Delivery Performance
8 minutes reading time
For this dimension, you can monitor the number of deployments that fail or require fixes after going live. This can be done using tools like CI/CD platforms (e.g., Jenkins, CircleCI, or GitHub Actions), which flag failed deployments and provide reports on remediation efforts.
A high change failure rate usually signals inefficiencies or gaps in the development and deployment processes. This could be due to insufficient code review practices, a lack of automated testing, or issues in the DevOps pipeline.
Productivity is the backbone of software development, directly influencing a team’s ability to deliver high-quality products on time. As development processes become more complex, measuring productivity effectively becomes crucial.
SPACE metrics offer a more extensive approach to understanding developer productivity across multiple dimensions.
Wondering how to use these indicators effectively? You’re in the right place! This guide will walk you through the key SPACE metrics, explain how to measure them and highlight which metrics to prioritize and avoid.
Let’s begin.
What Are SPACE Metrics?
SPACE metrics offer a comprehensive framework to assess productivity and well-being in software engineering. They cover five key dimensions:
- Satisfaction: Measures how content and motivated developers are. It considers aspects like job satisfaction, mental health, and the impact of frequent or minimal interruptions on overall happiness.
- Performance: Evaluates outcomes such as the failure rate of deployments, resolution time, and other tangible results that demonstrate your team performance and product quality.
- Activity: Tracks operational behaviors, including developer activity, such as code commits or tasks completed over a defined period of time.
- Collaboration and communication: This section examines how effectively the software development team collaborates using collaboration tools. Strong collaboration quality supports the software development life cycle.
Efficiency and flow: This measures how smoothly tasks progress. Metrics like cycle time, maker time (i.e., lack of interruptions in Axify), and infrastructure readiness help identify roadblocks to maintaining focus and achieving high-quality code output.
Why Measure SPACE Metrics?
The SPACE framework, developed by researchers from GitHub and Microsoft Research, emerged to address misconceptions about developer productivity. It recognizes that developer productivity is multidimensional and cannot be understood through a single metric.
Some of the myths that this framework debunked are:
- Productivity is just about activity: Metrics like commits or pull requests may reflect activity, but they don’t capture the actual value of performance. These numbers fail to measure team collaboration, creativity, problem-solving, and code quality.
- Productivity is about individual performance : Focusing solely on individual metrics ignores the team productivity that is crucial for effective software development. Traditional metrics overlook collaboration quality and team dynamics, but they are key to delivering successful projects.
- One metric tells the whole story: The idea that a single metric can represent productivity is fundamentally flawed. Productivity is multidimensional, with several contributing factors, such as developer satisfaction, code quality, and developer activity.
- Metrics are only for managers: Productivity metrics aren’t just for managers; they can also empower developers to improve their workflows and time management. When implemented well, these parameters provide actionable insights that help developers identify bottlenecks and optimize their productivity.
- Only engineering systems matter: Traditional metrics prioritize outputs and performance indicators tied to engineering tools and systems. They typically overlook the cultural factors and work environment that are just as crucial to a team’s success.
The bottom line is that SPACE metrics offer a balanced and multidimensional view of developer productivity. Through them, you can pinpoint bottlenecks, enhance team morale, and optimize software development processes. Moreover, they also prevent burnout to ensure that your team remains engaged and productive over the long term.
Here’s a high-level view of the SPACE metrics at individual, team, and system levels.
How to Use SPACE Metrics
To use the SPACE metrics, you need at least three metrics from three dimensions to be objective. The below guide explores a correct example of using SPACE metrics to get the most out of them. Notice that we’ve picked one metric from three dimensions to respect the framework’s principle.
1. Satisfaction and Well-Being → Developer Satisfaction
To track developer satisfaction, you can use regular surveys or pulse checks by focusing on aspects like work-life balance, stress levels, job fulfillment, and developer experience (DevEx).
If satisfaction scores are low, investigate the reasons, such as workload imbalance, lack of recognition, or unclear expectations. Address these issues to improve morale, which will ultimately boost team productivity.
Alternatively, use Axify’s Wellbeing Tracker which also measures developer satisfaction.
2. Performance → Change Failure Rate
For this dimension, you can monitor the number of deployments that fail or require fixes after going live. This can be done using tools like CI/CD platforms (e.g., Jenkins, CircleCI, or GitHub Actions), which flag failed deployments and provide reports on remediation efforts.
A high change failure rate usually signals inefficiencies or gaps in the development and deployment processes. This could be due to insufficient code review practices, a lack of automated testing, or issues in the DevOps pipeline.
To reduce the failure rate, focus on:
- Enhancing code quality through a comprehensive checklist
- Ensure unit tests, integration tests, and end-to-end tests
- Streamline your deployment pipeline to reduce the likelihood of defects
3. Efficiency & Flow → Cycle Time
Axify lets you track cycle time, which is the time taken from task initiation (e.g., the first commit) to task completion (e.g., deployment). The key is to measure this metric at each stage (e.g., development, code review, QA) to identify issues and improve efficiency.
