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📣📣🎉AI in Resource Management - Learn More 🎉📣📣

  • 1.  📣📣🎉AI in Resource Management - Learn More 🎉📣📣

    GENESYS
    Posted 13 days ago
    Edited by Tracy Vickers 13 days ago


    Hey fellow WEMers,

    Hello from Xperience in Denver – are you here, find the WEM Knowledge Hub Booth and say hi 😊

    Following on from our AI in Speech and Text Analytics last week, did you know there are lot of features that use AI in Resource Management!

    These include:

    • Automatic Best Method Forecasting

    And not only that - check out what is also on the Roadmap 🙌🙌🙌🙌

    • Continuous Forecasting

    Here we go again!  To put a bit more context into these and what they are, let me try to explain in my own way😉

    Firstly, lets cover Forecasting in Genesys Cloud - what does it do?

    It provides forecasters with a continuous and accurate AI/Machine Learning powered prediction of the future, with the ability to perform what-if analysis and create permanent overrides, so that workforce planners can effectively schedule into the future as business demands change.

    AI Forecasting in Genesys Cloud


    Artificial Intelligence in the forecast generation process provides extremely fast results.

            The average total processing time is around 10 seconds, with a maximum of 20 seconds.

            Total processing time is the time that each request waits in queue and the time it takes to process the request.

            Genesys Cloud batch processes all the optimal models nightly using an extensive set of historical data and chooses the best forecast using AI; when a forecast request is made to Genesys, the model and optimal parameters are already available.

            As your history changes and updates, the AI will make modifications to the variables and parameters and will provide the best model as time goes on. 

            Complexity may exist when a Planning Group definition changes during the day, where there is a need to recreate and re-optimize models, in which case it could take up to 150 seconds to complete the transaction.


    What are the Core Capabilities of Forecasting with Artificial Intelligence

            Completely automates the Forecast Process.

            Automatic Detection of Time Series Events

            Missing Data

            Operating Hours

            Leading or Trailing Zeroes

            Outliers and Anomaly detection

            Special Event Detection and Calendar day impacts.

            27 individual Algorithms, 1000's of configurations

            Average Forecast generates 200,000 iterations per model.

            Automatically chooses most accurate model.

    This enables Forecasters to make informed decisions such as:

            Filtering

            Metric filtering.

            Planning group filtering.

            Select 1/3/5-day period view.

            Weekly and Daily view.

            Charts

            Easily see the forecast in a chart.

            Drill into a specific date or time range.

            Adjust values directly in the chart.

            See your forecast vs actuals.

            Historic Overlays

            Easily view the forecast for days in the past.

            Easily add modifications to the forecast being viewed.

            Applies to various metric types.

            Auditing

            View who imported or made changes to a forecast.

    What is Automatic Best Method Forecasting?


    The Automatic Best Method forecasting method is the most sophisticated methodology offered in workforce management. It includes:

    • Built-in, automated capabilities for historical data cleanup
    • Outlier and calendar effect identification
    • Pattern detection including seasonality and trends
    • Best-of-best modeling to select from 20+ methodologies including ARIMA, WM, Decomp

    This AI powered forecasting method creates individual forecasts with the lowest possible error using: 

    • Best practices
    • Outlier detection
    • Mathematical fixes for missing data
    • Advanced time-series forecasting techniques 

    Ensemble forecasting

    Ensemble is a post processing activity that evaluates multiple forecasting models to create “one” forecast. 

    • By combining various models, we increase the overall accuracy of the forecast.
    • This helps avoid any situations where a peak or valley can be overvalued by one model.
    • Combines different forecasting models.

            Arima

            Holt Winters

            Random Walk

            And More

    Well, I do hope that gives you an insight of what we have now for Resource Management – isn’t AI great??

    Oh yes, it is, here's a little more about what’s on the roadmap…….

    Continuous Forecasting – will provide forecasters with a live two-year forecast in a new UI that updates nightly.

    Again, I am not party to too much more info than this but keep an eye out for more information as we learn more here on the WEM Community!


    #Forecasting

    ------------------------------
    Tracy
    Genesys
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