outputs such as participation. These lead to outcomes like increased confidence and attendance, and over time, impacts such as higher graduation rates.

The PLM clearly connects effort to results. But reality is rarely so orderly. Journeys drift as inputs and activities evolve. Some outputs won’t produce expected outcomes, and outcomes may fall short of intended impacts.

When this happens, the model isn’t wrong – it needs revisiting. Learning becomes essential, and feedback helps teams adapt and adjust direction.

The PLM mirrors the journey elements but presents them in a structured, sequential form. That structure is useful – as long as we remember real journeys are more fluid.

Outcome-Driven Innovation (ODI)

In the 1980s, Tony Ulwick developed Outcome-Driven Innovation (ODI) after recognising that there was too much focus on ideas and not enough on customer needs.

Closely related is Jobs-to-Be-Done (JTBD), popularised by Clayton Christensen. At its core, JTBD suggests people “hire” products to get a job done – for the outcome they enable.

Innovation, then, shifts from building solutions to understanding what people are trying to achieve. This leads to clearer expressions of need, such as:

These statements capture the situation, the job, and the desired outcome – without prescribing a solution. And they unfold through a process:

1. Define the market around the job

2. Uncover desired outcomes

3. Identify unmet needs

4. Discover opportunity segments

5. Formulate and deploy a strategy2

Early stages explore possibilities; later stages narrow toward strategic decisions. While impacts are not explicitly defined, they can be understood as the longer-term effects of outcomes.

What sets ODI apart is its focus on needs over inputs and outputs. It encourages teams to identify unmet outcomes and revisit assumptions as new insights emerge.

Seen this way, ODI offers a grounded way to navigate journeys to value – beginning with understanding rather than execution.

But there’s a tension. Focusing too heavily on outcomes – and even impacts – can introduce its own challenges.

The Flaws of “Outcomes over Outputs”

Different frameworks offer different approaches – some for community projects, others for product development. In each case, outcomes and impacts are the ultimate success criteria.

But even the outcome-oriented paradigm has its limitations. In some cases, it can quietly reinforce the very behaviours it aims to avoid – including a return to feature factory thinking.

Jens-Fabian Goetzmann, Head of Product at RevenueCat, explains why.3

1. Chasing the “Right” Outcome

Many product teams misinterpret “Outcomes over Outputs” as executing a single hypothesis perfectly. A lot of effort goes into finding the “right” solution, but in reality, most ideas fail.

Success in creative work relies on practice and variability. Teams improve by exploring multiple variations of an idea. The more they test, the more likely they are to discover what works.

This is fundamental to product design. Working on a single version is like trying to hit a bullseye with one dart. Throwing more darts increases the chances of success through prototypes, experiments, and tests.

Seen this way, achieving meaningful outcomes often requires producing more outputs – not fewer.

2. Outcomes Become Unreliable Signals

Not all outcomes are easily measurable. Those that are can drive short-termism, where teams start gaming the numbers.

In venture contexts, outcomes may take years to emerge, making them unreliable short-term signals. This shifts focus back to inputs. In uncertain or long-term work, the quality of inputs – research, data, and decision-making – becomes critical for guiding direction.

3. Mistaking Outcomes for Value

Focusing too heavily on outcomes can lead to false positives – results that appear promising yet still fail. Often, this comes down to weak inputs or poor execution.

This highlights a simple truth: outcomes alone don’t tell the full story.

Innovation, then, can’t be reduced to results. It depends on how inputs, outputs, outcomes, and impacts interact – and how we interpret them along the way.

Quality inputs shape better outputs. Those outputs increase the likelihood of meaningful outcomes, which influence longer-term impacts.

But there is one more element at the centre of it all: feedback.

Learning is the Real Leverage Point

Having identified the flaws in the outcome-oriented mindset, Goetzmann calls for product teams to complete the innovation cycle with a feedback loop. This mechanism connects outcomes back to inputs, turning results into lessons that inform the next iteration.

Feedback as a Learning Mechanism

When we introduce feedback, we enable learning. The more we learn, the better we can navigate our journeys. The real leverage point, therefore, does not sit at the endpoint of outcomes, but within the “messy middle” – the journey itself.

