Flow Time in Software Development: Challenges, Tools, and Tips

Software development is a competitive, fast-paced world. 

That’s why your goal is to deliver high-quality products efficiently while helping your team thrive.

Understanding and optimizing flow time is the first step to improving your team's productivity. 

And you’re on the right page because you’ll find out:

• What is flow time, and how do we interpret it in the context of other flow metrics
• How this metric compares to lead time and cycle time
• Best practices to track and improve flow time
• Challenges and measurement tools

Let’s begin.

Insider tip: With Axify's historical data tracking, you can monitor your average flow time across different projects and teams. This allows you to establish benchmarks and track improvements over time. Use this data to set actionable goals to reduce your average flow time, ultimately improving your team's productivity.

What Are Flow Metrics?

Flow metrics are a set of key performance indicators essential in the Lean toolkit. These variables measure the end-to-end unit of value of a product. As such, they indicate the efficiency and productivity of your software development process. 

And it’s all related to the concept of “flow.”

These metrics help you understand how work moves—or flows—through the development lifecycle. This enables you to have a more comprehensive understanding of any project, from when work items enter the workflow until you complete them. 

Standard flow metrics include flow time, flow efficiency, flow velocity, and flow load. 

Each of these metrics provides insights into different aspects of the workflow, such as the speed of delivery, the amount of work in progress, and the overall effectiveness of the development process.

What Is Flow Time?

Flow time is the total time it takes for a work item to move through the entire development process, from when work begins until it is completed and delivered. 

This metric includes both active work time and any waiting time between different stages of the development cycle.

Flow time directly correlates with how quickly your team can deliver value to customers. 

A shorter flow time indicates a more efficient process, where work moves smoothly without unnecessary delays. 

Pro tip: More than flow time alone is needed to provide a complete picture of the development process. You need to consider it alongside other metrics like:

• Flow efficiency: To understand how much flow time you spend on productive work versus delays.
• Flow load: To gauge whether the team’s capacity is appropriately balanced or if too much work is in progress simultaneously.
• Flow velocity: To measure how much work you complete over time and whether the team maintains a consistent delivery pace.

For instance, developing a new feature with a high level of complexity or addressing deep technical debt may result in a longer flow time. Plus, teams strategically prioritize tasks to align with their goals. As a result, some tasks may have longer flow times because you intentionally deprioritize them to allow more critical work to progress faster.

Insider tip: Use Axify's Value Stream Mapping (VSM) feature to break down your flow time into its constituent parts. This detailed view lets you see exactly where delays occur and take targeted action to streamline your process, reducing overall flow time and accelerating your delivery cycle.

What Is Average Flow Time?

Average flow time is the mean duration work items spend in the development process. You calculate it by taking the total flow time for all completed items over a specific period and dividing it by the number of items.

This metric helps you understand the typical time it takes to deliver work, so it’s like having a benchmark for continuous improvement. Plus, monitoring average flow time over time reveals trends and helps you set realistic expectations for project timelines.

Flow Time: Benefits and Key Uses

Flow time offers several benefits across different roles within a software development team. The point of understanding flow time is ultimately to optimize it. That way, you can increase your team’s efficiency and delivery performance. 

Let’s break down some of these benefits:

• Developers:
  • Improved efficiency: Tracking flow time lets you identify bottlenecks and delays. Therefore, you can optimize your processes and reduce unnecessary waiting times.
  • Faster delivery: Shorter flow times mean you can deliver features and fixes more quickly. This leads to more frequent releases and faster value delivery to customers.
• Project managers:
  • Better forecasting: Understanding the average flow time helps you create more accurate timelines and delivery estimates. This reduces the risk of delays and improves stakeholder communication.
  • Resource allocation: Analyzing flow time data helps you allocate resources more effectively. This ensures that your high-priority tasks receive the attention they need to meet deadlines.
• Product owners:
  • Improved resource allocation: Tracking flow time helps identify potential bottlenecks and areas where the team might need additional support. By understanding where delays typically occur, you can allocate resources more effectively to keep the project on track and ensure that critical tasks progress smoothly.
  • Customer satisfaction: By reducing flow time, you can respond faster to customer feedback and market demands. That ultimately leads to higher customer satisfaction.

Insider tip: While optimizing flow time is essential for enhancing productivity, it’s crucial not to overlook team morale. At Axify, we believe a healthy, motivated team is just as important as efficient processes. Our Team Well-Being feature helps you monitor and improve resilience, motivation, and psychological safety. Striking a balance between efficient workflows and a positive work environment ensures sustainable success and higher overall performance. 

