Process mining is an analytical discipline to analyse business processes in order to identify bottlenecks, deviations, and sources of waste in their processes, and to discover opportunities to optimize performance via automation.
Today, enterprises are more often than ever before under pressure to constantly evolve and keep pace with the customer expectations, competition, varying regulations and cost savings. Intelligent automation has swiftly accelerated from a long-term strategy to a high priority undertaking for organizations across industries.
Process Mining helps in addressing these challenges and contributes to make intelligent automation successful by providing a data driven approach to not only discover the as-is process but also constantly monitor and optimize them.
Process mining applications helps in:
- Understanding how business operations are executed by discovering “as-is” process diagrams based on event data from an IT system.
- Analysing data to identify friction points in a business process and relate these friction points on key performance indicators.
- Understanding what makes the difference between desirable and undesirable process outcomes, for example between orders that are delivered on-time versus orders that are delivered late.
- Identify non-compliant behaviour, understand the root causes of deviations, and quantify the impact of these deviations on process performance.
- Predict the future performance of a process under different scenarios to make better decisions and to prioritize their process automation and process improvement efforts.