Process Mining vs. Process Discovery: 5 Key Differences to know
- 12th May 2023
- 7 minute read
Process Mining and Process Discovery are powerful tools for improving business process management (BPM). The global process mining software market is set to reach USD 15,546.4 million by 2029, according to Fortune Business Insights.
These tools help organizations to understand their existing processes better, identify inefficiencies, and improve overall efficiency. However, many people confuse the two and this blog highlights their differences and provides guidance to choose the right tool.
What is Process Minning?
Process Mining is a data-driven technique that uses algorithms to discover, monitor, and improve real processes. It involves analyzing event logs to extract knowledge from data generated by systems of records.
The purpose of Process Mining is to understand how a process works, identify bottlenecks, and optimize process performance. By analyzing event logs, Process Mining provides organizations with insights into how their processes are functioning in real-time, identifying inefficiencies and areas where the processes can be automated.
Learn More: What is Business Process Mining?
What is Process Discovery?
Process Discovery, on the other hand, is a more traditional approach to process analysis that relies on manual methods, such as interviews and workshops, to gather information about existing processes.
The goal of Process Discovery is to document the current state of a process and identify opportunities for improvement. Unlike Process Mining, Process Discovery is not data-driven, and the insights it provides are limited to the knowledge and experience of the people involved in the process.
Learn More: Process discovery and hyperautomation: the hype is real but not all discovery approaches are equal
5 Differences between Business Process Mining and Data Mining
- Data-Driven vs. Manual
The most significant difference between Process Mining and Process Discovery is the approach used to gather insights. Process Mining is a data-driven approach that relies on analyzing event logs to extract insights automatically. In contrast, Process Discovery is a manual approach that relies on people’s knowledge and experience to identify workflows for automation.
- Real-Time vs. Snapshot Analysis
Another key difference between Process Mining and Process Discovery is the way they analyze processes. Process Mining is a real-time analysis technique that captures process data continuously, providing insights into how a process is functioning at any given moment.
Process Discovery, on the other hand, is a snapshot analysis technique that captures process data at a specific point in time, providing insights into how a process was functioning at a specific moment.
- Scalability
Process Mining is highly scalable, and it can be used to analyze large volumes of data quickly to identify processes that can be automated. Process Discovery, on the other hand, is less scalable and can be time-consuming when analyzing large and complex processes.
- Implementation
Process Mining requires access to event logs generated by system of records, and it’s often implemented with the help of specialized software tools. Process Discovery, on the other hand, can be implemented with the help of interviews and workshops, and it’s often a more accessible and affordable option for small and medium-sized organizations.
- Level of Detailing
Process Mining provides a high level of detail into how a process is functioning, identifying bottlenecks, and areas for improvement. In contrast, Process Discovery provides a higher-level overview of the process, identifying major process flows that can be automated.
Learn More: Business Process Mining vs. Data Mining: 3 Key differences
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