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On the left (in green) is the ratio of the standard deviation of the mean to the average of the mean. The higher that percentage, the more variable is the demand.  The other indicator that you see is the number of days in the year that the item had activity.  If you look at the very first item, it had 330 days in the year with activity, and the standard deviation of demand over the average demand is 100 percent which means it is one.  Based on what you see in that graph, what is the relationship between the popularity of the item and the demand variability?  It sounds like a good quiz question. All right, fill in the blank.  Items that are very popular have a higher or lower demand variability than items that are hardly ever ordered?  Lower demand variability and usually a higher forecast accuracy because you get to see the demand more often, so you have a better chance to predict it.  Suppose you are a basketball team and you are in a conference. For example, in the ACC Georgia Tech may play Carolina three, sometimes four times in the year.  They play them at home, they play them away, they may play them in the ACC tournament, and they may play them in the NCAA tournament. How well do you think Georgia Tech can forecast what Carolina is going to do in a game by the time they get to the NCAA tournament?  They know exactly what they are going to do.  They can call the play for the other team.