BY ELIMINATING THE NEED FOR SHIFT AND SCHEDULE MANAGEMENT , BUSINESSES EMPOWER THEIR AGENTS TO HAVE CONTROL OVER THEIR WORK HOURS .
Many contact centers operate 24 / 7 , requiring agents to work shifts during irregular hours , including weekends and holidays ; this can be challenging from a work-life balance perspective .
One of the most significant opportunities for improving the agent experience is flexible scheduling . Yet contact centers are challenged to offer the flexibility employees demand . Fixed shift work is fundamentally at odds with what employees want . This may be why absenteeism and attrition have remained stubbornly high for 30 years .
Shift-bidding alone is no longer a viable solution . And businesses cannot hire enough WFM resources to manually adjust schedules to provide the required flexibility .
Scheduling bots leveraging AI are quickly becoming a game-changer for unlimited employee schedule flexibility . These bots make it possible to balance the scheduling needs of the organization with the needs of the employees .
The business impact is substantial , as are the options for schedule flexibility and agent autonomy .
To illustrate , a leading insurance company was able to save $ 2,000 per agent per year on average , including a 30 % reduction in agent attrition and 23 % reduction in agent absenteeism .
And in addition to the more than $ 300,000 annual savings the company achieved , a 32-point increase in employee Net Promoter Score ( NPS ) also resulted .
THE “ UBERIZATION ” OF WFM
The shifts we are seeing in the contact center mirror the flexible scheduling we are seeing in other sectors .
For example , rideshare vendor Uber uses a combination of algorithms and pricing strategies to determine the fare for each ride , aiming to balance supply and demand while providing a competitive rate for both riders and drivers . Uber drivers also have the flexibility to choose their own working hours without needing explicit approval from a manager .
Contact centers now have an opportunity to use this same approach to WFM via AI-infused bots that can automatically calculate the impact of shift changes based on forecasted volumes , capacity , and performance . With AI applied to WFM forecasting , agents can make autonomous scheduling changes without manager involvement or approval .
Incentives and gamification are other elements of this approach . For example , giving each 15-minute increment of the schedule a “ value ,” and agents are given “ currency ” to spend or earn points when making schedule changes .
In this scenario , an agent can choose to leave work early in exchange for using or earning points by offering not to work a shift when it ' s forecasted to be slow .
For example , employees can earn points when they make a change that is beneficial to the company , like choosing to work an interval for which the company is understaffed . Employees can then opt to spend those points to make changes to their schedule as needed .
These calculations are made in real-time , so as employees make changes , the model stays current . If employees maintain a positive points balance and don ’ t change the total number of hours they are working , they can make unlimited changes to align their schedules to meet their needs .
By eliminating the need for shift and schedule management , businesses empower their agents to have control over their work hours . This frees managers to focus on more critical aspects of customer support , such as coaching for quality and for compliance assurance .
Managers will then have more time to offer valuable guidance and support to agents , helping them improve their performance , enhance their customer service skills , and navigate any challenges they may face on the job . Ultimately , this shift in focus can lead to more efficient and effective customer support operations .
COACHING BOTS IMPROVE REAL-TIME GUIDANCE
Behind every happy employee is a supervisor equipped with AI-driven tools like coaching bots to drive continuous improvement in CX , compliance , and revenues , while ensuring every agent is performing at the top of their game .
AGENT EXPERIENCE For example , when customer service interactions involve negative sentiments , escalations , long silences , or multiple interruptions , real-time agent assist tools provide AI-driven , real-time guidance based on acoustic ( nonverbal ), linguistic ( verbal ), and desktop activity to employees working from anywhere .
Knowledge articles are surfaced to support timely and accurate responses to queries while also reducing cognitive overload for agents .
BY ELIMINATING THE NEED FOR SHIFT AND SCHEDULE MANAGEMENT , BUSINESSES EMPOWER THEIR AGENTS TO HAVE CONTROL OVER THEIR WORK HOURS .
In addition , these bots evaluate calls , identify non-compliance , and assign coaching for 100 % of voice and text interactions . Generative AI-powered scoring models enable them to extend beyond compliance or “ script ” scoring and accurately evaluate abstract concepts like agent empathy to ensure customers receive the best outcomes and experiences .
These real-time coaching tools provide immediate feedback on calls or interactions , helping agents correct mistakes or improve performance in the moment . Agents hone their skills more rapidly by learning from mistakes as they happen and receiving guidance on how to handle similar situations better in the future .
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