Process enhancement is a technique used in process mining that focuses on improving an existing process model by incorporating additional knowledge or data. It's different from process discovery and conformance checking, which are other key techniques in process mining.

1. **Process Discovery**: This is the foundational technique in process mining, where a process model is constructed directly from event logs. The goal is to uncover the actual process flow as it happens in reality, without any prior knowledge of the process. Techniques like Alpha, Heuristics Miner, and Fodina are used for process discovery.

2. **Conformance Checking**: After a process model has been discovered or manually designed, conformance checking compares this model with the actual behavior recorded in an event log to identify differences (non-conformances). This helps in understanding where deviations from the intended process occur. Techniques like Alignment Mining and Fitness Metrics are used for conformance checking.

3. **Process Enhancement**: Unlike process discovery and conformance checking, process enhancement assumes that a base process model already exists, which is typically created by domain experts or using process discovery techniques. The goal of process enhancement is not to create a new model from scratch, but to improve the existing one using additional data or knowledge.

   - **Data-driven Enhancement**: This involves incorporating additional data from the event log that wasn't used in the initial model creation. For example, timestamps can be used to add information about process durations, resource utilization, or performance metrics to the process model.

   - **Knowledge-driven Enhancement**: This involves adding domain knowledge to the existing model. Experts may provide insights into why certain activities are performed, what decisions are made at specific points, or which data is important for particular tasks. This knowledge can then be integrated into the process model.

The key difference between these techniques lies in their starting point and goal:

- Process discovery starts with no prior knowledge of the process and aims to create a new process model.
- Conformance checking compares an existing process model with reality to find deviations.
- Process enhancement takes an existing process model as its starting point and seeks to improve it by adding additional data or knowledge.

In summary, while process discovery is about uncovering unknown processes, conformance checking is about validating known processes, and process enhancement is about improving known processes.