Does all of this information have to be on one worksheet? I can imagine this can be done creating a couple of sheets and placing them on a dashboard--perhaps creating different sets in tandem with different fields on the view.
I'm pretty sure you can achieve it with custom SQL. I'm also fairly sure I managed to do this with table calcs in reply to a similar question on the forums a year or two ago. I'll see if I can hunt out the thread I'm thinking of (and see if it was indeed the same question).
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I couldn't find the old thread I was thinking of, but I found the workbook from it. I'm fairly sure this was one that I bounced around with one of the other forum regulars at the time (maybe Andy Cotgreave), but I can't even remember which of us put it together.
Anyway, the workbook lets you display a list of customers who have bought at least one out of the list of products selected in the filter.
Optionally you can also limit it to customers who have bought all of the selected products, or none of them, or some but not all of them.
Whilst not exactly what you asked for, I think the same technique may answer your question.
I haven't looked to remind myself how it works - but this was over a year ago in the early days with table calculations, so it may well not be the best way to do it.
That's fantastic, thank you.
I simplified my model to give the total sum of minutes against each unique task number, whether we hit SLA on that task, and if so, to increment the count of every team that touched that task in it's lifetime. So, we have an overall team SLA achieve picture, even if it doubles up some tasks that are worked on by multiple teams along the way. At least encourages people not to game SLAs by throwing them to other team members at the last minute :-)
I suspect I'll be asked to do things differently, so will go through your model when I'm back on my work PC in the morning. But in he meantime, thank you for finding this for me - it is greatly appreciated.
FYI I had a quick look to see how that example worked and it's a bit of convoluted trickery with an extract created from a custom SQL connection and then table calculations. I didn't try to get my head around it properly - but it's certainly not trivial.