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| Criterion |  Agile NoEstimates |  Decision Making Cynefin Workshop |  Knowledge Modeling IBIS |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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. | When problems are unclear, chaotic, or only seemingly familiar, standard recipes fall short. A Cynefin Workshop sorts situations by the nature of their problem and connects them with matching action logic. | IBIS structures thinking about complex questions as a sequence of issues, ideas, and arguments. The method keeps discussions open without forcing them into premature consensus. | 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | laufend | 60-180 min | 1-3 h | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 4-20 | 2-8 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Cynefin Map, Domain-specific Actions, Sensemaking Notes | Issue Map, Positions, Argument Notes | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | ComplexitySensemakingDecision | RationaleKnowledgeDecision | ForecastingFlowDelivery |