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          Workload Histories and Intelligent Forecasts

          Workload Histories and Intelligent Forecasts

          A workload history aggregates all or some of a contact center’s historic workload volume data. Use a workload history as the foundation to build an intelligent forecast, which predicts future work volume based on your historic trends.

          Required Editions

          Example
          Example
          Note
          Note Workforce Engagement is scheduled for retirement. See Workforce Engagement Retirement.
          View supported editions.

          Understand Your Workloads

          You can visualize and identify trends in your historical workload volumes by using workload histories. When you create an intelligent forecast from a workload history, Workforce Engagement predicts future volume.

          For example, this dashboard shows the contrast between actual volume from a workload history and predictions for the forecasted volume.

          Intelligent forecast dashboard

          If you use an Omni-Channel queue-based routing workflow, you select which queues to analyze when you create a workload history. The dashboard shows data for your selected queues. The skill field identifies the queue for the corresponding workload volumes.

          Intelligent forecast created from a queue-based routing workflow

          To identify trends such as seasonal demands, you can filter the dashboard by date ranges, time intervals, and other criteria.

          Note
          Note There’s a one-to-one mapping between each forecast and its workload history. If you create a forecast from a workload history, you can’t reuse that history to build a new forecast.

          Forecasting Models

          When you set up Workforce Engagement, choose Holt-Winters or Machine-Learning as your forecasting data model.

          Holt Winters Machine Learning
          Faster results. Takes more time.
          Sensitive to recent trends. Greater accuracy.
          Can generate forecasts for up to 12 weeks. Can generate forecasts for up to 52 weeks.

          With the Machine Learning model, the forecast also includes upper and lower bounds for predicted workload volumes. The data graph view includes a confidence band that reflects the certainty of the predictions. A smaller delta between upper and lower values indicates a higher degree of confidence.

          Data graph view displaying the confidence band on an intelligent forecast

          You can create a workload history from 3 weeks to up to 260 weeks (5 years).

          When Machine Learning is the forecasting model, create a workload history that’s at least three times as long as the forecast that you want to create. For example, use a workload history that’s 60 weeks to create a 20-week forecast.

          • Admin Checklist for Workload History and Forecast Setup
            Format your data to ensure that your team can create workload histories and intelligent forecasts.
          • Workload History and Intelligent Forecast Glossary
            To make sense of all the data going into your workload history and intelligent forecast, read this glossary. Refer to it as you move through the setup steps.
          • Create a Workload History
            A workload history aggregates all the historical channel data that you specify. When you create an intelligent forecast later, it makes predictions based on data in a workload history.
          • Create an Intelligent Forecast
            You created a workload history to aggregate your past work volume trends. Use that workload history to create an intelligent forecast that predicts future case volume based on historic trends. As your real workload catches up to your forecast, the two display in the dashboard, side by side, for comparison.
           
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