Hi,
I am looking for a way to decrease calculation time for Epics lead time of issues with the following constrains:
- Exclude issues with cycle time < 3h (because the transitions were not done in time)
- Exclude the top 15% of epics with longest lead time (because they aggregate issues and irrelevant)
- Include only specific statuses in calculation (for example: “Development” and “Validation”)
The current measure looks like that:
IIF(
[Time].CurrentHierarchyMember is [Time].CurrentHierarchy.DefaultMember,
([Measures].[Workdays in transition status],
[Transition Status].[Epic CycleTime] --new calculated member
)
/
[Measures].[Issues closed],
NonZero(Avg(
BottomPercent(
Filter(
Descendants([Issue].CurrentMember, [Issue].[Issue]),
DateInPeriod(
[Measures].[Issue closed date],
[Time].CurrentHierarchyMember)
),55,
NonZero(([Measures].[Workdays in transition status],
[Transition Status].[Epic CycleTime], --new calculated member
[Time].CurrentHierarchy.DefaultMember))) ,
NonZero(([Measures].[Workdays in transition status],
[Transition Status].[Epic CycleTime], --new calculated member
[Time].CurrentHierarchy.DefaultMember))
)
)
)
While, [Transition Status].[Epic CycleTime] is an aggregation for statuses:
Aggregate(
{
[Transition Status].[Development],
[Transition Status].[Validation]
}
)
And I still need to implement the first constrain for <3h.
This calculation takes way too long on some of the reports and I was wondering if you have recommendations for simplifying it to increase the loading times.
Thanks in advance.