Workforce Management Systems: It’s All About the Algorithms

By Bob Webb

Workforce management may be the most undervalued of all contact center solutions. Often it is bundled and sold as part of an end-to-end solution by vendors who specialize in other software and have no in-depth knowledge of workforce management. Some solution providers minimize the value of workforce management in favor of their area of expertise – when, in fact, workforce management is the cornerstone of any contact center operation. Accurate forecasting and scheduling is imperative for achieving the balance of having agents consistently in the right place at the right time. There are many vendors who offer workforce management; however, their products are not all equal. The disparity lies in the algorithms.

Many workforce management systems lack critical functions and flexibility to meet the needs of contact centers, or their platform is unable to maintain sufficient historical call data to generate accurate forecasts. The most common problems found with workforce management systems are inaccurate forecasting and an inability to generate requirements at the interval level. Both of these problems, coupled with inadequate scheduling algorithms, can prove costly and hurt a company’s bottom line.

Algorithms: Workforce management software should use mathematical algorithms for accurate call volume forecasting and scheduling based on data exclusive to each center’s target service levels, fluctuating call volumes, agent skill sets, and “what if” scenarios. Accurate forecasting takes into account all the historic dynamics. Systems that use a weighted moving average can only use thirteen weeks of historical data, which is not enough to provide a statistically valid forecast. Forecasting for specific events that produce wide fluctuations in call volume can only be performed by sophisticated systems using all historical data.

Algorithms should reflect real-life customer behavior and include curve mapping and pattern recognition. In environments where workloads regularly ebb and flow due to definable variables, historical trend analysis is the only way to ensure proper staffing because it is the only methodology that can incorporate complex historical trends into its calculations. Without pattern matching to predict different customer behaviors for different events, the risk of over-staffing or understaffing increases dramatically. Historical trend analysis accurately predicts the continuation of trends, and more advanced algorithms also incorporate pattern recognition to fine-tune forecasts for special events like promotional mailings or national holidays. Each time a particular event reoccurs, the forecasted call volume is automatically adjusted to reflect the change in incoming work caused by comparable occurrences in the past, such as a historical 40 percent drop in volume on the Fourth of July.

Multi-Skilled Agents: An important component of accurate forecasting is having an integrated approach to support multi-skilled issues. It is necessary for forecasting algorithms to directly calculate requirements in a multi-skilled environment, while also avoiding repetitive analytical simulations. A single forecasted set of requirements should be generated for all interwoven skilled activities, regardless of the type of work being offered (such as email and chat). Recognizing secondary skills and accounting for call overflow to available secondarily skilled agents will help eliminate overstaffing. Forecasts based solely on primary skills will generally lead to over-staffing, since overflow cannot be considered as a factor.

Over-Staffing: Over-staffing occurs when abandoned calls are not taken into consideration. Staffing operational costs, which account for 70-80 percent of a call center’s budget, can be severely impacted by over-staffing. For absolute maximum efficiency, software should have an algorithm to incorporate abandoned calls. Systems that don’t understand abandons will always over-staff your call center. This is like the airplane that takes off with empty seats; you will never have another chance to recover that revenue.

Once scheduling requirements are known, use an algorithm that maximizes the achievable quality of service. Avoid using a simple “hours-net-to-zero” scheduling algorithm. Scheduling systems that use a simple net-to-zero algorithm cannot distinguish between schedules that deliver good and bad service. If understaffing or over-staffing during different intervals throughout the day nets to zero, you are not truly meeting your service-level objectives during those intervals. Wasted labor expenses can occur through over-staffing, while understaffing results in lost revenue.

Conclusion: Workforce management is based on science, and it should be approached from a scientific perspective. The best option is to choose a vendor who specializes in workforce management and understands its complexities. Starting with a solid workforce management foundation will help reach service-level objectives with fewer problems.

Bob Webb is with Pipkins, Inc. Founded in 1983, Pipkins is a supplier of workforce management software and services to the call center industry, providing sophisticated forecasting and scheduling technology for both the front and back-office. Its award-winning Vantage Point is the most accurate forecasting and scheduling tool on the market. Pipkins’ systems forecast and schedule more than 300,000 agents in over 500 locations across all industries worldwide.

[From Connection Magazine Sep/Oct 2014]

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