Economics & Markets
Section 1
The Core Idea
Utility is the satisfaction or benefit an agent gets from an outcome. It is not directly observable — we infer it from choices. Economists model decision-making as utility maximisation: given options, the agent chooses the one that yields the highest expected utility. Utility functions can be ordinal (ranking) or cardinal (magnitude); for most applied work, ordinal ranking is enough. The core move is to treat "value" as a single index that captures whatever the decision-maker cares about.
Marginal utility is the change in utility from one more unit of something. The law of diminishing marginal utility says that each additional unit adds less satisfaction than the previous one. The first slice of pizza has high marginal utility; the fifth has low. That declining curve drives consumption patterns, pricing, and the shape of demand. It also explains why equalising marginal utility across uses — spending time or money until the last unit gives the same bang per buck everywhere — is the condition for optimal allocation.
Expected utility theory extends the idea to risk. Faced with uncertain outcomes, the agent assigns probabilities and utilities to each and maximises expected utility (probability-weighted sum). That framework underlies insurance, investment, and any decision under uncertainty. It breaks down when people violate its axioms — ambiguity aversion, loss aversion, probability weighting — which is why behavioural economics exists. Utility remains the organising concept: decisions reveal preferences; preferences can be modelled as utility.
In business, utility lurks behind every allocation decision. A founder allocates time across product, sales, and fundraising by implicit utility — where does the next hour add the most value? An investor ranks deals by expected utility of return adjusted for risk and time. A customer chooses a product by comparing utility per dollar across options. Nobody writes down a utility function; everyone acts as if maximising one. The model makes that implicit logic explicit.
Utility is not the same as money. People derive utility from status, fairness, leisure, and avoiding risk. A job that pays less may have higher utility if it offers meaning or flexibility. A deal that maximises revenue may have lower utility if it damages reputation or increases stress. The utility function is multi-argument. When you model your own or others' choices, include the non-monetary dimensions. The decision that "makes no sense" in dollar terms often makes sense once you infer the full utility function.
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Section 2
How to See It
Utility shows up whenever someone chooses among options. Look for trade-offs, allocation of scarce resources, and decisions under risk. The agent is maximising something; that something is utility in the model.
Business
You're seeing Utility when a product team prioritises the roadmap. Each feature has an expected impact; each consumes time. The team implicitly ranks features by utility per unit of effort. The chosen order is the outcome of utility maximisation — even when "utility" is a mix of revenue, user satisfaction, and strategic fit.
Technology
You're seeing Utility when a user chooses between two apps. The choice reveals relative utility: the selected app delivered higher expected utility (features, price, habit) at the moment of decision. A/B tests are utility experiments — the variant that wins is the one that raises user utility on average.
Investing
You're seeing Utility when an investor compares two deals. Expected return, risk, liquidity, and time horizon get folded into a single ranking. That ranking is the investor's expected utility. Portfolio construction is utility maximisation subject to constraints — risk tolerance and correlation shape the utility function.
Markets
You're seeing Utility when a consumer allocates a budget across categories. Spending shifts until marginal utility per dollar is equalised (or roughly so). The result is a demand pattern. Price changes shift that equilibrium; utility is the underlying maximand.
Section 3
How to Use It
Decision filter
"Before a significant choice, ask: what am I maximising? Name the dimensions (money, time, risk, reputation) and how they trade off. Make the utility function explicit. Then compare options on that basis."
As a founder
You're constantly allocating — time, capital, people. Each allocation is a utility comparison. Make the comparison explicit: what's the marginal utility of the next dollar in R&D vs sales vs marketing? Rank by impact per unit of resource. The mistake is defaulting to what's urgent or familiar instead of what has the highest marginal utility. Write down the criteria. Revisit when new information arrives.
As an investor
Every investment is a claim on expected utility — return, risk, optionality. Different investors have different utility functions (risk aversion, time horizon, liquidity needs). Size and structure deals to match your utility. The same deal can be high-utility for one fund and low for another. Know your own utility curve.
As a decision-maker
When you choose between options, you're revealing a preference. Reverse-engineer the utility: what weights did I put on the various attributes? That clarifies your priorities. When designing offers for others, model their utility. What do they maximise? Price, convenience, status, certainty? Align the offer with their utility function.
Common misapplication: Assuming everyone maximises the same thing. Customers, employees, and partners have different utility functions. Your "obvious" best option may be low-utility for them. Elicit or infer their weights.
Second misapplication: Ignoring marginal utility. Total utility can be high while marginal utility is low. Optimal allocation equalises marginal utility across uses. The next unit of resource should go where marginal utility is highest.
Section 4
The Mechanism
Section 5
Founders & Leaders in Action
Charlie MungerVice Chairman, Berkshire Hathaway
Munger talks about "margin of safety" and "inversion" — both are utility concepts. He maximises long-run compounded return while avoiding ruin. His utility function heavily weights survival and avoids large permanent losses. "The first rule is don't lose money. The second rule is don't forget rule one." That's a utility function with extreme penalty on negative outcomes.
