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In this paper we present a business case carried out in Poste Italiane, inthe context of fair performance evaluations of human resources engaged ininternal audit activities. In addition to the development of a Bayesian networksupporting the goal of the Internal Audit unit of Poste Italiane, the work hasled to the development of a methodological approach to advanced analytics incorporate context, whose usefulness goes well beyond the specific use casedescribed here. We thus present the different stages of such analyticalstrategy, from feature selection, to model structure inference and modelselection, as a general toolbox that allows a completely transparent andexplainable process to support data-driven decisions in business environments.

Bayesian probabilistic models for corporate context, with an application to internal audit activities