Hire a team of qualified analysts to manually label the historical performance data, then train a model on this dataset.

Create a simple heuristic, like a z-score, to label historical performance data and use this for real-time monitoring.

Develop a heuristic to label historical data, then train a model to predict anomalies from this labeled dataset.

Train a time-series model to predict performance values and alert on significant deviations from predictions.