What is Cycle Time in Agile: A Breakdown

Are you curious about how to measure and improve your team's efficiency? Cycle Time is a key metric that Agile teams use to understand how well the work is flowing.

In this article, we'll explore what is Cycle Time, why it's valuable for your workflow, and how it's different from other common metrics such as lead time. Whether you're new to Agile or looking to refine your practices, understanding Cycle Time can help your team deliver value to customers more effectively.

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Cycle Time is a key metric in Agile development that measures how quickly teams can turn an idea into a working product. It tracks the time from when work begins on a task to when the work is delivered.

However, to better understand Cycle Time, it’s best to think of it as one of 3 key metrics that measure speed in a development process: Cycle Time, Lead Time and Lead Time for Changes. As these are commonly confused, it is helpful to know all 3 definitions:

1. Cycle Time: Measures active development time — from the moment development starts on an item to it being delivered to the end user.
2. Lead Time: Measures entire lifecycle from documented idea to delivery — from the moment it is added to the backlog to when it is delivered.
3. Lead Time for Changes: Measures what DORA considers the most predictable part of the development lifecycle — from the moment of the first commit to when it is delivered.

Cycle Time vs Lead Time

The main difference is that Lead Time includes time in backlog but Cycle Time does not.

Lead Time gives a broader view of the entire process, including prioritization and planning. However, it's generally an unsuitable metric for truly agile teams due to variability in backlog time. Lead time might be more relevant in teams working on large projects with a waterfall structure and fewer customer feedback cycles.

Lead Time is not typically controlled by the engineering team. Product Managers or the business determine work prioritization, making it a poor metric for engineering teams to use. In most businesses, strong prioritization of customer needs is more important than measuring overall Lead Time.

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Cycle Time vs Lead Time for Changes

The key difference is that Cycle time begins from when development starts, whereas Lead Time for Changes begins from the first commit.

Lead Time for Changes is one of the DORA Metrics by Google and measures one of the most predictable parts of the software development pipeline, which helps teams become higher performing. This is because Lead Time for Changes is most squarely in the control the engineering team, and relatively less affected by external stakeholders (though some coordination is inevitable). However, it is a marked improvement on using overall Lead Time.

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Measuring Cycle Time provides insights to help teams work together more effectively by:

1. Improving Workflow: If your Cycle Time is consistently longer than expected, it’s a signal that a particular phase is taking too long, indicating a need for more resources or a process overhaul.
2. Setting realistic goals and improve planning: Historic Cycle Time data helps you create achievable objectives based on your team's actual performance. Instead of setting arbitrary deadlines, you can use past Cycle Times to help estimate how long similar tasks may take in the future.
3. Fostering continuous improvement: Regularly keeping a pulse on Cycle Times encourages your team to fine-tune their processes. It creates a culture of constant improvement, where team members are always looking for ways to improve their work.

Ultimately, this leads to more value flowing through to the end customer, faster.

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Cycle Time is an indicator of Flow — which reflects the pace at which value moves through a system. A popular framework for thinking about Flow is the Flow Framework, created by Dr. Mik Kersten in 2018.

This framework categorizes work into 4 types of Flow items:

• Features: New value-adding functionalities or enhancements that drive business results, such as a new user interface or payment integration.
• Defects: Fixes for quality issues that negatively impact the customer experience, like bugs, crashes, or incorrect functionality.
• Debts: Improvements to software or operational architecture that don't add new features but enhance maintainability and future development speed.
• Risks: Work addressing security, privacy, or compliance concerns to protect the business from potential threats or legal issues.

The framework then introduces 5 metrics to measure how the above items “flow” through the development process:

• Flow Velocity: The number of Flow Items of each type completed over a particular time period. Flow Velocity measures whether value delivery is accelerating.

• Flow Time: The time it takes for Flow Items to go from ‘work start’ to ‘work complete’, including both active and wait times. Flow Time helps identify when time-to-market is getting faster. Cycle Time can be considered a version of Flow Time.

• ‍Flow Efficiency: Compares active time versus wait time to show how much time is spent actually working versus waiting. This metric can help identify areas where Cycle Time can be improved by reducing wait states.

• ‍Flow Load: Measures the number of Flow items in progress, highlighting if a team is overloaded or underloaded. This can impact Cycle Time, as overloaded teams may struggle to complete work efficiently.

