Ask the Workforce Wizard


I am working on evaluations for the Analysts that report to me and part of that review is on Call Volume Forecasting Accuracy. The current goal is 90% of days in the year forecast within +/- 10% of actual volume. I am hoping to introduce a sliding scale – based on forecasting experience – and was wondering if there is a standard for this metric in the industry.


Unfortunately, there is no industry standard to go by since every business and even different call types in the same center can have very different behaviors. In some cases, the call volume is very stable with few drivers that would throw off the forecast much. But in others, system failures, marketing programs, special offers, news events, and a variety of other stimuli can make the volume go up and down unexpectedly or change the handle times as well. So holding all analysts and all call types to a 10% variance standard may not be realistic. It may actually be too stringent in some cases and not enough in others.

Here is what I would suggest. Do an analysis of the current state of forecasting accuracy for each call type. Look at the daily, but also look at the half-hourly within the days. It is common to have patterns of variation within the day that can help to identify the causes. For example, if the typical variance by half-hour is within 10%, but the 2-3 PM period seems to be consistently off by more than 15%, then looking for the cause of that and reconciling the problem can do a lot to improve the overall day results. It is also common for there to be higher variance during the low volume periods than during the peak times. Averages can do a lot to hide such things. The idea is not to shoot for a number but to seek data that would help to improve the results.

Starting with the historical variance that you have experienced, set a goal to improve it by just a little – maybe 1 or 2%. A good way to look at it is to calculate the standard deviation of the variance over time and seek to bring it down. This measures the highest and lowest variance and by pulling the results closer to the average and not having big outliers, you are making a substantial improvement in the manageability for operations.

On another note, be aware that forecasting accuracy is not totally within the control of the WFM analyst. If marketing launches campaigns without notice, systems failures impact AHT, or you are subject to other forces beyond your control, that really should be considered.