Purpose and scope
What this dashboard measures
Use historical cycle times to forecast completion at a selected percentile.
The Agile Cycle-Time Percentile Forecaster keeps Historical cycle times days, Forecast percentile, Items remaining, and Average parallel items visible beside the result so the inputs can be checked, saved, and reproduced without reconstructing the calculation later.
Instructions
How to use this calculator
Enter the values requested for the Agile Cycle-Time Percentile Forecaster and replace every sample with the actual schedule, record, or system being analyzed.
- Use Historical cycle times days and Forecast percentile to establish the starting conditions for the Agile Cycle-Time Percentile Forecaster.
- Set Items remaining and Average parallel items to match the actual case rather than leaving example assumptions in place.
- Run the Agile Cycle-Time Percentile Forecaster with a baseline set of values, then change only one uncertain input at a time when comparing alternatives.
Calculation
Method used
The selected empirical percentile is multiplied by the number of serial item waves.
The displayed formula makes the role of Historical cycle times days, Forecast percentile, and Items remaining explicit. In the Agile Cycle-Time Percentile Forecaster, keeping those inputs separate helps distinguish a changed assumption from a changed calculation rule.
Calculation method last reviewed: June 20, 2026.
Worked scenario
Example calculation
To audit your own Agile Cycle-Time Percentile Forecaster result, compare Historical cycle times days and Forecast percentile with the worked scenario. In the Agile Cycle-Time Percentile Forecaster, if the direction or scale looks wrong, verify Average parallel items before changing several inputs at once.
Interpretation
Interpreting the headline metric
A higher percentile is more conservative but still assumes future items resemble the historical sample.
Read the headline together with the supporting metrics for Historical cycle times days, Forecast percentile, and Items remaining. A plausible-looking Agile Cycle-Time Percentile Forecaster result can still be unreliable when one of those values uses the wrong unit, date boundary, or local convention.
The Kanban WIP Age Tracker extends the Agile Cycle-Time Percentile Forecaster by letting you summarize work-item ages and flag items beyond an entered threshold.
Visual audit
Reading the supporting metrics
The Agile Cycle-Time Percentile Forecaster dashboard summarizes Historical cycle times days, Forecast percentile, Items remaining, and Average parallel items in a headline and supporting measures. For the Agile Cycle-Time Percentile Forecaster, read the original units beside any percentage or status label so a rounded headline does not hide a small but important shortage or overrun.
Boundaries
Important edge cases and limitations
Historical items must resemble future work; dependencies, blocked time, and changing WIP can invalidate the forecast.
If one of these exclusions applies, treat the Agile Cycle-Time Percentile Forecaster output as a baseline and correct Average parallel items or another affected input before recalculating.
Practical use
Recommended workflow
Remove incomparable outliers only with a documented reason and refresh the sample as workflow changes.
Use the Sprint Burndown Finish-Date Forecaster alongside the Agile Cycle-Time Percentile Forecaster to project when remaining sprint work will finish at the observed delivery rate.
Input audit
Checklist for this calculation
- Confirm the source and units for Historical cycle times days and Forecast percentile before entering them.
- Preserve Items remaining and Average parallel items with any saved or shared Agile Cycle-Time Percentile Forecaster result.
- For the Agile Cycle-Time Percentile Forecaster, review the exclusions above for conditions that could change Average parallel items or the calculation method.
- Recalculate the Agile Cycle-Time Percentile Forecaster whenever a recorded input or real-world condition changes.
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.
What falls outside the scope of the agile cycle-time percentile forecaster?
Historical items must resemble future work; dependencies, blocked time, and changing WIP can invalidate the forecast.
How is the agile cycle-time percentile forecaster result calculated?
The selected empirical percentile is multiplied by the number of serial item waves. Forecast days = empirical cycle-time percentile × ceiling(remaining items ÷ parallel items).