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| Criterion |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |  Decision Making Force Field Analysis |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication. | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. | 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. |
Complexitydifferent | High | Medium | Low | Low |
Timedifferent | 30-90 min Setup, danach laufend | laufend | 45-90 min | 1-2 h |
Participantsdifferent | 1-8 | 2-12 | 3-12 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules | Force Field Map, Change Levers, Risk Notes | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingFlowDelivery | EstimationForecastingFlow | ChangeDecisionStrategy | StrategyDecisionAssumptionsHypothesis |