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There are many steps in data review and analysis before the forecasting process begins. In this seminar, you will learn about the up-front essentials of forecasting workload. Hear about the sources of input data and how to decide which best represents future needs. Learn about agent work state activity and techniques to ensure you have predictive AHT data. Practice identifying and adjusting for data aberrations and other considerations for data clean-up before it enters the forecasting process.

Seminar attendees will learn to:

  • Outline the elements of forecast workload.
  • Identify the impact of work state usage on forecast data accuracy.
  • Identify data anomalies that require adjustment.
  • Adjust data aberrations to improve forecast accuracy.