Schedule Fairness Intelligence In recent years, em...

Schedule Fairness Intelligence In recent years, employee engagement has grown in importance for contact center leaders—and for a good reason. Typically, engaged employees contribute about 20 percent more revenue and are 44 percent more productive than employees who are categorized as satisfied. And scheduling is one of the most critical ways to ensure employees are engaged—more than one in four employees who feel they have no support for work/life balance say that they’ll leave within two years, while only 17 percent of those who feel their work/life balance is supported are planning to leave. Artificial Intelligence (AI) is used by employee engagement solutions to give employees a degree of ownership in the often overwhelming process of meeting customer demand. Machine Learning (ML) can also be used to create a fair workplace that replaces or enhances traditional seniority-based assignment processes. Some examples of this in action include: Adaptive Assignment: When workforce management AI is combined with adaptive intelligence, work schedules can be assigned using the uniquely identifiable metrics, attributes and preferences of each employee. Preference Persona Assignment: As robust personas are managed and updated by employees, an AI machine monitors constantly for changes in employee preferences and adjusts the schedule accordingly. Details such as, shift availability can be customized by staff, and the machine will automatically take into account their preferences when scheduling. Policy Assignment: Intelligent ML policies have been integrated into modern workforce management solutions that create schedules and manage assignments in a balanced way while meeting customer demands. There are algorithms designed in the technology to balance the needs of both the employees and the business. Personalized Fairness Assignment: Often, employees want to volunteer to work specific days of the week, weekends or holidays, while their colleagues may want to be rotated through the assignments routinely. ML workforce management tools can monitor assignment history, fairness credits, volunteerism, work rules, and business need to manage the assignments fairly. AI’s utility and promise is an exciting shift for contact centers. The technology’s ability to learn the unique, decision-influencing factors of any omnichannel environment and rapidly apply intelligence is already benefiting contact centers, back-office operations, and branch environments. Adopting this technology frees your staff to focus on those activities and thought processes that require a human touch. Q: Some examples of scheduling fairness intelligence include:

A、Adaptive Assignment

B、Preference Persona Assignment

C、Policy Assignment

D、Personalized Fairness Assignment