Overview
The WFM market has reached a critical juncture in its 50-year history, and it’s time for
WFM solutions to adapt to the times. Due to contact centers’ increased complexity from handling both synchronous and asynchronous interactions, WFM solutions need to optimize the use of both live agents and automated bots. Enterprises need new WFM applications built for today’s digitally oriented environments to accurately forecast and schedule.
In addition, WFM solutions must adjust to agent expectations for
schedule flexibility. With persistent high attrition rates, contact center leaders cannot ignore this expectation. WFM solutions need to be reimagined to support
flexible scheduling strategies, and these strategies range from bidding on shifts to agents building their own schedules to some combination of required and agent-selected shifts.
AI can help create these new WFM solutions. Deep learning, generative AI, and predictive analytics are some of the AI technologies being used in WFM technologies today. But in order for them to work at optimal levels, AI technologies need the right data, which will require changes to the current WFM status quo.
See the top issues in workforce planning today:
- Main forecasting challenges for contact centers
- Most pressing issues for WFM vendors
- Top reasons that agent scheduling strategies must adapt
- Most effective and non-effective agent scheduling strategies
Get insights on what to look for in WFM solutions.
