Data-driven Time filters in PerformancePoint M&A

Recently I've been working on methods to display time filters in PerformancePoint M&A that are more user-friendly and efficient for users.  The conventional alternatives--Member Selection, Time Intelligence Post-Back and Time Intelligence Filter--have their strengths, and all of them are user friendly!  However I find that often the underlying data structure doesn't fit with the design of these filter tools.

The fundamental problem I seem to encounter most often is that the data in the average cube isn't "as of" the current system date and/or the [Time] dimension extends well beyond the last date/time used in the data set.  For example, a cube may be processed daily, and the [Last Order Date] is yesterday, but the [Time] dimension extends one year in the future (to support forecasting, perhaps).