Date Published: November 17, 2020 - Last Updated 2 Years, 307 Days, 12 Hours, 55 Minutes ago
Call centers are constantly dealing with unexpected scenarios, but 2020 has taken this to an entirely new level. Centers have been forced to manage the pandemic’s many impacts, including remote work shifts and requisite operational changes, all while managing changing agent and consumer behaviors.
As we transition into 2021, call centers would be wise to leverage artificial intelligence, which takes control of real-time data to get ahead of unpredictable scenarios and ensure seamless customer experiences. With call center conditions constantly changing, companies must turn to AI-powered technology to optimize their operations.
Workforce planning is both an art and a science. Workforce managers leverage the science of historical call center data to generate forecasts and create schedules, then layer on the art of experience to refine and optimize plans. Still, a variety of circumstances can yield negative impacts for call centers that are difficult to foresee.
Macro events specific to different industries can spark volume increases, forcing call centers to pivot their operations on a dime. In utilities, this could be an unexpected severe weather event like a winter storm or tornado, causing power outages and volume to spike. Seasonal events, like open enrollment for healthcare or the holidays for retail, lead to surges in volume and the need for optimal staffing decisions. New product launches for the telecommunications sector can trigger changes in consumer activity which can be difficult to predict. While workforce managers know the intricacies of their particular industry and center, planning is only as good as the historical data that it leverages.
Micro events such as an error on a billing statement or typo on a website can cause unexpected call volume increases, wreaking havoc on an otherwise well-planned day. A wildly successful marketing campaign launched without communicating with the contact center can create a situation where agents learn about promotions from customers, leaving them unprepared and unable to assist effectively.
Humans often make decisions based on their emotions or previous experiences, rather than on logic. Both agent and customer behavior factor into the unpredictable nature of a call center. Managers cannot predict when agents will be late or absent, and consumer behavior has always been a variable in the staffing equation.
Now, agent behaviors have been further disrupted with the shift to remote work. Managers have less visibility and cannot rely on physical cues to determine whether agents are struggling. Gone are the days where managers are sitting in bays with agents, and a simple hand raise or frustrated face from an agent could be acted upon - these signs are much more challenging to identify virtually.
Likewise, consumer behaviors may follow historical trends, but their exact behavior is impossible to forecast with one hundred percent accuracy. Consumers choose when to call – often while trying to find the fastest path to resolution. They may reach out via chat while waiting to speak to a live agent, and post to social media when placed on hold. Often, their outreach is triggered by external events, but behaviors are unique to individual consumers and what kind of day they’re having, mood, or level of frustration.
The only way to ensure success in the face of unexpected scenarios is to act in the moment. Sometimes even the best plan isn’t enough and other times, a situation arises entirely out of the blue. Regardless, call centers must rely on data and technology to adapt operations appropriately.
An intelligent assistant may be one tool that can help. It can automate actions based on real-time data flowing through the call center. This includes making staffing changes depending on call volume, offering struggling agents assistance or wellness breaks and scheduling training and coaching sessions to ensure agents are engaged and prepared for any scenarios thrown their way—all without sacrificing service levels.
An intelligent assistant, powered by AI, that leverages the power of real-time data can help call centers avoid being ill-prepared in unexpected situations. It can serve as a safety net when the plan isn’t enough. This leads to smarter staffing decisions, higher agent engagement, lower attrition and better customer experiences - all factors driving value to the bottom line.