I have 12 data points representing 12 months of data for each of 100
people. I'm looking for outliers. So I set up a high z score, max-mean/
SD, and a low z, mean-min/SD. When I look at my table, my z scores
look low; I see clear outliers that have a reletively low z.

I think that this is due to the outlier being compared to a set of
data that it is already part of, contributing both to increasing the
denominator as well as lowering the numerator by being part of the
mean. If I were to compare a new value to the set of twelve data
points, the z would be accurate, but I somehow have to take the
outlier out of the group and then recalculate the z and I have to
check for both low and high.

With a lot of rows of data, doing this manually is impossible. I can't
figure out how to do it in excel either. Am I using the wrong approach
or is there a way, or a mathematical compensation that makes up for
the high and low outlier being part of the mean and SD?