WFM Finds a Better Direction

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The year 2015 looks exciting for contact center and back-office workforce management (WFM) solutions. After more than three decades of slow adoption and even slower innovation, this essential contact center IT sector is finally attracting companies' interest and investment dollars, driving a desperately needed round of research and development (R&D) and innovation. What makes this wave of R&D investments interesting is that much of it is coming from emerging competitors or is being targeted to the developing back-office WFM sector.


Workforce management is a mission-critical solution for multichannel contact centers with 50 or more agents. It remains the most important productivity tool in many contact centers because it forecasts staffing requirements and schedules agents. WFM solutions are dependent on mathematical algorithms to forecast interaction (calls, email, fax, chat, SMS, social media, etc.) volumes and to identify optimal work schedules for agents. There are two primary methods of addressing this mathematical challenge: algorithms and simulations.

Many established WFM vendors developed or acquired their algorithms many years ago. While they have made some changes to incorporate new channels and address inherent weaknesses of the Erlang algorithm, these software companies are not invested in the science of WFM and are not dedicating time and effort to create or enhance the underlying math. (It's more a question of tweaking what they have to address the demands of the market than investing in the future of these solutions.) While there are many reasons for this lack of interest, it is primarily because vendors have a limited amount of R&D dollars and invest those that they have in solutions for which they anticipate seeing a significant return. Additionally, leading contact center WFM solutions are now owned by vendors that view WFM as a complementary module in a greater suite and are not dedicated to the underlying science. As a result, these companies are not employing the Ph.D.s or researchers committed to moving this science forward.


Simulation is a science dedicated to replicating real-world experiences. As it relates to contact centers, this means identifying the optimal allocation of scarce resources (agents) to handle the forecasted volume of interactions within a service level. Simulators are designed to start the process by modeling the existing environment. This is where the complication arises for contact centers. It typically requires a significant amount of start-up time, resources (professional services), and money to develop the initial model, as well as a great deal of time and effort to keep the model up to date, as variables inevitably change within the contact center.

A second challenge for simulators is knowing where and when to stop the models. Simulators typically go through a process where they modify a variable or two and then rerun the model until an optimal result is obtained. As there are so many variables to control (and change) in a contact center, it can be difficult to know when to stop the process, as a simulation could take hours. If these issues could be addressed practically and cost-effectively, many believe that a simulation model would yield better results (and schedules) than many algorithm-based solutions.

Some of the WFM vendors have included simulation functionality in their solutions for the purpose of validating the system's primary algorithm-based outputs. However, in most cases, these simulators are limited in the scenarios that they are running and testing.

Given the growing complexity of contact centers, including the increasing number of channels and, more recently, the introduction of adaptive real-time intelligent routing, DMG expects to see simulation play a more important role in the science of contact center WFM.


Despite the inherent mathematical limitations of Erlang, most contact center WFM solutions are pretty good at forecasting and scheduling for phone calls. Many packaged WFM solutions address the weaknesses of Erlang by modifying the basic model. Some of these solutions also do an adequate job of forecasting for noncall interactions on a stand-alone basis. Generally, a challenge arises when these solutions have to forecast and schedule on a combined basis for various channels with different service levels.

Multichannel contact centers have been discussed in the market since 1997, but companies are finally building them. For years, organizations have handled multiple channels, but typically on a siloed basis, in which different groups of agents were assigned to each channel or where agents' days were split among channels. Most companies use different servicing systems to handle each channel they support, which produces inefficiencies and training challenges. In the past, it did not matter that WFM solutions were not designed to generate schedules for universal agents, as few contact centers employed multiskilled staff. But this is changing, and it is presenting a challenge for many of the WFM products in the market.

When back-office work is added to the mix of interactions handled by contact centers, the challenge grows. Back-office work has different mathematical characteristics from phone calls, which, by definition, do not have a backlog. Back-office work is often deferred and therefore has a backlog. A back-office work item typically has multiple tasks or components, and an employee is likely to work on multiple items (or have multiple items open) at the same time. The service level for back-office work is also different. Each task in a work item can have its own service level, which might be longer than one year in duration. Erlang was designed for short-duration phone calls that arrive continuously, without disruption. Therefore, the WFM solutions that apply Erlang to email or other types of nonphone activities are not effective. And, despite vendor claims to the contrary, some form of automation is not necessarily better than none.


The cloud is slowly democratizing the world of contact centers, and small organizations with 20 or less seats are increasingly demanding their right to use WFM. This is a wonderful problem for the WFM competitors, particularly for vendors that offer multitenant solutions from well-designed and easy-to-use provisioning environments. The challenge is that Erlang's inherent limitations become more glaring in small-volume contact centers; the result is a significant amount of overstaffing. However, in this case, the argument that some automation is better than none appears to be valid. The deficiency of Erlang in these smaller environments, however, is another challenge that contact center WFM vendors need to address and overcome.


The WFM market has finally woken up. End users want better and more accurate WFM solutions for their contact centers. Since there are more offerings available than at any time in the history of this market, companies are rightly asking for better solutions with vastly improved user interfaces, and prospects no longer feel tied to their incumbent vendors. Although most large contact centers have already been penetrated with WFM solutions, these solutions are not as "sticky" as they were in the past.

DMG estimates that the number of back-office/branch employees is 2.3 times higher than the number of contact center agents. Increasingly, companies are starting to consider the use of WFM in their back-office operating groups, and many are already using it to forecast and schedule for branches and retail outlets. The potential of expanding sales to a larger audience is appealing to the WFM contact center market leaders, but it has also attracted vendors from many geographies, as well as new competitors. Prospects of all sizes are encouraged to push vendors to deliver feature-rich and flexible WFM solutions that allow them to do what they want and need for their companies instead of being limited by the capabilities of the existing solutions.

Donna Fluss ( is founder and principal of DMG Consulting, a provider of contact center and analytics research, marketing analysis, and consulting.

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