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| Criterion |  Product Strategy DIBB |  Agile Planning Poker |  Decision Making Force Field Analysis |  Agile Affinity Estimation |
|---|---|---|---|---|
Purposedifferent | 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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | 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. |
Complexitydifferent | Low | Low | Low | Medium |
Timedifferent | 1-2 h | 2-5 min je Item | 45-90 min | 30-90 min |
Participantsdifferent | 2-8 | 3-9 | 3-12 | 3-12 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Relative Estimates, Assumption Notes, Split Candidates | Force Field Map, Change Levers, Risk Notes | Affinity Size Map, Grouped Estimates, Unclear Items |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | EstimationAgileRelative sizingTeam | ChangeDecisionStrategy | EstimationBacklogRelative sizing |