So, I have a distribution of numbers that doesn't appear to be normal...as in it doesn't fit the conventional bell curve. Rather, the curve peaks much further to the left and trails off for a while out to the right.

To add some additional context, across a population of several million widgets, they have a min/avg/max of 1 / 2000 / 2.5 million. The calculated standard deviation for my example population is something like 37,000+, which is a pretty large number compared to the avg.

My very basic and dumb question is: is standard deviation even a useful metric worth reporting on when the distribution is non-normal? Would it be correct that the usefulness of standard deviation diminishes as the normality of a distribution decreases?

Thanks, in advance!

Standard deviation and variance are meaningful for non-normal distributions, but their meaning is not as straightforward. I would recommend ready about Chebyshev's Inequality for an application to non-normal distributions.

Many distributions can have a right-handed tail, one of them being the lognormal. This distribution is characterized by the logarithm of the variate being normally distributed. Check it out on Wikipedia or other internet sites.