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| Criterion | ![]() Delivery Monte Carlo Forecasting | ![]() Operations Learning Review | ![]() DevOps Game Day |
|---|---|---|---|
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. | After a project phase with mixed results, the method makes learning from the individual case reusable. It connects events, decisions, and systemic conditions into robust insights. | In preparing for rare incidents, the method tests response capability under controlled conditions. It shows where assumptions about stability, roles, and recovery are too optimistic. |
Complexitydifferent | High | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | Halber Tag |
Participantsdifferent | 1-8 | 3-10 | 5-20 |
Formatdifferent | Workshop + async | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Learning Review Notes, System Factors, Improvement Actions | Simulation Notes, Gaps List, Updated Runbooks |
Tagsno overlap | ForecastingFlowDelivery | LearningRetrospectiveIncidentOperations | ResilienceOperationsIncident |
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