We have a complex multi-skill routing setup in Genesys Cloud where agent capacity is dynamically adjusted based on their current WFM status. The environment runs on the latest stable release, and we are using the standard WFM APIs to manage schedule adherence and shift trades.
The issue arises specifically when agents perform shift swaps via the self-service portal during peak hours. When a swap is approved and the schedule updates, the Predictive Routing engine seems to lag in recalculating the available capacity for specific skills. This results in a mismatch between the WFM published schedule and the real-time routing queue depth.
We are seeing a spike in abandoned calls for high-priority skills during these transition windows. The logs show that the agents involved in the swap are still marked as ‘Available’ in the routing engine for their previous skill set even after the swap is confirmed in WFM. This causes the predictive algorithm to overestimate the available resources, leading to longer wait times and increased abandonment rates.
We have verified that the WFM webhook integration is functioning correctly and that the status updates are being pushed to the routing engine. However, there appears to be a processing delay or a caching issue within the Predictive Routing service that prevents immediate synchronization.
We have tried adjusting the skill priority settings and tweaking the overflow rules, but the problem persists. The delay seems to be around 30-60 seconds, which is significant for our high-volume inbound queues.
What is the correct way to force an immediate recalculation of agent capacity in Predictive Routing when a WFM shift swap occurs, or is there a known workaround to minimize this synchronization delay?