Many failures – even disasters – share a common pattern: feedback is ignored, delayed, or suppressed. Opportunities to question, challenge, or adapt are missed, and learning collapses.

When this happens, systems drift – often gradually at first, then all at once – toward failure.

Illusory Leverage Points

But even feedback can misguide. Surface-level metrics, such as satisfaction scores, offer a snapshot of sentiment at the end of a journey, yet reveal little about the deeper reasons behind behaviour.

Chasing these signals can feel productive. Positive scores make a product appear “successful,” even “loved.” But this creates a false sense of progress – an illusory leverage point.

That illusion can quickly embed itself within an escalation loop. Metrics begin to dictate what gets repeated, defended, funded, prioritised, and scaled. As commitment grows, teams double down. If scores dip, optimisation intensifies. If scores rise, complacency sets in.

Either way, the system begins to orbit the metric rather than the reality it was meant to represent. Teams risk mistaking signal for substance.

Feedback is an Untapped Goldmine

Events from the past – and patterns in the present – reinforce the risks of focusing solely on outcomes. Reacting only to what worked and what didn’t can miss the deeper signals shaping the journey. But when feedback is treated as a true leverage point, something shifts.

We begin to adjust direction earlier – before decisions harden, paths become fixed, and escalation takes hold.

Seen this way, the messy middle becomes an untapped goldmine. By contrast, focusing only on surface signals is like searching for tiny fragments with a metal detector – occasionally useful, but largely blind to what lies beneath.

Journey navigation, then, is not about control. It is about responsiveness – to signals, context, and the evolving meaning of value.

Reframing the System Around Feedback

Now that we understand feedback as a core element of the journey, we can rethink how the system is structured.

Rather than sitting at the end of a linear process, feedback becomes a central, resonant core. Inputs, outputs, outcomes, and impacts all feed into this core, which in turn redistributes learning across the system.

Inputs and outputs no longer appear as singular steps, but as distributed elements – emerging from multiple directions, like cells within a living system. Information flows continuously, rather than sequentially.

From this perspective, the feedback loop does more than connect stages. It orchestrates them. And it is this orchestration – not control – that enables systems to remain adaptive, coherent, and alive.

Orchestrating Journeys to Value

To navigate a journey to value, we don’t just need direction – we need awareness of how value forms, shifts, and reveals itself along the way. And that awareness arises through feedback.

But information, insight, and signals don’t move on their own. They rely on people to receive, interpret, synthesise, and translate them – shaping how they flow through the system.

In this sense, navigating a journey is less like following a map and more like conducting an orchestra. Different signals emerge from different places, at different times. Without coordination, they remain noise. With orchestration, they begin to form coherence.

This is where the journey begins to evolve – from direction and awareness into orchestration.

Something to think about: How are you reading your journey – reacting to surface signals, or learning from what lies beneath? And where could feedback help you adjust direction early?

Feel free to share your thoughts in the comments 👇

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Post-it notes are a proven office necessity. They let us quickly jot down ideas or capture moments that unfold during a journey. They also make pretty office confetti, albeit annoying for the manager who prefers clean, pristine white walls.

While we use them every day without a second thought, they only became valuable after years of iteration and reframing – and even through “happy accidents.”

In this post, we’ll explore how value emerges through journeys – often in ways we don’t expect.

From Weak Signal to Everyday Staple

In 1968, scientist Spencer Silver aimed to create a super-strong adhesive, but instead developed a weak, reusable glue that seemed useless for years. Everything changed when his colleague Arthur Fry used it to mark pages in his choir book, discovering its true potential.

Even then, the journey wasn’t straightforward. There was internal resistance, failed launches, and uncertainty around its usefulness. But over time, through experimentation, reframing, and even free sampling campaigns, the idea gained traction.

What began as a failed experiment became the Post-it Note – now a staple of offices around the world, including my own desk.

It’s a clear example of how a weak signal can strengthen over time. More broadly, it shows how ideas, inventions, and innovations unfold through a continuous process of interpretation, experimentation, and learning.

Many only reveal their value over time – through iteration, reinterpretation, and use. As they evolve, so too does our understanding of them.

Journeys represent the paths we travel. They shape how we plan, reflect, and make sense of the world – and how we come to understand where value lies. Above all, they are what we experience.

