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  • 1.  Predicted Metrics - Intraday Monitoring view in WFM

    Posted 05-11-2023 10:37
    No replies, thread closed.

    Hi Community, 

    I was wondering if anyone knows how the predicted metrics under the Intraday Monitoring are calculated, more precisely the predicted Service Level or have any insights or documentation to share (other than what we could find in the resource center) on this subject?

    Under the Intraday Monitoring view, we are noticing odd numbers for the predicted service level on some intervals throughout the day. On some intervals, we are getting a very low % of predicted service level when our number of forecasted calls, AHT vs agents scheduled seem to be sufficient to meet our service level goals. 

    Also, we are noticing high numbers for the predicted ASA. The predicted service level for the day shows as 90%, but the ASA for the day seems elevated based on a projected service level of 90%.

    Note : Our Average Speed of Answer and Abandonment Rates are turned off in our Service Goal Template. 

    Thank you for any advice you can provide! 


    #Genesys Cloud CX
    #Workforce Management
    #Performance Management
    #GeneralQuestion

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    Tam Cao
    i3Vision Technologies Inc.
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  • 2.  RE: Predicted Metrics - Intraday Monitoring view in WFM

    Posted 05-12-2023 06:39
    No replies, thread closed.

    Hi Tam.  If it is just the occasional interval that is presenting unexpected service levels, could it be an accumulation of previous intervals creating a predicted bad performance?  The interval in isolation may look well-resourced, but there could potentially be an overspill from previous intervals and the system may be predicting interactions queueing for longer than your service goal dictates. 



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    Heather Henderson
    Sabio Ltd
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  • 3.  RE: Predicted Metrics - Intraday Monitoring view in WFM

    Posted 05-12-2023 07:50
    Edited by Tracy Vickers 08-04-2025 05:26
    No replies, thread closed.

    Predicted metrics are derived by ML/AI, nightly built models, continuous simulation, and other items.

    Good predictions are dependent on good forecasts (volume, aht, and pattern) and good configuration (ensuring you are not splitting shared load across BUs, ensuring agents don't work volume from other BUs, that you have reasonable service performance goals compared to what you actually attain, etc.).

    The following article addresses staffing requirement prediction, but there is enough info there to look at other issues you might have:
    https://help.mypurecloud.com/faqs/why-are-staffing-requirements-higher-or-lower-than-expected/

    If you cannot find anything obvious, then I would recommend opening a support ticket.



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    Jay Langsford
    VP, R&D
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