Find outliers in time-series data
I have been using one heuristic to detect outlier values that is very simple. Start by calculating an interval centered on the mean and with three standard deviations in radius. Next, calculate a second interval using Tukey's box and whiskers measures, placing the interval limits at the whiskers' limits. Finally, calculate the union of both intervals and use this new interval to detect your outliers: any observation outside this interval is a potential outlier. Please note that you may have to tweak both intervals to calibrate for your desired precision. Also, you may have to take into account possible trends and seasonalities in these intervals, depending on how the historic data behaves.