1. A combined computer/human method for automatically identifying actionable insights for a process, the method comprising: a computer system automatically and iteratively performing the steps of: calculating metrics for data within a data set, wherein the data in the data set was generated by the process; identifying norms for the process based on the calculated metrics; identifying potentially valuable patterns in the process, comprising: calculating metrics for different samples of the process, and identifying potentially valuable patterns in the process based on which samples of the process have calculated metrics that vary from the calculated metrics for the identified norms for the process, whereby the identified potentially valuable patterns are patterns in the process that may cause deviations from the norms for the process; requesting from statistically untrained humans feedback regarding whether the potentially valuable patterns are patterns that actually produce deviations from the norms; and receiving said feedback from the statistically untrained humans; and iteratively developing actionable insights for changing the process based on said steps taken by the computer system.