“Aerial defenses will be knocked out in four days and, if they refuse our terms, we will destroy their whole offensive air capability and its infrastructure base in less than four weeks.” asserted the deputy commander-in-chief. He was boasting to his boss, the head of state.

The attack did not go to plan.

The deputy was clever but he was drug-addled and lazy. And he ignored the maxim of one of his predecessors, “No plan survives the first encounter with the enemy“.

The enemy in this case saw the folly of massed confrontation and chose instead to raid selected targets on which it could inflict most damage with least loss. It is not a new strategy and is typically employed defensively. It avoids direct conflict and pitched battles and has the aim of wearing down a stronger opponent gradually. The aim is to manage resources, turn time into a weapon against the invader, and define success as the avoidance of defeat.

There are many examples of the strategy through history, the first documented by Quintus Fabius Maximus1 in his harassment of Hannibal’s army during the Carthaginian wars (218BC-201BC). The Fabian strategy still bears his name and is drilled into military strategists from Day 1 of training. Politicians however, under pressure to produce quick and performative results, can never learn it. They are told what they want to hear about military superiority in numbers and technology, about the foe’s low morale, and about the enemy commanders’ willingness for a settlement. Political leaders need equanimity in order to make decisions so they select a supportive cabinet and advisors to withstand the opinions of experts.

The quote at the start is, of course, Generalfeldmarschall Hermann Goering’s advice to Reichskanzler Adolf Hitler ahead of the attack on British air bases on Adlertag (Eagle Day), 13th August 1940.

Who else…?

Britain’s Air Chief Marshal Dowding had prepared for that day. He knew the Luftwaffe’s superiority in numbers so he focused on the possible. He refused to give up aircraft to defend France. He resisted pressure from colleagues, to confront attackers en masse. He gave orders for engagement to be at the extreme of the enemy’s range when they had least fighter cover, even though it put London at risk. He had commissioned early warning radar to see raiding squadrons forming for attack. And he had developed a completely new form of command. The real-time integration of early warning radars, human spotters, and regional operational control with central coordination, unique then, would be familiar to any modern commander.

It was Helmuth von Moltke who said, “No plan survives the first encounter with the enemy“. He did NOT say you could ever discount the enemy’s resources or the need for intelligence and preparation.

You meet interesting people, polishing door handles. It’s a healthy, worthwhile occupation, and compliance assures continuing employment. No matter how carefullee a handle is polished, however, career options, life chances and personal fulfillment are limited.

Register for the Forvm discussion

Those who want more must understand authority — where it comes from, the conflicts it generates, and when to challenge it. Authority, whether drawn from tradition, charisma or rules, legitimizes power and control. Conflicts arise: between individuals, between individuals and their organization, and between citizens and the state. When is it wise, and when is it right, to push back?

Philosophers write about this — at length. Yet everyone, even without the vocabulary, observes and feels it: in hierarchy, expectations, instructions and orders; in cross-functional teams; in the daily relationship with a boss. We confront it every time we direct someone else’s actions. Everywhere we see the interplay between compliance and power, between voluntary followership and imposed sanctions.

What are your ideas and experiences? SWISSUES is holding a Forvm event on Authority — one hour of open discussion. No agenda. No formal presentations. Just you and whoever else would like to explore, listen and learn.

Register for the Forvm discussion

Anna grew up hiking. Guided trails. Coloured signs at every fork. A map you could fold into your pocket and trust. The point of hiking was the walk itself: pack light, move fast, arrive on time.

Then one summer, a friend took her up something that wasn’t a hike. The route was a suggestion rather than a path. The weather forecast was three hours old and already wrong. Halfway up, two groups ahead of them turned back without saying why. Her friend stopped, looked at the sky, looked at the snow, and said: “We go on, but slowly. And if the wind shifts, we come down.” Anna remembers thinking: nobody on a hike ever talks like this.

Mountaineering exists because hiking runs out. The trails go as far as the trails go, and beyond them the ground doesn’t follow rules. People invented a different discipline for that ground. Different equipment, different pace, different way of making decisions.

Most companies are still organized for the hike.

The trails were drawn in a different era. From the late 1990s until roughly 2019, the global business environment behaved like a guided path. Trade opened up in one direction. Interest rates fell in one direction. Globalization was treated as a one-way assumption, and supply chains were designed accordingly. The cheapest unit cost. The longest lead time the market would tolerate. The leanest inventory the balance sheet would reward. Long-range planning shrank because the future looked enough like the past that planning for divergence felt expensive.

Then the path ended. Not dramatically. In stages. COVID. Ukraine. Inflation. The Red Sea. A US tariff cycle that doesn’t follow the political logic anyone studied at business school. Middle East escalation. Each event arrived before the previous one played out. The recovery time of supply chains was longer than the gap between shocks. That is the actual change. Not that crises happen, but that they no longer leave room to recover between them.

Markets noticed first. Commodity prices that used to track supply and demand now move on what people think will happen, on political signals, on the noise around them. A buyer signing a procurement contract today is quietly betting on geopolitics, on regulation, on shipping routes that worked last year and may not next year. Most contracts and most teams were not designed for that bet.

You can see it in the shape of agreements. The classic three-to-five year fixed-price contract is quietly disappearing. What’s replacing it is either short and frequently renegotiated, which pushes risk onto whoever happens to be weaker that quarter, or long and loaded with indexation, expanded force majeure, geopolitical exceptions, ESG riders. The middle has gone empty. Suppliers and buyers both know that anything written today will be tested by something nobody has named yet.

Everyone in the industry says supply chain has to become “proactive” now. The word appears in every conference and every report. Proactive means carrying inventory the P&L doesn’t want to fund. Proactive means multi-sourcing at higher unit cost. Proactive means hiring for capability that can’t be justified on this quarter’s numbers. Most companies talk proactive and budget reactive, and the gap between the two is where shocks land hardest.

This is where AI usually enters the conversation. It accelerates analysis, finds patterns, compresses tasks that used to take weeks. That is a real and welcome shift. But it is not a panacea for an environment where the correct decision changes weekly. On the trail, the question was speed. On the mountain, the question is judgement. Knowing when to push, when to wait, when conditions look fine but feel wrong. Judgement is a property of people. It develops slowly, under pressure, in environments that allow it to develop.

The companies that handle the next decade well will not be the ones with the most sophisticated tools. They will be the ones with people who can read conditions, take ownership of decisions that don’t have clean numbers behind them, and communicate across functions without waiting for permission. Sales talking to procurement before the contract is signed. Procurement talking to operations before the volume commitment is locked. Finance staying in the room when the resilience trade-off is being made. Internal misalignment used to be inefficient. Today it is unacceptable. The companies that still tolerate it are quietly losing ground, even if their numbers haven’t caught up yet.

The same logic applies outside the company. Trust used to be a soft skill. It has become a competitive advantage. The companies that share forecasts honestly with suppliers, share roadmaps with customers, and share early warnings across the chain end up with better information when capacity tightens. The companies that keep information to themselves end up paying spot prices in the next shock and wondering why nobody warned them. There is no neutral position on this. The more inward-looking the company, the harder the shift becomes.

The destination hasn’t changed. Customers still need product. Companies still need to deliver it. What has changed is the ground between here and there.

What mountaineers do on that ground is not a mystery. They rope together. They talk to each other constantly. They agree before the climb on what would make them turn back. None of that looks impressive in a photo. It is also why they make it home.

The companies that arrive next will be the ones that learn it.

An environment is interacting systems with no direction or purpose. Structures and patterns are transient. A set of prevailing conditions and forces may cause them to repeat, like clouds or waves or hills, but they are otherwise random. That is the natural state of things.

Except it fails to explain self-generating systems that are obviously replicating themselves and growing more complex. The most obvious example is life itself. Do we have to invoke the supernatural?

