NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
NICE WFM 7.0’s Forecaster unlocks a high level of transparency into interaction history, allowing you to centrally forecast, schedule and manage contacts between multiple locations and ensure that site- and enterpriselevel objectives are met. With more than two thousand customers and two million users depending on its unparalleled ability to fine-tune the most precise forecasts, Forecaster allows you to plan and respond to the peaks and valleys of customer history through automatic collection of key historical data from all types of contact sources:
• Automatic call distributors (ACDs)
• Outbound dialers • Multi-channel routing platforms
• Back-office employee desktops
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