Decision support systems require a form of situation awareness. to generate situation awareness information is needed. not all available information is necessary or equally influential. this paper proposes a way to determine which and when information is relevant. the goal of this is to minimize communication and processing of irrelevant information. our system is inspired by a few first responder experiments done in our lab. in these experiments first responders had to respond to a calamity. the information need of responders was analyzed. to have good team performance it was clear that at certain times certain information was important. we modeled a toy problem after this scenario and we use this illustrate our method of reducing irrelevant information. our toy problem consists of a bayesian network with which sensitivity analysis is used to illustrate which information is relevant. a simple tracker scenario with information theoretic techniques is used to illustrate when information is relevant.