Towards visualizing and analysing legal proceedings with process mining

Process mining (PM) is a family of data-driven techniques which use data with the goal of studying the process behind the data, i.e., the data-generating process. Despite initially tailored for the engineering and industrial domain, it is becoming popular also in more human-centric domains like the legal and healthcare ones. This paper proposes preliminary steps towards a general-purpose process mining methodology utilizing Fluxicon’s Disco tool aimed at analyzing and optimizing the complex processes underlying legal decision making by Courts. We consider specifically the domain of civil proceedings, with a focus on divorce cases. In PM terms, a case is a legal proceeding, and activities are the different internal phases in which a legal case transits from its beginning to the final judgment. The studied process is, therefore, the internal process followed by the Court, possibly varying over the years, to handle specific types of proceedings. By leveraging process mining techniques, this preliminary study examines the evolution of divorce proceedings within a selected Italian court in the time frame 2013-2019, identifying key performance indicators and uncovering hidden process inefficiencies and efficiencies. The findings highlight the potential of process mining to reveal critical process patterns, enabling organizations to make data-driven decisions and implement targeted process improvements.