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| Criterion |  Operations Bottleneck Analysis |  Knowledge Modeling Feynman Technique |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. | The Feynman Technique checks understanding by explaining a topic so that it stays easy for others to understand. It makes knowledge gaps visible before they become costly in everyday work. | 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 | Low | High |
Timedifferent | 1-3 h | 20-60 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-8 | 1 | 1-8 |
Formatdifferent | Workshop + async | Async | Workshop + async |
Outputdifferent | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Plain-language Explanation, Knowledge Gaps, Study Notes | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FlowMeasurementConstraints | LearningKnowledgeUnderstanding | ForecastingFlowDelivery |
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