For me, the most straight forward way of doing cumulative difference calcs is by reshaping the data to have a row for start date and end date.
For any particular period, the number of closed accounts / terminated employees is just:
Closed Accounts =
SUM(IIF([Date Type]=='End Account Date', 1, 0))
And the number of current customers / active employees in any time period is:
Customer Count =
RUNNING_SUM(SUM(IIF([Date Type]=="Start Account Date", 1, 0))) - RUNNING_SUM(IIF(FIRST()==0, 0, LOOKUP([Closed Accounts], -1)))
And your cumulative turnover rate is the same formula as you used previously:
running_sum([Closed Accounts]) / running_avg([Customer Count])
I believe you can also do this without reshaping the data, but it's not trivial.
The other technique I've seen used is a self blend, where you duplicate the data source and rename the End Date to Start Date in the duplicate source. Now you can use number of records in each to see the cumulative counts. The self blend method is a bit perilous, however, as you need to be aware of domain padding (you can have problems if the start dates in the primary don't align with end dates in the duplicate source). For these reasons and because it'll confuse anyone who's maintaining the workbook, I'm not a fan of this technique.
I reshaped in the data in Excel, but you can of course do this with custom sql or create a view in your database, perhaps specifically for this view.