Cycle Time

5 minutes 5 Questions

Cycle Time helps to gauge the efficiency of a process or system. In Scrum, it's the time taken from when work starts on a User Story until it's ready for delivery. Shorter Cycle Times represent a well-functioning delivery process. To improve Cycle Time, teams look at reducing inefficiencies like wait times, task switching, or non-value-adding activities. Monitoring this metric over time allows teams to forecast project delivery and helps to manage stakeholders' expectations.

Guide to Understanding Cycle Time in Scrum Metrics

Cycle Time is a critical metric in Scrum and Agile methodologies. It is the time taken from when work begins on a user story, feature, or other piece of work, until it is finished.
Why is it Important?
It gives teams an understanding of their efficiency and helps to identify bottlenecks in the development process. Tracking Cycle Time over time can help teams to see trends, and make necessary adjustments to improve speed and quality.
How does it Work?
It starts when work begins on a particular item and ends when the item is declared done. It includes all time, even if the item was waiting in queues.
Exam Tips: Answering Questions on Cycle Time
When answering exam questions on Cycle Time, remember the key points: 1) Cycle Time includes all time, not just active working time, 2) Lower Cycle Time usually indicates higher efficiency, 3) It can help teams identify bottlenecks and 4) It's an important aspect of process improvement.
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PSM I - Cycle Time Example Questions

Test your knowledge of Cycle Time

Question 1

A team's cycle time metrics reveal that the Preparation phase consistently takes 60% of the total cycle time. What should be the most effective approach?

Correct Answer: Analyze and optimize the preparation phase workflow through value stream mapping

Value stream mapping is the most effective approach because:

It allows the team to:
- Identify wasteful activities and bottlenecks in the preparation phase
- Visualize the entire workflow to spot improvement opportunities
- Make data-driven decisions to optimize the process
- Address root causes rather than symptoms

The other approaches are less effective because:

Adding more team members could lead to increased coordination overhead and complexity, potentially making the situation worse (Brooks' Law).

Parallel processing might introduce dependencies and risks that could compromise quality and create additional complications in workflow management.

Replacing the phase with automation and documentation is too extreme, may not address underlying issues, and could create new problems in knowledge transfer and team collaboration.

Value stream mapping provides a systematic way to understand and improve the workflow, making it the most sustainable and effective solution for reducing cycle time in the preparation phase.

Question 2

A project manager notices that the cycle time of their project is consistently longer than similar projects in their organization. Which step should be taken first to address this issue?

Correct Answer: Analyze the underlying reasons for the longer cycle time.

To address the longer cycle time, it's important to first analyze the underlying reasons by comparing the different processes between the projects and identifying potential inefficiencies.

Question 3

In a DevOps-oriented project, the team observes that cycle time fluctuates based on the technical complexity of features. What measurement should they implement to better understand and improve their cycle time?

Correct Answer: Track cycle time separately for different types of technical work and create complexity-based baseline metrics

The best approach is to track cycle time separately for different types of technical work and create complexity-based baseline metrics. Here's why:

Strengths of this approach:
- Acknowledges that different types of work have different inherent complexities
- Enables more accurate forecasting by categorizing work
- Provides detailed insights for targeted process improvements
- Allows teams to set realistic expectations based on work complexity

Why other options are less effective:

Using a standardized system across all features oversimplifies the reality that different work has different complexity levels, leading to inaccurate measurements and unrealistic expectations.

Calculating average cycle time across all features masks the variability in complexity and provides misleading metrics for planning.

Measuring cycle time based on story points introduces unnecessary complexity and potential bias, as story points are already an abstraction of complexity and effort.

The chosen approach acknowledges the natural variation in work complexity and provides actionable data for continuous improvement while maintaining transparency about different work types.

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Other Scrum Metrics concepts

Cumulative Flow DiagramEscaped DefectsLead TimeRelease Burn-up ChartSprint Burn-down ChartSprint Goal SuccessTeam VelocityThroughputVelocityWork In Progress (WIP)
All Scrum Metrics questions · PSM I practice test