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| Criterion |  Knowledge Modeling Knowledge Mapping |  Operations Waste Analysis |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | For a process that keeps people busy but creates little value, the method exposes waste. It directs attention to unnecessary movement, waiting times, rework, and overdelivery. | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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 | Medium | High |
Timedifferent | 1-3 h | 45-120 min | laufend | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-12 | 2-8 | 2-12 | 1-8 |
Formatdifferent | Workshop | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Waste Map, Prioritized Waste, Improvement Backlog | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | KnowledgeMappingRisk | WasteLeanProcess improvement | EstimationForecastingFlow | ForecastingFlowDelivery |