  Improving the understanding of diffusive processes in networks with complex
topologies is one of the main challenges of today's complexity science. Each
network possesses an intrinsic diffusive potential that depends on its
structural connectivity. However, the diffusion of a process depends not only
on this topological potential but also on the dynamical process itself.
Quantifying this potential will allow the design of more efficient systems in
which it is necessary either to weaken or to enhance diffusion. Here we
introduce a measure, the {\em diffusion capacity}, that quantifies, through the
concept of dynamical paths, the potential of an element of the system, and
also, of the system itself, to propagate information. Among other examples, we
study a heat diffusion model and SIR model to demonstrate the value of the
proposed measure. We found, in the last case, that diffusion capacity can be
used as a predictor of the evolution of the spreading process. In general, we
show that the diffusion capacity provides an efficient tool to evaluate the
performance of systems, and also, to identify and quantify structural
modifications that could improve diffusion mechanisms.
