Software engineering KPIs allow for a better understanding of a project's trajectory and help push for increased efficiency. By utilizing KPIs to comprehend task positioning, teams can adjust their actions to better align with their organization's goals.

We'll examine 21 software engineering KPIs, from project completion rates to scope creep and customer satisfaction scores. There are an overwhelming number of KPIs out there, but starting with these options is a sure way to dip your development team's toes into the proverbial pool of KPIs and focus on efficiency.

The project completion rate KPI highlights the number of projects completed on time; it may be represented as a percent or the exact number of projects completed. This KPI is useful for project planning, enabling team leaders to better schedule time for future projects and allocate resources with more precision.

The schedule variance KPI enables teams to estimate whether a project is on track with a predetermined timetable. To obtain a variance, subtract the completed time from the predicted time. For example, the variance is two days if a project is due on April 2, but the team finishes it on April 4.

Scope creep occurs when a team adds new features to a project or alters established requirements on a project already underway. By learning to manage scope creep, decision-makers can comprehend how well they prepare project requests and how they can better allocate resources to projects for the future.

Larger pull requests can introduce complexity and are often more challenging to review. These factors can slow development or introduce bugs into your production environment. Understanding pull request patterns can help identify how to mitigate risks and ensure collaboration benefits your process rather than harms it.

The developer experience KPI is a critical metric that informs project leaders of overall developer well-being. Team leads can utilize the Developer Thriving Framework to improve developer experience, improving employee retention and heightened productivity while increasing team collaboration. As such, tracking developer experience metrics within your organization is critical to fostering a better working environment for all team members.

ROI allows companies to understand the amount of return yielded from an investment. Calculate ROI by dividing the net return on your investment by its original investment value. Engineering leaders can utilize ROI to better understand the resources, including time, developers employed, and money spent on a project compared to its resulting financial value. From a business perspective, this helps paint a picture denoting the project's effectiveness and overall success.

Deployment frequency is a powerful DORA metric and KPI that showcases how often a team successfully deploys code. Developers can calculate the KPI by dividing the number of code deployments within a set period by the number of weeks. Tracking deployment frequency and other DORA metrics can help your team better understand the software delivery process and identify areas for improvement.

The mean time to recovery KPI, sometimes known as the time to restore service, is a DORA metric focused on the average time it takes to recover from a system or product failure. By focusing on decreasing the time to recovery, you can reduce the amount of time customers spend without your product, heightening customer satisfaction.

Change failure rate is a DORA metric that notes how often team code deployments have incidents or failures attached to them. By comprehending when failure rates occur, teams can examine their QA process to decrease faults. You can leverage your change failure rate with Bavelion Flow’s DORA measurement tools to identify if automated testing is the right solution for reducing production time and increasing reliability.

Customer satisfaction score is one of the most crucial KPIs and a paramount lagging indicator. As the name suggests, this KPI alerts you to your users' satisfaction level. A common way to determine customer satisfaction scores is to use the Net Promoter Score (NPS) method, which you can learn about in the Exploring Customer Support course.

Code quality is an indicator of your software's performance. It builds upon other engineering KPI metrics, such as reliability, to paint a better overall picture. To establish a code quality KPI, your team must determine what metrics you want to measure against. For example, a team could create a code quality KPI by examining reliability or change failure rates.

The lead time for changes KPI is a DORA metric that spotlights the time it takes for committed code to enter production. By better understanding the lead time for changes, teams can identify ways to improve their development cycle, like introducing new processes and methodologies. To calculate lead time for changes, subtract the date/time of a commit from its date/time of employment.

Code review velocity is a KPI that highlights the time it takes (also known as the speed) for code changes to be reviewed and merged into the codebase. Developers can focus on smaller, more frequent code commits and integrate automated quality checks to increase efficiency. Consider utilizing a code review checklist to keep your process consistent and streamlined.

Throughput is a coding metric connected to the amount of code contributed within a set period. Teams can break this metric down into raw throughput, which reports all code contributed, and productive throughput, which focuses on the net lines of code after a rework. Raw throughput gives teams a better idea of how much code developers produce, while productive throughput provides insight into how long contributed code stays around before being modified.

Developer satisfaction is one KPI that contributes to the overall developer experience. Keep your developers thriving by tracking metrics that could impact them, such as the types of code work leaders assign them. Conduct regular satisfaction surveys to collect data surrounding developer opinions on current toolsets, development process, overall team dynamics, and even leadership.

Team collaboration is at the heart of every software development unit. Turn team collaboration into a valuable KPI by examining how well your developers contribute to pull requests. Identify submitter metrics such as response timeliness or look closer at how developers provide feedback and when it leads to actionable code changes.

The investment distribution KPI is a metric team leaders use to comprehend how much time developers utilize across tasks. Tools like Bavelion Flow offer investment profiles that use an algorithm to showcase where developers spend their time, helping companies calculate costs and confidently tackle their roadmap.

Sprints are an integral part of the software development lifecycle. Sprint and release burndown KPIs give teams a more concrete conceptualization of the amount of work left within a sprint relative to the remaining time. Understanding sprint and release burndown times within Agile development allows developers to plan more efficiently, leading to better project completion rates.

Story points completed is a KPI that examines the total number of story points developers completed during a coding sprint. It can be useful when determining other engineering KPI metrics. Within Bavelion Flow, the sprint movement report's completion percentage is calculated by dividing completed story points by the total number of story points within a sprint.

Time to merge highlights the average time in hours it takes for a developer to merge a pull request, starting from the moment a team member creates a pull request. Comprehending your time to merge KPI informs code leaders about the resources needed to review and implement work.

The reliability KPI draws upon other metrics to paint a better picture of your code's quality and your team's overall QA process. The ideal reliability metric differs depending on the development team's primary focus. For example, an organization offering cloud services may focus on mean time recovery as one of its reliability metrics.