Anomaly Detection
Food for Thought
AI models can identify data points or events that deviate significantly from the norm.
Example
AI-powered anomaly detection predicts equipment failures in manufacturing by identifying deviations in sensor data, enabling proactive maintenance and reducing downtime.
Key Questions
- Where are there processes or systems where unexpected deviations from the norm could indicate a problem or opportunity
- What metrics or key performance indicators (KPIs) are crucial to the business, and how might anomalies in those metrics reveal valuable insights?
- Are there existing manual monitoring or auditing processes that could be automated or improved with anomaly detection?
- How could early detection of anomalies lead to cost savings, increased efficiency, or improved customer experience?
- What are the potential consequences of not detecting anomalies in a timely manner?
- Where are there areas in the business where predicting or preventing problems is more valuable than reacting to them?