In part one of the blog series, we summarized how AI is augmenting today’s WFM team. We also took a small peek into the future to imagine where AI might be taking us—more to come in part three. But now, let’s turn to the present—what tools are already available to augment and ease the workload for your team?
AI has come a long way in the contact center, and added features are available more than ever to manage schedules, boost forecasting, improve customer experience, and optimize staffing. NICE CXone WFM, for example, includes many applications that help in these areas.
In forecasting, CXone WFM offers an “Auto Select” option. This feature compares multiple forecasting models against one another and picks the best method per skill for both volume and average handle time (AHT). No gut feelings or “best guesses” are required; instead, CXone can leverage all the information available and tap several methodologies at once to give you a science-backed path forward customized for different teams and skill areas.
CXone WFM also has a lot to offer in scheduling. The Closed Loop Schedule Optimization tool takes a unique machine learning approach to generate schedules. By employing a closed-loop feedback process, the system starts with some self-educated “guesses,” then learns and fine-tunes information with each successive iteration of a planning and scheduling “pass.” The user can determine how many passes and how much time to allow the system to run through this learning process. This allows the user to give the machine more opportunities to learn from the outputs of multiple iterations.
After running through multiple schedule combinations, the tool will present you with the most optimal schedule possible. Better yet, the scheduling tool is intelligent enough to recognize if one of the initial passes is good enough to be the final schedule set, rather than continuing to optimize already optimal schedules. This is especially applicable to environments with limited scheduling flexibility.
To create the most optimal schedules, CXone WFM needs an inherent understanding of how contacts are being routed to agents. Maintaining this logic in a WFM tool can be daunting, but CXone WFM has infused AI into this process by automatically creating these rules any time a new skill is added. Customers only need to modify the rules if they have specialized configurations.
In addition, because staffing conditions can change greatly during the day, making last-minute adjustments a common occurrence in contact centers, CXone WFM’s Schedule Optimization helps managers configure optimization rules that can constantly review opportunities to move lunches and breaks to ensure the best possible coverage.
This is just a small sampling—and only the beginning of where AI is going. A new technical era is dawning, and with it comes new AI benefits. Part three of this series will explore the future of AI and WFM.
