Keep an eye on
Aging Time to Merge
The Aging Time to Merge visually aggregates open Pull Requests into three phases:
the Pull Request was opened, and the team has not interacted or reviewed it.
one or more people commented on the Pull Request. However, it’s not approved, nor changes were requested.
the Pull Request received at least one review (be it an approval or request changes)
Pull Requests needing attention
The table displays a prioritized list of open Pull Requests. The prioritization takes into account many aspects, such as the current Time to Merge, idleness, and impact (number of lines and files changed).
It’s an excellent tool for easily finding and acting on stale work. Share this page with the team, so coordination gets easier.
Understand the team’s Engagement
SourceLevel breaks down the team’s engagement into actions. The chart measures the volume of Pull Requests opened in a week in bars. The lines represent the number of comments, approvals, and request changes in the week.
It’s an excellent tool to understand how engaged the team is. The number of comments should be proportional to the team’s size. Besides, the chart is useful for monitoring rework. A high number of request changes usually indicates code needs severe interventions.
Time to Engage
Accelerating deliveries requires measuring how much time the team spends on each step of the development flow. The Time to Engage chart displays how much time it takes for the first engagement to happen. Be it a comment, an approval, or a request change, the first action defines the starting point of the engagement.
The chart displays the 75th and 95th percentile of this number. We don’t use medians. It means that SourceLevel calculates the Time to First Engagement taking into account 75% and 95% of Pull Requests, respectively.
Accelerate and increase Deliveries
Throughput with Time to Merge
Throughput is the number of Pull Requests merged in a week. SourceLevel ignores closed Pull Requests as they didn’t add value for the final user. The Time to Merge tells how many days each pull request remained open.
Finding the correlation between the amount of work done by the time it took is the best way to determine what accelerates or slows down the process. Plus, the numbers can give you the confidence to forecast future deliveries.
Time to Merge Histogram
Histograms are an accurate representation of the distribution of numerical data. In practice, it’s a bar chart that shows the number of merged pull requests (Y-Axis) grouped by the number of days they stayed open (X-Axis). The higher the bars on the left, the faster pull requests get merged.