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The software development process is frequently inadequately measured compared to other critical business functions like sales or customer service.
Many in the tech industry have long believed that accurate measurement is impossible and that only experienced engineers can adequately evaluate their colleagues’ performance. However, this perspective has fallen short.
As companies increasingly evolve into data-driven enterprises, irrespective of their sector, leaders need to ensure they are utilising their top talent as effectively as possible.
Measuring developer productivity is undeniably challenging. While other functions can often be assessed with a single metric, the connection between inputs and outputs in software development is much less clear.
Software development is an inherently collaborative, complex, and creative process that requires varied metrics for different levels—such as systems, teams, and individuals.
Even with a genuine intent to track productivity accurately, traditional metrics often require implementing systems and software capable of more detailed and comprehensive measurement.
In some cases, adjusting existing tech stacks and development pipelines is needed to facilitate proper tracking, and setting up the right tools for valuable insights can demand substantial, long-term investment.
What is the productivity of the software engineering team?
Whenever we think of “developer productivity,” a specific image likely comes to mind, and you might have encountered various definitions online.
As a rule, developer productivity is defined as the extent to which a developer or software engineering team effectively manages software development tasks within a set timeframe.
This covers everything from building and deploying to maintaining software.
Enhancing developer productivity is a must, as it leads to faster and more efficient tasks completed throughout the software development lifecycle.
How are businesses measuring developer productivity?
DORA and SPACE are the most common metric frameworks to measure developer productivity.
DORA in the software development process
Named after Google’s DevOps Research and Assessment (DORA) team, the DORA standards now focus on measuring outcomes.
This team identified four key metrics for DevOps, aiming to enhance developer efficiency and provide business leaders with meaningful results.
These metrics fall into two categories: velocity and stability. Both categories are crucial for balancing the emphasis between speed and quality in development.
- Deployment frequency: Measures how often the team successfully releases code changes to production, reflecting velocity.
- Lead time for changes: Tracks the duration from when a commit is made to when it reaches production, also indicating velocity.
- Change failure rate: The percentage of deployments that result in a failure in production, which assesses stability.
- Time to restore service: The amount of time required to recover from a production failure, evaluating stability.
Dedicated software development teams can be categorised into elite, high, medium, and low-performing groups as per DORA to foster improvements.
Google’s internal data reveals that elite teams are twice as likely to achieve or surpass their organisational performance targets compared to teams in other categories.
SPACE
Another set of metrics, known as SPACE, complements the DORA framework.
Developed collaboratively by GitHub and Microsoft, these metrics address the DORA framework’s perceived shortfall in measuring the often challenging-to-quantify aspect of developer satisfaction.
- Satisfaction and well-being: Surveys gauge developers’ perspectives on key aspects of productivity, including their likelihood to recommend their team, whether they have adequate tools and their risk of burnout.
- Performance: This is best measured by outcomes rather than outputs or impacts, e.g., a developer might produce code, but its quality is key. Similarly, code quality alone may not influence customer behaviour. Often, performance is evaluated with a simple question: Does the code fulfill its intended purpose?
- Activity: Productivity can be inferred from counting outputs such as builds, tests, or issue resolutions. However, high activity levels alone don’t necessarily equate to high productivity.
- Communication and collaboration: This challenging-to-measure attribute can be evaluated through proxies, such as the speed of code integration, the quality of work reviews from team members, and the time taken to onboard new team members.
- Efficiency and flow: Flow, a state where developers work without interruptions, is crucial. This can be measured by tracking the number of process handoffs, surveying developers about their ability to maintain flow, counting interruptions, and similar metrics.
Other developer productivity metrics
Organisations use various important metric systems, either as part of DORA, SPACE, or independently, to assess developer productivity:
- Cycle Time: Measures the duration from the initial commit to the production release or from the start to the completion of a task. Shorter cycle times are generally preferred, but they should not come at the expense of quality.
- PR Size: Pull requests are initiated when a developer is ready to merge new code changes into the project repository. This process allows for the addition of new features or bug fixes without disrupting users or risking damage to the service or application.
- Investment profile: This metric helps software engineering teams visualise their resource and time allocation. It also helps management distribute work more effectively according to business priorities.
- Planning accuracy: It measures the ratio of completed story points versus the total planned for an iteration. It serves as a useful metric for improving sprint planning.
What software development metrics to measure: Team or individual developer productivity?
Typically, experienced CTOs avoid measuring individual productivity directly. Instead, industry experts and developers generally agree that a thriving software product development team is defined by delivering valuable products and services rather than focusing on the performance of individuals working in isolation.
Developers frequently collaborate and interact in ways that are difficult to quantify due to the process’s twists and turns.
For example, some team members may not generate a large volume of code but still provide immense value through their support, advice, and expertise.
In contrast, team productivity is more easily observed. Managers or HR professionals assessing individual performance for annual reviews or other evaluations should focus on establishing strong organizational practices for people management.
This includes holding regular one-on-one meetings, gathering anonymous feedback from all team members, and promoting personal accountability among individuals.
Much of this is influenced by the team’s culture rather than any systematic method for tracking productivity.
Does a one-size-fits-all approach work?
Each organization measures developer productivity differently. Therefore, it’s important to align your engineering metrics with your specific business priorities and customer needs.
It is clear without saying that a tech giant would assess its developers differently compared to a Series A startup, as their stages of growth and business objectives would vary significantly.
Google, for example, employs the goals/signals/metrics (GSM) system to monitor productivity by setting specific goals for products and features. This approach requires the engineering lead to establish the goal, associate a signal with it, and support it with quantifiable metrics.
Additionally, Google assigns a team of engineering productivity specialists to work alongside the core engineering team, a strategy that has proven highly effective. In contrast, smaller companies may have different levels of resources.
The final words
Assessing agile teams productivity is not a simple task. To accurately measure and enhance it, you must first establish your business priorities and rely on the right metrics that go beyond just counting lines of code.
To thoroughly understand your software engineering team’s performance, integrate these quality metrics—such as DORA, value stream, and flow metrics—with a well-defined framework and a developer productivity dashboard.
How we can help you?
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