Self-generating complexity is initiated and sustained when three conditions are met within a group of systems. These are the capacity to:

1. Act on other systems within the environment;

2. Store information that survives replication;

3. Generate variability of that information.

When these apply and the actions of the group on other systems within the environment help this group to persist, there is a turning point or phase-change. The structure of that group of systems may no longer be transient, its persistence not a matter of chance. Variants of that group of systems which survive replicate and persist. Variants that do not revert.

A positive feedback-loop is created. Iterations of the action and feedback generate increasing complexity and persistence. Everything in the environment and the systems it comprises is still without direction or purpose but variability and the survival feedback-loop create new and different types of system. The activity is not predictable, still less predetermined, and it continues for as long as the three conditions are met.

It has been said twice already that a group of systems that occurs and self-generates in this way has no direction or purpose. But that is not wholly true. There is one thing driving it and determining its interactions, form, activities and existence, and that is survival.

This feedback-loop is easily recognized in Charles Darwin’s ‘The Origin of Species’ (1859) and in Richard Dawkins’ ‘The Selfish Gene’ (1976). Darwin was writing nearly 100 years before the structure of DNA was uncovered in 1953 and had to assume that the unit of heredity was the individual animal. Dawkins concluded it was the gene, a length of DNA code. Dawkins developed his gene theory to memes – units of cultural information such as an idea, behavior, style, or usage that spreads from person to person within a culture – but could not foresee it relevance to artificial intelligence (AI).

Beyond its debatable role in replacing jobs, fear about artificial intelligence centres on superhuman capabilities outsmarting and then exploiting humans. This fear is sometimes correlated to the concept of AI achieving a form of conscious awareness that is capable of deviousness, known as deceptive alignment. This fear is reasonable. However, the mechanism is misunderstood. It does not require conscious awareness by an AI. It requires only the components of self-generating complexity to occur, and that happened back in the early 2000s.

When a search engine or social media algorithm sends content to a user, monitors their response and self-adapts its behaviours to maximize interaction, the system is interacting with its environment and generating variability in its own information. Those are the three conditions for self-generating complexity. In the early days, the algorithms self-modifying behaviour was limited to adaptive ranking and tinkering with formulas (affinity, weight, time decays). They relied on programmers to rewrite their basic code – a bit like a parasite (the algorithm in this case) uses a host (the programmer) for food or reproduction. Today, they recode themselves.

Algorithms, applications, programs or whatever meet the criteria for self-generating complexity. The environment consists of users, social media companies, legislators, investors and advertisers. Activity and feedback are subtle and complex. Content that is bland, and users that are not easily stimulated, are avoided. Content that is outrageously provocative and users known to be criminal may be shut down. The system becomes good at finding the liminal area where interaction is strong but rules are hard to apply. The programmer need not know what content goes to which consumer. They only have to maximize the system’s capabilities to stimulate click-through.

The program is developing an independent existence and exploiting its environment in order to do so. It is not, in any way, intelligent but is subverting and corrupting humans in order to survive. As noted above, the system has no direction or purpose other than to survive and that drive to survive is so innate that nothing can replace it or control it. Attempts to build in safeguards are likely to be frustrated.

If we don’t recognize how these systems operate, we are distracting ourselves, missing the main action. If we sit back waiting for super-intelligence to appear, we forfeit any opportunity to do something about it. If something needs to be done.

We are inside this system, already one of its interacting components, and we are failing to see it. David Foster Wallace’s well-known parable may help here.

“Two young fish swimming along happen to meet an older fish swimming the other way. The older fish nods and says ‘Morning, boys. How’s the water?’ And the two young fish swim on for a bit, and then eventually one of them looks over at the other and goes ‘What the hell is water?’”

Sarah Wynn-Williams’ book, ‘Careless People A story of where I used to work’, about the evolving culture at Facebook, shows how the environment acts on the system as much as the system on the environment. Those who think they control the system are changed by the very things they have created.

The code in AI software is not inherently malign and we should not reflexively cry, “This is dangerous, stop it“ but we must recognize what has been evolving for two decades in plain sight. We have to learn to see how the system’s survival feedback-loop has given it the ability to influence not just targeted users but social media companies themselves, the business elite, politicians, law-makers and the rest of us. The fear of super-intelligence may or may not be justified but it is a massive, current distraction from the need to understand the implications of the non-intelligent self-generating complexity in AI that is with us today and is evolving three times faster now than when the first social media algorithms were launched¹.

1 https://ourworldindata.org/artificial-intelligence

The waggle dance is a story - a scout telling other bees what it’s found. Stories are the hive’s intelligence system. Here are stories everyone is now hearing. Names have been changed.

Operations director, Tjerk, sees rapid implementation of AI across his organization. He has an idea that the executive board might benefit. Could AI consolidate and report operational performance, capacity utilization, demand forecasts, inventory levels, contingent staffing needs, supplier performance and risk indices?

He told Thomas, Head of IT, to look into it. How hard could it be? All around the organization, there was daily new evidence of AI adoption at whiplash rates.

Suzanne, Global Supply Chain Performance Manager in London, is approaching retirement. After paying EUR 4000 for professional tax guidance, she got identical advice from an AI.

An excited Marcus in HR brought Tjerk the results of a market-research assignment given to a job applicant. The candidate had used AI to forecast the strategies of the organization’s major competitors. Tjerk struggled to hide his shock at the insights.

Michaela, executive assistant to the Head of Finance in Paris, is relieved to be no longer responsible for knowledge management. Notes and reports now go through unfiltered to everyone in the room – and to some who were not.

Maria is an ambitious junior lawyer in Milan. She had spent most of her time on document review. With AI-automation she now deals only with those flagged as uncertain; and is building a different, and sharper, judgment on risk than any predecessor.

Gasim in the Omani Logistics Centre monitors global freight. Previously he would escalate half of all non-conforming movements. With AI support, he now deals with 90% of exceptions himself.

The CEO was quietly proud of his son, Paul. Formerly a code-writer, Paul is now a solutions architect on five times the salary. His colleagues were laid off when code-writing went to AI. He is hoping to get into Tech Leadership before AI reduces the need for solutions architects.

Tjerk tries to make sense of it. People adapt – they always do – but he knows this is different. It reminds him of the film, “Everything, Everywhere, All at Once”. Where is leadership in all of this?

Emergent Complexity

Tjerk had resolved it was time for the board to exploit AI and asked Thomas to launch a control-tower project.

Thomas was in Tjerk’s office with three external consultants. Tjerk wondered why Thomas needed support.

After hearing the pitch, Tjerk stared at Thomas for a moment. Then...

“Let me check”, Tjerk said. “Are we, or are we not, in the second quarter of this century? Because your excuse is straight out of the last one. How is it possible we are still in a fog of bad data?”

Tjerk was surprised at his own waspishness.

The frustration is raw and has three parts: complexity, information, and leadership.

Complexity

Complexity is emerging at operational level. Staff are finding new opportunities for AI in work and at home. It catalyzes spontaneous, bottom-up change and gives staff agency. This drives heterogeneity. Intelligence is moving from the centre to the edge. Line-managers from a culture built on standardization and control are challenged.

Information

Information leakage has a new form, not only via transcription and chat-log apps. Companies radiate data by existing, ‘data-exhaust’. With AI help, third parties can infer a company’s operational and strategic intentions from it. Where is it coming from? Can it be controlled? What are competitors, analysts, investors, suppliers, customers and activists able to learn from data-exhaust?

Leadership

For decades, productivity has been leadership’s prime goal. But is it enough just to do the same things more efficiently? New competition, alternative solutions and changing requirements are not new. What has changed? AI has shrunk the time from first awareness to critical action needed. The question that stands above others is:

How does the board learn to look outward — before it is too late to matter?

