  In this paper we present a business case carried out in Poste Italiane, in
the context of fair performance evaluations of human resources engaged in
internal audit activities. In addition to the development of a Bayesian network
supporting the goal of the Internal Audit unit of Poste Italiane, the work has
led to the development of a methodological approach to advanced analytics in
corporate context, whose usefulness goes well beyond the specific use case
described here. We thus present the different stages of such analytical
strategy, from feature selection, to model structure inference and model
selection, as a general toolbox that allows a completely transparent and
explainable process to support data-driven decisions in business environments.
