prosessikaivanta

Prosessikaivanta, often translated as process mining, is a discipline that bridges the gap between traditional data mining and the analysis of business processes. It involves analyzing event logs, which are records of activities performed by a system, to discover, monitor, and improve real business processes. The core idea is to reconstruct the actual process flow as it happened, based on the timestamped data.

Unlike traditional process modeling, which relies on experts to define how a process *should* work, process mining uses data to reveal how a process *actually* works. This can uncover inefficiencies, bottlenecks, deviations from the intended workflow, and even compliance issues. The inputs for process mining are event logs, which typically contain at least a case ID (identifying a specific instance of a process), an activity name (describing the task performed), and a timestamp (indicating when the activity occurred).

The outputs of process mining can include visual process models, performance metrics, and dashboards. These tools help organizations understand their operational reality, identify areas for improvement, and make data-driven decisions to optimize their processes. Common applications include analyzing customer service workflows, supply chain operations, and financial transaction processes. Process mining enables organizations to gain objective insights into their operational performance and identify opportunities for automation, streamlining, and cost reduction.