- **Description:** Deep dive analysis of model prediction errors - **Activities:** - Analyze systematic errors: - Identify consistent over/under-prediction patterns - Analyze error by time of day, department, etc - Quantify systematic bias - Identify error patterns: - Identify scenarios with high errors - Analyze error distributions - Identify error outliers - Propose improvement areas: - Suggest features that might help - Recommend data collection improvements - Recommend model architecture changes - Create error visualizations: - Residual plots - Error distributions by category - Prediction vs actual scatter plots - Document insights: - Write findings and recommendations - Create error analysis report - Suggest next steps for improvement - **Deliverables:** Error analysis report, recommendations for improvement