methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
Shape Up helps clarify scope, sequence, and delivery flow. It makes work boundaries and decisions explicit and captures results as pitches, bet-table decisions, and hill charts.A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes.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.
Complexitydifferent
MediumMediumLowHigh
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-Down10-30 min je Item5-20 min30-90 min Setup, danach laufend
Participantsdifferent
2-4 pro Pitch1-83-201-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesThree-Point Estimate, Risk Range, Assumption NotesEffort Heatmap, Risk Signals, Discussion TargetsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
PlanningDeliveryAutonomy
EstimationUncertaintyForecasting
EstimationEffortRisk
ForecastingFlowDelivery
Add more methods