If cycle time is high, you may have problems in the workflow. Reasons range from excessive waiting times to slow testing cycles. The point is to identify issues and solve them. Reducing these delays by streamlining the development pipeline improves agility and enhances team performance.
Interpreting SPACE Metrics Together
Developer satisfaction, change failure rate, and cycle time are interconnected.
- If developer satisfaction scores are low, you might notice an increase in the change failure rate due to disengaged or overworked team members. This could lead to longer cycle times, as demotivated developers may struggle to complete tasks efficiently.
- Conversely, improving developer satisfaction by addressing workload balance or recognizing contributions can lead to better collaboration and focus, which may reduce the change failure rate and shorten cycle times.
To maximize the SPACE framework's potential, you need to identify relationships between metrics and look for patterns across dimensions. For instance, if one metric shows a decline, check whether the other metrics you’ve picked also dropped. Metrics don’t exist in isolation.
You can also use retrospectives and other feedback mechanisms to connect qualitative insights (like satisfaction surveys) with quantitative data (like cycle time). This helps teams address bottlenecks while fostering a healthy work environment.
SPACE Metrics We Recommend
According to experts at Axify, you must track the following SPACE metrics for optimized results:
1. Team Morale
Team morale reflects your development team's overall well-being, motivation, and psychological safety. A strong sense of morale supports effective collaboration, individual performance, and long-term team productivity.
2. Deployment Frequency
This metric tracks how frequently new code is pushed to production. A high deployment frequency shows your team’s ability to consistently deliver updates, features, and bug fixes. It also signals agility and responsiveness within the software development life cycle.
In addition, regular deployments improve product quality while keeping customer satisfaction high, as teams can address feedback promptly and deliver new functionality without delays.
3. Lead Time For Changes
Lead time for changes measures how quickly a change transitions from the initial commit to being live in production. It indicates the efficiency of your team’s workflows and processes, which tells about their productivity levels.
Shorter lead times for changes highlight optimized operations, minimal interruptions, and the ability to resolve issues effectively.
4. Change Failure Rate
The change failure rate represents the percentage of deployments that lead to production failures. This metric offers a clear picture of the code quality and the reliability of deployment processes. A lower failure rate signifies strong quality control practices, such as effective code reviews and robust testing.
5. Cycle Time
Cycle time captures how long it takes to complete a specific task in the development process, from initiation to completion. It identifies workflow inefficiencies, such as delays during code reviews or quality assurance processes.
Axify includes idle periods in its cycle time metric to provide a precise view of total task duration. This insight allows teams to improve active work time and avoid bottlenecks that slow down software development projects.
Our case studies prove this.
The Development Bank of Canada used Axify’s tools to improve its cycle time remarkably. They reduced time spent in the pre-development phase by 74% and cut quality control time by 81%. As a result, their product delivery speed increased by 51%.
6. Failed Deployment Recovery Time
Previously referred to as MTTR, failed deployment recovery time calculates how quickly your team restores service after a failure. It highlights their ability to respond to and recover from issues in production, which indicates system reliability.
A faster recovery time reduces the impact of failures on developer productivity, system stability, and software delivery performance. Furthermore, this metric is closely tied to the change failure rate and provides a comprehensive view of deployment efficiency and operational resilience.
SPACE Metrics We Don’t Recommend
While some traditional metrics are commonly used to measure developer productivity, they may not always provide valuable insights or could lead teams to focus on quantity rather than quality. Let’s have a look at them:
1. Lines of Code (LOC)
Lines of code is an outdated metric that doesn't necessarily correlate with software quality or developer productivity. In fact, longer codebases can result in more bugs, harder-to-maintain code, and increased complexity, which leads to longer development cycles and increased technical debt.
Prioritizing this metric could encourage your team to focus on writing more code than high-quality code. This can reduce code stability and increase the overall difficulty of future optimizations.
2. Story Points Completed
Tracking the number of story points completed may seem helpful in measuring development velocity, but this can encourage a focus on quantity over quality.
As a result, your team may prioritize volume and complete tasks that don’t necessarily contribute to the overall performance.
Conclusion: Use Axify to Implement SPACE Metrics in Your Company
SPACE metrics offer a comprehensive view of software engineering productivity. However, they can be challenging to implement as manually compiling and analyzing data from various sources like developer activity, collaboration levels, and cycle time can be time-consuming.
That’s where Axify comes in with an intuitive dashboard that tracks all the related metrics to provide a holistic view of team performance. The image below shows you precisely the KPIs we track:
In addition, the platform offers additional benefits that can streamline your entire workflow. These include:
- Different view options: The Axify dashboard has a team view, group of teams view, and organization view. Our view options give managers, cross-team leaders, and executives tailored insights. Use this data to align efforts with business objectives at every level.
- Value Stream Mapping (VSM): It visualizes the entire software development lifecycle to highlight inefficiencies, streamline workflows, and accelerate delivery.
- Probabilistic forecasting tools: These tools leverage historical data to predict future software delivery outcomes, which helps teams make data-driven decisions and optimize release timelines.
Ready to transform your team’s productivity? Book a demo with Axify now!