In this time of global and economic uncertainty, it’s never been more important to have a quick way of knowing which engineering processes are working and which are broken.
And while it can be tempting to focus on bottlenecks and struggling team members, it can be even more useful to look at the practices, behaviors, and culture of your strongest teams.
This post runs through a framework for using Velocity, our Engineering Management Platform, to identify and scale the most successful habits of high performing teams.
Finding the Top 5% of Your Organization
While all engineering organizations might define success slightly differently, there are two metrics within Velocity that indicate an extremely proficient engineering team:
- Throughput, measured in deploys or PRs merged, which indicates how much your developers are getting done.
- Cycle Time, measured in hours from first commit to when a PR is merged to production, which indicates how fast your developers are getting that work done.
In Velocity’s Compare report, you can select both of these metrics and compare them across your organization to identify the teams that are merging the most the fastest.
Once you’ve identified your strongest teams using success metrics like Throughput and Cycle Time, you’ll want to dig into what has made them successful. For this, you’ll need different, diagnostic metrics.
Identifying the Best Practices of Your Strongest Engineering Team
You can think of your software delivery process in three phases:
- Time to Open, or how long does development take.
- Review Speed, or how long does work sit before getting picked up for review.
- Time to Merge, or how long does the entire code review process take.
Typically, a strong engineering team will move faster in one of these stages.
Velocity makes it easy to look at these three metrics side-by-side. You can view them as bar graph clusters by week or by month.
Or, you can view these metrics by team.
Here, we can see that the top team — Gryffindor — is most distinguished by their extremely fast Review Speed. Although they have a long Time to Open and Time to Merge, this isn’t remarkable when looking at the other teams. The other teams (especially the Hogwarts team) frequently had work stuck in the review process.
Pair your quantitative analysis with qualitative information, and speak to the members of the Gryffindor team. Find out what makes their review process different from the other teams’ processes, and think about ways the other teams can apply those learnings.
DORA metrics are also useful to identify high performing teams within the organization.
Creating a Blueprint For Your Entire Organization
Now that you’ve identified your top-performing teams and their defining characteristics, you can create a blueprint for better processes across your organization.
One of our customers, a health data analytics solution, used Velocity following a Series B funding round to level-up the way they coached engineers at scale.
Their VP of Engineering had been brought on to help build out the engineering department. But after getting to know his teams, he realized that there wasn’t any consistency in how and when teams shipped features to end-customers.
The VP of Engineering worked with his engineering leads and product managers to identify agile practices that worked for his team, then shared them org-wide. Together, they created documentation and set up onboarding and mentoring around encouraging healthy coding habits at scale.
With stronger processes in place, the team was able to increase PR throughput 64%. With objective data and learnings from your highest performing teams, you’ll be able to replicate successful practices across your organization, and help boost productivity at scale.
Subscribe to our newsletter for more engineering intelligence.