What it means
Economics textbooks describe agents who compare every option and pick the best. Herbert Simon watched real people and saw something else: they search until an option clears the bar, then stop.
The word blends satisfy and suffice, and Simon built it into his theory of bounded rationality: minds with limited time, information, and computation cannot maximise, so they satisfice. Simon's 1978 Nobel lecture lays out the research programme that earned the prize: the decision processes of actual human actors, with the aspiration level, the point that counts as good enough, at the centre.
The mechanism is adaptive: the aspiration level rises when options come easily and falls when search is hard, so satisficers calibrate their bar to the market they face. The concept explains behaviour maximising cannot: why people stay in decent jobs, buy the third house they tour, and renew the same supplier for a decade, not from ignorance but from the cost of searching.
It also predicts the pathologies: an aspiration set too low leaves value on every table, while one set too high turns the satisficer into a paralysed maximiser with a guilty conscience. Management inherited the idea wholesale: targets, budgets, and hurdle rates are institutionalised aspiration levels, and organisations satisfice through them as surely as shoppers do.
For a non-finance reader, satisficing is the honest description of every decision you finished: not the best imaginable choice, but the first one that was good enough to let you move on. Simon chose the concept deliberately as a description, not a failing: he called maximising a theory for gods and satisficing the theory for humans, and spent a career showing the human version predicts better.
Consumer research found the two styles coexist: some shoppers are habitual maximisers who exhaust options, some are natural satisficers, and the maximisers report more regret despite objectively comparable outcomes.
In practice
Real-world examples.
Example
A committee prices its own search time and signs the first vendor that clears every criterion. Attention was the real budget, and the committee records the cost of further search as the reason for stopping.
Example
A buyer's aspiration level falls after three months of house hunting, exactly as the model predicts. The bar moved with the market, and the buyer accepts a good house that would have been rejected in the first week.
Example
A company splits decisions into the few worth optimising and the many worth finishing. Hiring a chief executive gets a long search, while choosing office stationery gets a thirty-minute decision.
Formula
Calculation
No formula; the rule: search options sequentially, compare each against the aspiration level, accept the first that meets it, and adjust the aspiration level up or down as search proves easy or costly. A useful stopping test is to continue searching only while the expected improvement from one more round exceeds the cost of that round.
Worked example. A company has three vendors that clear its criteria, and the realistic gap in value between the best and the worst of them is $15,000 over three years. Each extra month of evaluation costs $6,000 in staff time and $2,000 in delayed reporting, a total of $8,000.
- Two more months of searching cost $8,000 x 2 = $16,000.
- That is more than the $15,000 gap it might close, so the rational move is to sign the first vendor that clears the bar.Case study
Seen in the real world.
This case study is fictional and illustrative. A made-up restaurant group needs a new point-of-sale system across forty locations. The operations director, a reformed perfectionist, sets the brief with Simon's logic: five criteria that matter, three vendors that clear them, a decision in thirty days. The first vendor passes every criterion and the committee's instinct is to keep looking for the best, until the director prices the search itself: each extra month of evaluation costs more in staff time and delayed reporting than the realistic gap between the top three systems.
They sign with the satisficing choice, and the rollout's real problems, training and data migration, turn out to be things no amount of vendor comparison would have revealed anyway. Two years later a competitor chain is still in its second evaluation round, and the director's retrospective to the leadership team names the discipline: maximising would have found a marginally better system and a much worse rollout, because the scarce resource was never information about vendors, it was the organisation's attention. The group's playbook now separates decisions into two piles, the few worth optimising and the many worth finishing, and the second pile always outnumbers the first.
Watch out
Common mistakes.
- Reading it as laziness; satisficing is rational under search costs, and maximising everything is its own expensive error.
- Setting the bar once and forgetting it; the aspiration level must adjust to what the search reveals, or the rule stops being adaptive.
- Applying it to irreversible decisions; the cheaper the reversal, the more satisficing fits, and the few truly one-way choices deserve the slower search.
Questions
People also ask.
What is satisficing?
Choosing the first option that meets a good-enough threshold instead of searching for the best, Herbert Simon's account of real decision-making under limits.
Where did the idea come from?
Simon's theory of bounded rationality, central to his 1978 Nobel Prize, which replaced the perfectly optimising agent with one whose aspiration level adapts to search costs.
When is it the wrong tool?
On rare, irreversible, high-stakes choices where search costs are small next to the cost of a mediocre outcome.
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