We have a schedule published in PureEngage WFM. in the Schedule Summary, stats for the schedule scenario are displayed, and the stats of interest are Service Level Sch and ASA Sch.
From the screenshot here, the coverage scheduled and calculated graph looks pretty close, which probably means that there shouldn't be any massive under/over-staffing for this activity.
However, at the 9:30am interval, the ASA Sch is calculated to be 2494 seconds (compared to the ASA Act of only 5.86 seconds). This huge ASA Sch discrepancy is affecting the SL% Sch. This is just one example of many if the schedule summary whereby the discrepancy is huge and cannot be explained.
The customer constantly looks to this SL% Sch to check if they expect under/over-staffing on the day, and are questioning how the ASA Sch numbers are derived.
The definition of ASA Scheduled is described here (https://docs.genesys.com/Documentation/WM/8.5.2/Admin/CCPerf#ASAS):
The Average Speed of Answer that was scheduled to be achieved, based on the scheduled number of agents. Calculated by using the inverse of the WFM's staffing forecast algorithm.WFM uses a modified Erlang algorithm to derive Calculated Staffing, based on the IV, AHT, and service objectives such as ASA that were stated when building the forecast. Therefore, to calculated the Scheduled ASA it uses that formula in reverse.I'm still stumped as to how this mystery algorithm came up with such seemingly random ASA Sch numbers.
#WorkforceManagement------------------------------
Cherith Law
Telstra Corporation Ltd
------------------------------