Complex Systems such as those described by partial differential equations can be approximated in some cases by models of reduced order with a surprising accuracy. We give some examples how these reduced order models can be obtained. These reduction techniques are particularly useful when an optimization problem is involved. We show how reduced order models can be used efficiently in the context of PDE-constrained optimization either through trust region techniques but also in the context of preconditoners.