View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Operations PDCA Cycle |  Facilitation Dot Estimation |  Delivery Monte Carlo Forecasting |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Low | Low | High | Medium |
Timedifferent | 1 h bis mehrere Wochen | 5-20 min | 30-90 min Setup, danach laufend | 45-60 min |
Participantsdifferent | 1-8 | 3-20 | 1-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Effort Heatmap, Risk Signals, Discussion Targets | Forecast Percentiles, Throughput Dataset, Risk Communication | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Continuous improvementLeanExperiments | EstimationEffortRisk | ForecastingFlowDelivery | AssumptionsRiskExperimentsValidation |