The need to build a link between the structure of a complex network and the dynamical properties of the corresponding complex system (comprised of multiple low dimensional systems) has recently become apparent. Several attempts to tackle this problem have been made and all focus on either the controllability or synchronisability of the network --- usually analyzed by way of the master stability function, or the graph Laplacian. We take a different approach. Using the basic tools from dynamical systems theory we show that the dynamical stability of a network can easily be defined in terms of the eigenvalues of an homologue of the network adjacency matrix. This allows us to compute the stability of a network (a quantity derived from the eigenspectrum of the adjacency matrix). Numerical experiments show that this quantity is very closely related too, and can even be predicted from, the standard structural network properties. Following from this we show that the stability of large network systems can be understood via an analytic study of the eigenvalues of their fixed points --- even for a very large number of fixed points.