When you need full precision, the Kahan approach helps but doesn't make 
guarantees and can sometimes hurt (it makes some assumptions about the 
data).  One use case in is computing stats like a mean where many of 
the larger magnitude entries tend to cancel out but only after clipping 
bits off of the lower magnitude components.