Process mining is a discipline that aims to discover, monitor, and improve business processes, generating knowledge through the application of data mining techniques to the Event Logs found in the systems that support a company's business processes.
Automatic discovery of processes based on data
Data-driven Process Improvement and Optimization
Analítica de Procesos
Smart Audit (Compliance)
Stochastic Processes.
Optimization.
Operations Research and Management.
BPM
Process Improvement (TQM, Kaizen, Lean, Six Sigma, TOC and BPR).
Process Automation and Robotization (Workflow / RPA).
Statistics.
Machine Learning.
Predictive Analytics.
Databases.
Distributed Systems.
BI.
Marketing and business models.
Behavioral/Social Analysis
Discover the actual execution model of the process and determine if it complies with regulations and procedures.
Increase process execution capacity with the same resources (Celonis).
Analyze the interaction of the personnel executing the process and monitor their productivity.
Determine the relationship between variables in a case.
Its characteristic is to find a good characterization of all possible routes/variants of the process.
It focuses on the actors of the business process and looks at how and in what way those involved relate to each other, classifying them into roles/units and representing the social network of the process.
It focuses on the analysis of time and frequency of events. Bottlenecks are discovered, SLA measurement, productivity and resource utilization monitoring and time prediction.
Analysis of the influence and relationship that the attributes of a case have on the result variables of a process such as response time, customer satisfaction, costs, quality, reprocesses.