Trend analysis is a valuable technique that can help organizations improve their development processes. By examining data over a period of time, trends can be identified, which can provide insights into potential areas of improvement. In this article, we'll explore some ways that trend analysis can be used to optimize development processes.
What is trend analysis
Trend analysis is a statistical technique that involves the examination of data over a specific period to identify patterns and trends. In software development, trend analysis is used to gain insights into the performance of the development team, the quality of the software, and other important metrics.
Types of Trends in Software Development
There are several types of trends in software development that can be identified through trend analysis. These include:
- Process trends: These trends focus on the performance of the development process, including the speed of development, quality of deliverables, and adherence to deadlines.
- Quality trends: These trends focus on the quality of the software developed by the team. This includes metrics such as defect rates, customer satisfaction, and user feedback.
- Team trends: These trends focus on the performance of the development team, including factors such as communication, collaboration, and productivity.
Why use trend analysis
- Removing noise: When we look at data of single period there are chances that it may be affected by one off event for instance unexpected customer demand leading to spike in work or too many team members on leave in the same period leading to low output. It is therefore necessary to look at data from multiple periods to get clear picture of our development process to make informed decisions.
- Tracking progress of goals: It is not sufficient to set goals for the team it is also important to track them to ensure that course correction can be done in case team is deviating from the goals. Getting data for multiple sessions helps you in seeing if the goals that are set are converging based on week over week progress.
- Identifying bottlenecks and improving process: Apart from tracking, past sessions also help you in uncovering new trends for instance you may find that there are too many unmerged prs which are leading to wastage of work or that that your workload is consistently decreasing which may indicate capacity to take up more work.
Using trend analysis to identify patterns in different engineering metrics
Using Gitimprove, managers can track a range of metrics, including progress on tasks, time spent on PRs, and the number of bugs encountered. By comparing this data across multiple sessions, managers can identify trends and patterns that can help them make better decisions about how to manage their team. Gitimprove provides charts for multiple metrics. By analyzing these charts, managers can make more informed decisions about how to allocate resources, identify potential problems before they become major issues, and track the overall progress of their team over time.
Charts for comparing data across multiple sessions
- Issues Chart: Provides details of issues closed in current period by their type and average time it took to close the issues in a given period. It can be used to check what type of issues are getting solved by the team.
- Bugs Chart: Gives details of number of defects closed in acceptable and unacceptable ranges along with average time it took to close a defect. It can be used for analyzing trend in time it takes to fix defects.
- Features Chart: Provides details of different phases of feature evaluation before its accepted for development and average time it takes for feature to be accepted. It can be used for identifying trends in time it takes to accept features.
- Backlog Chart: Provides details of type of issues open in a given period and average time of open issues. It can be used for assessing trends in workload.
- Triage Chart: Provides details of non development related tasks and average time spent on them. It can be used for identifying trends non development related issues.
- Prs Chart: Provides details of merged/unmerged details of closed prs and average time it takes to close prs. It can be used to identify trends in pr disposal rate, percentage of prs getting merged etc.
- Prtomerge Chart: Provides details of prs merged in acceptable and unacceptable ranges along with average time it takes to merge PR. It can be used to find trends in overall number of prs merged week over week, if time to merge is increasing/decreasing etc.
- Prtoclose Chart: Provides details of prs closed without merging in acceptable and unacceptable ranges along with average time it takes to close PR. It can be used to find trends in overall number of prs closed without merging week over week, if time to close is increasing/decreasing etc.
- Prapprovetomerge Chart: Provides details of time spent on infrastructure in acceptable and unacceptable ranges along with average time it takes to merge PR after review is completed. It can be used to identify trends in time spent on infrastructure.
- Prcodetoreview Chart: Provides details of time spent on reviewing in acceptable and unacceptable ranges along with average time it takes to get first review/comment on PR. It can be used to identify trends on how quickly reviews are getting performed after code is completed.
Conclusion
Gitimprove's ability to compare data across multiple sessions can be an incredibly valuable asset for managers looking to stay on top of their team's progress and identify areas for improvement. By using this feature, managers can make more informed decisions, optimize their team's performance, and ultimately drive better results for their organization.