Time is Money – and other dangerous half truths

We’ve all heard the phrase “time is money.” It’s the sort of thing people say when they want to sound brisk and commercial, usually while checking their watch with the air of a man who has better things to do. Benjamin Franklin gets the credit, though even he might have raised an eyebrow at how modern life has turned it into a moral commandment. Waste time and you are, by implication, burning banknotes.

The reverse is far more interesting. Money is time. With enough of it you can buy other people’s hours – cleaners, drivers, assistants, software, machines, entire systems that perform in seconds what once took days. You are not merely acquiring goods; you are purchasing a claim on the future organisation of human effort. A wealthy man does not so much own a car as own the right not to stand in the rain waiting for a bus. That is a profoundly different proposition.

Once you accept this two-way street, life sorts itself into four awkward quadrants.

First: lots of time and lots of money. The lottery-winner fantasy. On paper it looks like pure bliss. In practice it is often slightly terrifying. Sudden abundance of both can remove the constraints that give life shape. Without scarcity, purpose has a nasty habit of evaporating. Studies of actual lottery winners (the Swedish and German ones are particularly good) show that large windfalls do raise life satisfaction, and the effect lasts for years. People tend not to blow it all on yachts; many keep working but simply work less, converting cash into higher-quality leisure. The gain is real. Yet the absence of friction can leave the mind slightly adrift, rather like a sailboat in a dead calm.

This brings us to the eternal question: does money make you happy? Within any society, richer people report higher life evaluation. That is not controversial. The old Kahneman–Deaton finding suggested day-to-day emotional well-being plateaued around US$75,000 (roughly US$90–100,000 today), while broader life satisfaction kept climbing. More recent work by Matthew Killingsworth, including a re-analysis with Kahneman, suggests that for about four-fifths of us happiness continues to rise with income – no obvious ceiling. Only the chronically unhappy plateau. Money is extremely good at removing the emotional pain of genuine hardship and at expanding the freedom to shape your days. Beyond that, its power depends almost entirely on how you spend it and on the temperament you started with. Spreadsheet economists tend to miss this because they treat money as a pure utility maximiser rather than a context-dependent psychological tool.

Paul Dolan, the behavioural scientist at the LSE, has done some of the most useful work here. In Happiness by Design he argues that happiness is simply experiences of pleasure and purpose over time – not the abstract life-satisfaction score you give a researcher, but the actual moments as you live them. Attention is the crucial production process: the same income, job or relationship can generate wildly different levels of happiness depending on what you pay attention to. Money only makes you happier to the extent that it directs attention towards pleasurable or purposeful experiences rather than anxiety or comparison. In Happy Ever After, Dolan dismantles the “narrative traps” of the perfect life – the relentless story that more money, more status and more hours will eventually deliver fulfilment. Time-use data show that daily happiness often peaks at moderate incomes and moderate working hours (roughly 21–30 a week). Beyond that, high earners frequently divert attention towards activities that fuel the pursuit of still more wealth – longer days, longer commutes – and away from the things that actually generate pleasure and purpose. Paying attention to “time as money,” he notes, actively diminishes the enjoyment of leisure. The result is that the richest are sometimes less happy day-to-day than those in the comfortable middle. We keep chasing the wrong story because society keeps telling it, not because the data support it.

Second quadrant: no time, lots of money. The high-flying lawyer, banker or management consultant. Handsomely paid, permanently exhausted, and privately convinced that one more promotion will finally buy the freedom it has so far only postponed. Here the tyranny of the diary is absolute. Every hour is optimised, every minute accounted for, and the second-order costs – fraying relationships, eroded judgement, the quiet accumulation of resentment – never appear on the P&L. These people are not rich; they are highly compensated prisoners. Dolan would say they have fallen into the “reaching” trap.

Third: lots of time, no money. Students, some artists, and a regrettable number of poor pensioners. Temporal space in abundance, yet choice is severely constrained. You have the freedom to stare at the wall, but not much else. Opportunity cost is measured not in lost billable hours but in experiences and security quietly forgone.

And the final, bleakest cell: no time and no money. Historical slavery or its modern economic equivalents. Both scarce resources controlled by someone else. Agency collapses. The language of “optimisation” becomes almost obscene.

