I can agree. The calculation is quite tough. Therefore I used a bit different approach in my formula I suggested for you. Sorry, I missed the part of unresolved issues.
I will walk you through how I made my formula for maximal performance optimization. The main idea is to split filters, using filtering by issue properties and only after that apply any measure to already filtered issue set.
I used SUM function instead of COUNT for splitting filters into two parts.
I used only issue properties as criteria to Filter initial issue set.
Filter(All issue set, properties as filter criteria only)
Then I used SUM over this filtered issue set:
SUM (filtered issue set, numeric expression)
where numeric expression uses measures Story Points history and Issues created as filters within CASE <> WHEN <> THEN <> END
Measure Story Points history will check if there is no value. Measure Issues created is the main filter for this formula. Measure Issues created works as a counter (numeric expression) for SUM function as well.
You are using a calculated member in Issue type dimension Items with SP in a tuple with measure Issues created. It aggregates several issue types and will multiply any calculation by a number of aggregates issue types. If you are facing performance issues, avoid calculated members if you can. You can use filter by issue property [Meausre].[Issue type] and use MATCHES there to filter by several issue types there.
If the formula still does not work in the account. You can consider minimizing the issue amount per account.
Daina / email@example.com