Introduction
In agile development environments, Jira is one of the most widely used tools to plan and track progress. But its usefulness heavily depends on how well teams are actually using it. Empty fields, poorly categorized issues, or vague descriptions can seriously hurt follow-up processes and decision-making. That’s why at WELLFLEX, we built a solution to objectively measure how well Jira is being used.
This post documents the design and build process of that dashboard, as well as the lessons learned while automating the data feed using a Python script connected to the Jira API.
Defining the Problem
Our goal was to answer a simple but powerful question: How well are teams actually using Jira?
To get there, we defined what “proper use” means: each issue type (Epic, Story, Bug) has a specific set of required fields. For example:
- Epics should have name, description, due date, and a link to an initiative.
- Stories need to include priority, estimation, user story, and acceptance criteria.
- Bugs should contain steps to reproduce, environment, and severity.
We built a field-requirement schema by issue type and used it to calculate a compliance metric:
Compliance = fields properly filled / expected fields
Important: if a field doesn’t apply to an issue (e.g. a Bug without a due date), it doesn’t affect the score.
Building the Dashboard
To visualize the data, we used Power BI. The dashboard included:
- Average compliance by issue type.
- Compliance breakdown by team and sprint.
- Field-level breakdown of incomplete issues.
- Historical trends to show improvement (or decline) in Jira usage.
Each component was fully interactive and filterable, which made it super useful during follow-up and review meetings.
Automation with Python and the Jira API
The dashboard needed fresh data on a regular basis, so we built a Python script that:
- Authenticated via token with the Jira API.
- Pulled issues based on custom filters (by project, sprint, etc.).
- Applied the compliance logic per issue.
- Exported a clean CSV file ready to plug into Power BI.
The process was scheduled to run daily, keeping the dashboard always up-to-date—zero manual effort required.
Results We Saw
After rolling out the dashboard, compliance scores improved steadily. Teams started acting on the data:
- Clear “owners” were assigned for key fields.
- Compliance review became part of sprint closure routines.
- The dashboard was used as input for coaching and continuous improvement.
Beyond the numbers, the real win was cultural: Jira stopped being a passive task bucket and became a living quality tool.
Final Thoughts
This project showed us that measuring tool usage is just as important as using the tool itself. With clear definitions, automation and good data visualization, meaningful change is totally possible.
At WELLFLEX, we love building solutions like this—practical, real-world, and results-oriented.
If you’re looking to level up how your teams use Jira or want to streamline similar processes, hit us up! We’d be happy to help.