Helps clarify backlog, sprint work, and team flow in concrete terms. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.
NoEstimates
Moves backlog, sprint work, and team flow toward a concrete result through "clarify the planning question", "slice work smaller", and "calibrate regularly with reality".
Which planning decision do we need to make, and which flow data or slicing rules answer it more cheaply than an estimation ritual?
The team follows the steps "clarify the planning question", "slice work smaller", "measure throughput and cycle time", "derive the forecast from historical data", and "calibrate regularly with reality". Each step is made visible. At the end, Throughput Data, Flow Forecast, and Slicing Rules are available so decisions, tests, or actions can continue directly.
Visual orientation
Method sketch for a quick mental model.
Flow
- 1Clarify the planning question
- 2Slice work smaller
- 3Measure throughput and cycle time
- 4Derive the forecast from historical data
- 5Calibrate regularly with reality
The runsheet guides execution with 4 phases, timeboxes, 5 pitfalls, and clear stop criteria.
Open runsheetIdeal for
- Flow-based teams
- Kanban systems
- Stable delivery data
Not good for
- New teams without history
- Large fuzzy initiatives
- Budget processes with detailed estimates
Deep dive
NoEstimates is less a single technique than a counterposition to elaborate effort estimation. The approach asks which decision a estimate actually supports and whether that same decision can be made better through smaller items, historical throughput data, or continuous learning. Instead of producing story points, work is sliced as similarly small as possible and observed through flow metrics. Forecasts come from completed work and probabilities, not from estimated effort.
First clarify which planning decision needs to be answered. Invest in slicing, flow metrics, and transparent assumptions. Avoid dogmatic debates; sometimes a light estimate is cheaper than building a heavy data foundation.
NoEstimates Working TemplateCompact working template for NoEstimates with context, input, output artifacts, and next step.markdown
no-estimates-working-template.md
Compact working template for NoEstimates with context, input, output artifacts, and next step.
NoEstimates Working Template
Goal
Approach that reduces explicit effort estimation and instead uses small items, throughput, and forecasting.
Context
When and for what do we use this method?
Input
Which data, observations, decisions, or materials are available?
Execution
Short notes along the runsheet.
Output artifacts
- Throughput Data:
- Flow Forecast:
- Slicing Rules:
Assumptions and open questions
- ...
Decision / Next step
Owner, date, and success signal.
When to choose differently
Short decision aid for existing alternatives.
Statt NoEstimates, wenn ihr relative Komplexität statt Kalenderzeit schätzen wollt und eure Schätzung im Team kalibrieren möchtet.
Statt NoEstimates, wenn euer Umfeld weiterhin Schätzsignale braucht und relative Größen teamweit kalibriert werden müssen.
Similar methods
All methodsProduct Backlog, Sprint Goal, Increment, and retrospective loops create a repeatable cadence for complex product work.
Moves backlog, sprint work, and team flow toward a concrete result through "explain the ideal day unit", "calibrate with a reference item", and "do not confuse it with calendar days".
Moves scope, sequence, and delivery flow toward a concrete result through "formulate the forecast question", "choose historical flow data", and "update the forecast regularly".
Turns backlog, sprint work, and team flow into a tangible result by presenting the item, clarifying questions, and discussing deviations before estimating again.
Statt NoEstimates, wenn euer Umfeld weiterhin Schätzsignale braucht und relative Größen teamweit kalibriert werden müssen.
Turns backlog, sprint work, and team flow into a tangible result by explaining the scale, choosing reference items, and marking large items.
Turns backlog, sprint work, and team flow into a tangible result by preparing items as cards, building a relative size axis, and clarifying outliers and uncertainties.