In software development, it is difficult to comprehensively understand the effort of every individual contributor. This is especially true for distributed teams made up of people who are working remotely from all corners of the world. Good managers should be equipped to keep track of their teammates’ productivity and help them sustain their focus.
Software development teams working on a project typically use git to coordinate their efforts. Each member of the team is assigned a task and must commit the code to the remote repository. This way, their productivity is easy to measure. Managers only have to look at the frequency and quality of their contributions.
Doing this manually can be a lot of work. Instead, modern companies prefer to use git analytics. These tools provide data about the input of every employee. A good leader can use this data and tailor communication and feedback meetings to maximize the value of every software developer under her supervision.
What is git analytics?
Overseeing the quality and the volume of the code is typically the job of the manager. However, manually checking every software developers’ contributions can be exhausting. That’s why most managers use git repo analytics, which can track engineering team productivity and the quality of the output.
To measure performance, git analytics tools examine committed code. The data from these tools can answer two simple questions: does the specific software developer write good quality code and how much time does it take for her to do so. Github analytics can paint a no-nonsense picture of software developers’ productivity and their output. A good git analytics tool will put employee productivity into numbers.
Git analytics can paint a good picture of the programmers’ work habits and potentially any bottlenecks in the software development process. Managers can use pull request insights to raise the productivity of the entire team. First and foremost, it allows them to provide more constructive feedback. Second, these analytic tools can highlight potential areas for growth.
Managers’ primary responsibility is to communicate with their employees. Gitlab analytics can summarize the data so it becomes easy to digest and communicate with others.
The benefits of using git analytics
Managers play an important role in raising the effectiveness of the software development team. It’s their responsibility to track developer productivity and provide useful actionable feedback. Fortunately, they don’t have to manually track the productivity of those under them. Git analytics tools can do this job and summarize the results with nice visuals that are easy to understand.
These tools benefit software developers as well. It allows them to focus on writing code, instead of writing reports about their progress towards the goal. Meanwhile, their work is automatically tracked by git analytics.
Thanks to data visualization, managers can better understand the problem at hand and communicate it with their subordinates. Equipped with practical, tangible data, they can get their point across more easily. Software developers, on the other hand, are more likely to positively respond if the feedback is backed up by actual data. Git analytic tools can help managers find the proofs without spending too much time. They can use this information to back up their performance reviews and ensure a good outcome from their 1:1 meetings.
Managers can use the insights from git analytics tools to analyze the effectiveness of the software development process. They can use this opportunity to experiment with the software development cycle and see how the changes affect overall engineering team productivity. An attentive manager can use this information to tweak the process until it’s as efficient as it can be.
For instance, if the reports show that the code written in one specific language produces much fewer errors than others, that can be a cause to shift focus to that language. Also, if certain practice or habit is associated with inefficient output, leaders can implement company-wide policy to discourage them.
Git analytics can be useful for task delegation as well. For instance, high-risk commits should go to experienced developers, not beginners. This way, experienced developers have something challenging to work on. On the other hand, junior developers are not forced to work on difficult tasks and can be eased into the complexities of the job. This is beneficial for everyone involved: the company, the junior developers, and even end-users who get to use the more functional product.
Key metrics
Tracking the contribution of each developer is a good start. However, it’s not enough. Finding metrics that actually measure the quality of the code and align with the goals of the organization is very important. Under normal circumstances, the three metrics below provide a good basis for measuring developer productivity:
Cycle time
This metric accounts for the time from initial commit to final release. It is useful for measuring the efficiency of the team and its individual members. Short cycle time means that everything is working fine and the team is highly productive. If the manager notices that cycle time is becoming longer, she should investigate the root causes of the delay and resolve any possible bottlenecks in the process.
Rework vs New work
These two metrics measure the quality of the code. The rate of rework measures how much time your team spends on re-writing the code before the release. Mistakes are natural and it’s impossible to have a 0% rework, but managers should try to minimize it. New work is a positive metric, which denotes the portion of new, fresh code produced by the team. It’s always better if your team spends more time on producing new code, instead of fixing old mistakes.
Review involvement
It has been established that participation in the code review process is positively correlated with code quality. Managers can look at the rate of review involvement to see which individual developers are actively engaged in the process and which are not. Then they can have a 1:1 meeting with the developer and ask them to participate.
Hatica is a comprehensive engineering analytics tool that couples git analytics with activity from all the tools that developers use to map out workflows and discover opportunities for your team to be better and faster while ensuring well-being. Discover how Hatica can equip your engineering teams to perform at their best. Request a demo: https://www.hatica.io/
