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How do I reduce false alarms from an anomaly detection system?
Model normal patterns first, including seasonality, weekdays and promotions, so predictable swings are not flagged. Then tune thresholds on past data, require anomalies to persist or exceed a money value before alerting, and feed back whether each alert was real. Fewer, better alerts are acted on more reliably.
Alert fatigue is the main reason monitoring projects fail: people learn to ignore noisy messages.
Tactics:
- Alert on residuals from a good forecast, not on raw values.
- Add materiality filters, such as ignoring deviations below a set amount.
- Combine signals, for example a drop in orders together with a rise in errors.
- Review a sample of alerts monthly and adjust.
- Give each alert type an owner and a suggested action.
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