When should I use a frequency spectrum rather than a spectrogram representation? It seems to me that the spectrogram representation of a finite signal gives you significantly more useful information than a frequency spectrum.  As I understand it, the spectrogram breaks down the spectrum over time whereas the frequency spectrum gives you no time dependent information.  Why wouldn't I want to use this kind of representation all the time?  When would it be more useful to use the frequency spectrum rather than the spectrogram?  Is it just computationally expedient to produce a frequency spectrum?
The spectrogram suffers from a time/resolution restriction - the smaller your time step, the smaller your analysis windows become, the worse your frequency resolution gets.

It is a waste of frequency resolution to break down a stationary signal into tiny temporal slices. Thus, if you know in advance that your signal you analyze is stationary; or if you have pre-segmented your signal into stationary segments (using a transient/onset detector; novelty detection; or an auxiliary signal/sensor), there is no reason to lose frequency resolution by using the spectrogram.