Workforce management is a term that is used rather widely in today’s organizations. Particularly when it comes to reducing overtime costs. Whenever conversations about the reasons behind overtime ensue, the difficulties of predicting the right number of team members to match actual upcoming demand seems to be at its heart. Improved “workforce management” is typically what is called for as a result of those conversations. But what does “workforce management” really mean and how does it work?
According to Wikipedia, “Workforce management (WFM) is an institutional process that maximizes performance levels and competency for an organization. (…) As workforce management has developed from a traditional approach of staff scheduling to improve time management, it has become more integrated and demand-oriented to optimize the scheduling of staff.”
While the description is accurate, it is the actual implementation of demand-oriented scheduling that many organizations struggle with. Additionally, while “maximizing performance levels” is a reasonable business goal, successful workforce management goes beyond the monetary benefits to a company. A true, inclusive workforce management plan places equal—or greater—emphasis on the well-being of its employees. Using the example of reduction in overtime, the end result may, of course, be the same: less overtime resulting in a more balanced work-life experience for the employees, and lower payroll expenses for the organization. However, it is the intention behind team scheduling that makes a difference and improves employee morale—which in turn has its own positive effects on profit. And to take it even further, a balanced employee will be able to provide a much better customer service experience. Because no one likes to be at the receiving end of a stressed or overworked team member.
But that still doesn’t solve the challenge of how to actually forecast upcoming demand in order to build those balanced team schedules. Wikipedia also addresses this challenge in a separate paragraph titled “Software”. It states, in part, that “By using a software solution for demand-oriented workforce management, planners can optimize staffing by creating schedules that at all times conform to the forecasted requirements. (…) This is achieved by establishing likely demand by analyzing historical data (such as the number and duration of customer contacts, sales figures, check-out transactions or orders to be handled). Many workforce management systems also offer manual adjustment capabilities.”
Again, while the description is certainly correct, the leading products in today’s workforce management industry go a few steps further. When it comes to “establishing likely demand”, historical data is indeed of great importance. As certain repetition exists in customer demand cycles, any workforce management software should apply as many learnings as can be gleaned from past figures and behavior. However, the more advanced software solution providers also incorporate external and future data. The reason this is so important is that it allows for a larger set of data to be analyzed – going beyond yesterday’s figures. These data sets can be anything relevant from weather to economic factors. Further, if employing a software that uses applied artificial intelligence to create its demand prediction, the forecast models will be developed in more depth and, what’s even better, will continue to “learn” and further improve over time. So rather than just recycling yesterday’s data from a spreadsheet or off-the-shelf software package, AI will analyze all information it is supplied with and weigh each input with its appropriate level of importance, to ultimately build a prediction model that is virtually impossible to be matched by any human. As Wikipedia points out, manual adjustments are an option in many software solutions, and are important to allow for ultimate scheduling control by management.
Finally, the leading software solutions in workforce management will be able to assign schedules to team members based on the predicted future demand, as well as the skill level of each employee. As noted above, manual adjustments should always be an option for managers to ensure the algorithm can be taught further, and to account for some instances that may not have been input into the data AI is working with (like an unscheduled early store closing or a valued customer that may be accommodated although there is no available appointment slot).
Workforce management software is certainly a valuable tool for any organization. Those businesses that deal with fluctuating demand will benefit the most from AI-powered software, as the superior prediction models generated by AI truly improve business operations — for business owners, customers, and employees.
Author: Daniela Kister
Daniela is responsible for marketing and design at Weave Workforce, a workforce optimization company providing AI-based forecasting and scheduling to match the fluctuating demand of service-oriented businesses. Having worked in automotive, consumer goods, education, healthcare, and not-for-profit management on three different continents, Daniela is passionate about time management and its benefits on business revenue and work-life balance.