• ‍Flow Distribution: Examines the balance of different types of Flow items (features, defects, debt, and risk) being worked on, ensuring a healthy mix of value-creating activities.

It is helpful to have the Flow Framework back of mind when considering Cycle Time — because ultimately you are solving for how efficiently value can be created and shipped to the customer. As an aside, if you’ve ever heard the term Value Stream Management (the practice of measuring and improving flow), it is closely related to this framework.

Applying the Flow Framework can not only help you improve your Cycle Time, but more broadly optimize the overall process of delivering value to the world.

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Calculating Cycle Time typically requires historical data from your issue-tracking tool, but the steps are relatively simple:

1. Identify the start and end points for your work items
2. Track the time it takes for each item to move from start to finish
3. Calculate Cycle Time using the formula:
4. Cycle Time = End Time (Date/Time when the work is ready for deployment) - Start Time (Date/Time when active work begins)

Precise cycle time calculations depend on teams clearly defining task start and end points.

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Common challenges in Cycle Time calculation

Calculating Cycle Time accurately can be tricky due to 2 common challenges

• Issue tracking: One of the biggest hurdles in calculating accurate Cycle Times is poor issue tracking hygiene. Inconsistent or inaccurate status updates, improper labeling, or neglecting to move tickets through the proper workflow can significantly skew Cycle Time measurements. Ensuring your team maintains good issue tracking data for accurate assessment.
• Inconsistent definitions of start and end points: Teams may have different interpretations of when a task starts and ends, leading to inconsistent measurements – even within the same organization. Clear, team-wide agreement on these definitions is essential.

Being aware of these common challenges and working as a team to overcome it can help improve the usefulness of your Cycle Time measurements (and also any other metric you may be tracking).

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Reducing Cycle Time is all about finding the balance between speed and quality. There are two main areas to focus on to reduce Cycle Time:

Streamlining workflows

The Flow Framework we shared above can help you improve your value streams to be more efficient. Here's how you can achieve this:

• Regularly examine your processes to identify and eliminate speed bumps. For example, streamline your change approval process to reduce delays. According to the DORA report, efficient change approval processes can significantly cut down Cycle Times. Look for opportunities to eliminate unnecessary steps and automate approvals where possible.
• Remove any unnecessary steps that aren't adding value. Focus on what truly matters and eliminate redundant procedures that slow down your team. You can do this by examining the outliers in your Cycle Time data and working with your team to identify root causes.
• Ensure that handoffs between team members are seamless and that there is clear communication throughout the transition of tasks between people.

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Improving Definition of Ready (DoR) and Definition of Done (DoD) criteria

DoR and DoD are critical concepts in Agile development that help ensure work items are properly prepared before development begins, and actually completed when marked as done.

• Definition of Ready (DoR): A set of criteria that a work item must meet before it's considered ready for the team to start working on it. It might include having clear acceptance criteria, being properly sized, and having necessary design or architectural decisions made.
• Definition of Done (DoD): A shared understanding among the team of what it means for a work item to be complete. It typically includes criteria such as code being reviewed, tests passing, documentation updated, and the feature being deployed to a staging environment.

By having clear DoR and DoD metrics, you can improve your Cycle Time as teams won’t begin work on items with unclear scope, which can really blow out the working time. Having clear signposts to ensure everyone understands what "ready" and "done" really mean helps achieve this.

Additionally, continuous improvement practices such as holding regular workshops to collaboratively refine these definitions ensure that the current DoR and DoD are speeding up our flow (as opposed to slowing us down).

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Software to improve Cycle Time

Multitudes offers tools that can help you track and enhance your team's performance. By integrating with your existing development tools, such as GitHub, JIRA and more, Multitudes provides real-time insights into your workflow, specifically focusing on Cycle Time.

With Multitudes, you can:

• Automatically track Cycle Time to measure how long it takes for your team to complete tasks from start to finish.
• Gain visibility into work patterns and types of work, such as feature development vs. bug fixing, to understand where time is being spent.
• Identify collaboration patterns and potential silos within your team, which can affect Cycle Time.
• Understand individual and team well-being through metrics like out-of-hours work and responsiveness, which can influence productivity.

By leveraging Multitudes, teams can spend more time acting on insights to improve their Cycle Time, thereby boosting overall efficiency and satisfaction.

Ready to unlock happier, higher-performing teams?

Try our product today!