Predictive Routing Weight Configuration Impacting Agent Performance Metrics

Observing anomalous data in the Agent Performance dashboard following the activation of Predictive Routing rules. The environment utilizes EU-West region settings with a standard queue configuration. When specific interaction attributes are weighted heavily in the routing algorithm, the ‘Average Handle Time’ metric displays significant variance compared to historical baselines. This discrepancy suggests that the routing logic may be influencing agent workload distribution in a manner that skews performance reporting.

The goal is to determine if Predictive Routing adjustments can be isolated within performance views to validate data integrity. Current attempts to filter by ‘Routing Method’ in the Queue Activity view do not provide granular visibility into individual agent assignments based on predictive scores. Is there a recommended methodology for correlating routing weight changes with agent performance deviations? Additionally, are there known limitations in the Performance Views API regarding the attribution of handle time to specific routing strategies? Assistance in aligning these metrics for accurate business reporting would be appreciated.

Predictive routing weights don’t directly alter AHT calculations, but they can skew data if high-priority interactions are routed to agents with different handling patterns. Check if your bulk export metadata includes the routing_weight attribute to correlate specific weights with individual AHT spikes. This helps isolate whether the variance is due to routing logic or actual agent performance differences.