Process mining

Process mining is a family of techniques in the field of process management that support the analysis of business processes based on event logs. During process mining, specialized data mining algorithms are applied to event log data in order to identify trends, patterns and details contained in event logs recorded by an information system. Process mining aims to improve process efficiency and understanding of processes. Process mining is also known as Automated Business Process Discovery (ABPD). However, in academic literature the term Automated Business Process Discovery is used in a narrower sense to refer specifically to techniques that take as input an event log and produce as output a business process model. The term Process Mining is used in a broader setting to refer not only to techniques for discovering process models, but also techniques for business process conformance and performance analysis based on event logs. Process mining is a family of techniques in the field of process management that support the analysis of business processes based on event logs. During process mining, specialized data mining algorithms are applied to event log data in order to identify trends, patterns and details contained in event logs recorded by an information system. Process mining aims to improve process efficiency and understanding of processes. Process mining is also known as Automated Business Process Discovery (ABPD). However, in academic literature the term Automated Business Process Discovery is used in a narrower sense to refer specifically to techniques that take as input an event log and produce as output a business process model. The term Process Mining is used in a broader setting to refer not only to techniques for discovering process models, but also techniques for business process conformance and performance analysis based on event logs. Process mining techniques are often used when no formal description of the process can be obtained by other approaches, or when the quality of existing documentation is questionable. For example, application of process mining methodology to the audit trails of a workflow management system, the transaction logs of an enterprise resource planning system, or the electronic patient records in a hospital can result in models describing processes, organizations, and products. Event log analysis can also be used to compare event logs with prior model(s) to understand whether the observations conform to a prescriptive or descriptive model. It is required that the event logs data be linked to a case ID, activities, and timestamps · . Contemporary management trends such as BAM (Business Activity Monitoring), BOM (Business Operations Management), and BPI (business process intelligence) illustrate the interest in supporting diagnosis functionality in the context of Business Process Management technology (e.g., Workflow Management Systems and other process-aware information systems). Process mining follows the options established in business process engineering, then goes beyond those options by providing feedback for business process modeling: A database of applications of Process Mining list all the major process mining initiatives. There are three classes of process mining techniques. This classification is based on whether there is a prior model and, if so, how the prior model is used during process mining.