Aalst, W.M.P. van derW.M.P. van derAalst2022-03-152022-03-152021https://publica.fraunhofer.de/handle/publica/41271110.1007/978-3-030-85315-0_12-s2.0-85115173526Process mining dramatically changed the way we look at process models and operational processes. Even seemingly simple processes like Purchase-to-Pay (P2P) and Order-to-Cash (O2C) are often amazingly complex, and traditional hand-made process models fail to capture the true fabric of such processes. Many processes are inherently concurrent and involve interaction between different objects (customers, suppliers, orders, items, shipments, payments, machines, workers, etc.). Process mining uses event data to construct process models that can be used to diagnose performance and compliance problems. If such models reflect reality well, they can be used for forward-looking forms of process mining, including predictive analytics, evidence-based automation, and what-if simulation. The ultimate goal is to create a "digital twin of an organization" that can be used to explore different improvement actions. This paper provides a high-level overview of the different process mining tasks followed by a more detailed discussion on concurrency and object-centricity in process mining.en004005006conference paper