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| Criterion |  Product Discovery User Story Mapping |  Operations ALPEN Method |  Decision Making Decision Tree |  Decision Making Constraint Analysis |
|---|---|---|---|---|
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. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | 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 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. |
Complexitydifferent | Medium | Low | Medium | Low |
Timedifferent | 2-4 h | 10-20 min daily | 30-90 min | 30-90 min |
Participantsdifferent | 4-10 | 1 | 1-6 | 2-8 |
Formatdifferent | Workshop | Async | Workshop + async | Workshop + async |
Outputdifferent | Story Map, Release Slices, Backlog Candidates | Daily Plan, Time Estimates, Review Notes | Decision Tree, Option Map, Assumption List | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | BacklogJourneyPlanningMVP | PlanningTime managementProductivityOperations | DecisionTreeOptions | ConstraintsDecisionPlanningOptions |