What is scenario analysis?

Scenario analysis compares a plan under different possible futures, for example a base case, a good case, and a bad case. Rather than predicting one outcome, it prepares decision makers for a range and shows which choices are robust across them.

How it works

Each scenario is a coherent set of assumptions, not a random mix. A recession scenario would pair lower demand with tighter credit, for instance. Teams then compare outcomes for each scenario and for each decision they could take. A plan that wins in only one scenario is fragile. A plan that performs acceptably in all is robust. Scenarios differ from sensitivity analysis because they change many inputs together and tell a story about why.

Scenarios work best when they differ in the few uncertainties that really matter, not in every detail. Naming each scenario with a short story makes it easier for a team to discuss and to remember.

Example

Say a retailer plans a new store. In the base case, sales are 2 million a year against costs of 1.6 million, so profit is 0.4 million. In a weak-economy case, sales are 1.5 million, and profit is minus 0.1 million. In a strong case, sales are 2.4 million, and profit is 0.8 million. The retailer sees that the risk is a small loss, while the upside is large, and decides to proceed with a lease that can be exited. This is an illustration with round numbers.

How to model it in Machinations

Group the inputs for each scenario as saved Lever settings. Play the diagram once per scenario, or many Plays at once if randomness matters, and compare the same charts side by side. Change the plan Levers to find the option that holds up in all scenarios.