By René LeBel
As a tool that brings us closer to virtual reality, simulators are used in a wide range of industries – from training pilots and soldiers and forecasting weather patterns to predicting call centers volumes. While simulators are better than nothing, in nearly every case the technology is a poor to average substitute for the real thing. Oftentimes, simulators lead to overconfidence in abilities or analysis.
The purpose of a workforce management (WFM) call center simulator is the ability to mimic call routing, given the routing rules of an automatic call distributor (ACD) while attempting to adjust agent work schedules to fit call volume and category requirements. In general, these simulators require that the user specify the various skill levels and contact routing rules by date periods. Simulators usually generate many different scenarios, leaving it up to the user to select the one that appears to be most probable, and they typically come in a one-size-fits-all package. This leads to three main sources of inaccuracies:
1. One size fits…one. How well can a generic application accurately simulate the contact routing algorithms of any ACD available on the market? To use the aviation industry as an example, airplanes, like contact centers, come in all sorts of shapes and sizes, so it makes sense that their flight simulators are specific to the plane type. For instance, it wouldn’t do much good to learn how to fly a Boeing 747 on a Cessna flight simulator.
Therefore, we might reasonably expect a similar decline in accuracy and usefulness with a WFM simulator if we try to force-fit a generic program into a contact center which typically has varying or unique needs and conditions.
2. Experts only. Like other kinds of sophisticated simulators, WFM simulators require significant input as well as intuition from the user to properly make forecast calculations. Simulators are not out-of-the-box applications for beginners and often are quite complicated. Looking again ata flight simulator, we would not get much information or usefulness from its dashboard without having already spent countless hours studying and training.
That’s the nature of WMF simulators – in order to approximate reality, they confront the user with what can be an overwhelming number of choices. Following the “garbage in, garbage out” (GIGO) principle, if WFM simulator users enter incorrect data or simply make guesses, the simulator will carry over that deficiency and output inaccurate forecasts.
3. I think the sun is shining. Finally, if the simulator does not take into account the existing workforce – such as overlapping skills or varying agent proficiency levels – to simulate and cover the resource requirements, the generated result can only be theoretical and is potentially based on inaccuracies or approximations. This is like a flight simulator that does not account for external conditions, such as wind and other weather. The simulated flight experience will likely be different than one in the real world, so the decisions or actions taken in the simulator may not be the same ones needed in real flight.
In the contact center, schedules vary with different scheduler input, making accuracy a constantly moving target. Therefore, any insight generated by a WFM simulator has limited value since it represents ideal or unique scenarios and may not be applicable to the actual workforce.
WFM call center simulators are valuable, if not indispensable, in learning the contact routing rules – just as flight simulators are critical to learning the different instrumentation of an aircraft and get the “feel” of real flight. But once training is complete, should a simulator be used to actually fly or, in the case of the contact center, for actual forecasting and scheduling?
Accuracy in forecasting is a foundation that must be built before attempting scheduling. With a solid forecast, the next step is to schedule your agents – not with simulated agents, but with those that you actually have and their real availability.
Best Practices for Greater WFM Accuracy: There are two keys to sound workforce planning: simplicity and precision. Where WFM simulators are the foundation, simple and precise software provides the necessary link to desired outcomes. By keeping things simple, users can minimize the areas where things might go wrong. By being precise and continuously measuring contact center performance, users ensure that correct and current data enters the system, avoiding the GIGO problem. With these two guiding ideals in mind, and with the help of a WFM software application, schedule production can be conducted in five best-practice steps:
1. Conduct daily call or contact distribution calculations by skill and interval from a historical reference period selected by the user.
2. Compare accuracy of each skill forecast within the last three months against actual results. This enables you to adjust the next forecasts accordingly to continually steer accuracy rates towards 100 percent.
3. Observe call or contact forecast calculations based on the actual absenteeism of all agents for the hours they were gone, rather than lumped together as all day averages (that is, the shrinkage percentage).
4. Monitor call and contact routing ratio calculation for every skill of each agent. This calculation is done using a reference period selected by the user.
5. Finally, schedule production from the real requirements (again, without “shrinkage”), using the actual contact routing ratios specific to each agent already in place and from his or her personal profile.
With this simple and straightforward approach, you can generate accurate results that are easily understood by workforce management users. To continuously improve accuracy rates in forecasting and scheduling, contact center managers should repeat this process every week. Workforce management specialists agree that forecast quality is the key to optimum schedules, so when a forecast is highly accurate, there is less need for simulators or other related “what if” planning tools.
René LeBel is vice president and general manager of Calabrio Canada. LeBel founded the original workforce management company before it was acquired by Spanlink. Today, Calabrio Software develops and distributes workforce optimization, performance management, and unified desktop products for IP-based small to midsize contact centers and large, distributed contact centers. LeBel can be reached at email@example.com.
[From Connection Magazine – December 2007]