Many asset-intensive organizations stock Maintenance, Repair and Operations (MRO) inventory at multiple locations to cater to geographically-distributed demand. Where there are common items used at the different locations, it is advantageous for them to share this common inventory for greater efficiency. In doing so, they set up a network of interacting nodes that can be optimized to obtain additional inventory savings. Achieving these savings, however, requires a network-centric analysis to optimize the stocking decisions at each of the nodes, such that the global inventory in the network as a whole is optimal with respect to defined management objectives. Such an analysis is significantly more complex than that for a stand-alone location because the analysis must consider the interactions between the nodes, the stochastic nature of MRO inventory demand and supply as well as practical operational constraints.