We derive qualitative relationships about the informationalrelevance of variables in graphical decision models based on a consideration of the topology of the models. Speci cally, we identify dominance relations for the expected value of informationon chance variables in terms of their position and relationships in in uence diagrams. The qualitative relationships can be harnessed to generate nonnumerical procedures for ordering uncertain variables in a decision model by their informational relevance.