Control limits
The simplest rule suggesting a special cause is any value that is outside two control limits. Values outside the control limits suggest that the process is out of control — they trigger an examination of the process for a special cause.
Control limits are usually based on the mean and standard deviation of the process when it is in control. The 70-95-100 rule of thumb states that in many distributions,
By setting the upper and lower control limits to be 3 standard deviations on either side of the process mean, we avoid many 'false alarms' when the process is in control. This is important since values outside the control limits would trigger an examination of the production process — possibly a costly exercise.
Shape of the distribution
The 70-95-100 rule of thumb is most accurate for reasonably symmetric, bell-shaped distributions, though values more than 3 standard deviations from the mean are rare for all distributions. However these control limits should be avoided for very skew distributions — consider transforming the data before producing a run chart.