Engineering productivity is notoriously difficult to measure. Classic metrics tend to focus exclusively on outputs, but this approach is flawed — in software engineering, quantity of output isn’t necessarily the most productive goal. Quality is an important complement to quantity, and a team that’s measuring success in lines of code written may sacrifice conciseness for volume. This can lead to bloated, buggy code. A team focused on the number of features shipped may prioritize simple features that they can get out the door quickly, rather than spending time on more complex features that can move the needle for the business. The SPACE Framework aims to address this by replacing output-focused measurements with a more nuanced approach to understanding and optimizing developer productivity.
This research-based framework offers five key dimensions that, viewed in concert, offer a more comprehensive view of a team’s status. These dimensions guide leaders toward measuring and improving factors that impact outputs, rather than focusing solely on the outputs themselves.
Importantly, SPACE foregrounds the developer. It recognizes that leaders must empower their team members with the ability to take ownership of their work, grow their skills, and get things done while contributing to the success of the team as a whole.
What is the SPACE Framework?
The SPACE Framework is a systematic approach to measuring, understanding, and optimizing engineering productivity. Outlined by researchers from Github, Microsoft, and the University of Victoria, it encourages leaders to look at productivity holistically, placing metrics in conversation with each other and linking them to team goals. It breaks engineering productivity into five dimensions, Satisfaction and Well-being; Performance; Activity; Communication and Collaboration; and Efficiency and Flow.
Satisfaction and Well-being – Most often measured by employee surveys, this dimension asks whether team members are fulfilled, happy, and practicing healthy work habits. Satisfaction and well-being are strongly correlated with productivity, and they may even be important leading indicators; unhappy teams that are highly productive are likely headed toward burnout if nothing is done to improve their well-being.
Of all five SPACE dimensions, satisfaction and well-being is the hardest to quantify. Objective metrics can’t directly measure developer happiness, but they can point to circumstances that are likely to cause dissatisfaction or burnout. By viewing quantitative metrics in tandem with qualitative information and survey data, engineering leaders can better assess team satisfaction.
In Code Climate Velocity, leaders can view engineering metrics like Coding Balance to get a sense of developer workload. Coding Balance displays the percentage of contributors responsible for 80% of your team’s most impactful work. If work is not evenly distributed, overloaded team members may be overwhelmed, while those doing less impactful work may not be challenged enough.
Another informative measure, Work in Progress PRs, offers a count of Pull Requests with activity over a 72-hour period. A high Work in Progress number could mean that developers are forced to context switch often, which can prevent developers from entering a state of flow. The ideal number of Work in Progress PRs is usually 1-2 PRs per developer.
To get a better understanding of overall satisfaction, engineering leaders should look at both short term changes and overall trends. For example, when an engineering manager at Code Climate noticed a spike in volume of PRs and reviews in a short amount of time, she took it as a sign to further investigate the workload of each developer. When she discovered that engineers were working overtime and on weekends in order to ship new features, she successfully advocated for extra time off to recharge and avoid potential burnout.
Performance – The originators of the SPACE Framework recommend assessing performance based on the outcome of a developer’s work. This could be a measure of code quality, or of the impact their work has on the product’s success.
Metrics that help evaluate performance include Defect Rate and Change Failure Rate. Change Failure Rate is a key performance metric, as it measures the percentage of deployments causing a failure in production, helping engineering leaders understand the quality of the code developed and shipped to customers. Every failure in production takes away time from developing new features and ultimately has a negative impact on customers.
When assessing team performance, PR Throughput is an important counterpoint to quality metrics. This metric counts PRs merged (a bug fix, new feature, or improvement) over time, and is correlated to output and progress. To get a full picture of performance, PR Throughput should be viewed alongside quality metrics; you’ll want to ensure that your team is delivering at volume while maintaining quality.
Activity – This dimension is most reminiscent of older measures of productivity as it refers to developer outputs like on-call participation, pull requests opened, volume of code reviewed, or documents written. Still, the framework reminds leaders that activity should not be viewed in isolation, and it should always be placed in context with qualitative information and other metrics.
