Im no expert on benfords law (in fact i never heard of it!).
Having said that, it is exactly true if your data is log-uniformly distributed.
If benford's law does not hold for your data then (ignoring sampling error) it is probably because it is not log-uniformly distributed. Now, you can apply an arbitrary transformation to your data so that it appears to be log-uniformly distributed and benford's law will apply...but then it isn't really the same data anymore.
The point is that by applying your transformation, you are changing the statistical properties of the data; you wont be able to learn much about the underlying data by examining the transformed version.