Here is where the research becomes useful. Ashley Whillans and her colleagues have shown, across thousands of people, that those who consistently value time over money report higher well-being. In one longitudinal study of graduating students, those who prioritised time at the outset were happier a year later and more likely to choose intrinsically rewarding work. Roughly 60 per cent of people still claim they would prefer more money, yet the minority who choose time are, on average, the happier lot. Experiments confirm that spending money specifically to buy time – outsourcing the chores you hate – reliably lifts life satisfaction across income levels. Dolan’s pleasure-purpose principle explains why: buying time frees attention for experiences that actually feel good in the moment.

The real insight is not that one quadrant is morally superior. It is that the exchange rate between time and money is one of the most important, and least examined, variables in human decision-making. Most of us drift between these states across a lifetime. Conventional economics treats both resources as simple inputs to be maximised. In reality they are psychological currencies whose value depends heavily on context, perception and signalling. Money is superb at buying back time; time is superb at making money feel worthwhile. Confuse the two and you end up optimising the wrong thing with great efficiency.

As Dolan keeps reminding us, time is the one resource you cannot beg, borrow or steal more of. We’re five minutes closer to death than when you started reading this. That fact alone should make the spreadsheet look a little less authoritative.

In a world that still worships rational optimisation, a modest bias toward protecting time – and a willingness to spend money in ways that feel slightly irrational to an economist – remains one of the few reliable competitive advantages left. Sometimes the smartest move is to stop treating every hour as a potential invoice and start treating it as the only currency that cannot be reprinted.

Our Networks – Clusters, Hubs and Distant Ties

It is a truism, but every day we navigate a dense thicket of human connections. A chance remark in a meeting, a forwarded email, a shared contact on social media – suddenly an idea, a rumour or a risk has travelled farther than we ever intended. In business and finance this is not abstract theory; it is the practical reality of how opportunities arise, how crises cascade and how decisions take on lives of their own. Understanding the architecture of these networks is as important as understanding balance sheets or volatility models. The patterns that govern our relationships shape the flow of information, influence and vulnerability in ways that pure numbers rarely capture.

British evolutionary psychologist Robin Dunbar’s well-known observation offers a useful starting point. Drawing on the relationship between neocortex size and group living among primates, Dunbar suggested that humans can maintain roughly 150 stable social relationships – the number of people with whom we can keep track of mutual obligations, history and emotional nuance. Beyond that circle the quality of connection thins rapidly. We may recognise many more faces, but genuine reciprocal knowledge runs out. Christmas card lists, military companies, traditional village sizes and even modern workplace teams have long hovered around this figure for good evolutionary reasons. Our cognitive bandwidth is finite; attention is a scarce resource. His later work refined the picture into concentric layers: roughly five intimate bonds, fifteen close friends, fifty good acquaintances, and then the outer ring of 150. Time and emotional energy are not evenly distributed; most of us devote the bulk of our social effort to the inner circles. Attempting to stretch far beyond this limit tends to produce shallow interactions rather than deeper insight.

Yet the world feels far smaller than 150. Stanley Milgram’s 1960s letter passing experiments popularised the notion of six degrees of separation: any two people on the planet are, on average, linked by a surprisingly short chain of acquaintances. Participants in the Midwest were asked to forward a letter toward a target in Boston, always through someone they knew personally. The successful chains averaged around six steps. Modern network studies, including those on vast online graphs, continue to find diameters in the region of four to six steps even as populations grow into the billions. The apparent paradox is resolved by the architecture of the network itself. Most of our contacts sit inside tight clusters – family, colleagues, old school or university friends – while a handful of long-range bridges and highly connected individuals shrink the global distance dramatically. Mathematicians Duncan Watts and Steven Strogatz later formalised this as the “small-world” phenomenon: high local clustering combined with a few random long-distance links produces short path lengths across the entire system.

Mark Granovetter’s 1973 paper on the strength of weak ties supplies a crucial missing piece. Strong ties – the close relationships that dominate our Dunbar core – tend to form dense, overlapping clusters. Everyone in such a group already knows much of what the others know; information becomes redundant. Weak ties, by contrast – the acquaintances, the occasional contacts, the people we see only intermittently – often act as bridges between otherwise separate clusters. Because these weaker connections link different social worlds, they are disproportionately valuable for bringing in novel information, fresh opportunities and unexpected perspectives. Granovetter showed that people looking for jobs frequently found them through weak ties rather than close friends. The same logic applies to the diffusion of ideas, market intelligence and even risk signals. Strong ties give us trust and emotional support; weak ties give us reach and surprise.

