  Inventory decision frameworks proposed in the literature for single-echelon
supply chain systems rely on assumptions to obtain closed form expressions. In
particular, two such frameworks - one conventional and the other with a demand
undershoot - determine optimal reorder point for a desired $\beta$ or Type-II
service level. In this work we assess the accuracy and applicability of these
frameworks with the help of a discrete event simulation framework developed in
SimPy. While in several cases the closed form literature models under-predict
the service level, and thus result in a higher reorder point and safety stock,
we observe some situations where model predicted service levels match the
simulated results with statistical significance.
