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| Criterion |  Product Strategy DIBB |  Engineering Kanban |  Delivery Monte Carlo Forecasting |  Decision Making Delphi Method |
|---|---|---|---|---|
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 work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. |
Complexitydifferent | Low | Medium | High | High |
Timedifferent | 1-2 h | Ongoing | 30-90 min Setup, danach laufend | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-12 | 1-8 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Kanban board, WIP policies, Flow metrics | Forecast Percentiles, Throughput Dataset, Risk Communication | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | FlowVisual managementDelivery | ForecastingFlowDelivery | ForecastingExpertsDecisionStrategy |