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  • 1.  do user deletions cause downstream forecasting issues

    Posted 14 days ago
    Good morning,
    We are seeing a situation where when an employee leaves the contact centre, our IT team (even though we have asked them not to) deletes the user from the system.
    Are there any downstream issues that this might cause, I am particularly concerned that it might throw off staff forecasting calculations, and forecasted Service Levels. For example on Saturday August 1st we received 5 calls less than forecast, (well done me), and we received a 77% SL versus a forecasted 56%.
    On the schedule I can see that 2 deleted agents had worked that day, but on the intraday report they are not showing for the intervals that they were logged in to work. During the 30-minute interval 2:30 - 3PM we had 10 scheduled in the "Scheduled Vs. Require Graph" on the schedule, but in the intraday report for that interval it only shows 8 were scheduled. I forecast we would get 18 calls that interval and we received 18 calls, but instead of the 64% Service Level, we received 100% Service Level. I know both of these deleted agents took calls that day and our AHT was longer than forecast for that interval, 319 seconds versus 280 seconds.
    As a result, will the system think now that we are able to achieve better results with fewer staff? Or am I worrying needlessly?

    #CapacityPlanning
    #Forecasting
    #Intraday,Shrinkage,Adherence

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    Conor
    Workforce Management Specialist
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  • 2.  RE: do user deletions cause downstream forecasting issues

    Posted 13 days ago

    Even if an agent is deleted, their past schedules still exist (you just won't be able to see a user name and instead Unknown) and would still be accounted for if you looked at a past day in intraday.

    For schedule agent count we sum up the scheduled on queue time for all agents honoring your filter conditions and then divide by corresponding interval length (consistent in schedule editor and intraday for the same published schedule for that period).

    If nothing obvious then I would suggest opening a support ticket.

    When it comes to staffing requirement and performance prediction, there are many facets that come into play. https://help.genesys.cloud/faqs/why-are-staffing-requirements-higher-or-lower-than-expected/



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    Jay Langsford
    VP, R&D
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  • 3.  RE: do user deletions cause downstream forecasting issues

    Posted 12 days ago

    hi @Conor Twomey,

    I think your concern is valid, especially when you see discrepancies between the Schedule view and Intraday metrics after users have been deleted.

    From a forecasting perspective, Genesys uses historical workload data (volume, AHT, arrivals, etc.) to generate forecasts, so deleting users should not directly change the historical contact demand. However, if deleted agents are no longer represented consistently in staffing and intraday reporting, it can create the perception that the same service levels were achieved with fewer scheduled resources than were actually available.

    If historical staffing records are being understated, I would be concerned less about the forecast itself and more about any future analysis that compares required staffing versus actual staffing, occupancy, productivity, or planning assumptions derived from historical performance.

    Jay's comment suggests that historical schedules should still be retained and counted, even when the user record has been deleted and appears as "Unknown". Based on that, the difference you're seeing between 10 scheduled in the schedule and 8 scheduled in Intraday sounds more like a reporting inconsistency than expected behavior.

    My recommendation would be:

    1. Open a support ticket and provide the specific interval where the discrepancy exists.
    2. Verify whether the deleted users appear as "Unknown" in historical schedules.
    3. Review any historical reports used for staffing analysis to confirm that deleted users are still being included in the calculations.
    4. If possible, establish a process with IT to deactivate users rather than delete them, since preserving historical workforce records is generally a best practice for reporting, auditing, and WFM analytics.

    In short, I wouldn't expect user deletions to directly make the forecasting engine assume that fewer agents can achieve higher service levels. But if historical staffing data is not being represented correctly in reports, it's definitely worth investigating to ensure future planning decisions are based on accurate staffing history.

    Regards,



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    Cesar
    INDRA COLOMBIA
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