What does the Weighted Historical Index method utilize for creating forecasts?

The Weighted Historical Index method focuses on generating forecasts based on previously captured historical data within Genesys Cloud. This approach leverages past call volume and performance metrics, taking into account factors such as seasonal trends, anomalies, and patterns that have been observed over time. By weighting historical data effectively, the method is able to account for variations in performance and improve the accuracy of forecasts.

The rationale behind this method is that historical data serves as a reliable indicator of future performance, especially when it is supplemented with adjustments for recent trends or significant changes in operations. This allows businesses to create more nuanced and informed forecasts that can better anticipate future workloads, leading to more effective workforce management.

In contrast to other methods mentioned, such as real-time data analysis or agent workload reports, the Weighted Historical Index method is fundamentally rooted in historical performance data. Current performance metrics might not capture longer-term trends, which are essential for creating robust forecasts, and therefore are not the primary focus of this method.