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Criterion
Scenario Planning method illustration showing its working structure
Business Strategy
Scenario Planning
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
Scenario Planning opens the view to several plausible futures instead of a single forecast. The method protects strategies from depending on too narrow an expected path.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
HighMediumMediumLow
Timedifferent
0.5-2 Tage30-90 min45-75 min30-60 min
Participantsdifferent
4-121-62-81-5
Formatdifferent
WorkshopWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Scenario Set, Strategic Implications, Robust OptionsDecision Tree, Option Map, Assumption ListTest Matrix, Test PlanCompleted Experiment Canvas, Success Metric
Tagsno overlap
StrategyUncertaintyPlanning
DecisionTreeOptions
ExperimentsValidationDiscoveryOptions
ExperimentsValidationDiscoveryHypothesis
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