Process Mining

Introduction: Process Mining

Process Mining is a data-driven technique used to analyse, visualise, and improve business processes based on event logs recorded by information systems. It bridges the gap between traditional process mapping and real operational performance by showing how processes actually occur, rather than how they are assumed to work.

Background

The concept of Process Mining emerged in the late 1990s from research in Business Process Management (BPM) and data science. Professor Wil van der Aalst is widely recognised as one of its pioneers. With the rise of digital systems and big data, Process Mining has become an essential tool for organisations seeking transparency and continuous improvement. It uses algorithms to extract insights from system event logs, revealing real workflows, bottlenecks, deviations, and inefficiencies.

Key Elements / Features

• Event Logs: Digital records of process steps captured in IT systems such as ERP, CRM, or MES.
• Discovery: Automatically generating a process model based on actual data, showing the real process flow.
• Conformance Checking: Comparing real-world execution against predefined process models to identify deviations or compliance issues.
• Enhancement: Using data insights to optimise process performance, reduce waste, and improve compliance.
• Visualisation: Graphical maps display flows, rework loops, delays, and frequency of process paths.

Applications / Examples

• Manufacturing: Analysing production data to identify delays or unnecessary rework.
• Healthcare: Tracking patient journeys to detect bottlenecks in diagnostics or treatment.
• Finance: Monitoring purchase-to-pay or order-to-cash cycles for compliance and efficiency.
• Service Processes: Revealing hidden process variations in customer service or IT support systems.
  Example: A company uses Process Mining to analyse order fulfilment data and discovers repeated approval loops that delay shipments. Simplifying the approval path reduces lead time by 20%.

Relevance / Impact

Process Mining enhances operational excellence by combining Lean thinking, Six Sigma analytics, and data science. It transforms hidden process data into actionable insights, allowing organisations to make evidence-based improvements. By providing transparency, it supports root cause analysis, continuous improvement, and digital transformation initiatives.

See also

• Business Process Management (BPM)
• Business Process Redesign (BPR)
• Process Layout
• Process Mapping