The Value of Information (VoI) framework, developed by Ruslan Stratonovich, bridges Claude Shannon’s information theory with economics, particularly utility and decision theory. This paper revisits the VoI concept in the Boolean utility setting of hypothesis testing and then extends the discrete Bayesian VoI framework to more general decision contexts with arbitrary utility matrices. We also provide a method to compute a robust VoI estimate that is independent of input distributions.