Warren BuffettChairman & CEO, Berkshire Hathaway
Buffett's capital allocation is utility maximisation at scale. He ranks opportunities by expected return, adjusted for risk and durability. "Price is what you pay; value is what you get." Value is utility. He repeatedly chooses businesses and deals that maximise his (and Berkshire's) long-term utility, often passing on higher nominal returns when risk or complexity is too high.
Section 6
Visual Explanation
Utility — Satisfaction from quantity. Marginal utility (slope) falls as quantity rises (diminishing marginal utility). Optimal allocation equalises marginal utility per unit of resource across uses.
Section 7
Connected Models
Utility is the backbone of microeconomic choice. The models below either formalise it (expected utility, marginal analysis), capture its curvature (diminishing utility), or connect it to observable behaviour (revealed preference, trade-offs).
Reinforces
Expected Utility Theory
Expected utility is utility under risk: weight outcomes by probability and sum. Utility gives the payoff dimension; probability gives the weights. Decisions under uncertainty are expected-utility maximisation when the axioms hold.
Reinforces
Marginal Cost/Benefit
Marginal benefit is marginal utility in another guise. Optimal quantity is where marginal benefit equals marginal cost — i.e. where the marginal utility of one more unit just offsets its cost. Utility underlies the benefit side of the equation.
Tension
Diminishing Utility
Diminishing marginal utility is a property of utility functions, not a tension. The tension is with "more is always better" intuition: after some point, more of one thing lowers marginal utility and reallocation to other uses raises total utility.
Tension
Loss Aversion
Loss aversion says losses reduce utility more than equivalent gains increase it. The utility function is kinked at the reference point. Standard smooth utility doesn't capture that; prospect theory does. Utility remains the frame; the shape changes.
Leads-to
Revealed Preference
We can't see utility directly. Revealed preference infers it from choices: if you chose A over B, then U(A) ≥ U(B). Utility is the theoretical object; revealed preference is the empirical method.
Leads-to
Trade-offs
Every trade-off is a comparison of marginal utilities. Give up X, get Y. You trade when the marginal utility of Y exceeds the marginal utility of X. Trade-offs make the utility comparison explicit.
Section 8
One Key Quote
— Jeremy Bentham, An Introduction to the Principles of Morals and Legislation (1789)"Nature has placed mankind under the governance of two sovereign masters, pain and pleasure. It is for them alone to point out what we ought to do, as well as to determine what we shall do."
Bentham framed utility as the driver of behaviour. Later economics dropped the moral "ought" and kept the positive "shall" — we model what people do as utility maximisation. The quote anchors the idea that choice is governed by a single index of benefit and cost. Your job is to make that index explicit when you decide.
Section 9
Analyst's Take
Faster Than Normal — Editorial View
You're always maximising something. Founders who say they "just prioritise" are doing utility maximisation without writing it down. Make the criteria explicit. What's the marginal utility of the next hour, dollar, or hire? Write the utility function — even roughly — and allocation improves.
Other people's utility functions differ from yours. Customers don't all value the same things. Investors weight risk and return differently. Design offers and pitches around their utility, not yours. Revealed preference: watch what they choose, then infer the weights.
Marginal utility beats total utility for allocation. The question isn't "which project is best?" but "where does the next unit of resource add the most?" Equalise marginal utility across uses. That's the optimum.
Expected utility under risk is the standard. When outcomes are uncertain, weight by probability. Expected utility is the workhorse. When people deviate (loss aversion, probability weighting), that's behavioural nuance — utility is still the organising concept.
Utility is multi-argument. Money is one input. So are time, risk, reputation, fairness, and emotion. When someone chooses "irrationally," they're usually maximising a different utility function than you assumed. Elicit or infer the full set of arguments. That's how you design offers and predict behaviour.
Summary: Utility is the satisfaction or benefit from an outcome; agents maximise it. Marginal utility diminishes; optimal allocation equalises marginal utility across uses. Under risk, use expected utility. Use the model to clarify what you're maximising and to interpret others' choices.
Section 10
Test Yourself
Is this mental model at work here?
Scenario 1
A founder allocates a full day to product work instead of sales. She has limited time and chooses product because she believes the next hour there will move the needle more.
Scenario 2
A customer chooses Brand A over Brand B even though B is cheaper. The customer says B 'doesn't feel right.'
Scenario 3
An investor passes on a deal with a higher expected return because it's riskier. He chooses a lower-return, lower-risk deal.
Scenario 4
A team adds a fifth person to a project. Output goes up but by less than the increase from the fourth person.
Section 11
Top Resources
01
Book
The classic source for utility as the basis of choice and welfare.
02
Book
Axiomatic expected utility theory. The foundation for decision under risk.
03
Book
Standard treatment of utility, demand, and marginal analysis.
04
Book
Behavioural deviations from expected utility: loss aversion, framing, probability weighting.
05
Book
Accessible treatment of utility, revealed preference, and marginal analysis with applications to business and policy.