What's Better: Cycle Time or Velocity?

Cycle Time and Velocity are two metrics that can significantly impact a team's performance. But what's the difference, and which one should you focus on?

This article will break down these key metrics, exploring how they affect your team's efficiency and output.

We'll dive into the nuances of each, helping you understand Cycle Time, Velocity, and other engineering metrics that can provide insights for improving developer productivity.

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Cycle Time and Velocity are two key metrics that help software development teams measure and improve their workflow efficiency and predictability. These metrics enable teams to assess their performance, identify bottlenecks, and drive continuous process improvements.

To clarify the difference between the metrics, let's take a closer look at each one:

Cycle Time

This 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 it is delivered.

Cycle Time can show how efficiently the team handles individual tasks, and it is valuable because it acts as a diagnostic tool for your development process. A rising Cycle Time may indicate bottlenecks or challenges within the workflow, or could indicate that the work wasn't well-scoped before the team picked it up. Exploring Cycle Time can help teams identify areas for improvement and streamline their processes.

Velocity

This measures the total amount of work completed within a specified timeframe, typically during a sprint. It is commonly measured in story points, which represent the effort required for tasks in Agile frameworks.

Velocity is particularly useful for sprint planning. By understanding the team's average Velocity, it becomes easier to predict workload capacity for future sprints. However, we recommend using Velocity  in a blameless way for internal improvement and not as a means to compare team or individual performance.

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If a choice must be made, Cycle Time stands out as the more valuable metric. Here's why:

Benefits of Cycle Time

1. Cycle Time provides greater accuracy and reliability: Cycle Time measures the actual duration of tasks, offering a precise and reliable gauge of team performance. Unlike Velocity, which uses potentially subjective story points (which can vary from team to team), Cycle Time is based on objective time measurements. This makes it a more objective and dependable indicator of efficiency, harder to game, and more likely to drive genuine process improvements.
2. Cycle Time enhances team productivity and efficiency: By focusing on Cycle Time, teams are encouraged to identify and address bottlenecks, which leads to more efficient processes. Cycle Time naturally promotes working in smaller batches, allowing teams to iterate faster and deliver value more frequently. Unlike Velocity-based planning, which often requires additional meetings for planning, Cycle Time measurement integrates seamlessly into existing workflows.
3. Cycle Time enhances project planning and risk management: Accurate Cycle Time data enables teams to forecast more precise project timelines and manage risks effectively. For example, by knowing the average time tasks take, teams can set realistic deadlines, mitigate risks of scope creep, and adjust workloads before bottlenecks emerge.

Overall, Velocity's reliance on story points introduces an extra layer of abstraction, making it harder to identify and learn from workflow anomalies or deviations.

While Cycle Time is a better metric, there may be benefits to also reviewing Velocity as a supplementary metric. Cycle Time tracks task efficiency, while Velocity assesses workload capacity (as long as story points aren’t being gamed). Together, these metrics can help teams balance fast delivery with effective sprint planning.

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Cycle Time is arguably more closely related to business outcomes compared to velocity. This is because Cycle Time is more similar, but not identical, to Change Lead Time (previously called Lead Time for Changes). Led Time DORA Metric, which means there's over a decade of research that shows that it's correlated with positive outcomes for the company and the team.

DORA's research and the book Accelerate show a direct link between high performance on Change Lead Time plus the 3 other DORA metrics and improving profitability, productivity, and customer satisfaction.

While improving Cycle Time may contribute to business success, there is more evidence-backed research for Change Lead Time, which shows:

• Faster Time to Market: Reducing Change Lead Time allows teams to release products and features more quickly, directly impacting deployment frequency. While Velocity can help with sprint planning, it doesn't necessarily translate to faster delivery — whereas Change Lead Time focuses on actual delivery speed which provides a more direct link to market readiness.
• Increased Customer Satisfaction: Delivering value to customers faster and more consistently increases satisfaction and builds customer loyalty. A focus on delivery aligns more closely with customer-centric outcomes than Velocity's focus on internal story point completion.
• Better Decision-Making: Change Lead Time provides actionable insights into team performance and efficiency. These insights help leaders make informed decisions on resource allocation, process improvements, and strategic planning.

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Although Cycle Time is valuable, relying on it alone doesn't provide the full picture of team performance. Adopting a balanced scorecard approach—considering other dimensions such as software stability or team well-being — offers a more holistic view and gives you visibility into the broader trade-offs that engineering teams need to make.

Including metrics in tension, such as speed versus quality or workload versus well-being, helps reveal the trade-offs that teams are making. The SPACE framework offers a great approach to selecting metrics that are “in tension”.

Some other important metrics to consider:

• Change Lead Time: Measures how quickly code moves from initial commit to successful production deployment.
• Deployment Frequency: Tracks how regularly teams push code to production or deliver updates to users.
• Failed Deployment Recovery Time: Originally called Mean Time to Recovery, this metric captures how long it takes teams to restore service after a software change disrupts production.
• Change Failure Rate: Shows what percentage of deployments lead to service degradation or need fixes (including issues requiring hotfixes, rollbacks, or patches).

Each metric brings its own insight, and together they create a more complete understanding of team productivity and overall health.

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Multitudes offers tools that can help you track a whole suite of engineering metrics to 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, helping you balance these key metrics.

With Multitudes, you can:

• Automatically track key engineering metrics like DORA across your projects
• Get visibility into work patterns and bottlenecks that might be inflating your times
• Identify collaboration patterns and potential silos within your team that could be slowing things down
• Understand individual and team well-being through metrics like out-of-hours work
• Receive timely nudges via Slack about blocked work and who might need more support, helping you address issues before they significantly impact your delivery

By leveraging Multitudes, teams can spend more time acting on insights to improve their software development delivery and boost overall efficiency and satisfaction.

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