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Criterion
Surveys method illustration showing its working structure
UX Research
Surveys
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Purposedifferent
When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal.In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures.When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped.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.
Complexitydifferent
MediumLowLowMedium
Timedifferent
3-14 Tage20–45 min30-90 min30-90 min
Participantsdifferent
50+Small cross-functional group2-81-6
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Survey Results, Charts, Segment InsightsRisk list, Mitigation plan, Assumption logConstraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesDecision Tree, Option Map, Assumption List
Tagsno overlap
QuantitativeResearchValidation
RiskDecisionFailurePlanning
ConstraintsDecisionPlanningOptions
DecisionTreeOptions
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