Process mining is a method that utilizes data mining algorithms to analyze business processes. This approach allows business analysts and IT experts to understand and review the performance of various business processes within a computer system or IT network. 

Anomaly detection plays a critical role in process mining, because it identifies irregular, unusual or unexpected patterns that deviate significantly from the standard, normal behavior, which potentially represent instances of a significant issue, such as a security breach or a system failure.

Here are a few ways anomaly detection enhances operational security within IT networks.

1. Timely Detection of Security Threats: Unusual activities like unusual login attempts, sudden database changes, or unusual data transmission can be instantly flagged.

2. Fraud Detection: Anomaly detection in network traffic and user behavior can help identify malicious insiders or compromised users. Effective anomaly detection algorithms can spot fraudulent operations and aid in early detection and prevention.

3. Improvement in System Performance: Anomalies can indicate bugs or performance issues. Early detection allows IT teams to rectify them before they become significant issues.

4. Minimizing False Alarm: Sophisticated anomaly detection techniques help minimize the number of false alarms, letting security teams concentrate on true threats.

5. Regulatory Compliance: Some industries have regulatory requirements for identifying and correcting anomalies. Advanced detection helps maintain compliance and avoid penalties.

In conclusion, anomaly detection in process mining is fundamental for enhancing operational security in IT networks. It facilitates the early detection of issues, allows timely rectification, optimizes system performance, aids in regulatory compliance, and overall, contributes to the robustness of the IT system.