Flow Metrics & Analytics

Cycle Time Breakdown Chart

What it answers

Where is work slowing down?

See where completed work spends its cycle time and identify process states causing delays.

Example

How to read it

Cycle Time Breakdown Chart in Nave: a stacked bar per delivery period colored by process state, a hover tooltip with cycle time and throughput, and the Breakdown widget comparing process state cycle times
  1. Process state segment

    Each colored section of a bar represents a process state. Together, the sections show the delivery times of completed tasks split across the process.

  2. Hover details

    Hover over a bar to see the combined delivery times, the delivery time split by process state, and the number of tasks delivered in the selected period.

  3. ‘Breakdown’ widget

    The ‘Breakdown’ widget compares process state cycle times with the overall cycle time. It helps identify the states with the longest sections for further analysis.

See the Cycle Time Breakdown Chart in action

Analyze your cycle time breakdown

The Cycle Time Breakdown Chart shows the total time needed to complete your work, split by process state.

Each bar represents the delivery times of completed tasks. Its colored sections represent the process states.

Focus on how the data changes over time. If the longest colored sections are getting shorter, your improvement efforts are paying off.

The Cycle Time Breakdown Chart: bars split into colored sections by process state

Identify bottlenecks that hinder your performance

Hover over a bar to see the combined delivery times of your completed work and the delivery time for each process state.

You can also see how many tasks were delivered during the selected time period.

Evaluate cycle time by process state to identify impediments. Compare the sections to see how time spent in each workflow step affects the total time needed to finish your work.

Hovering over a bar in the Cycle Time Breakdown Chart: cycle time, throughput and the breakdown by process state

Highlight the disruptive nature of your waiting times

The ‘Breakdown’ widget supports bottleneck analysis by comparing process state cycle times with the overall cycle time.

Find the states with the longest sections, analyze their cycle times, and identify the root causes of delays. This can help improve flow efficiency and reduce delivery times.

Use the Blocked issues control to view all time, blocked time, or time without blockers. The chart applies this filter without removing items unless they were fully blocked.

For completed work, you can break down blockers by column or state. When grouping by work items, the pie chart shows blocked or defect reasons, with accumulated time, item count, and percentage share.

This analysis is especially powerful with a Kanban pull system, where you can assess how much time work spends sitting idle in your process.

The Breakdown widget on the Cycle Time Breakdown Chart comparing process state cycle times with the overall cycle time

Export the filtered data shown in this chart as a CSV file.

What to look for

Longest sections shrinking over time

Check whether the longest colored sections are getting shorter. This indicates that your improvement efforts are paying off.

A process state with the longest section

Investigate states that account for the longest sections and analyze the root causes of their delays.

A queue holding the largest share

Look for a large share of Cycle Time in a state where work waits for a signature, decision, release, or approval.

How to Find the Queue States Eating Your Delivery Time (One Approval Step Held 40% of Ours)

What decisions it helps you make

  • Decide whether your improvement efforts are paying off by checking whether the longest colored sections are getting shorter over time.
  • Decide which process states are impeding performance by assessing how time spent in each workflow step affects the total time needed to finish your work.
  • Decide which delays to address by finding the states with the longest sections and identifying their root causes.

See these analytics with your own delivery data.

Connect your existing delivery data and start exploring your flow.