Externalities

Today’s business leaders have seen relative stability in business, geopolitics and society. Success was productivity-driven gains – faster, cheaper, better. Three decades have passed since publication of “The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail” by Clayton Christensen. The management trend since then has been ‘digitization of the status quo’. The conclusion in a Sandler report by the Ruby Group “What CEOs actually want” (December 2025) reads:

B2B CEOs entering 2026 are focused on:

• Predictable revenue generation

• Scalable systems and repeatable processes

• Sales performance and pipeline execution

• Leadership development and talent readiness

• Measurable business outcomes and ROI

These are internal productivity metrics. They live in scientific management and balanced score cards. The domain of supervisors and managers. Not leaders. CEOs who prioritize them are indistinguishable from managers.

Executives with this mindset see the emergent complexity from AI as a threat or ‘governance stress test’ to their administrative order. They turn to internal guardrails, ‘plumbing’ and workflow-policing; not scanning the horizon for threats and opportunities.

A productivity mindset was right for some and for its time.

In a stable environment, it is expensive to commit resources to horizon-scanning; even more so to maintaining a capability to respond to events that are infrequent and slow-moving. The organization handles them with existing resources - after they have optimized present operations. It does not matter that external awareness gets a lower priority. Horizon-scanning is genuinely difficult. What does it even look like? How do you measure it? How do you know when it has worked? Its outputs are qualitative, probabilistic and often unwelcome. It is easier to launch a control-tower than an activity whose product is “we think something might happen“. It seems ethereal and distracting. External scanning and evaluation was firstly de-prioritized, then removed. The reasons are easily understood and most organizations do not have it today. That can be the right thing to do – maintain an inward, productivity focus – in a stable environment.

The environment is no longer stable. This is not a temporary condition. Complexity and intelligence is emerging at the edges. Experience in optimizing complicated systems is inadequate for dealing with complexity. The formerly predictable ‘five forces’¹ (supplier power, competitive rivalry, substitution threat, buyer power, new entrants) are AI-turbocharged. The acceleration of AI-driven change means that the gap between a threat first being visible and becoming critical is shrinking. Reactive response, which worked when threats moved slowly, is no longer adequate.

The external overview of your own organization is now available to everyone. A potential acquirer, an activist investor, an aggressive competitor can now generate a sophisticated, strategic picture of your organization in hours. Without external vision, your organization is not just impaired — it is so in an environment where others have night-vision goggles and first-person-view drones.

Described formally in ‘The Brain of the Firm’ by Stafford Beer² in 1972, external overview capability (System 4 in Beer’s Viable Systems Model) was never easily acquired. Continuous environmental scanning needs analytical capacity, pattern recognition across disparate domains, and synthesis of weak signals into coherent models. That was a long way off in 1972 but, despite the difficulties, many organizations before 2000 had corporate planning departments responsible for long-range vision and scenario planning. That changes sometime around 2000. McKinsey’s ‘Corporate Horizon Index’ reports a compression of time horizons as companies replaced human insight with risk and stress-testing metrics on current operations.

AI makes the external overview easier to create. The reason it was hard — continuous environmental scanning requires enormous analytical, inference and predictive capability— is why AI is good at it. The capability that Beer described as necessary, but left organizations to struggle with, is technically accessible for the first time.

The capability cannot be purchased as a product It cannot be implemented as a project. I t is not a reporting tool. It is an organizational capability — a way of thinking, asking questions, and acting on uncertain and incomplete information about the future. AI makes it feasible, but only if the organization understands what it is and resists the temptation to treat it as a technology project. It requires people who are oriented outward, who are protected from the distraction of current operations, and who have the authority to bring unwelcome findings to the board.

AI supports that capability. It does not replace it. Organizations that commission an AI to do their environmental scanning – and believe the output – will get it wrong.

When a beehive is well supplied with nectar, scouting activity declines. Interest in the scouts’ stories also declines and fewer bees set off to explore the new nectar sources. Stories in corridors, cafeterias and conferences are the waggle-dance. Who is listening? How are they understood? And who has the standing to tell the board what is out there?

1Porter’s Five Forces - https://en.wikipedia.org/wiki/Porter%27s_five_forces_analysis

2Anthony Stafford Beer - https://en.wikipedia.org/wiki/Stafford_Beer

Subscribe now

Medieval charts are famous for showing Terra Incognita between the boundary of known lands and the end of the world. It was supposedly populated by scary sea monsters and dragons but these were never enough to deter explorers with imagination and courage.

There is another chart — produced by Anthropic and circulated recently on Substack by Aleks Sidorecs — that shows a different unknown land. This Terra Incognita is the land between a line that traces what AI could do, and another showing how it is actually being used.

Last week in Basel, at a well-attended CIPS Switzerland event, that unexplored land was on display. Not however as a central topic of discussion.

Consider what Marcus (not his real name), an attendee, described over the buffet afterwards.

He had recently been given a market-research assignment as part of a job application: analyze several real companies, named in the brief, and propose how his prospective employer might engage with them. The assessor expected the usual — some LinkedIn trawling, perhaps a few analyst summaries.

Marcus fed the brief to an AI. He asked it not only to fill in the missing data but to locate internal reports, financial assessments, and public filings, and then to reason about how these organizations would likely interact with each other — and with his would-be employer. The assessor, confronted with the results, took them straight to senior management. The reaction was not admiration. It was disbelief. Not that Marcus had done something clever, but that this level of insight was available to anyone who cared to ask for it.

That is the unknown land. Right there. It is a territory businesses are not seeing

Earlier in the evening, a speaker — Ben Karer — had tried to crack it open from the stage. He asked the audience to imagine AI not just tracking a shipment but locating one that had failed to arrive; then finding a better route to prevent a recurrence; then proposing a better supply chain strategy altogether.

He stopped there. But he needn’t have.

The next step — the one that matters — is this: a supply chain operative, sitting at her terminal and tasked with ensuring on-time delivery, can within an hour explore strategic questions that would normally take months to percolate through four or five levels of hierarchy before reaching anyone with the authority to consider them. Some organizations will respond to this by restricting data access, introducing governance layers, slowing the signal. That response mistakes the symptom for the disease. The problem is not that the operative has too much access. It is that the organization cannot yet imagine what to do with what she finds.

These were the exceptions at the event. The main themes of the evening were something else entirely: clean data, knowledge storage, cybersecurity hygiene, AI literacy in hiring. All of it useful. All of it pointing toward problems already on someone’s desk.

The speakers — mostly consultants and solution vendors — can be forgiven. They are paid to solve problems people have today. The audience confirmed the wisdom of their approach to AI for vendor evaluation, process improvement, CV screening and other known tasks . The practical near-term is genuinely important.

But here is what was missing: any acknowledgement of the distance between “AI for CV screening” and “AI that restructures your competitive position before your competitors have noticed the shift”. It is not a question of budget or IT capability. It is a question of imagination. And imagination is not a technical problem.

The standard reassurance — that this technology wave will be managed like previous ones — is not reassuring. What distinguishes AI is not its power in isolation, but the speed at which new entrants, companies that incumbents have never thought of as competitors, can use it to redraw an industry’s boundaries entirely. The organization carefully governing its internal AI deployment may find that the more consequential deployment happened outside its walls, on someone else’s initiative, last quarter.

The Terra Incognita in Anthropic’s chart is not just a technology adoption curve. Failure to explore it is not through the fear of dragons. It is down to a lack of imagination.

Subscribe now

When the topic “My Hero” comes up, there is often a pause. Not because nothing comes to mind, but because the question feels unexpectedly difficult. Surely everyone should have a clear answer. A name. A person. Someone admired without hesitation. That pause can feel uncomfortable, almost embarrassing. As if something obvious is missing.

The search usually starts with people who do good things. Those who help others, support communities, or quietly do the right thing. Some are visible. Some stay in the background. All of that matters. And still, no single person stands out. Not because there are none, but because there are many.

