Reference

Decision-making glossary

The vocabulary of decision analysis, in plain English, with an example for each term and a link to the guide that goes deeper.

These terms come up throughout PreRipple's guides and inside the product itself. None of them require a background in economics or statistics — they are simply names for things people already do when they think carefully about a choice.

Scenario planning

Comparing several plausible versions of the future instead of forecasting one. Each scenario spells out its assumptions, so you can see which outcomes depend on what.

Example: Instead of asking whether freelancing will work, you describe a slow-start year, a steady year and a strong year, and check whether you survive the slow one.

How to make a major life decision

Opportunity cost

The value of the best alternative you give up by choosing something. Every yes is also a no.

Example: Taking a role with a 10% raise but no learning may cost more over five years than a lateral move that builds a scarce skill.

How to choose between two options

Reversible decision

A choice you can undo at a cost you would willingly pay. Reversible decisions deserve speed rather than long analysis.

Example: Renting in a new city for six months before deciding whether to settle there.

Reversible vs. irreversible decisions

Irreversible decision

A choice that cannot be undone, or whose reversal costs more than you can absorb. These earn extra analysis and a written exit plan.

Example: Selling a home in a market where transaction costs exceed a year of savings.

Reversible vs. irreversible decisions

Decision paralysis

Being unable to choose because the options feel close, the stakes feel high, or the information feels incomplete. It is usually a framing problem, not a willpower problem.

Example: Two months of re-reading the same job offer. Naming the one unknown that would settle it converts the stall into a task.

Sunk cost

Money, time or effort already spent that cannot be recovered. Sunk costs should not influence what you do next, though they almost always do.

Example: Staying in a degree you no longer want because of three years already invested, rather than because of what the remaining year is worth.

Trade-off

Accepting less of one thing to get more of another, because both cannot be maximised at once.

Example: A shorter commute for a higher rent; a higher salary for less autonomy.

Uncertainty

Not knowing which outcome will occur. Some uncertainty can be reduced with information; some is irreducible and must be planned around instead.

Example: You can research a city's rents. You cannot know whether you will like it in year three.

Risk

Exposure to an outcome that would harm you, described by how bad it is, how long it lasts, and how likely it feels.

Example: Six months without income is a risk; the size of your reserve determines how severe it is.

Downside

The realistic worst plausible outcome of a choice, including how long it lasts and what recovery requires.

Example: Not 'the business fails', but 'nine months of lost income and a re-entry salary 10% lower'.

Expected outcome

The unremarkable middle case — what usually happens when neither the good nor the bad scenario dominates. It is the case most worth planning for.

Example: The side business earns a modest supplement rather than replacing a salary or dying quietly.

Assumption

A belief your plan depends on that has not been verified. Load-bearing assumptions should be tested before committing.

Example: 'Clients will pay this rate.' Testable with one paid pilot.

Test before you commit

Constraint

A fixed limit the decision must respect: money, health, visa status, caring duties, notice periods.

Example: A mortgage approval that lapses in 60 days sets the deadline whether you like it or not.

Decision tree

A branching diagram of choices and their possible consequences, used to trace what follows from each option.

Example: Quit now, or stay six months then reassess — each branch leading to its own set of next choices.

Sensitivity analysis

Changing one input at a time to see how much the outcome moves. It identifies which variables actually matter.

Example: If the plan survives a 20% revenue miss but not a two-month delay, timing is your critical variable.

What-if analysis

Exploring how outcomes change under different conditions, without claiming to know which condition will occur.

Example: What if rates rise a point? What if only one income continues for a year?

Decision support

Tools and methods that help a person structure and understand a decision. Decision support does not make the decision or predict the result.

Example: PreRipple is decision-support software: it organises scenarios, it does not forecast your life.

How PreRipple works

· Published by PreRipple, a product of Panzica Technologies Inc. · Educational information, not personalised professional advice. See our editorial policy.