Service-level goals are key performance indicators (KPIs) in most support and contact centers. These goals measure the time callers spend in queue. In benchmarking surveys, the most common goal given by respondents is to answer 80% of calls within 20 seconds. Another common response is an average speed of answer (ASA) of 30 seconds or less. But not all contact center professionals understand the calculations that make up these statistics and that different statistical methodologies can produce varying results.
Service-level measurement is a science
The typical automatic call distribution (ACD) system offers two measures of queue time for callers. The first is service level: X percent of calls answered within Y seconds. So if the center met the goal of 80% of calls answered within 20 seconds, that means 20% of callers waited at least 21 seconds. But while we know how many were queued longer than 20 seconds, we don’t know how long these callers actually waited.
The other queue-time goal is ASA. This goal is expressed as an average number of seconds, and the most common goals cited are less than 30 seconds. ASA is the average queue time for all callers whether they queue or not. So if 60 of 100 calls are answered immediately by idle agents, that is 60 times 0 seconds in the calculation. Let’s assume the other 40% of callers wait between 1 and 300 seconds, with an average of 60 seconds. That is a total time in queue of 2,400 seconds (40 callers x 60 seconds). This 2,400-second total is then divided by the 100 total callers, for an ASA of 24 seconds. ASA does not really tell us how many queued or how long they waited, just that the overall average was X seconds.
These two statistics do not track very well against each other, and it is possible to reach the goal of one and not the other during the same period even though they were aligned at a certain call volume and average handling time. Contact centers have plenty of things to measure without having two metrics devoted to speed of answer.
The art of service-level measurement
To really assess service levels, you must consider two more factors: the way in which the calculation is done, and the interval over which the measurement is calculated.
When does the ACD system begin measuring the queue for calculating the service level or ASA, and which calls are included? It differs from one ACD to another. For example, in one ACD the queue time can begin to count when the call enters the ACD for a specific agent group and the caller hears ringing. In another ACD the ringing could be ignored, but the recorded announcement will be included in the service level or ASA calculation. The ACD could also be set to ignore the recorded announcement and start counting when it ends. The ACD could even be set to ignore a standard interval (such as five seconds) before starting the count.
To make it even more interesting, the system can be set to measure only those calls that are actually answered within 20 seconds or can include all calls, including those that are abandoned within the 20 seconds as well. Do you know what your system is set for and what your options are?
The second factor is the interval. Centers absolutely committed to their ASA goals measure each hour or half-hour and determine what percentage of these intervals meet the goal. In many centers, the average is calculated across a whole day so that if the peak hours are awful and the low hours are great, then it all averages out. Still more centers average across a whole week so that the peak day’s bad service is buried in the slower days’ great results. In some extreme cases, it is even possible that a center averages across a month or even the whole year, rendering any measurement meaningless.
The longer the averaging interval, the more that dreadful service can be successfully hidden. Of course, these busy intervals are the periods when the most customers are affected. When the interval is long, it enables some centers that give terrible service early in the interval to later in the period overstaff so that they give more than fabulous service just to make the average. This is neither good service or cost-effective.
It’s important to understand how your contact center measures service levels in order to make sure that those measurements give you the information that truly reflects performance. The time to do it is now because performance management is only going to get more complicated. As we move to include other kinds of contacts in our centers, such as e-mails and Web chats, we need to consider how we will measure the service level. Some will need similar queue measures, while others will be driven by time to complete response. But knowing what to calculate and how the systems work will be key to setting your goals and meeting your customers’ expectations.
Maggie Klenke is a founding partner of Lebanon, TN-based educational and consulting firm The Call Center School.