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| Criterion |  DevOps ChatOps |  Product Strategy DIBB |  Delivery Monte Carlo Forecasting |  Decision Making Force Field Analysis |
|---|---|---|---|---|
Purposedifferent | For operational work in a distributed team, the method links communication with direct system control. It records decisions right where the signal, the context, and the execution come together. | 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. | 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. | 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | Ongoing | 1-2 h | 30-90 min Setup, danach laufend | 45-90 min |
Participantsdifferent | 2-20 | 2-8 | 1-8 | 3-12 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Chat Transcript, Action Log, Automations | DIBB document, Belief list, Bet list, Learning report | Forecast Percentiles, Throughput Dataset, Risk Communication | Force Field Map, Change Levers, Risk Notes |
Tagsno overlap | CollaborationEngineeringIncident | StrategyDecisionAssumptionsHypothesis | ForecastingFlowDelivery | ChangeDecisionStrategy |