First, the key terms.

Objective
The outcome or value a decision is intended to improve.
Scenario
A specified combination of assumptions used to explore consequences.
Decision variable
An action or quantity that the decision-maker can choose.

The idea, explained

Risk can sometimes be described using justified probabilities; other uncertainty may involve poorly known probabilities, missing alternatives or disagreement about the model itself. Variability is a property of outcomes, not automatically a measurement error. Begin by defining the decision-maker, deadline, feasible alternatives and relevant consequences. Best-case and worst-case scenarios reveal a range under chosen assumptions but do not assign probabilities. A decision should account for important nonfinancial effects and identify evidence that could change the recommendation.

STEP 1

Define the boundary

For a capacity choice, state the period, who is served, budget limits and unacceptable outcomes. Include the current process or doing nothing as an explicit alternative where feasible. The model should not quietly omit affected groups.

STEP 2

Separate control from uncertainty

Order quantity is chosen; demand is uncertain. Unit cost may be fixed for the decision period or may itself be uncertain. Label each input so a solver cannot accidentally improve results by choosing an uncontrollable quantity.

STEP 3

Explore and communicate assumptions

Use a spreadsheet with clearly separated inputs, formulas and outputs. Change one assumption at a time for basic sensitivity, then inspect coherent combined scenarios. Best and worst cases can be informative but should not be called likely without evidence.

Follow a worked example.

A fictional school chooses between renting a small or large projector kit for an event. The large option serves more attendees but costs more. Attendance is unknown, and the school also values accessibility and reliability.

Walk it through, one step at a time

  1. List costs, capacities and consequences for each alternative, including what happens when attendance exceeds capacity.
  2. Calculate results under low and high attendance. Do not assume attendance takes whichever value makes an alternative look best.
  3. Identify the attendance level or risk tolerance at which the choice changes, and explain any outcomes that cannot be reduced to one financial total.

Where people get stuck

Using precise numbers for weakly justified assumptions can make a model seem more certain without adding evidence.

Now try it yourself.

Pause before opening each answer. Explain your reasoning in your own words.

1. Check the core idea

Does a best-case scenario describe the most likely outcome?

Reveal the answer & reasoning

No. It specifies favorable assumptions. Likelihood requires separate probability reasoning, and the scenario may be deliberately extreme.

2. Apply what you learned

Why should a model include the option to keep the current process?

Reveal the answer & reasoning

It provides a relevant baseline and opportunity-cost comparison. Otherwise a team may choose the best of several unnecessary changes.