Flow

Cycle time, time per status, throughput and forecast.

Completed Tickets

420

Median Cycle Time

💡
12 j

P85 : 22 j

Work In Progress

💡
20

Story Points

1819 SP

Actual / Planned

105%

Time Spent per Status

Average time spent in each status (working days)

Demo Data
💡 How to read this chart?↓

Lines show the cumulative elapsed time as tickets progress through each pipeline stage — each point is the total time spent from the start of the pipeline up to and including that status.

Hover over any status to see the average time spent exclusively in that stage (in working days).

Cohort: only completed ("Done") tickets {period}are counted. This ensures data is not skewed by tickets stuck in progress.

GOOG
AAPL
MSFT
Moyenne

Aging WIP

Age of each in-progress ticket (working days since work started)

Demo Data
💡 How to read this chart?↓
  • Each dot is an in-progress ticket — the higher, the older.
  • Dashed lines: P50 / P85 of the historical cycle time. A ticket above the P85 line is already taking longer than 85% of past tickets.
  • Tickets above P85 are your first candidates for the daily standup.
GOOG
AAPL
MSFT

Weekly Throughput

Tickets completed per week, by brand

Demo Data
GOOG
AAPL
MSFT

🎲 Monte Carlo Forecast

based on the last 26 weeks of throughput
Horizon
Likely (85%)
Median (50%)
2 weeks
≥ 12
≥ 15
4 weeks
≥ 26
≥ 31
8 weeks
≥ 55
≥ 63

Planned vs Actual (Dev)

Estimated Story Points vs actual development Man-days

Demo Data
💡 How to read this chart?↓

This chart compares estimates with actual time spent.

  • Hatched bars: planned Story Points (initial estimate)
  • Solid bars: actual development Man-days
  • Exclusion: tickets without Man-days (= 0) are ignored.
GOOG - Planned
GOOG - Actual
AAPL - Planned
AAPL - Actual
MSFT - Planned
MSFT - Actual