As a journey unfolds, we learn more about our ideas, our work, and even ourselves. Sometimes we begin with a clear sense of value, but that notion can shift – or drift – over time. Other times, it can feel as though we’re simply stumbling forward.

But the most important part of any journey isn’t the destination – it’s what we learn along the way.

We don’t follow just one path. We move through many – sometimes hundreds or thousands – both physically and metaphorically. Thinking in journeys means navigating multiple paths at once.

And through those paths, we begin to realise the value in our actions – whether intentional or not.

Innovation, in particular, is a journey that continually evolves. It bends, turns, and branches, often leading to multiple outcomes – some expected, others not. And there’s a nostalgic racing video game that offers a useful way to visualise how these journeys unfold.

Let’s take it for a spin.

Seeing the Journey as a Racing Adventure

We can see a journey as beginning with a narrow, dusty track that gradually widens into a highway, connecting multiple places over time. An innovation journey unfolds in a similar way. And one way to visualise this is through the classic 1986 arcade driving game Out Run.1

The game’s premise is straightforward: you drive a red Ferrari Testarossa Spider, racing against the clock through a series of stages. Along the way, you encounter forks in the road, choosing different routes that lead to one of several distinct endings.

Innovation journeys share similar characteristics. The game itself is a system – a structured environment in which movement takes place. The Ferrari represents an idea moving through that system. And the journey is about navigating those branching paths under pressure.

At key points, players choose between routes, shaping the direction of their journey. This balance between precision and mess reflects how many innovation journeys unfold – guided by constraints, yet open to exploration.

One way to visualise this is shown below.

Outcomes show where value is realised. But much of the value emerges along the way—through learning, discovery, and unexpected signals.

Seen this way, navigating these journeys means shifting between different roles within us. The “Pathfinder” explores new routes, the “Sensemaker” interprets decisions at each fork, and the “Translator” brings others along by sharing the journey.

Of course, Out Run is ultimately finite. It offers a fixed number of routes and endings, all contained within a predefined system. Real-world journeys – particularly innovation journeys – are different. They are continuous, evolving, and rarely have a clear endpoint.

Consider building an app. Launch isn’t the finish line; it’s one point in a longer journey of iteration, refinement, and learning.

Today, tools like AI can accelerate development significantly – like putting your foot down in a Ferrari. But speed alone isn’t enough. If learning doesn’t keep pace, we risk moving quickly in the wrong direction.

Innovation, therefore, is rarely a clean, linear process. It’s messy, iterative, and often uncertain. While there are moments when we can move quickly, there are also times when we need to slow down – or even pause – to reassess.

Out Run might give us the ideal car, but in reality, not everyone starts with a Ferrari. And speed isn’t always the answer. So the question becomes: what do we begin with – and how do we navigate from there?

The Early Sparks of Innovation

We all have ideas. Sometimes great ones. But most remain trapped within our minds. Talking or writing about them can help bring them to life, but description alone isn’t enough. An idea’s true value comes from taking action on it.

Innovation is how we execute those ideas – turning them from concepts into something tangible. They might begin as a scribble on a napkin, but over time, they evolve into products, services, or systems. But how do we know if we have the right idea? And is there even a “right” idea?

Ideas and Context

Back in my designer days, I would remind others that there is no such thing as a good or bad idea. This message wasn’t about reassurance; it was about preventing the group from prematurely dismissing concepts or latching onto one too quickly.

Ice cream on a hot day sounds like a good idea – but less so in winter. How about sharks with laser beams attached to their heads? That might sound absurd – but even that depends on the context.

These issues can vary from social and environmental challenges to overlooked opportunities for improvement. Sometimes, there isn’t even a clear problem – just the potential to make something better.

While signals help guide direction, they are often grounded in something more stable – a core of purpose, values, or intent. As explored in atomic innovation, this core doesn’t dictate exactly where to go, but it helps us navigate uncertainty without drifting aimlessly.

During an innovation journey, we explore the terrain to build that context. We branch out, test different routes, and develop a clearer understanding of real needs and opportunities. In doing so, we begin to clarify what value truly looks like.

From Idea to Adoption

So, what about those sharks with laser beams attached to their heads?

