Purpose and scope
What this dashboard measures
Use historical cycle times to forecast completion at a selected percentile.
Historical cycle times days, Forecast percentile, Items remaining, and Average parallel items feed the breakdown values beneath the Agile Cycle-Time Percentile Forecaster headline; Maintain Average parallel items in its entered unit for comparison.
Instructions
How to use this calculator
Choose Historical cycle times days and Forecast percentile from the Agile Cycle-Time Percentile Forecaster recorded basis, then maintain Items remaining and Average parallel items in their recorded units.
- Choose Historical cycle times days and Forecast percentile from one Agile Cycle-Time Percentile Forecaster reporting period.
- Choose Items remaining and Average parallel items without changing the Average parallel items unit.
- Derive the Agile Cycle-Time Percentile Forecaster and test its headline with breakdown values.
Interpretation
Interpreting the headline metric
A higher percentile is more conservative but still assumes future items resemble the historical sample.
Scan Historical cycle times days, Forecast percentile, and Items remaining beside the Agile Cycle-Time Percentile Forecaster headline; Average parallel items reveals rounding across the breakdown values.
After the Agile Cycle-Time Percentile Forecaster, open the Kanban WIP Age Tracker to summarize work-item ages and flag items beyond an entered threshold.
Calculation
Method used
The selected empirical percentile is multiplied by the number of serial item waves.
The Agile Cycle-Time Percentile Forecaster evaluates Historical cycle times days, Forecast percentile, and Items remaining separately; maintain Average parallel items visible outside any percentage, rate, or total.
Calculation method last reviewed: June 21, 2026.
Worked scenario
Example calculation
Test Average parallel items with the Agile Cycle-Time Percentile Forecaster breakdown values before judging the Average parallel items headline scale or units.
Visual audit
Reading the supporting metrics
The Agile Cycle-Time Percentile Forecaster dashboard places breakdown values beside Historical cycle times days, Forecast percentile, Items remaining, and Average parallel items. Scan Average parallel items in its original unit before accepting the breakdown values or headline status.
Boundaries
Important edge cases and limitations
Historical items must resemble future work; dependencies, blocked time, and changing WIP can invalidate the forecast.
Modify Average parallel items in the Agile Cycle-Time Percentile Forecaster before reading the breakdown values or headline.
Input audit
Checklist for this calculation
- Scan the Agile Cycle-Time Percentile Forecaster period and Historical cycle times days and Forecast percentile units.
- Test Average parallel items with the Agile Cycle-Time Percentile Forecaster breakdown values.
- Derive a fresh Agile Cycle-Time Percentile Forecaster after any Average parallel items modify.
Practical use
Recommended workflow
Remove incomparable outliers only with a documented reason and refresh the sample as workflow changes.
The Sprint Burndown Finish-Date Forecaster covers the related step of helping you project when remaining sprint work will finish at the observed delivery rate.
Questions
Frequently asked questions
What does an eighty-fifth-percentile cycle time mean?
Approximately eighty-five percent of the historical observations completed at or below that duration.
When is a previous agile cycle-time percentile forecaster output no longer comparable?
Another Agile Cycle-Time Percentile Forecaster run is warranted when Historical cycle times days moves, Average parallel items is redefined, or the governing calculation rule changes.
Which convention should Historical cycle times days use in the
Test Historical cycle times days with Average parallel items inside the Agile Cycle-Time Percentile Forecaster reporting basis. Maintain the Average parallel items unit aligned with the Historical cycle times days period before reading the headline.