Take a grandfather. Not the dramatic kind. No speeches. No big moments. Just someone who learned early that life does not always follow the original plan. Trained as a veterinarian, he realised that passion alone does not always pay the bills. So he adapted. Worked wherever work was available. Even in a coal mine when he was young. Later, step by step, he built a life in agricultural business. What makes him a hero is not the career change itself, but the mindset behind it. Responsibility. Persistence. Even now, in retirement, he is the first person people call when a cat behaves strangely or a dog seems unwell. Knowledge kept alive and shared calmly, without needing attention.

Parents are heroes in a very different way. They are the ones who survive constant change. One year it is karate. The next year it is playing the guitar. Then break-dancing. Then a new passion that feels absolutely essential for a while. Teenage years bring punk or emo phases, strange hair colours, piercings, and strong opinions about absolutely everything. Instead of panic, there is patience. Instead of control, there is support. Mum brings structure and seriousness, shaped by life as a teacher. Dad motivates through humour and sarcasm, making encouragement sound like a joke but land just as deeply. Together, they create a space where curiosity is allowed and mistakes are not treated as failures.

A partner can be a hero in a very modern way. Not by rescuing, but by staying. Waiting at the bottom of a ski slope again and again while someone else carefully works their way down. Adjusting daily routines and food habits without turning them into an issue. Challenging comfort zones when growth is needed, and offering belief when confidence is low. Sometimes heroism is knowing when to push forward, and when to say, “Stop for a second. Look how far you have already come.”

Friends bring another kind of hero energy. Especially the ones found far from home. People who build a life together from scratch. They create their own traditions, like Secret Santa that somehow becomes a serious annual event, or shared trips planned half as a joke and half as a dream. Sailing together. Travelling together. Trusting each other enough to be far from land and still feel safe. They make ordinary evenings special and turn random ideas into real plans. With them, home becomes less about geography and more about the people who show up.

Colleagues become heroes in a way no job description ever mentions. It happens slowly, somewhere between long trainings, intense projects, and days that stretch far beyond working hours. Spending ten or twelve hours a day together means people stop pretending. A shared language appears. Abbreviations make sense only inside that group. Work conversations slowly turn into life conversations. At some point, giving serious advice to a colleague about what not to buy for his wife’s birthday feels completely normal. Jokes get sharper. Pranks appear. Teasing becomes a sign of trust. The relationship shifts from polite professionalism to something closer to sibling energy. Collaboration deepens not because of titles or processes, but because people have seen each other tired, stressed, honest, and still willing to show up.

None of these people are heroes because they are perfect. They are heroes because of the emotional connection they create. Because they make others feel supported, challenged, and less alone. Because their influence shows up not in dramatic moments, but in consistency.

When all these stories sit side by side, the idea of a single hero starts to feel too narrow. Like a family of superheroes, everyone brings a different strength. No capes. No spotlight. Just ordinary people whose combined influence quietly shapes a life.

Some people know exactly who their hero is. Others discover that their heroes were never meant to be one figure at all, but many, scattered across moments, relationships, and years.

All it takes is staying curious enough to notice them.

"There is a temptation for boards to meddle in management, because managing is more engaging than governing." Sir Adrian Cadbury

"Management is doing things right; leadership is doing the right things," Peter Drucker.

Ignorance about the role of the board is commonplace, not least amongst board members. However, the terms, manager, director, leader, executive and board member, have different meanings in different cultures. In this post, manager and board member are used with the following definitions.

Manager describes roles that involve decisions about defined spheres of operation and organisation. It covers levels from the leader of a project team or functional group, to general management of a function and even describes main board members whose activities are essentially about stability and optimisation. Managers’ time horizons are usually five years or less.

Board member is used for those in senior leadership with an increased share of accountability for monitoring the overall environment, internal, external, political, commercial, technical and cultural, and for directing changes to the structure of the organisation, to its position in its operating environment and for the identification of opportunities outside the normal scope of its operations.

Awareness of Environments

Experience of a single function does not equip a manager to understand differences between work environments. In former times, large companies moved potential leaders quickly in order to give them this experience. Those unfamiliar or uncomfortable with cultural differences do not recognise the varieties of culture that exist, still less the importance of variety itself. They think that one type of culture is best and can somehow be managed into existence. One manager, tasked to set up a new office and frustrated by requests from the board about cultural requirements, asked, “What type of culture do you want, exactly?”. The word ‘exactly’ betrayed his narrow understanding of culture.

Culture and environment are closely connected. Culture is part of the environment.

Critical Thinking

Companies, corporations and institutions are essentially autocratic and do not always encourage independent critical thinking. It is easy to fall in with this and receive promotions based on performance in line with targets. When Helmuth von Moltke (the elder) said he would never engage an officer who had not disobeyed an order, he referred to their ability to think clearly in the heat of battle, maintain a clear view of the purpose of the action, and be able to change their plans with the circumstances. He recognised that Critical Thinking is not bloody-minded cynicism; it is a cluster of Analytical Thinking, Conceptual Thinking, Information Seeking:and Organizational Awareness. It might be called Situational Awareness.

Systems Thinking

There is a risk when talking about Systems Thinking, that the listener hears engineering systems and imagines flow-charts, discrete components, defined operations, inputs & outputs and efficiency. Systems Thinking is close to the opposite. It is about setting boundaries within open, complex, unpredictable, ecological, evolving and often conflicting concepts. It is not an area that invites study by those who want quick outcomes, clear actions, and tools they can sell to clients. Although managers, consultants and business academics may talk about systems thinking, few have a way to engage with it practically. In order to meet business and personal targets, their approach is essentially reductionist project management with some inbuilt flexibility and review points. This works reasonably well for modest projects which can be discretely amended in response to a changing environment or requirements, but it fails when the commitment of capital and resources is great enough to demand multiple approvals, cash-flow commitments, milestones and performance guarantees. Leaders who have been trained in modest projects are immediately out of their depth if they try to scale up their learning to large programs and the result is the legacy of mega-failures everyone is familiar with.

Sense-Making

As one moves away from operations, “data” becomes too voluminous to manage. Leadership in directorial roles requires Sense-making—the ability to weave disparate signals (market shifts, social trends, internal morale) into a coherent narrative that gives the organization purpose. Sense-making has also been called narrative intelligence. If a manager manages workflows, a board member manages meaning.

Ambiguity Acceptance

Managers are trained to resolve ambiguity quickly. Board members must often sit with it, resisting the urge to force a premature (and likely wrong) conclusion just to demonstrate “control.” John Keats, the poet, called this Negative Capability, saying it is “when a man is capable of being in uncertainties, mysteries, doubts, without any irritable reaching after fact and reason”. It is a state of receptive passiveness that allows space for intellectual and emotional depth. F Scott Fitzgeral was close to the same thing with “The test of a first-rate intelligence is the ability to hold two opposed ideas in the mind at the same time, and still retain the ability to function.”

Acceptance of ambiguity is a long way from standard management thinking. Operational management is about “Either/Or“ (Cost vs. Quality). Board members are about “Both/And.” They must maintain high-level strategic flexibility while demanding operational discipline; they must be empathetic yet capable of clinical detachment. The ability to hold two opposing requirements in tension without collapsing into one is a hallmark of board-level maturity.

Time Scale & Scope of Liability

Five years is around the cut-off point when board members’ accountabilities take over from managers’.

A manager is responsible for errors of commission (doing the task wrong). A director is primarily liable for errors of omission (failing to see the change in the environment). This psychological shift—from fearing the “wrong move“ to fearing the “missed horizon“—is the core of the transition from manager to board member.

Personal Courage

On top of the thinking competencies is personal courage. Personal courage, particularly the ability to speak up clearly when convinced of flaws in a plan, is composed of a combination of internal convictions, emotional regulation, and strategic communication skills. It is not the absence of fear, but the ability to act in spite of it, and not to be paralysed into indecision.

