What is cycle time?
Quick definition
The total elapsed time from when work starts until it is completed and delivered, measured across the entire workflow in Kanban systems.
Cycle time is a critical metric in Kanban and agile workflows that measures the duration between when a work item enters the system and when it exits as finished. This encompasses all stages: development, testing, review, and deployment. Unlike lead time (which includes waiting before work starts), cycle time focuses only on active processing time, making it a precise indicator of workflow efficiency and team productivity.
For AI coding agents and developers, cycle time helps identify bottlenecks in automated workflows and manual processes. A high cycle time suggests tasks are blocked, queued, or encountering technical friction. By tracking cycle time across sprints or iterations, teams can establish realistic velocity estimates, optimize WIP limits, and improve delivery predictability. AI-driven systems benefit from cycle time analysis to fine-tune agent orchestration strategies and reduce latency in multi-step processes.
In Kanban boards, cycle time is visualized through the movement of cards from left to right across columns. Shorter cycle times indicate healthy flow, while spikes signal process degradation. Development teams use cycle time as a performance baseline to measure the impact of process improvements, infrastructure changes, or staffing adjustments.
Example
How it shows up in practice
A bug fix task enters the workflow on Monday at 9am and completes on Wednesday at 2pm. The cycle time is approximately 53 hours of elapsed time, regardless of how many hours were actually spent on development versus waiting for code review.
In Kanboard
In Kanboard, cycle time is tracked by measuring the duration from when a task moves to 'In Progress' until it reaches a completed status. Kanboard displays this metric in reports and analytics, helping teams monitor workflow efficiency and identify when tasks spend excessive time in specific columns, indicating process bottlenecks or resource constraints.
Frequently asked questions
How is cycle time different from lead time?
Lead time includes waiting time before work starts (from request to work beginning), while cycle time only measures active processing from work start to completion. Cycle time is typically shorter and more actionable for process optimization.
Why should AI agents track cycle time?
Tracking cycle time helps AI orchestration systems identify delays, measure agent performance, and optimize task routing. High cycle times reveal where agents spend excessive time waiting for responses or processing complex subtasks.
How can I reduce cycle time in my workflow?
Reduce cycle time by lowering WIP limits, removing blockers, parallelizing independent tasks, and automating repetitive steps. Regular retrospectives and bottleneck analysis help identify specific improvement opportunities.
Is cycle time the same across all Kanban implementations?
The core concept is consistent, but measurement start/end points may vary. Some teams measure from task creation, others from when it enters active development. Define clear boundaries for your team's measurement.