How much should I make when product has a fixed shelf life?  I should be OK if production does not exceed what I can sell on average before it goes out of code, right?  As Johnny Carson might have said, “You are wrong, bell curve breath!”

We live in a world that talks about averages all the time.  We assume if the expected average result meets our requirements, things will turn out fine. That is not necessarily true.  If it takes an average of 30 minutes to get to work, you should be fine leaving the house with 5 minutes to spare, right?  What if the average includes a one in five chance of being stopped by a train for ten minutes? Four out of five days you can get to work in 28 minutes and one out of five days it takes 38 minutes.   What time would you leave?

In real life, demand for your product fluctuates.  Because of the demand variability, there can be significant risk of obsolescence even when the production run is much less than average demand.   The best way to model this variability may be a gamma distribution (see my prior blog: A Probability Distribution for Demand Variability).  If so, the gamma probability density function can be used to estimate the expected number of units that will become obsolete for a given starting inventory. See how to calculate the expected obsolescence here.