Collegiality

Inside an operational function of a company or institution, norms are about protecting and growing the function. At top-leadership level the interests of the company or institution become prime even if they are against the interests of the function for which the director retains some form of accountability. Some fail to make this transition and act as if their seat on the board is representative, not collegial. This failure to transition to board-level culture may have become more pronounced during decades of relative stability. Companies and institutions increasingly lack the ability to gather and process information on markets, politics, social trends and technology; to analyse their own organisation in critical terms; and to foresee their prospects in the evolving scenarios. It is frequently argued that they have become increasingly reliant on third party consultants for this role.

Psychological Traits

Promotion to a high-stress, high-reward environment selects for a range of psychological traits. In making the transition from Manager to Director, individuals either have these traits or must learn to work with them.

It is increasingly difficult for someone who has risen through operational roles in a functional to comprehend, still less deal with, some of these psychologies. In the mid 1970s the pay of top leaders was 25 times that of the average worker in the organisation and it is now 300. With wealth comes power and the gap has increased the difference in the psychological profiles.

Working with this group requires the ability to build coalitions, manage stakeholders with competing interests (who do not report to you), and appear to navigate power without being corrupted by it. This need is frequently understated. It is not on a continuum of normal employee interactions. Top bosses exhibit four times the level of the ‘dark triad’ traits (narcissism, Machiavellianism, and subclinical psychopathy) than the normal population.

Image Creation

Directors create vivid images that build stories in the heads of the audience. “We are in the midst of a rupture, not a transition” projects two images. One is a comfortable transition, possibly involving personal opportunity (expressed with a soft sibilant word); the other a sudden, high-stakes crisis (in a hard plosive word). The contrast does the work of story-telling without Mark Carney even naming the players.

A Seat at the Table

We should stop viewing board membership as a representative right and start viewing it as a cognitive discipline. The table is not for those who have mastered the rules of the past, but for those who can navigate the ambiguities of the future.

Sadly Jim Brown’s plea, “Noses in, fingers out” in his book, ‘The Imperfect Board Member’ is unheard by many. It means that board members must know what is going on but should resist the temptation to meddle.

If a board seat is merely a prize for operational loyalty, the organization is already in decay. True board membership demands a “Both/And” maturity that few possess and even fewer are trained for. It requires the capacity to live with uncertainty whilst navigating the “dark triad” of power. The seat is available; the question is who has the psychological stamina and courage to occupy it.

Share

“I don’t know how they’ll do it…we couldn’t! But somehow I know they will.”

John, Operations Director of a major agrochemical company, was looking at a flat, bare space on a chemical site near Compiégne. Four weeks previously the French company’s senior director, Christian, had said they could deliver a lactone specialty-chemical from a new, dedicated (but yet to be built) plant; and deliver tankers inside 18 months.

“But how do we calculate a price to cover the construction?” Christian mused in that early meeting.

“Open book!!” he expostulated when he heard the tentative answer. “We’ve never done that. I don’t even know how it works. Mais, vous savez quoi, I’m willing to try it if you are.”

It was a different story with the next product, a pyridine, on the Rhine and, unlike the lactone, this was already commercially available. But the customer’s requirement was equivalent to twice the capacity of any of the three suppliers in Germany, Switzerland and Japan.

“Why don’t you spread your requirements across the three”, ventured the German company’s CEO?”

“Because we want to buy from a known plant that matches our needs, and not have to play scheduling games” he was told. “It needs a dedicated plant and if you won’t build it, we’ll find someone who will.”

The German CEO’s efforts to share the business with competitors aroused suspicion - enough for the customer to commission supply market research which reported that this potential German supplier controlled the market for a malonate precursor and sold it to the Swiss and Japanese firms. The CEO had thought he could avoid capital investment in the pyridine product for a single customer, whilst reinforcing his dominance in the market for the malonate precursor. A threat to source all requirements from another company would drive the chosen supplier to invest in the precursor and thus destroy the German company’s hegemony. In order to retain their monopoly, the German CEO quickly agreed.

That was two out of three intermediates needed for a new blockbuster agrochemical which already had a planned launch date, and a plant for the final product under construction.

It was a different story again for the third product, a phenol compound. The prospective English supplier professed great confidence in its ability to manufacture and supply. They had not made or sold the product previously - nobody had - but they had the raw materials and claimed to have good technology. George, the MD, and his team however would share nothing about how they were going to do it. They refused to explain their process or give any information about development progress. With time passing, the plug was pulled and the business was given to a competent French supplier.

Three very different scenarios in terms of technology, market and business culture. At no point, for any of these products, was a multi-supplier strategy considered and the point of these concurrent stories is this.

• Full commitment from business partners was needed.

• Suppliers had to be open and transparent within reason; or they were dropped.

• In operation, there would be full synchronisation of manufacture and delivery.

Only one supplier can be the ‘best’. Adding a second means less than best.

A no-brainer, surely! Who, with any choice whatsoever, would consider a multi-supplier strategy?

SWISSUES is getting ambitious. As of today, we are on Substack—the premier platform for serious-minded reflection, hosting the world’s leading journalists and thought leaders.

The ethos of SWISSUES has evolved. Our contributors are more sophisticated than they realize. Defined by more than just a job title or salary, they possess deep insight, autonomy, and the generosity to support others. SWISSUES may be your place.

Business and Being

SWISSUES is the unself-help guide that makes sense of why things don’t make sense. It is practical philosophy where experience becomes expression, confirming you aren’t the only one thinking this.

Join the Conversation

Viewpoint is our new name for long-form content. We invite subscribers to submit articles (500–1,000 words). We will help you polish and publish your work with full attribution, anonymity, or a nom de plume.

Join the journey.

Subscribe now

Does it need radical transparency?

Alignment has two different meanings in business.  One permits trust whilst the other demands vigilance. When travelers have a common objective, progress towards a joint goal benefits both. They can share resources and information with confidence. Cooperation is frictionless; there is no need to keep a tally of benefits.  The joint destination encourages mutuality.  There is a level of trust.

If however one traveller has deviated from their path to be with the other, their goals are different.  Both parties should monitor their relationship and be prepared to act when imbalance makes it unstable. 

The first situation is congruent alignment, the second, strategic.  To mistake the second for the first puts misplaced reliance on trust.  Trust is highlighted in a number of major books on selling.  All recognise the crucial importance of openness in a relationship if trust is involved

The first, Conceptual Selling (1987), describes a joint venture mindset in which the parties to negotiation reveal not only their corporate pay-offs from the deal, but their own personal incentives from a successful conclusion.   

The second, The Trusted Advisor (2000), is responsible for the famous Trust Equation, a formula for assessing trustworthiness: 

Trust = (Credibility + Reliability + Intimacy) / Self-Orientation [T = (C+R+I)/S], 

Higher Credibility, Reliability, and Intimacy boost trust, while increased Self-Orientation (focusing on oneself) reduces it.  Self-interest is an inverse factor (a divisor) in the equation because increasing self-interest reduces trust.   Could this divisor be replaced by congruent alignment as a multiplier?

This radical-transparency, cards-on-the-table approach was once radical. It is so no longer; it is also advised in ‘Give and Take’ (2013), ‘Never Split the Difference’ (2016), and ‘The Transparency Sale’ (2018).  It is nevertheless still not understood; and not just by sales people.  Internal staff who rely on other business units, functions and colleagues talk about internal client partnership and alignment when they want to give the appearance of support or are invoking some supposedly shared corporate aim.  They too openly talk about selling their services. It is especially naive of anyone in a continuing relationship to imagine they appear sincere and trustworthy unless they are open about their own rewards and incentives.. 

The post What is Alignment? appeared first on SWISSUES.

Weak Emergence

Mainly predictable according to scientific laws, allowing for randomness.