Those highly connected individuals we call super-spreaders of relationship networks often operate precisely through a combination of strong local clusters and carefully maintained weak ties. In epidemiology the term is familiar; in social and organisational life the same pattern holds. A few people sit at the intersection of many otherwise separate groups. They are the ones who hear the early rumour, introduce the distant expert, or inadvertently amplify a fragile piece of market intelligence. Their influence is outsized because the rest of us are busy maintaining our own limited Dunbar circles. Remove or isolate a handful of such hubs and the speed of transmission – of ideas, confidence, panic or opportunity – falls sharply. In financial markets we see the effect repeatedly: a single well-placed analyst, a central clearing-house contact, or a widely trusted industry figure can move sentiment faster than any formal announcement. Often these super-spreaders are not the most intimate members of any single group but the ones who cultivate a wide periphery of weaker connections.

For anyone concerned with risk and decision-making this structure matters profoundly. Classical models often treat information as flowing evenly or assume that “the market” is an efficient, near-random diffusion process. Reality is closer to a small-world network with pronounced hubs and a critical reliance on weak ties. A single conversation across a weak bridge can move capital or reputation faster than any formal report. Conversely, critical knowledge can remain trapped inside closed clusters of strong ties for months, creating blind spots that only become obvious when the damage is done. Digital platforms have not abolished Dunbar’s limit; they have merely extended the outer rings of weak ties while intensifying the power of the super-spreaders who bridge them. The result is both greater connectivity and greater fragility: information travels faster, but so do distortions and cascades.

The practical implication is not to collect ever more contacts – that way lies shallow networking and cognitive overload – but to understand the topology of the networks we already inhabit. Who are the natural bridges in our organisation or industry? Where do the dense clusters of strong ties sit, and what information fails to cross between them via weak ties? Plastic control of the kind Karl Popper described becomes useful here: we form conjectures about how influence actually travels, subject them to criticism, and adjust. We might deliberately nurture a few weak ties into adjacent fields, or map the super-spreaders whose absence would slow the flow of critical signals. We cannot redesign human nature, but we can stop treating social structure as invisible background noise.

In a world of accelerating change the quality and configuration of our connections remain more decisive than their sheer number. Dunbar’s limit reminds us of the cognitive ceiling on strong relationships; six degrees shows us the surprising global reach; Granovetter’s weak ties explain how novelty crosses cluster boundaries; and super-spreaders reveal the leverage points where influence concentrates. Navigating that tangled web with open eyes is one of the quieter, more durable advantages available to decision-makers.

Clouds, Clocks and Plastic Controls

Every day in business we make choices that carry real risk. The next big investment, the hiring decision, or how to navigate a supply-chain shock. Some days it feels like clockwork: gather the data, run the numbers, and the optimal path clicks into place. Other days it’s pure fog – a swirl of incomplete information, gut feelings and second-guessing.

Karl Popper, the philosopher of science, gave us a simple but powerful metaphor in his 1966 lecture Of Clouds and Clocks. Picture every system on a spectrum. At one end are clocks – precise, regular, predictable machines like the solar system or a well-engineered financial model. At the other end are clouds – irregular swarms of gnats or market sentiment where each particle seems random yet the whole somehow holds together. Popper’s punchline? All clocks are clouds. Even the most precise mechanism has tiny irregularities – friction, quantum jitter, the unexpected. The old idea that everything, including human minds, is a flawless deterministic clock is simply wrong. Reality is a mix of both. This insight matters enormously for decision making and risk.

 First, the clock trap. Many risk models and strategy frameworks treat decisions as pure mechanics. Input the variables – cash flows, probabilities, discount rates – and out pops the answer. Behavioural economists call it rational choice theory. In practice it leads to paralysis. You wait for perfect data that never arrives. Or you follow the spreadsheet slavishly and miss the second-order effects that actually matter. As Arthur Compton, the physicist who inspired Popper, once asked: if our actions are just atoms following immutable laws, why bother trying? Effort and responsibility become illusions.

This is a common trap in boardrooms. A beautifully engineered DCF model convinces everyone the deal is “low risk”. Then geopolitics or a competitor’s move turns the clock into smoke. The opposite danger is the cloud trap. Here decisions become pure emotion or intuition. “Trust your gut.” “Let the market decide.” In uncertain times this feels liberating but it is no better. Pure randomness offers no explanation for purposeful choice. You end up with impulsive bets or endless procrastination dressed up as mindfulness.

