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| Criterion |  Delivery Monte Carlo Forecasting |  Engineering Kanban |  Product Strategy Lean Canvas |  Operations 5 Whys |
|---|---|---|---|---|
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. | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | Ongoing | 45-90 min | 15-30 min |
Participantsdifferent | 1-8 | 2-12 | 1-6 | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics | Lean Canvas, Core Assumptions, Experiment Backlog | Root cause notes, Countermeasures |
Tagsno overlap | ForecastingFlowDelivery | FlowVisual managementDelivery | StartupLeanAssumptionsBusiness model | Root causeIncidentLeanProblem solving |