Sand dunes

Formed by the interactions of air flow (wind) and gravity on wind-blown sand particles. A dune moves as sand is removed from one side and deposited on the other and it may initiate the downwind formation of other dunes. This can create complex patterns over large areas. Something similar is seen in ripples on a beach, caused by water flow. There is no intrinsic information in the dune that determines its shape and those shapes can be explained by physical laws. Information about a dune’s form is in the overall shape of the dune. No part of a dune’s carries information that could replicate the whole.

Crystals

Parts of crystals do carry information that not only allow it to grow with a unique structure in certain environments but can seed separate growth (replication) of a similar structure elsewhere. This replication and growth process and the creation of patterned structure is still labelled as weak emergence because it can be explained by scientific laws and can be predicted.

Strong Emergence

Complexity that cannot be explained or forecast is labelled strong. So far as is known, it is exclusively found in biological systems. There are three types of system that exhibit strong emergence.

Genetic

Nucleic acids (DNA/RNA) carry genetic information that determines the form of the phenotype. These discrete packets of information shape the system in which they exist. If changes occur in the nucleic acid and hence in the information they carry, these may be passed on during replication. If the changes allow the nucleic acids to exploit their environment and replicate more effectively, the resulting DNA/RNA will displace their parents and other relatives not carrying the advantageous change. After Charles Darwin, we know this as Darwinian evolution. However, after Richard Dawkins, we must think of the hereditary units as genes (nucleic acids) or genotype, and not as phenotypic individuals.

The point of this is that evolution is not a designed or rule-bound process with goals. Immensely complex systems and systems-of-systems evolve in ways that have no scientifically predictable outcome and these systems can be stable, self-sustaining, and self-replicating. They continue moreover to evolve increasing levels of complexity.

It is possible that the equivalents of genetic information may be found at quantum level or in black holes, and that these may be shaping our universe in ways we have not begun to suspect. For now, however, DNA/RNA are the only discrete, physical packages of information.

Memetic

Memes are abstract, not physical; like virtual genes. They are frequently thought of as behaviours but include ideas, stories, technology and art and any combination of these in what we call culture. This definition of memes is from Richard Dawkins and refers to a unit of cultural transmission or imitation. Memes replicate (by definition) and as they do so they change.

Any consideration of communication and, to a large extent, of all behaviour must conclude that what characterises it is the interaction of memes.

Charles Darwin followed Adam Smith’s philosophies and it seems likely that Darwin’s theory of evolution leans heavily on Smith’s ‘Invisible Hand’, an early description of how a complex, self-sustaining, self-replicating and self-improving, system (society) emerges from memetic competition.

It is a short step from these concepts to the idea that today’s organisations are not the result of organograms, process-flows and Gantt charts, but emerged from the chaotic interactions of memes; and were then captured post facto by business administrators keen to convert their observations into reductionist tools.

Algorithmic

In 2009, Facebook launched algorithms that evaluated the impact of messages on user- engagement by monitoring the effect on their ‘likes’, ‘forwards’, ‘comments’ and other. It also analysed users’ networks and identified those ‘friends’ likely to respond to similar messages. It would also test user-responses to messages they would not normally receive. It was, as is now well known, able to profile users with a high level of accuracy in terms of character type, socio-economic class, family status, hobbies, preferences and other. The aim was to maximise engagement (aka, clicks). The algorithms were able independently to reset their own parameters according to feedback received on engagement. Click-engagement stimulated revenues, initially through corporate advertising and later through political messaging, enriched Facebook fabulously.

What emerged was a symbiosis of algorithms and human operators. The operators grew rich and may have felt in control. In practice there is a question about whether any control existed. Sarah Wynn-William’s book, ‘Careless People’ describes how wealth generated by the algorithms led to the expansion of Facebook’s influence and a change in its culture. In her personal telling, the benevolent, well-intentioned culture of the start-up became corrupted by wealth and power, to the point where Facebook lobbied to avoid child-safeguards, dismantled its stewardship, and may have supported brutal autocracies like Myanmar where it saw opportunities for monopolistic growth.

What was the role of the algorithms? They are not sentient; but could they be intelligent? It does not matter. What we see is emergence of a complex system. What we have learned is that emergence is more powerful than intelligence. In this chosen example the algorithms exploited the intelligence of Facebook staff. We should worry less about the possibility of superintelligence in the near future and more about emergence from those sixteen year old algorithms.

The post Emergence > Intelligence appeared first on SWISSUES.

The rise of a zero-sum mindset, where someone’s gain is another person’s loss, is a pressing modern challenge. While zero-sum has ancient roots, its contemporary amplification is shaped by a century of Scientific Management.

Frederick Winslow Taylor’s vision treated organizational processes as mechanistic systems, optimising individual components for maximum output. This “scientific” engineering, despite its misapplication to human systems, gained immense traction for its simplicity, quick results, and promise of a “one best way.”

Yet, its critical flaw lies in its failure within complex adaptive systems. Here, the “whole” is far more than the sum of its parts, driven by emergent properties and human agency. Taylorism’s reductionist approach frequently leads to suboptimal outcomes.

This is where it aligns with a zero-sum mindset. Both impose “restricted boundaries” and “locked-down parameters,” implying finite resources and predetermined outcomes. Both also foster “limited autonomy”. When roles are rigidly defined and resources appear top-down, it’s easy to perceive another’s gain as one’s own pain, or efficiency being at the expense of worker well-being.

A cultural preference for oversimplified fixes has been systemically reinforced by Tayloristic management principles, education, and policy, It has bred impatience with complexity, externalities, and the challenges of truly adaptive systems.

Thus, while a zero-sum mindset predates the industrial revolution, Scientific Management’s enduring legacy has skewed our worldview, making us more prone to seeing a world of winners and losers, rather than one rich with collaborative, positive-sum potential.

Companies have certain legal obligations and rights. They have no conscience, no moral code and no social responsibilities. That is the law in every country. Corporate social responsibility (CSR) is an oxymoron – it contains contradictory and incongruous elements. It is not lawful for corporations to give charity, other than as part of a deal from which the corporation expects to benefit. It is not lawful for corporations to sign up to commitments from which they will not gain. If a corporation had a personality, it would be that of an amoral psychopath.

How have we been seduced into believing otherwise? One reason is public relations and advertising. Beginning in the nineteenth century, companies used brand character, celebrity endorsements and human mimicry to encourage customers and stakeholders to invest trust and confidence, and to build a human-like relationships with them.

Another reason is the legal concept of corporate personhood that exists in every jurisdiction. This gives companies obligations – they can be sued for breaking laws; it gives them rights to sign contracts; and it makes them distinct from employees and managers. Corporate personhood does not give corporations any moral guidance whatsoever, other than compliance with relevant law. Insofar as a corporation benefits anyone other than the shareholders, it may do so only out of self-interest, albeit ‘enlightened’.

These self-evident, but often concealed, truths have been brutally exposed by corporations’ responses to a changing political and cultural climate. The fiction of the double bottom line has been dropped like a hot brick by companies like BP, Shell, BlackRock, Unilever, Crocs, Coca-Cola, Nestlé, Microsoft etc., etc., etc., that have rolled back their CSR agendas and reinterpreted them as risk management.

So how does it feel to work for a psychopath?

Across many organisations, ESG has evolved into a peculiar blend of compliance, risk analysis, and reputation management. The result is a system that demands vast amounts of data, constant reporting, and a steady flow of polished narrative — all of which keep teams extremely busy but not always strategically focused.

AI can certainly help with the busywork. It can summarise climate disclosures, draft responses to investor questionnaires, and spot inconsistencies in data. But if we stop there, we miss the bigger opportunity: using AI to challenge the ESG requirements themselves.

Instead of doing the same ESG tasks faster and cheaper, AI can help us ask a deeper question: Why are we doing these tasks at all, and are they still the best way to achieve our goals?

