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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 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 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
HighMediumLow
Timedifferent
0.5-2 Tage30-90 min30-60 min
Participantsdifferent
4-121-61-5
Formatdifferent
WorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Scenario Set, Strategic Implications, Robust OptionsDecision Tree, Option Map, Assumption ListCompleted Experiment Canvas, Success Metric
Tagsno overlap
StrategyUncertaintyPlanning
DecisionTreeOptions
ExperimentsValidationDiscoveryHypothesis
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Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB