Create new Calculated Metrics based on Multiple Users

I have a multi tiered problem that I’m trying to solve:

  1. I want to add a calculated member field that will incorporate assignee and any tagged person in the description
    Example: Person A is assigned to issue ABC-1 but Person B is mentioned in the description. Person A and Person B should both have issue ABC-1 under their names
  2. I need to add a calculated measure. Our company won’t let us do custom fields beyond what is out of the box. I have repurposed an “Additional Notes” field to have what are essentially story points. I need to get those values from the field and have them roll up under the calculated member field in part 1.

Result Desired:

Person | Effort Points (from customfield_123)

Person A | 1
ABC-1 | 1
Person B | 2
ABC-1 | 1
ABC-2 | 1

Hi @cms521,

I see this topic has been hanging without response for a long time. This is quite complex use case, but there is an option to get some data out of the “Additional Notes” field (I believe it is a multi line free text field).

Consider using a JavaScript calcauted field to process data from the “Additional Notes” and “Assignee” and import those users as new dimension. The script should grep all user names mentioned in the “Additional Notes” field based on some textual pattern to recognize which words are user names and check on user names in the Assignee field. Here are more details on javaScript calculated fields and how to make them: Account specific calculated fields.

The challenge here is how to recognize the tagged user in the field:

  • How do tagged users look in the field when you check on issue data in the JSON format (raw values without any prettifying for the user interface, the same as eazyBI sees them)?
    To check the issue fields in JSON format, open an issue in Jira. Modify the URL of the issue by replacing browse with rest/api/latest/issue.
  • Is there any pattern for recognizing user names?
  • Could user names be used in your report as you see them in the JSON form? For example, on Cloud, all mentioned user names look like account IDs in the JSON format, which is not readable in the report.

Zane /