Perhaps there’s a gap in the video game or theme park industry for dangerously modified predators. Or maybe they could be part of a grand plan for world dominance – something that would certainly impress Doctor Evil.

With sharks aside, the point is this: there is no inherently bad idea. What matters is the path it takes – how it’s shaped by context, how it is executed, and the value it ultimately creates.

Many innovations are often recognised long after their introduction. Even Dieter Rams’ iconic portable radio was initially rejected2, but later influenced products like the Apple iPod. Today, we rarely think about these advancements.

Mobile phones, for example, evolved from physical keyboards to glass screens driven by touch and gesture. What once felt unfamiliar is now second nature.

Matt Watkinson, in his book Mastering Uncertainty, highlights that many innovations arise from “happy accidents” rather than intentional efforts – Similar to how the Post-it Note eventually found its purpose.3 Often, ideas require demonstration before people can truly understand their value.

An early example of effective value demonstration is Brownie Wise. In the 1940s, she pioneered the concept of the “Tupperware party” to educate consumers about plastic containers and their airtight seals.

Similarly, TV shopping channels have long relied on live demonstrations to show why products – from Snuggies (a blanket with sleeves) to Squatty Potties (a toilet stool designed to improve posture) – are worth buying. Seeing and experiencing value is often what makes it real.

Hype and Misjudgement

Not all ideas fail quietly. Some are amplified far beyond their actual value.

In certain cases, this is intentional. Theranos, for example, generated enormous hype around its blood-testing technology to attract investment, despite lacking a viable product.4

In other cases, the belief is genuine. Inventor Dean Kamen was convinced that the Segway would transform urban transport. Backed by high-profile supporters, including Steve Jobs, it was widely seen as an engineering breakthrough.

Yet the Segway failed to gain widespread adoption.

As Adam Grant notes in Originals, Kamen’s overconfidence – combined with a limited understanding of the transportation problem – led to a “false positive.” The invention was impressive, but it wasn’t grounded in a sufficiently compelling need.5

Kamen approached the problem from a technology-first perspective – a push rather than a pull. The lesson is simple but important: products don’t create value on their own; people do.

Even well-executed ideas can lose value over time. For instance, BlackBerry was once a leader with its physical keyboard and secure messaging. But as users moved towards touchscreens and apps, its relevance faded. What defined its value became a limitation.

Ideas begin as small sparks. But turning them into something enduring requires the right conditions, the right direction, and sustained effort. It requires friction, iteration, and persistence.

And as we’ll see next, that journey is rarely neat or orderly. More often, it looks something like spaghetti.

Iterative and Messy Like Spaghetti

The innovation journey is full of turns, dead ends, and crossroads. Where do we start? How do we correct course? Do we keep going, turn around, or try something different on the next journey?

These questions surface continuously. And, of course, no journey ever fills us with complete certainty.

We often think we’re moving in one direction, only to end up somewhere entirely different. Yet, over time, we loop back with more clarity than before. While not an innovation story, the film Big offers a useful reflection.

The story goes something like this: Josh, a thirteen-year-old boy played by Tom Hanks, tries to impress a girl by going on a carnival ride, but is refused entry because he is too short. Dejected, he inserts a coin into an antique fortune-teller machine and wishes to be “big.”

His wish is granted, but he soon learns that being an adult isn’t as straightforward as he imagined. He lands a job at a toy company, lives in a stylish New York apartment, and falls in love (questionable morals aside) with a fellow executive. Along the way, he begins to lose touch with what it means to be a child, straining his relationship with his best friend, Billy.

Josh’s journey is full of loops. Eventually, he returns to where he began – small – but with greater clarity. What he gains isn’t status or success, but a deeper understanding of what matters: friendship and the value of simply being a teenager while you can.

But this messiness isn’t dysfunction. In many cases, it’s a sign of adaptability, particularly in decentralised systems where learning and adjustment are continuous.

On a smaller scale, this mirrors escalation loops. Signals, meaning, and action reinforce one another. Over time, these loops expand into full journeys, shaping the paths we take and the value we realise.

We can view a typical innovation process as an idea moving through cycles, looping and branching into a spaghetti-like route.

