Speed matters in software development. Top-performing teams ship code in just two days, while many others lag at seven.
Software cycle time directly impacts product delivery and customer satisfaction - and it’s equally essential for your team's confidence.
CTOs and engineering leaders can’t reduce cycle time just by working faster. They must optimize processes, identify and eliminate bottlenecks, and consistently deliver value.
In this post, we’ll break down the key strategies to reduce cycle time.
Software cycle time measures how long it takes for code to go from the first commit to production.
It tracks the time a pull request (PR) spends in various stages of the pipeline, helping teams identify and address workflow inefficiencies.
Cycle time consists of four key components:
Software cycle time is a critical part of DORA metrics, complimenting others like deployment frequency, lead time for changes, and MTTR.
While deployment frequency indicates how often new code is released, cycle time provides insights into the efficiency of the development process itself.
Understanding and optimising software cycle time is crucial for several reasons:
Cycle time reflects how efficiently engineering teams work. For example, there are brands that reduce their PR cycle time with automated code reviews and parallel test execution. This change allows developers to focus more on feature development rather than waiting for feedback, resulting in faster, higher-quality code delivery.
Reducing cycle time accelerates product delivery, allowing teams to respond faster to market demands and customer feedback. Remember Amazon’s “two-pizza teams” model? It emphasizes small, independent teams with streamlined processes, enabling them to deploy code thousands of times a day. This agility helps Amazon quickly respond to customer needs, implement new features, and outpace competitors.
The ability to ship high-quality software quickly can set a company apart from competitors. Faster delivery means quicker innovation and better customer satisfaction. For example, Netflix’s use of chaos engineering and Service-Level Prioritized Load Shedding has allowed it to continuously improve its streaming service, roll out updates seamlessly, and maintain its market leadership in the streaming industry.
Cycle time is one aspect that engineering teams cannot overlook — apart from all the technical reasons, it also has psychological impact. If Cycle time is high, the productivity level further drops because of demotivation and procrastination.
Reducing cycle time is easier said than done. There are several factors that affect efficiency and workflow.
Reducing software cycle time requires a combination of technical improvements, process optimizations, and cultural shifts. Here are six actionable strategies to implement today:
Establish clear SLAs for review timelines—e.g., 48 hours for initial feedback. Use tools like GitHub’s code owners to automatically assign reviewers based on file ownership. Implement peer programming for critical features to accelerate feedback loops. Introduce a "reviewer rotation" system to distribute the workload evenly across the team and prevent bottlenecks.
Identify repetitive tasks such as testing, integration, and deployment. And then implement CI/CD pipelines to automate these processes. You can also use test parallelization to speed up execution and set up automatic triggers for deployments to staging and production environments. Ensure robust rollback mechanisms are in place to reduce the risk of deployment failures.
Break down silos by encouraging cross-functional collaboration between developers, QA, and operations. Adopt DevOps principles and use tools like Slack for real-time communication and Jira for task tracking. Schedule regular cross-team sync-ups, and document shared knowledge in Confluence to avoid communication gaps. Establish a "Definition of Ready" and "Definition of Done" to align expectations across teams.
Schedule dedicated time each sprint to address technical debt. One amazing cycle time reduction strategy is to categorise debt into critical, moderate, and low-priority issues and then focus first on high-impact areas that slow down development. Implement a policy where no new feature work is done without addressing related legacy code issues.
Track cycle time by analysing PR stages—coding, pickup, review, and merge. Use tools like Typo to visualise bottlenecks and benchmark team performance. Establish a regular cadence to review these engineering metrics and correlate them with other DORA metrics to understand their impact on overall delivery performance. If review time consistently exceeds targets, consider adding more reviewers or refining the review process.
A cluttered backlog leads to confusion and context switching. Use prioritization frameworks like MoSCoW or RICE to focus on high-impact tasks. Ensure stories are clear, with well-defined acceptance criteria. Regularly groom the backlog to remove outdated items and reassess priorities. You can also introduce a “just-in-time” backlog refinement process to prepare stories only when they're close to implementation.
Reducing software cycle time requires the right set of tools to streamline development workflows, automate processes, and provide actionable insights.
Here’s how key tools contribute to cycle time optimization:
GitHub and GitLab simplify version control, enabling teams to track code changes, collaborate efficiently, and manage pull requests. Features like branch protection rules, code owners, and merge request automation reduce delays in code reviews. Integrated CI/CD pipelines further streamline code integration and testing.
These CI/CD tools automate build, test, and deployment processes, reducing manual intervention, ensuring faster feedback loops and more effective software delivery. Parallel execution, pipeline caching, and pre-configured environments significantly cut down build times and prevent bottlenecks.
Typo provides in-depth insights into cycle time by analyzing Git data across stages like coding, pickup, review, and merge. It highlights bottlenecks, tracks team performance, and offers actionable recommendations for process improvement. By visualizing trends and measuring PR cycle times, Typo helps engineering leaders make data-driven decisions and continuously optimize development workflows.
In your next development project, if you do not want to feel that this is taking forever, follow these best practices:
Reducing software cycle time is critical for both engineering efficiency and business success. It directly impacts product delivery speed, market responsiveness, and overall team performance.
Engineering leaders should continuously evaluate processes, implement automation tools, and track cycle time metrics to streamline workflows and maintain a competitive edge.
And it all starts with accurate measurement of software cycle time.