Popper’s solution sits in the middle, so called plastic controls. These are flexible, hierarchical systems with soft feedback – not rigid gears, not random fog. Think of a soap bubble. The soapy film gently shapes the chaotic air inside; the air pushes back. Mutual, adaptive control. In human decision making this means treating your mind as an evolutionary problem-solving engine. You form bold conjectures – creative guesses about what to do. You criticise them hard: “What if this fails? Does it fit our risk appetite? What are we missing?” Bad ideas die in your head rather than in the P&L account Fresh evidence or reflection lets you revise.

This is trial and error with purpose. Your intentions and theories exert real downward influence on events. Purposes shape behaviour; behaviour feeds back into better purposes.

Take a real-world example. A fund manager faces a volatile energy market (sound familiar?). Clock thinking says optimise the portfolio on historical correlations. Cloud thinking says follow the latest headline. Plastic control says: generate three scenarios, test them ruthlessly against known unknowns, run small experiments or pilot trades, and let the weakest option die. The final allocation emerges – reasoned, adaptable, alive.

The beauty of this view is its practicality for risk professionals. It explains why effort in thinking actually counts. Decisions are not illusions; they are the spearheads of problem-solving. It also builds humility. Every choice carries some cloudiness. You will never have perfect information. But progress comes from surviving criticism, not from chasing certainty.

Next time you face a high-stakes call, pause and ask, am I treating this as a clock (rigid rules and models), a cloud (pure instinct), or a genuine plastic system (creative conjecture plus fierce criticism)? The third path turns decision making from a source of anxiety into a genuine source of competitive edge.

We are not passive cogs in a machine or drifting mist. We are plastic controllers – capable of shaping outcomes through reason and creativity even in the face of genuine uncertainty. This the optimistic lesson Popper left us.

More on Popper’s Lecture

ChokePoint Charlie

In this March 29th, 2026 episode of Equitile Conversations, Gerald Ashley and George Cooper offer a downbeat assessment of the escalating US-Iran war in the Gulf and its profound impact on global supply chains and financial markets. They describe a major negative supply shock triggered by widespread destruction of energy infrastructure, with the US reportedly planning ground troops into Iran. Oil prices spiked near US$120 per barrel before moderating above US$110 despite strategic reserve releases and temporary de-sanctioning of Russian and Iranian supplies. Fuel shortages are already appearing globally. They both warn the disruption will be durable, lasting months to possibly years, affecting not only energy but also fertilizers and agriculture. Emerging second-order effects, such as diesel and fertilizer shortages for Australian farmers, are expected to drive food price inflation with a 6–12 month lag. This points to a protracted inflationary period reminiscent of the late 1970s.

George argues that central banks should avoid hiking interest rates, as this is an exogenous shock; tightening policy risks compounding the damage by discouraging necessary investment. Despite this, the ECB is considering rate rises and the Bank of England appears uncertain. The discussion also covers ballooning US debt (now US$39 trillion), strained fiscal positions in the West, questions over AI investment viability, and geopolitical shifts. Using the physics concept of the “elastic limit,” they suggest the global order may not return to its previous state, potentially weakening US dominance and accelerating de-dollarisation.


https://www.equitileconversations.com/2459100/episodes/18924343-chokepoint-charlie

This Episodes Recommendations

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The Beer Game

A free easy to play simulation here:
https://beergame.transentis.com/

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Tiny Rowland – A Rebel Tycoon by Tom Bower

Gold & Dinner at The Savoy

A couple weeks back I joined my colleague George Cooper for dinner at The Savoy Grill. We also invited along macro economist Doug McWilliams, and explained to him why this fancy upmarket venue (A Gordon Ramsey badged place) was “critical research” regarding the price (or perhaps more accurately) the value of gold.

Investment in gold and more particularly gold miners has been a very favourable element in the spectacular success of two funds run by George at http://www.equitile.com

Last December I recalled the now largely forgotten metric, the Savory Dinner/ Gold ratio, coined by the well known 1990s stockbroker Julian Baring. So we thought we would do a new “fixing” at a dinner.

The story of this dinner and the background to Julian Baring and his ratio, was picked up by The Times, and below is a great article about it.

An ounce of gold now buys dinner for 14 at the Savoy

https://www.thetimes.com/article/bffadb3c-e65f-4900-b69c-a4cd33336796?shareToken=6029e52bd34de19def9d382fc4e0a7c8