As clarity builds, parts of the journey begin to straighten – like unwinding strands from an entangled heap. But the mess never fully disappears. It continues to evolve.

The Double Diamond and the Spaghetti Reality

To make sense of this mess, we often turn to frameworks.

The Double Diamond model6 is a popular innovation framework that illustrates alternating phases of divergence and convergence. The first diamond focuses on understanding the problem (discover and define), while the second moves towards creating a solution (develop and deliver).

The idea is straightforward: diverge to explore, then converge to focus. We repeat this pattern until we find a final solution. As a framework, it’s useful. It gives us a shared language for thinking about progress. But like any framework, it doesn’t describe reality as it is.

In practice, these phases rarely follow a clear order. They often overlap, with one idea being explored while another is refined. The journey weaves between stages rather than progressing linearly.

What appears structured in hindsight is often far more tangled in reality.

This is where the spaghetti metaphor returns, not as repetition, but as contrast. The Double Diamond offers structure, but the journey itself is fluid, with overlapping and looping strands. Some paths lead forward, while others circle back. Over time, we begin to untangle what matters.

The Double Diamond still has value, but it works best when treated as a guide for the journey – not a prescription for dictating it.

This is where problems begin. We push forward too quickly. We commit to ideas before fully exploring them. We converge before we’ve truly diverged.

We sometimes describe this as being “railroaded” – rushed into action before the journey has had space to unfold. When that happens, the path becomes constrained, and the project risks derailment before it has found its footing.

What the Double Diamond doesn’t explicitly show is how exploration and execution escalate over time.

Every journey begins with a signal – an idea for change. Through exploration, we give meaning, branching into wider, more exploratory paths. As we converge, that meaning hardens into something more tangible and usable.

Seen this way, the Double Diamond is not just a sequence of phases, but two overlapping escalation loops. In the first, signals strengthen through exploration and refinement. In the second, those signals take form – becoming decisions, outputs, and outcomes.

This can be visualised as two connected loops:

Rather than moving cleanly from one phase to the next, innovation unfolds through these loops, where meaning strengthens, commitment forms, and outcomes begin to take shape.

Journeys That Shape Systems

Up to this point, we’ve explored how systems shape innovation journeys – enabling movement in some cases, and constraining it in others. But the relationship isn’t one-way. Journeys don’t simply unfold within systems; they also reshape them.

Over time, the paths we take, the signals we follow, and the decisions we reinforce begin to influence the structures around us. New practices emerge. Old constraints loosen. Entire systems evolve through repeated journeys.

In this sense, innovation is not just something that happens within a system, but something that continuously reshapes it.

We see this in everyday artefacts. Sticky notes spread across office walls like corporate confetti show how journeys and systems co-evolve. What began as a failed adhesive experiment has changed our work habits, including how we coordinate – and even decorate our office surroundings.

Journeys often unfold in unexpected ways. The arcade game Out Run showed us how progress is less about racing towards a fixed destination and more about recognising signals and adjusting direction as conditions evolve.

As we move through our journeys, we encounter forks in the road, obstacles, delays, and setbacks. Not all early sparks of innovation lead to breakthrough outcomes.

Sometimes it takes repeated iterations for an idea to gain traction. Other times, it takes reframing – as with Brownie Wise’s demonstration of Tupperware – to help people see and experience value for themselves.

Regardless of skill or intelligence, we can’t fully control the outcomes of our journeys. The only reliable way to navigate uncertainty is to prioritise learning, not just execution.

Doing so helps us better understand people’s needs and respond to shifting conditions. As we saw earlier with the Segway, even a well-engineered idea can falter when it isn’t grounded in real demand.

And no journey follows a straight line. It often begins as a tangled, spaghetti-like path – looping, branching, and evolving over time. Through cycles of exploration and refinement, we gradually build clarity.

Seeing innovation as a journey gives us an experiential lens – one we can capture in a single line:

The journey determines how value is discovered, shaped, and realised.

Systems define the conditions for innovation. Journeys describe how we move through those conditions to realise value. Systems enable movement. Journeys are that movement.

Something to think about: Are you moving too fast down a single path – or taking time to explore, learn, and adjust as you go? And where might a shift in direction reveal value you didn’t expect? Feel free to share your thoughts in the comments 👇

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