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.