In general, Process mining is a technique used to analyze and improve business processes by extracting information from data systems. Waste detection in process mining involves identifying inefficiencies or non-value-adding activities in a process, such as unnecessary steps, delays, or rework.
These inefficiencies can lead to increased costs, longer lead times, and lower customer satisfaction. By using process mining techniques, organizations can discover and eliminate waste in their processes, leading to improved efficiency and effectiveness.
Some process mining techniques and tracks that can be used for waste detection:
- Idle Time Detection: Process mining can help identify periods of time where a process is idle or waiting for inputs, approvals or other resources, leading to unnecessary waiting times and delays. By analyzing the process deeply the process mining solution can identify where these idle times occur, and why not suggest ways to eliminate them.
- Redundant or Unnecessary Steps: Sometimes, processes can contain steps that are redundant or unnecessary, leading to additional work or delays. The Process mining solution can easily identify these steps, and suggest ways to eliminate them, thus reducing the amount of waste in the process.
- Conformance checking (like verifying Protocols and conformity)
- Bottlenecks: Process mining can also help identify bottlenecks in a process, where work is piling up, and causing delays.
- Rework loops or Rejections (exceptions): When work has to be redone or rejected, it can lead to additional waste in the process.
- Variations in Process Execution: Sometimes, there can be significant variations in how a process is executed, which can lead to inconsistencies and inefficiencies.
- Performance analysis (by analyzing trends for example)