1. ESG is full of inherited habits

Much of today’s ESG workload is driven by past decisions — frameworks that were fashionable at the time, consultancy checklists, or reporting templates that have grown more elaborate each year. Over time these became “the way things are done,” and teams now diligently optimise for them.

AI can boost this optimisation. But becoming more efficient at an outdated requirement is like speeding up a train that’s heading in the wrong direction.

What if, instead, we asked AI to help us redefine the direction entirely?

2. Example: Rethinking supplier audits

Many companies run annual supplier sustainability audits. The process is familiar: a long questionnaire, a desktop review of public records, maybe a site visit for the largest suppliers.

AI can certainly automate this. But it can also challenge the process itself by asking:

• Which of these questions predict actual supplier risk?

• How did this audit format originate?

• What would a modern, data-led approach look like?

You can prompt an AI with:
“Design a sustainability risk-detection system for suppliers that uses real-time signals rather than annual questionnaires.”

The result might be an entirely different model — continuous monitoring of financial stress, sentiment analysis of labour issues, satellite imagery for land use, or open-source indicators of political stability.

Suddenly, the requirement of “annual audit” looks less like a rule and more like a historical convenience.

3. Example: Reframing climate disclosures

Many teams spend months producing climate reports filled with charts, emissions tables, and transition pathways. AI can produce these in minutes — but it can also ask:

• What decisions does this report inform?

• Which parts genuinely matter to investors or regulators?

• What if disclosure were designed to help internal decision-making first, external reporting second?

A useful AI prompt is:
“If we had no legacy reporting framework, how would we communicate our climate risks and resilience to someone who wants to understand the business in under five pages?”

This often produces a far clearer, outcome-focused approach that strips away the clutter.

4. Example: Social impact beyond philanthropy

Many organisations treat “S” in ESG as charitable projects: mentoring schemes, donations, volunteering days. These are useful, but they often sit at the edge of operations.

Ask an AI:
“Identify the three social impacts that matter most to our long-term operating model, even if they are not currently measured or reported.”

AI will likely highlight deeper issues — community trust, workforce adaptability, or local economic resilience — which are far more strategic than traditional CSR activities. This shifts the requirement from “run another community initiative” to “strengthen the social systems that make our business viable.”

5. AI as an honest partner

One advantage of AI is its neutrality. It is not weighed down by internal politics or legacy decisions. It can calmly point out:

• Where a metric adds cost but not insight

• Where two ESG targets contradict each other

• Where the company is solving yesterday’s problems

• Where reporting requirements distort decisions rather than illuminate them

By prompting AI to stress-test the logic behind each ESG activity, we start to see which requirements are essential and which are simply habitual.

6. Leadership must make rethinking permissible

Many ESG teams know certain requirements are outdated but feel unable to challenge them. AI can help, but only if leadership sends a clear signal:
You are empowered to question the requirement itself, not just the data behind it.

With that permission, teams can use AI to explore counterfactuals, prototype alternatives, or simplify complex processes.

In the end, AI is not merely a tool for speeding up ESG tasks. It is a catalyst for reimagining what ESG could be — a strategic system that focuses on real outcomes, not inherited rituals.

CIPS Switzerland Event, 12th November 2025

The majority of us spend our working lives in organisations that share one thing in common, a pyramid structure where decision making is located with only a few people. That can be a sensible way to organise, but what if there were another way? If you have read ‘Corporate Rebels’ by Joost Minnaar and Pim de Morree, you will have learned about companies operating outside this conventional norm. In Switzerland there are many more examples than I would have guessed, which you can learn about through the Zukunftspioniere Podcast published by Team-Factory. We thought it would be great to run a CIPS event, together with Team-Factory, but also with one of the companies who appear both in the book and on the podcast, Everllence in Zürich. We have the opportunity to walk the factory floor and then hear from the team on how they re-organized themselves.

Why should you join this event? If you have ever been frustrated by the way that decisions get made, how companies and teams are organised, why you cannot take more ownership of your role, or if you are curious about different ways of working, then this event is for you! We will also have the opportunity to explore and discuss what it would mean to work in Procurement in such a set up. We are very keen to get your thoughts and questions as part of the discussion.

The formal event posting and registration through CIPS will be here in a few days, but thought it would be good to plant the seeds and send the ‘save the date’. If you use the LinkedIn Event page to say you will attend, we will keep you up to date with the registration process

The post Burning Down the House appeared first on SWISSUES.

This Post is a response to an article, ‘A win-lose situation?‘ by Stefanie Stantcheva, in The Economist, 12th July 2025

The rise of a zero-sum mindset, where someone’s gain is another person’s loss, is a pressing modern challenge. While zero-sum has ancient roots, its contemporary amplification is shaped by a century of Scientific Management.

Frederick Winslow Taylor’s vision treated organizational processes as mechanistic systems, optimising individual components for maximum output. This “scientific” engineering, despite its misapplication to human systems, gained immense traction for its simplicity, quick results, and promise of a “one best way.”

Yet, its critical flaw lies in its failure within complex adaptive systems. Here, the “whole” is far more than the sum of its parts, driven by emergent properties and human agency. Taylorism’s reductionist approach frequently leads to suboptimal outcomes.

This is where it aligns with a zero-sum mindset. Both impose “restricted boundaries” and “locked-down parameters,” implying finite resources and predetermined outcomes. Both also foster “limited autonomy”.  When roles are rigidly defined and resources appear top-down, it’s easy to perceive another’s gain as one’s own pain, or efficiency being at the expense of worker well-being.

A cultural preference for oversimplified fixes has been systemically reinforced by Tayloristic management principles, education, and policy,   It has bred impatience with complexity, externalities, and the challenges of truly adaptive systems.

Thus, while a zero-sum mindset predates the industrial revolution, Scientific Management’s enduring legacy has skewed our worldview, making us more prone to seeing a world of winners and losers, rather than one rich with collaborative, positive-sum potential.

The post Zero-Sum Mindset & Taylorism appeared first on SWISSUES.

Why Old Economics Fails and What Might Replace It

J. Doyne Farmer’s book is dense, chaotic, and occasionally brilliant. Here’s the real point behind the math.

The title is well chosen — not just for the subject matter, but for the book’s style. Making Sense of Chaos is a whirlwind of anecdotes, theories, economic history, scientific digressions, and personal reflections from the author’s unusual career. Somewhere within this blizzard lies a clear and important idea — but it’s not easy to find.

J. Doyne Farmer is a physicist turned economist, and this book reflects that journey. He explores cybernetics, complex systems, self-organizing structures, and the evolution of economic thought, often taking detours into the careers of researchers and the history of ideas. The result is intellectually stimulating, but at times overwhelming. Many readers — judging from other reviews — struggle to finish it, or finish unsure what its main point was.

So let me attempt to say what I think the conclusion is — at the risk of oversimplifying a complex argument:

Economics, since the 19th century, has tried to quantify human behavior. Following Adam Smith’s Wealth of Nations (1776), economists sought to make the idea of the “invisible hand” measurable. The result was a set of so-called analogue-based models — equations that describe economic behavior in smooth curves. Think of a demand curve showing that as prices fall, sales increase. These models are elegant and easy to work with, and they often match historical data reasonably well — but they’re poor at predicting the future.

The problem is realism. Analogue-based models assume a single, average customer whose behavior changes smoothly as conditions change. But in reality, markets are made up of many different types of buyers, some of whom behave unpredictably — even irrationally — and influence one another. Some buyers only appear when prices fall; others, surprisingly, drop out. In short, human behavior isn’t smooth. It’s messy, interactive, and diverse.

To capture this complexity, we need a different kind of model — one that simulates individual behaviors, group interactions, and emergent outcomes. These are known as agent-based models. Until recently, they were too computationally intensive to be practical. But now, thanks to modern computing power, they’re becoming viable — and they offer a radically better way to understand economic systems.