Useful Activity metrics to look at within Velocity include coding metrics, such as Commits Per Day, the average number of times Active Contributors commit code per coding day, and Pushes Per Day, the average number of times Active Contributors are pushing per day.
These metrics offer an overview of developer activity so you can gauge whether or not work is balanced, if workload matches expectations, and whether delivery capacity is in line with strategic goals.
It can also be helpful to look at Deployment Frequency, which measures how often teams deliver new features or bug fixes to production.
Communication and Collaboration – The most effective teams have a high degree of transparency and communication. This helps ensure developers are aligned on priorities, understand how their work fits into broader initiatives, and can learn from each other. Proxies for measuring communication and collaboration might include review coverage or documentation quality.
Velocity supports Pair Programming, which encourages collaboration. Credit can be attributed to two developers who write code in a pairing session.
Metrics like Review Speed, Time to first Review, and Review Coverage, can help you assess the health of your collaborative code review process. These metrics can help identify whether your team is keeping collaboration top of mind, has enough time to review PRs, and is giving thoughtful feedback in comments.
Efficiency and Flow – In the SPACE framework, flow refers to a state of individual efficiency where work can be completed quickly, with limited interruption. Efficiency is similar, but it occurs at the team level. Both are important for minimizing developer frustration. (Though it’s worth noting that when an organization has too much efficiency and flow, it’s not always a good thing, as it may be at the expense of collaboration or review.) Perceived efficiency and flow can be important information gathered via survey, while speed metrics can capture a more objective measurement.
In Velocity, Cycle Time is an important metric to view within the context of efficiency and flow, as well as Mean Lead Time for Changes. Cycle Time, aka your speedometer, is representative of your team’s time to market. A low Cycle Time often means a higher output of new features and bug fixes being delivered to your customers. Cycle Time is an objective way to evaluate how process changes are affecting your team’s output. Often, a high output with quality code can speak to a team’s stability.
Mean Lead Time for Changes, which refers to DevOps speed, measures how quickly a change in code makes it through to production successfully. This can be correlated to team health and ability to react quickly. Like Cycle Time, it can indicate whether your team’s culture and processes are effective in handling a large volume of requests.
How can you implement the SPACE Framework?
The framework’s authors caution that looking at all five dimensions at once is likely to be counterproductive. They recommend choosing three areas that align with team priorities and company goals. What a team chooses to measure will send a strong signal about what the team values, and it’s important to be deliberate about that decision. They also remind leaders to be mindful of invisible work and to check for biases in their evaluations.
At Code Climate, we’ve spent years helping software engineering leaders leverage engineering data to boost their teams’ productivity, efficiency, and alignment. With that experience in mind, we have a few additional recommendations:
- Be transparent. When introducing data in your organization or using data in a new way, it’s important to be open. Make sure your team members know what data you’re looking at, how you plan to use it, and what value you hope to gain from it.
- Place all metrics in context. Quantitative data can only tell you so much. It’s critical to supplement metrics with qualitative information, or you’ll miss key insights. For example, if you’re measuring activity metrics and see a decrease in pull requests opened, it’s important to talk to your team members about why that’s happening. You may find out that they’ve been spending more time in meetings, so they can’t find time to code. Or you may learn that they’re coding less because they’re working to make sense of the technical direction. Both these situations may impact activity, but will need to be addressed in very different ways.
- Work data into your existing processes. The most effective way to build a new habit is to layer it onto an existing one. If you’re already holding regular 1:1s, standups, and retros, you can use them as an opportunity to present data to your team, assess progress toward goals, and discuss opportunities for improvement. By bringing data to your meetings, you can help keep conversations on track and grounded in facts.
Why does the SPACE Framework matter?
The SPACE Framework helps engineering leaders think holistically about developer productivity. The five dimensions serve as critical reminders that developer productivity is about more than the work of one individual, but about the way a team comes together to achieve a goal. And perhaps somewhat counterintuitively, understanding productivity is about more than simply measuring outputs. In looking at multiple dimensions, teams can gain a fuller understanding of the factors influencing their productivity, and set themselves up for sustainable, long-term success.
If you’re looking to implement the SPACE Framework, Velocity can help you gather critical engineering data. Reach out to speak to one of our data specialists to find out how.
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