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How to Measure Engineering Performance Uniformly Across Teams

Madison Unell

By: Madison Unell
February 29, 2024

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Engineering teams are more distributed than ever. Nearly 70% of active engineering positions are open to remote applicants, and many companies have a mix of remote, hybrid, in-person, and contracted employees. So, how do engineering leaders measure performance uniformly across all of these teams? By creating a framework for understanding performance, asking the right questions, and using data to answer them.

Creating a Performance Framework

Engineering leaders want to mitigate surprises before they impact software delivery or the business. It’s not enough to make decisions based on gut feel or anecdotal performance reviews — especially when an engineering organization is made up of multiple teams with unique working styles and deliverables. To truly understand performance across teams, leaders must establish which metrics are important to their company and create a framework to measure them. Establishing a performance framework ensures that leaders are measuring engineering teams in a consistent and equitable way so they can identify and resolve bottlenecks faster to optimize the flow of work.

Tailoring a Framework for Your Team

Using a common framework like DORA is a great starting point, but leaders must tailor measurement to the needs of their unique team. Traditional engineering metrics, and even frameworks like DORA, can overrotate on the quantity of code that’s produced and underrotate on the quality of that code, how efficiently it was written, or how effectively it solves a specific problem. Solely measuring quantity can result in bloated, buggy code because engineers may prioritize simple features they can get out the door quickly rather than spending time on more complex features that can move the needle for the business.

Adding metrics and context that apply to your specific team can provide a more accurate look at engineering performance. For example, to understand team productivity, leaders may look at engineering metrics like Mean Lead Time for Change (MLTC) alongside Cycle Time. If MLTC is high, it could indicate that Cycle Time is also high. These metrics can be viewed in tandem with other metrics like Time to Open, Time to Merge, and Time to First Review to understand where changes need to be made. These metrics can then be compared across teams to understand which teams are performing well and establish best practices across the organization.

Monthly Engineering Metrics to Understand Team Performance

Data-driven insights can provide engineering leaders with objective ways to evaluate developer competency, assess individual progress, and spot opportunities for improvement. While quarterly KPIs and annual performance reviews are great goalposts, managers are constantly thinking about how their teams are progressing toward those targets. Reviewing engineering metrics on a monthly basis is a good way to assess month-over-month progress and performance fluctuations on an individual level and a team level. Which metrics a team considers depends on its defined framework and overall company goals. Here are a few to consider:

PRs Merged vs. PRs Reviewed

Looking at these metrics together can show how the two key responsibilities of writing and reviewing code are spread across a team.

Review Coverage vs. Review Influence

This helps leaders understand what amount of thoroughness of Code Reviews results in a desired action.

Review Cycles vs. Cycle Time

To understand the effect that back-and-forth cycles in Code Review have on shipping speed, leaders can look at Review Cycles vs. Cycle Time.

Impact vs. Rework

Comparing Impact and Rework will show which teams are making the most significant changes to the codebase and how efficiently they are doing so.

Communicating Engineering Team Performance

Understanding and communicating engineering team performance is an effective way to ensure teams are aligned and that all requirements are understood and met. Making this a standard across the engineering organization — especially in a distributed or hybrid environment — is essential to its success. How leaders communicate their findings is equally important as gathering the information. When feedback is a fundamental part of a blameless team culture, team members understand that feedback is critical to growing as a team and achieving key goals, and will likely feel more secure in sharing ideas, acknowledging weaknesses, and asking for help. Leaders can tailor the questions listed above to meet the unique needs of their organizations and use engineering metrics as a way to understand, communicate, and improve team performance.

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