scenarioanalyses

Scenario analyses are a systematic process for examining how different plausible future states could influence outcomes of interest. Rather than attempting to predict a single forecast, they explore a range of possibilities to illuminate uncertainties, stress-test strategies, and support robust decision-making across time horizons.

Typically, the process begins by defining objectives and identifying drivers that shape outcomes (economic conditions, policy changes, technological shifts, supply and demand dynamics). Scenarios can be qualitative narratives, quantitative models, or a mix arranged in a scenario matrix. Analysts select baseline, optimistic, and pessimistic or other relevant paths, then model relationships and estimate the consequences for key metrics. Techniques include storytelling, scenario planning, and, for quantitative work, Monte Carlo simulation and stress testing.

Scenario analyses are widely used in finance and risk management to evaluate investments, capital and liquidity needs, and contingency planning. They are also employed in corporate strategy to stress-test business plans, in project evaluation, supply chain resilience, and in public policy and climate risk assessments to consider ranges of futures under different assumptions about emissions, adaptation, and regulation.

Limitations include dependence on subjective assumptions and chosen drivers, potential bias in scenario selection, and the challenge of assigning probabilities or fully capturing tail risks. Results depend on model structure, data quality, and chosen time horizons. Best practices emphasize transparent documentation, governance, regular updates, and communicating uncertainties clearly. Related terms include sensitivity analysis and scenario planning.