Setting safety stocks traditionally relies upon the random sums approach.
The data requirements for
successful application of this approach, however, can be difficult to fulfill in certain settings and
necessitate that accurate records be kept for determining the input parameters. Furthermore, the random
sums approach assumes independence between demand and lead time, a condition that could be
violated during demand spikes. This paper examines the impact on safety stocks when record keeping is
compromised. An alternative formulation for setting safety stocks is proposed using a multiplication
approach for estimating the variance that eliminates the need for pre-specified relationships and
accounts for: (1) data quality issues; (2) demand and lead time correlation; and (3) computational
simplicity. Using simulation, general applicability of the multiplication method is examined and the
performance of alternative formulations is assessed. The multiplication approach, with its ease of
application, is found to provide comparable results.