1. A method of assisting with updating a model for diagnosing failures in a system, the method including: obtaining system model data representing a set of failures in a system including a plurality of components, a set of symptoms and relationships between at least some of the failures and symptoms; creating a Bayesian Network having parameters based on the obtained system model data, the Bayesian Network describing probabilistic relationships between at least some of the failures and at least some of the symptoms; obtaining failure cases data representing a plurality of failure cases, each said failure case describing presence/absence of at least one of the symptoms and presence/absence of at least one of the failures; performing a learning operation on the Bayesian Network using the failure cases data; assessing a contribution made by at least some of the failure cases to an updating of the parameters of the Bayesian Network during the learning operation by obtaining a three dimensional gradient analysis object based on a likelihood gradient contribution of the failure cases; and displaying information representing the assessed contribution of the at least some failure cases.