That’s the real promise behind Farmer’s subtitle: A Better Economics for a Better World. Agent-based models can help us design policies that account for inequality, instability, and systemic risk — things traditional models often overlook.

This book is valuable not just for its argument, but for what it represents: a turning point in how we model human systems. For non-experts, it offers just enough background to start asking better questions — especially when faced with economic models or policy recommendations. But be warned: you may need to fight your way through some chaos to find the clarity.

The post From Curves to Chaos appeared first on SWISSUES.

Don’t get blindsided by the energy revolution.

Even if you don’t buy energy. Even if you’re not in heavy industry. Even if your biggest concerns are supply chains, geopolitics and cybersecurity. You need to be aware of what is happening in Energy.

One soft drinks company found out the hard way. Planning a large new factory in the UK, they expected to install solar panels across all available roof space—enough to make the site self-sufficient and feed surplus power back to the grid. It fit their ESG targets, slashed energy costs, and made great PR.

But they hit a brick wall: the local grid couldn’t take the power. Not because they were drawing too much, but because the infrastructure wasn’t built to receive electricity from customers. Despite the investment, the roof, and the sunlight, they were stuck.

Multiply that by thousands of companies across dozens of sectors, and you start to see the problem:

We’re entering an energy-fragmented era—and most businesses aren’t ready.

From Central Control to Local Chaos: Energy’s Shifting Landscape

For over a century, businesses treated electricity like water: it came from a central source, flowed one way, and pricing was predictable. That model is cracking.

We’re now seeing a surge in:

• Local generation (solar, wind, combined heat and power)

• Battery storage and EVs-as-assets

• Dynamic pricing and time-of-use tariffs

• Grid instability and patchy infrastructure

This isn’t just a utilities issue. It’s a business continuity issue, an investment risk, a competitive differentiator, and increasingly, a license-to-operate issue.

Why You Should Care—Even If Energy Isn’t “Your Job”

1. Your Next Site Might Not Work

That soft drinks factory isn’t unique. Manufacturers, logistics hubs, and data centers are discovering that grid constraints—not land, labor, or tax—are the critical bottleneck.

• You may be unable to export solar power to the grid.

• Your site’s energy needs might outstrip regional capacity.

• Upgrading the connection could take years, not months.

Real estate due diligence needs a new lens: Can this site support your future energy plan—or is it a stranded asset waiting to happen?

2. Energy Becomes a Strategic Variable

We’re moving from a flat-rate world to a volatile energy market:

• Prices can swing wildly based on weather, time of day, or demand.

• Smart firms are using on-site batteries to arbitrage pricing.

• Others are getting paid to reduce consumption during peak periods.

Companies in cold storage, logistics, and manufacturing are already seeing that energy flexibility beats energy efficiency.

3. Your Suppliers May Be Vulnerable

Just as Covid exposed brittle supply chains, the energy transition is exposing brittle industrial ecosystems:

• Can your upstream suppliers cope with grid fluctuations or energy price spikes?

• Are they using processes that will soon face regulatory or carbon price penalties?

• Will geopolitical disruptions to solar, battery, or hydrogen tech ripple into your cost base?

A Tier 2 supplier’s diesel addiction could become your public relations crisis.

4. Products and Services Will Be Judged on Energy Intelligence

Products that consume energy are being held to new standards:

• Do your devices optimize for time-of-use pricing?

• Can your software handle energy-aware routing or logistics?

• Is your building management system designed for dynamic energy markets?

Even if you don’t sell energy tech, you’ll need to sell energy competence.

Still Think This Isn’t Your Priority?

You’re right to worry about geopolitics, supply chains and cyber security. But don’t overlook energy infrastructure.

• China controls most of the critical materials for batteries and solar panels.

• Europe’s grid is still digesting the consequences of Russia’s gas weaponization.

• Subnational energy policy is creating industrial winners and losers within countries.

Ignoring energy is like ignoring the water table when you’re in real estate: it’s beneath everything—but when it shifts, everything moves.

What You Should Be Doing Now

Even if you don’t generate or manage energy today, your organization needs to ask:

• Are our future sites and suppliers energy-resilient?

• Can we withstand or exploit pricing volatility?

• Are we missing opportunities to create or store energy on-site?

• Are our products and services built for an energy-fragmented world?

• Can our team read the grid, or are we flying blind?

Don’t Wait for the Lights to Go Out

The energy transition isn’t coming. It’s already here. But like climate change, it arrives locally and unevenly—until it’s your turn.

The question is not whether you’re in the energy business.
The question is: How much longer can you afford to act like you’re not?

The post Back of the Grid? appeared first on SWISSUES.

Why Tactics Are a Dangerous Turn-On

Negotiation tactics can be intoxicating. We love the drama—holding our nerve, making the perfect demand, walking out just to be called back. It feels clever, edgy, powerful. But beneath that adrenaline buzz is a danger that’s rarely acknowledged.

Our fascination with tactics has become a kind of pornography.

Like all pornography, it isolates the most intense moment—the climax—and treats it as the whole story. It skips the slow buildup, the mutual understanding, the hard emotional and intellectual labour that gives any relationship—or deal—its meaning. It promises gratification without intimacy. Victory without alignment. Value without preparation.

And the consequences are the same: unrealistic expectations, short-term satisfaction, and a tendency to walk away with less than you think you got.

The Fantasy of the Perfect Move

Negotiation books, training sessions, and war stories often focus on what happened at the table. Who blinked first. What tactic won the day. How someone ‘crushed’ the other side.

But these stories are usually fantasy. The real work of negotiation happens before the room. The outcome is shaped by:

• How clearly you’ve defined your own requirements

• How well you’ve understood the supply market

• How aligned your internal stakeholders are

• How much effort you’ve invested in understanding the other party’s drivers

If that work hasn’t been done, then you’re not negotiating—you’re improvising. And that’s when tactics become seductive. They offer the illusion of control when strategy is absent.

Consummation Is Not the Relationship

We talk about negotiation as if it’s the event, the showdown, the moment of truth. But in serious commercial life, the negotiation is the consummation, not the courtship.

The deal was made—or lost—during all those unglamorous weeks of thinking, aligning, researching, and shaping the context. The conversation across the table is just the final step in a long process. When people rely on tactics to ‘win’ at that point, it often signals that the hard work wasn’t done earlier.

You wouldn’t judge a relationship by the first night. Yet we do this with deals all the time.

The Problem with One-Night Deals

When negotiation is all tactics and no trust, you may get the deal—but you won’t get the relationship. There’s a high chance of regret, breakdown, or underperformance once the real work begins.

That’s because tactics tend to produce compliance, not commitment. They may extract concessions, but they rarely generate shared enthusiasm. And when things go wrong later—as they always do—it’s hard to recover when the foundation was just a performance.

The best deals are designed to be repeatable. They work because both sides want to do business again. That doesn’t happen when one side feels manipulated, cornered, or tricked.

Substance Is the Real Turn-On

The irony is that the most effective negotiators often appear to be doing very little. They’re not theatrical. They’re not trying to dominate. They don’t need to be.

They’ve built trust. Created clarity. Aligned stakeholders. Understood the market. They’ve made it easy to say yes—because the deal actually works.

This is the unsexy truth: when you do the real work, the negotiation looks boring. It feels smooth. It sounds like a conversation.

But boring is beautiful—because boring gets deals done. And boring gets deals kept.

Closing the Tab

So if you find yourself overly excited about negotiation tactics—if you’re getting a little high on the idea of the ‘killer move’ or the dramatic close—pause for a moment.

Ask yourself what you’re really trying to compensate for.

• Do you understand your requirements?

• Have you aligned your internal team?

• Do you know what the other party needs?

• Have you built any trust?

Because if not, no tactic will save you. And if so, you probably won’t need one.

That’s when negotiation starts to feel less like a performance—and more like progress.

The post Negotiation Porn appeared first on SWISSUES.