Accurate forecasting is the most important component of workforce management software, and call centers are inherently susceptible to the inaccuracies of call volume forecasting. Over-staffing can lead to wasted labor expense while understaffing can result in lost sales due to abandoned calls and a longer average speed of answer. In either case, staffing mistakes can have a lasting impact on a company’s bottom line.
For a company whose call volume fluctuates according to seasonal buying, catalog drops, or other special events, forecasting capabilities should be a major consideration in any purchasing decision of workforce management software. Only the most sophisticated systems can perform correlated forecasting – that is, forecasting for specific events that cause wide fluctuations in the volume of calls that must be processed. Consider these factors and the steps involved in maximizing the accuracy of your forecast.
The Importance of Pattern Recognition
There are two basic methods used to forecast workload in a call center: Exponential Weighted Moving Average and Historical Trend Analysis. Both utilize historical data collected from the call center’s ACD, and both take growth trends into account in their calculations.
The Exponential Weighted Moving Average calculates the average call volume over a specific time period and then bases its projections on a formula that assigns more weight to recent activity. This technique is effective for contact centers where there is little fluctuation in call volume and patterns, but it has shortcomings when trends change. It is unable to predict a continuation of trends during periods of generally increasing or decreasing volume, or to associate changes in volume and/or call arrival patterns with specific events (pattern recognition).
Historical Trend Analysis not only accurately predicts the continuation of trends, but the 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 recurs, the forecasted call volume is automatically adjusted to reflect the increase or decline in incoming work caused by comparable occurrences in the past, such as a historical 40 percent drop in volume on the Fourth of July.
In environments where workloads regularly ebb and flow due to marketing activities and other definable variables, Historical Trend Analysis is the only way to ensure proper staffing because it is the only method that can incorporate complex historical trends in its calculations. Without pattern matching to predict different customer behavior for different events, the risk of over- or understaffing increases dramatically.
Mapping Historical Data to Special Events
A key step in using a workforce management program that employs pattern recognition is regular data validation. Analysts must review the data collected by the ACD, preferably on a daily basis and not less frequently than weekly, to determine whether there is an identifiable cause for all spikes and drops in call volume.
Most unusual patterns will be related to recognizable events such as direct mail campaigns, catalog drops, TV infomercials, discount offers, competitors’ promotions, pay periods, billing cycles or holidays. Some may even be traceable to external factors such as the Super Bowl, the Olympics or a snowstorm.
If a given fluctuation was triggered by a recurring special event, analysts instruct the system to interpret that data set accordingly when producing a forecast. Conversely, if a given deviation was the result of a one-time anomaly like a product mention on Good Morning America, analysts can tell the system to ignore that data set when forecasting. These instructions are vital in producing the most accurate forecast possible.
Assigning Attributes to Specific Events
To further enhance accuracy, some forecasting tools also make it possible to describe each event in detail through the use of attributes. One catalog drop might consist of 10,000 pieces sent to women between the ages of 20 and 35 in Southern California, for example, while another might involve 5,000 pieces directed at older women in the Midwest. By logging these characteristics into the system, analysts ensure that the differing call patterns produced by each drop will be ‘remembered’ and used in forecasting call volumes the next time similar mailings go out.
The most advanced systems can search for historic trends that parallel upcoming events both by specific match (e.g. the specific guest host on a TV shopping channel) and by a range of values (e.g. products between $50 and $100). This aids in correlating past and future events. There will be a substantial difference in response to a piece of jewelry that sells for $200 and one that sells for $2,000, for example, and only a tool that allows this information to be recorded can factor in that difference when creating a forecast. Since all agent assignments are based on anticipated call volumes, a package with inadequate forecasting capabilities will result in a disproportionate number of wrong predictions.
The Impact on Call Center Revenues
Let’s say that a workforce management package has underestimated call volume and therefore staffing needs so substantially that 100 callers out of 1,000 hang up before they speak to an agent. In a sales environment where the average order is just $50, that means $5,000 in lost revenues per day, $150,000 per month, or a staggering $1.8 million per year. At best, these lost sales cut into a call center’s profits; at worst, they can ruin a business.
There are, of course, many other components in the equation that dictates the effectiveness of a workforce management software package. These include agent skill sets and work rules, real-time adherence capabilities, and the ability to calculate staffing requirements based on highly specific user-defined service levels ranging from mean time to answer to the percentage of busies and abandoned calls that will be tolerated.
But all that is moot if the software’s forecasting tool doesn’t meet the call center’s needs. For call centers that rely on proper staffing to do their work, choosing the right forecasting solution can make or break the bottom line.
Pipkins, Inc. is an American company and a leading supplier of workforce management software and services to the call center industry. For over thirty years, Pipkins has created and delivered superior workforce management products for contact centers of all sizes with thirteen industry-first applications. Pipkins’ premier product 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. For more information, visit www.pipkins.com.