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| Criterion |  DevOps Incident Command |  Decision Making Delphi Method |  Delivery Monte Carlo Forecasting |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | During an acute incident with several people involved, the method creates a clear leadership and communication structure. It reduces chaos when fast coordination and clean situational awareness are both needed at once. | 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. | 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. | 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 | Medium | High | High | Low |
Timedifferent | As needed | 1-4 Wochen | 30-90 min Setup, danach laufend | 1-2 h |
Participantsdifferent | 4-15 | 6-30 Experten | 1-8 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Incident Log, Action Tracker, Stakeholder Updates | Expert Forecast, Consensus Range, Assumption Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | IncidentOperationsReliability | ForecastingExpertsDecisionStrategy | ForecastingFlowDelivery | StrategyDecisionAssumptionsHypothesis |