Process Mining is a collection of techniques that combine the areas of Data Science and Process Management to support the analysis of operational processes based on event logs.
The goal of Process Mining is to transform event data into insights and actions. Process Mining techniques use event data to reveal what people, machines, and organizations are actually doing. Process Mining provides continuous insights that can be used to identify and address performance and compliance issues.
A common issue in process management is the lack of connections between business processes and a company's information systems. Some enterprise systems (e.g., SAP) are process-oriented in the sense that they support processes like "Order-to-Cash" or "Procure-to-Pay," but there is no easy way to understand how the process is executed. Other technologies support aspects of process design (e.g., Microsoft Visio) or provide insights into KPIs like customer retention rates (Business Intelligence tools). However, if you want information on how the process runs on a daily basis and where the causes of problems lie, Process Mining is the unbeatable tool of choice. Process Mining collects data from ERP systems like SAP, Oracle, and Salesforce, as well as from any other type of system (such as CRM or BPM). This data contains everything Process Mining needs to provide a complete picture of the end-to-end process. The entire process becomes visible: how the process truly operates, including who performs a process step, how long it takes, and how it deviates from the average. Problems within the process are uncovered, and AI algorithms can identify the causes of deviations, while KPIs allow a company to focus on the most urgent improvement steps. Process Mining is also a great partner for other technologies like Robotic Process Automation (RPA) since it can identify the best places for bot implementation and then track and calculate the positive impacts of RPA implementations. Valuedata Miner is an initiative of PMC Services GmbH (www.pmc-services.de) and ValueData (www.valuedata.io).