The standard deviation, or SD, measures the amount of variability or dispersion for a subject set of data from the mean, while the standard error of the mean, or SEM, measures how far the sample mean of the data is likely to be from the true population mean. The SEM is always smaller than the SD.

The standard deviation (SD) represents variation in the values of a variable, whereas the standard error of the mean (SEM) represents the spread that the mean of a sample of the values would have if you kept taking samples.

If the message you want to carry is about the spread and variability of the data, then standard deviation is the metric to use. If you are interested in the precision of the means or in comparing and testing differences between means then standard error is your metric.