Write an article about workflow management systems (WFM). Include information about why this is so important for larger companies. Mention how machine learning has enabled this industry. Keep the word count under 400 words. Write this using the tone that might appeal to the manager at a mid to large-size business.
Organizations that try to function using traditional workforce management systems (WFM) often find themselves struggling – both at the service level and the organizational level. It becomes hard to attain the level of productivity, agility, flexibility, and cost-effectiveness required to adapt and be competitive in today’s marketplace when your staff is using spreadsheets and manual, onerous processes to make entries and keep records at different levels of the organization.

Oftentimes, the organization that relies on manual processes ends up either spending too much time scheduling the workforce or scheduling them at the wrong time. It’s even worse when by estimating anticipated workloads at the service center, managers end up over or under-scheduling the employees. This can lead to both employee and client dissatisfaction. 

It is imperative that managers take a proactive approach by implementing comprehensive and more advanced management and scheduling strategies to best prepare for unexpected events, such as surges in work volumes or unscheduled employee time off.  This is where a workforce management solution comes in. 

A better workforce management strategy focuses on all the activities needed to cost-effectively create and sustain a productive and happy workforce. For this to happen, managers must be able to schedule people optimally for the work available for them to complete. This means having consistent procedures and policies around managing employee time and scheduling, attendance as well as times off.
  
Naturally, there is optimal scheduling of employees at the service center, ensuring that the right number of employees handle the right amount of work at all times. 

Advancements in machine learning, computer modeling, and predictive and prescriptive analysis in big data present managers with smarter, more streamlined, and forward-looking approaches to employee scheduling – to replace the traditional, ineffective WFM models. These new approaches and tools present better and more effective ways to handle the everyday complexities that characterize the modern service center.  
