Marcello La Rosa – Process mining and how this is changing the way we do BPM
Data abounds in modern organisations, but data without meaning is useless. Supported by a compelling case study, this talk will expose the value of process mining, an innovative technology to extract business process insights from transactional data commonly recorded by IT systems, and use this to analyse and improve organisational productivity, along performance dimensions such as efficiency, quality, compliance and risk. By using data rather than perceptions gained from interviews and workshops, process mining shifts the way of thinking from “confidence-based” to “evidence-based” business process management.
Marcello La Rosa – Director of Engagement at School of Computing and IS, The University of Melbourne
Marcello has an engineering approach to information systems (IS) research. His research leads to the design, implementation and validation of IS artefacts such as models, methods and techniques, with a focus on technology. He strives to implement the results of his research via open-source software tools to maximize community outreach.
The area of application of Marcello’s research is the management of business processes. Business Process Management (BPM) puts forward the idea of analysing organizational performance through a “process lens”, starting from the understanding that organizational performance is a function of process performance. His research interests span different BPM topics, with a focus on process mining, process modelling and consolidation, and process automation.
Given the multidisciplinary nature of BPM, in his research Marcello borrows approaches and techniques from a number of fields beyond IS engineering, including IS management, enterprise architecture, conceptual modelling, software engineering, data mining and machine learning, operations research and formal methods.
His research is showcased in public repository sites such as Google Scholar, UoM Minerva Access, arXiv, ResearchGate, QUT ePrints and BPMCenter, and on UoM Find an Expert profile.