A Guide to understanding Agile Control Charts in Jira
As part of of being a product development company, switching to agile was one of the main strategic decisions that any software house building products is ought to take at some point.
However, one of our main concerns about switching to agile was the fact that agile development methodologies are by nature dependent on the trust in the team. It follows, that the factor of control – an essential element in any project management methodology – had to be affected.
After long debates between our management team, coupled with various educational conversations about the merits of Agile. We finally took the decision. In the article, we will present the Control element available in the agile methodology, using the very famous tool : Jira.
About the agile control chart
The control chart is mainly concerned with the cycle time for your product. It essentially answers the question of : How fast does the issues you create move between statuses and team members ? This metric is very valuable as it provides the bases to understand the following :
- It helps you measure the effects of process changes or on boarding new members to your agile team.
- It helps to analyse the your teams past performance and predict the future performance .
- Provides visibility to your team efforts to external stakeholders or product owners.
- Helps you set goals for future performance specially if you are using a Kanban workflow.
Understanding the agile control chart
In order to be able to use the control chart, you need to understand how it is calculated. the following questions and answers will help you get started :
What is the Cycle Time ?
The cycle time is the time taken from when work starts on an issue to when the work is completed. Off course, it depends on the workflow given; for example, if the issue is re-opened then the cycle time increases until it is completely resolved. Cycle time is calculated by the day usually.
What is the Rolling Average ?
The rolling average ( represented by the blue line on the chart ) is issue based not time based. For all issues presented on the chart, the rolling average ( at each point of time ) is calculated by taking an issue, X issues before the benchmark issue and X issues after the benchmark issue, then averaging the cycle time. Jira uses %20 of total issues displayed to calculate the rolling average. As Jira Explains it
This method produces a steady rolling average line that shows outliers better (i.e. rolling average doesn’t deviate as sharply towards outliers). The rolling average line is also easy to understand, as the inflections are related to the positions of issues.