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    Top view of a mobile phone on a woman's hand

    Eight Steps to Enable Flexible Scheduling for Engaged Agents

    by Andrea Matsuda
    October 28, 2022
    Share

    If there is one single perk that contact centers can offer to agents to recruit and retain staff, it’s flexible scheduling. With the ability to work from nearly anywhere, agents want to fit their work schedule to their lives, not the other way around.

    And, flexible scheduling isn’t just about retaining agents, it’s about engaging them to forestall quiet quitting. If you give them some of the flexibility they want, they will be able to focus on their work, even go above and beyond, during their scheduled shifts.

    But what are the ins and outs of scheduling flexibility? How can you ensure that your contact center is adequately covered? With the right WFM solution, the back and forth of forecasting, creating, and modifying schedules can be done easily, without the constant tinkering by a manager. Donna Fluss of DMG breaks down the eight steps for letting artificial intelligence and machine learning do the heavy lifting for you.

    The right WFM solution will handle this iterative process with ease, accurately predicting and managing your staffing needs while helping you keep your agents happy. The NICE WFM solution excels with flexible scheduling. While ten years ago the solution’s focus was primarily on forecasting the number of agents needed to make a work schedule, now there is a balance with providing more flexibility once agents receive their schedules. This allows your contact center to respond to the remote work reality of today, keeping and engaging agents in a way that wasn’t possible before.

    About the Author

    Andrea Matsuda

    Andrea Matsuda is a Senior Product Marketing Manager at NICE, where she directs product marketing strategy, thought leadership and sales enablement in connection with select Workforce Engagement Management (WEM) product categories. With over 10 years’ experience in the contact center, Andrea is passionate about helping contact centers deliver a world class customer and agent experience.

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  • The first step is collecting transaction volumes, or in other words, gathering how many customer queries come in during a given time frame, whether those are phone calls, chats, texts, or any other channel. Here AI is crucial—it can spot the patterns much easier than a human alone can.
  • You’ll need to generate the agent requirements for a given time period, based on the predicted inbound volume. Once again, AI is crucial here in determining how many agents are needed to handle a particular volume amount.
  • Next, agents come more into focus. As a supervisor, you will identify their strengths and weaknesses according to the different channels you use. One agent may be excellent on the phone, while another may be an agile typist, able to write and respond well to chats. Agents themselves provide their schedule availability according to the increments of your choice—15 or 30 minutes, for example. And the beauty of flexible scheduling is that the blocks of availability do not need to be contiguous—agents can specify chunks during the day when they need time off to tend to other responsibilities.
  • Agents then request their specific work schedules.
  • AI will do more heavy lifting by allocating hours to the agents. By offering higher pay, step by step, for less desired shifts, contact centers can be sure to fill those slots.
  • The schedules are then delivered to the agents.
  • If the agent needs a schedule adjustment—even at the last minute—the agent can put in the request, without directly contacting their supervisor, and the WFM solution will almost instantly approve or turn down the request based on pre-defined work rules.
  • Lastly, AI is working in the background, constantly monitoring the schedule, and will automatically ask other agents to fill in for those who can’t make their shifts, based on your pre-defined work rules. All of this is done without direct intervention of the contact center supervisor.