Principal Component Analysis as a step between STFT and MFCC
One dimensionality reduction method (PCA) is linear, the other (MFCC) is  not. It  is thus unlikely that there is no difference at all since they probably do not commute. One serves more decorrelation, the other feature extraction. 

The importance of the order thus depends a lot on your signal class, and what your purpose is.