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| Criterion |  Product Discovery User Story Mapping |  Decision Making Constraint Analysis |  Agile Affinity Estimation |  Decision Making Decision Tree |
|---|---|---|---|---|
Purposedifferent | When user goals and delivery scope could drift apart, it orders the journey from goal to slice. It makes visible where an MVP can genuinely be cut. | 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. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 | Medium | Low | Medium | Medium |
Timedifferent | 2-4 h | 30-90 min | 30-90 min | 30-90 min |
Participantsdifferent | 4-10 | 2-8 | 3-12 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Story Map, Release Slices, Backlog Candidates | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Affinity Size Map, Grouped Estimates, Unclear Items | Decision Tree, Option Map, Assumption List |
Tagsno overlap | BacklogJourneyPlanningMVP | ConstraintsDecisionPlanningOptions | EstimationBacklogRelative sizing | DecisionTreeOptions |