Engineering success metrics (e.g., lead time, code review, time to merge, and time to deploy) serve as a guide for engineers, indicating what they should improve on. That is why an engineering success metrics program is essential in every engineering team. It provides a standard measure of key performance indicators (KPIs) to track your company’s progress and success over time.
In this post, Charity Majors, the founder and CTO of Honeycomb.io; Dana Lawson, Vice President of Engineering at GitHub; and Kathryn Koehler, Director of Productivity Engineering at Netflix, share valuable advice on how to build a continuous improvement culture in engineering teams. They also discuss ways to create an engineering success metrics program.
The SPACE methodology: A reliable method to predict developer productivity
The SPACE framework, an engineering success metrics program, is causing a stir in the industry. This framework, created by engineering managers and researchers Nicole Forsgren, Margaret-Anne Storey, Chandra Maddila, Thomas Zimmermann, Brian Houck, and Jenna Butler, defines, measures, and predicts developers’ activities to build safer and faster software and applications.
In SPACE, S stands for satisfaction and well-being, P for performance, A for activity, C for communication and collaboration, and finally E for efficiency and flow.
The SPACE framework allows managers and supervisors to understand better their team members and how they’re performing. While this methodology is still in its infancy, Netflix, GitHub, and other companies have already adopted it in their software development teams.
“There is no unicorn metric for anyone when it comes to adopting a metric system,” said Netflix’s Koehler. “People who are productive at the college level regularly measure their activity, lines of code, early release, deployment today. That’s what productivity entails, and that’s what you can understand. But, on the other hand, the SPACE technique is centered on well-being and enjoyment,” she further added.
The DevOps Research & Assessment model: The precursor to SPACE framework
The DevOps Research & Assessment (DORA) model, which came before the SPACE framework, allows you to assess your software delivery performance and compare it to the competition. The DORA team defined four essential performance measures when creating the model: deployment frequency, mean lead time for changes, change failure rate, and time to recovery.
The most important thing to understand about any success metrics program is that each data point and measure will be unique to your company.
“The DORA metrics are a good place to start understanding your organization,” said Lawson of GitHub. “However, with any analytics, only looking at activity is a big mistake. If you are going to read these in a vacuum, it surely is not a good idea. It won’t provide you with a complete picture of what’s going on. There are numerous variables, each of which is unique to the team that is working,” she added.
Should DORA have a fifth performance measure, and if so, what would it be?
The answer is yes! The fifth metric of the framework focuses on reducing your developers’ stress levels and preserving their out-of-office hours.
Use data & metrics to avoid burnout.
Engineering success metrics programs like SPACE and DORA provide a baseline understanding of how your company operates. They also highlight areas that need improvement. In addition to this, they provide a starting point for goals and objectives for your development teams.
Pulling developers back to work during their off-hours can lead to burnout over time. And so, you can also use these success metrics to ensure that your developers are not overworked. After all, you should never overlook mental health. Thus, success metrics and data are critical to determining how much time is spent on each activity and lining up priorities.
When you successfully deploy a success metrics program, you don’t assess individuals based only on the success metrics. Instead, you just make sure that your team is aware of the success metrics implemented in the organization.
Is data at the core of everything?
Data enables engineers to focus on the activities that matter while simultaneously guiding them towards the right success metrics. In other words, data allows management to track performance and growth throughout the business.
And thus, organizations must constantly assess their data to take the right actions. Consider corporate processes, interactions, and transactions as information flows to move data transformation ahead. Engineering teams can unlock large volumes of historical, financial, operational, and transactional data with the right success metrics and enable continuous improvement.
Conclusion: Success metrics can help optimize team performance
An effective engineering success metrics program considers your engineers’ workload, the mean time between interruptions, and other essential factors.
Here’s a rundown of a few more tips to help you get the most value out of your engineering success metrics program:
Review metrics frequently. Every meeting should begin with a review of metrics. This process ensures everyone is on the same page and understands what’s working and what needs improvement.
Start small. To begin, you only need one to three metrics. Then, you can add metrics over time if you’re intentional about tracking simple data, trying alternative ways, and seeing how those metrics evolve.
Look beyond execution metrics. When you combine engineering and business KPIs, you can better understand why you’re building what you’re building every day.
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Engineering Success Metrics for Continuous Improvement
Description
In this post, execs from Netflix, GitHub, and Honeycomb.io share critical insights into success metrics for continuous improvement for engineering teams.
Ankit is a writer and editor who has contributed his expertise to Govt of India, Reebok, Abbott, TimesPro, Chitale Bandhu, InsideAIML, Kolte Patil Dev., etc.
