LinkedIn
Twitter
Hi all. I've been working with GLS for a few months and I've hit a bit of a wall with my understanding.
I have a source of data that shows sales opportunities, including data about which partners are involved with each deal. I need to show the sum of values by partner (which works perfectly well) and show how this has changed over time (also works). I'm getting a fresh copy of data for every day of the week, this allows me to see what has changed, and when - it also means that if an opportunity exists for 7 days, it's in the data source 7 times. When I show a graph using the "snapshot" as the time/date, I get everything I want.
When I want to drill up, to show per-week or per-month stats, it shows 7x or 28x the value (as it's cumulating every day/week). I think what I need is to change the metric when drilling up, such that it shows an average for that period, not a total - I just can't work out how to do this, without breaking the graphs when I'm looking at the daily figures. I don't want an average on the deals, as I don't want to know the average deal value, I want to know the total for every day, and then the average of these totals for the week/month. Does this make sense?
I guess I've got a structural problem with how I'm working with the data, I just don't know how to achieve what I want to see. I don't want to lose the granularity in my source, as I need to see how individual opportunities can affect the overall number. Any advice gratefully received!