Flow Time vs Lead Time

In software development, lead time measures the total duration from when a task or request (such as a new feature or a bug fix) is first made until it is fully delivered and available to the customer. It captures the entire journey of the task, including any time it spends in the backlog or waiting for approval before active work begins.

On the other hand, flow time focuses specifically on the period during which your team works on the task. Flow time begins when the task is pulled into the development process, or Value Stream, and actual work starts (such as coding or testing). It ends when the task is completed and ready for delivery.

Example Time

Consider a scenario where a customer requests a new feature for a software application on Wednesday. However, due to other priorities,  the development team can only start working on it the following Tuesday. The team works on the feature throughout the week, and it is released to the customer the following Monday.

• In this case, the lead time is 12 days, from the initial request on Wednesday until the feature is delivered the following Monday.
• The flow time would only cover Tuesday, when the development team began working on the feature, until the following Monday, when it was completed—6 days. This excludes the time the request spent waiting before work started.

Therefore, tracking lead and flow times gives you a comprehensive view of the development process. 

• Lead time helps you understand the overall responsiveness of the team, including how long tasks spend waiting before work begins. Lead time is closest to the customer and could help you identify bottlenecks that happen during pre-development
• Flow time, however, allows teams to focus on improving the efficiency of the actual work process, identifying and reducing delays that occur once work has started. Besides, flow time helps you find bottlenecks during development.

Insider tip: Axify's metrics dashboard shows you all flow metrics, allowing you to gain crucial insights into your team's performance. Use these metrics to identify bottlenecks in your deployment process and take proactive steps to streamline your workflow.

For example, if you notice a longer lead time for changes, you may need better automation in the testing or deployment stages. 

Use Axify's detailed visualizations to track these changes over time, compare them against industry benchmarks, and set realistic goals to continuously improve your team's deployment efficiency. This proactive approach will help you enhance the speed and quality of your software delivery.

Cycle Time vs Flow Time in Agile

• Cycle time: In Agile, cycle time measures the duration a work item spends in progress, from when it starts being worked on to when it is completed, including any idle time. That’s why you can use cycle and flow time interchangeably in 99% of cases. However, cycle time can also be applied to specific stages within the workflow, not just the entire development process. That means you get more flexibility in what you measure.
• Flow time: Flow time, on the other hand, captures the entire journey of a work item through the development process—from the moment work begins to completion—encompassing all stages and any idle time within the workflow. This metric provides a broader view of the entire process, highlighting where delays or inefficiencies may occur.

Cycle Time vs Flow Time Similarities

• Both cycle time and flow time focus on the duration work items spend in the development pipeline and are used to measure team efficiency and predict delivery timelines.
• They are integral to Agile practices, where the emphasis is on continuous delivery and process improvement.

Cycle Time vs Flow Time Differences

• Scope of measurement: While cycle time and flow time include idle periods, cycle time can be applied to specific stages within the workflow, allowing teams to focus on particular process segments. Flow time, however, measures the entire journey of a work item from start to finish, offering a comprehensive view of the overall process.
• Application: Agile teams often use cycle time to monitor ongoing work and ensure smooth flow, while you can use flow time to analyze and optimize the entire development process.

Insider tip: The Axify Value Stream Mapping feature calculates precise cycle times for your entire workflow and specific work stages.

To optimize your team's efficiency, monitor the "Cycle Time Distribution" and "Time Invested by Item Type" graphs. These insights allow you to identify areas where work is getting stuck or consuming more time than expected. Addressing these bottlenecks improves overall cycle time and ensures you complete more items within each sprint. The result is a more predictable and efficient development process.

How to Improve Flow Time in Software Development 

Improving flow time in software development is essential for delivering high-quality products faster and more efficiently, as long as you don’t over optimize flow time to the disadvantage of other flow metrics.

That said, here are some strategies to reduce flow time:

• Optimize workflows: Streamline your development processes by improving test automation, deployment automation, and other repetitive tasks. Focus on simplifying the workflow to eliminate delays and reduce the time work items spend in each phase.
• Limit Work in Progress (WIP): Encourage close collaboration between developers, testers, and operations teams. Effective teamwork helps you identify and resolve issues faster, leading to shorter flow times. Visualizing work in progress can help the team stay aligned and avoid potential bottlenecks. Then, limit WIP to ensure work items flow more quickly through the pipeline.
• Implement Continuous Integration and Continuous Deployment (CI/CD): Automating the integration and deployment process can significantly reduce the time it takes to get changes into production. CI/CD practices help catch issues early and ensure that code is ready for deployment as soon as it's completed.
• Minimize hand-offs: Reduce the number of hand-offs between different team members or departments because these transitions introduce delays that increase cycle time. You can optimize your processes to keep work within a single team or define responsibilities during hand-offs more clearly. For example, you can involve QA early in the process instead of doing QA after development. The QA team can write test scenarios before development begins. Developers can then automate tests and work to optimize the flow.

