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| Criterion |  Product Discovery Dual-Track Agile |  Decision Making Decision Tree |  Product Strategy DIBB |  Decision Making Constraint Analysis |
|---|---|---|---|---|
Purposedifferent | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 | Medium | Low | Low |
Timedifferent | Laufend, Wochen bis Monate | 30-90 min | 1-2 h | 30-90 min |
Participantsdifferent | 4-10 | 1-6 | 2-8 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Decision Tree, Option Map, Assumption List | DIBB document, Belief list, Bet list, Learning report | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | AgileDiscoveryDelivery | DecisionTreeOptions | StrategyDecisionAssumptionsHypothesis | ConstraintsDecisionPlanningOptions |