Process Mining

About Process Mining

Process mining is when businesses apply specialized data mining algorithms to processes, cases and events logged by enterprise applications to understand real work done by employees, locating hidden bottlenecks and pinpointing where automation will lead to the biggest process improvements.

How it’s used

1. Discover and Model processes:

Discover process flows by applying data mining algorithms to event logs, including extracting data from enterprise applications and then automatically generate process models. When combined with task mining, which discovers and analyzes user interaction data, a business can analyze different levels of detail for a more complete picture of a process.

2. Gain Actionable insights:

Apply data analysis patterns to discovered processes, visually verifying metrics like frequency, duration, cost, compliance and conformance with advanced data visualizations. Define and evaluate company-specific KPIs and compare two or more process variants for a more holistic view of your processes.

3. Uncover Clear root causes for targeted fixes:

Look more closely at the processes that have issues and uncover exactly where and why problems are happening with root-cause analysis visualizations — whether there’s a resource snag, approval delay or other irregularity at a specific point in a business process.