Insider tip: While optimizing your team's flow time is crucial, keeping everyone aligned and focused on the right priorities is just as important. Axify's Daily Digest feature ensures that your team stays on track by providing a concise summary of actionable items every day. Use this feature to facilitate daily stand-ups, address potential bottlenecks, and maintain clear communication across your team. This way, you can optimize flow time without compromising collaboration or clarity, ensuring everyone is working toward the same goals.

Best Practices to Track and Measure Flow Time

Effectively tracking and measuring flow time is crucial to optimize this metric correctly. Here are some best practices to follow:

• Set clear definitions: Ensure that your team has a shared understanding of what constitutes the start and end of flow time. Consistent definitions are critical for accurate measurement and comparison. Axify has a workflow mapping feature that helps you do precisely that.

• Use the right metrics: When tracking flow time, consider related software engineering metrics like cycle and lead time. Together, these metrics provide a fuller picture of your development process and help identify areas for improvement. And, of course, keep track of all Flow Framework indicators.
• Automate data collection: Use tools that integrate seamlessly with your development environment to automate the tracking of flow time. This reduces manual effort and ensures that data is accurate and up-to-date.
• Focus on continuous improvement: Tracking flow time should be part of a broader strategy. Use the insights gained from flow time metrics to make incremental changes to your processes and regularly assess the impact of these changes.
• Communicate findings with the team: Share flow time metrics and insights with your team to foster a culture of transparency and collective responsibility. When everyone understands the impact of flow time on project delivery, they are more likely to collaborate on solutions to reduce it.

However, even following these best practices can present challenges when measuring flow time. That brings us to the next point.

Challenges in Measuring Flow Time and the Axify Solution

Measuring flow time in software development is sometimes easier said than done if you face these roadblocks:

1. Lack of Standardization

Different teams and organizations may define flow time differently, leading to inconsistencies in measurement. For instance, some may start measuring flow time when a task is picked up, while others may include backlog time.

These variations can make it challenging to compare flow time across teams or projects and lead to inaccurate efficiency assessments.

Solution: Axify standardizes the collection and analysis of key metrics through its comprehensive metrics dashboard. This ensures consistency across teams and projects, allowing for accurate benchmarking and comparison.

2. Incomplete Data

Flow time depends on accurate tracking of when work begins and ends. If teams fail to update their task management systems promptly, the data collected might be incomplete or inaccurate.

And incomplete data skews your measurements, making identifying bottlenecks and inefficiencies harder.

Solution: Axify automatically collects and synchronizes your data. This automation reduces the risk of human error and ensures that the data used for analysis is accurate and up-to-date.

3. Complex Workflows

Software development involves multiple stages and hand-offs between teams (e.g., development, testing, deployment). These transitions introduce delays that are difficult to measure accurately within flow time.

With clear visibility into each workflow stage, it becomes easier to identify where time is lost and how to optimize the process.

Solution: While Axify doesn't track flow time, its focus on cycle time and lead time provides valuable insights into the efficiency of your development process. By analyzing these metrics, teams can identify stages in the workflow where delays occur, even if flow time isn't directly measured.

4. Tool Integration

Many teams use various tools for different parts of the development process (e.g., Jira for task management and GitHub for version control). Ensuring that all tools are integrated and data is synchronized can be difficult.

Without proper integration, flow time data may be fragmented or incomplete, making it challenging to obtain a holistic view of the development process.

Solution: Axify integrates seamlessly with popular development tools like Jira, GitHub, and Azure DevOps. Thus, all data related to your software development lifecycle is captured in one place. This unified view allows you to monitor and optimize your workflows without dealing with the headaches that come from using disparate tools.

Wrapping Up

As you can see, flow time is an essential metric that provides valuable insights into your processes. Optimizing this KPI helps you deliver more value to your customers and stakeholders without compromising your team’s mental health.

However, it all starts with accurate measurements, and measuring flow time presents several challenges. 

However, Axify offers a powerful alternative by focusing on related metrics that provide deep insights into your development process. 

Leverage Axify’s features to avoid these challenges.

Book a demo today to see exactly how we can help optimize your software development workflows.