About schedule calibration

Note: Schedule calibration does not apply to AI-powered schedules.

Calibration attempts to adjust forecast and scheduled requirements by looking at past service performance compared with predicted service performance.

If calibration is enabled, then scheduling and re-forecasting will look at published schedules or actual agent activity information in the recent past along with historic service performance and adjust requirements accordingly.

Calibration first looks to see if there is enough published schedules and if not it will then look to see if there is enough actual agent activity information. If either of those cases is true, it then runs simulations using that information along with historic volume and handle time coming up with predicted service performance. That service performance is then compared to historic service performance.

If historically higher service performance has been attained compared to predicted service performance, then future requirements are adjusted downward. Conversely, if historically lower service performance has been attained compared to predicted service performance, then future requirements are adjusted upward.

Things that can attribute to lower or higher service performance compared to predicted service performance include: agent shrinkage, adherence, and conformance, non-scheduling unit resources handling scheduling unit interactions, scheduling unit resources handling interactions outside of the scheduling unit, forecast accuracy, and other operational behaviors, both good and bad.