I'm in the middle of a project, using Jira to capture Epics and Stories. We know in general what we need to do but as we go from Sprint to Sprint we keep expanding our detailed knowledge of what we have to do and we refine and expand the backlog of stories we need to complete.
I created a graph of stories created over time and the volume continues to grow. My gut tells me that if lots of projects like this were grafted over time from inception to completion, once the curve flattened there must be a way that a statistical model that could be used to predict how much longer the project will last.
The weekly management reports are constantly changing as to the outstanding number of stories, etc. The built-in Jira "Predicted Completion Date" function is based on a know quantity of groomed stories. My problem is more complicated. I know that I'm not the first person that thought of this. Any insight would be appreciated.
We use eazyBI plugin to create reports to predict completion dates. Here is an example of a report: https://eazybi.com/accounts/1000/cubes/Issues/reports/187086-project-prediction-report.
You can customize the formulas as you wish. The eazyBI support staff is excellent in answering any of your questions.
Jira is a powerful tool that helps teams to plan, manage, and report on their work. We love using Jira, especially for its ability to track issue progress. But how to monitor the...
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