Average call handling time is one of the most commonly used metrics for evaluating call center performance. It helps managers assess the overall time required to handle calls; however, it does not provide a complete picture of a call center’s operational performance on its own.
Two call centers may have the same average call handling time but experience different queueing and service capacity conditions because of differences in call duration. Therefore, more effective management requires examining not only the average but also the variability in call handling times.
Why Does Variability in Call Handling Time Matter?
Not all calls require the same amount of time to handle. Some requests are simple and brief, while others require further investigation or specialized guidance.
When some calls take longer than usual, agents remain occupied for extended periods, potentially reducing the available service capacity. Under these conditions, new incoming calls may have to wait longer in the queue.
For this reason, average call handling time alone does not reveal how much handling times vary or what proportion of calls occupies agents for extended periods.
Do Call Handling Times Follow a Consistent Pattern?
When analyzing call center performance, it is important not to assume that all calls have similar handling times. An analysis of data from a bank call center found that a lognormal distribution provided a suitable description of service times in that particular dataset.
This finding suggests that understanding the actual distribution of service times can help in selecting appropriate methods for analyzing queues and service capacity. However, a pattern identified in one call center cannot be generalized to all call centers without examining their data.
Which Metrics Should Be Examined Alongside the Average?
To obtain a more accurate picture of call center performance, several metrics should be examined together:
– Median handling time: Helps identify a typical handling time and compare it with the average.
– Handling time percentiles: Reveal how long it takes to handle calls with longer durations.
– Standard deviation: Measures the degree of variation in call handling times.
– Call type: Helps identify differences between handling simple and complex requests.
– Queue performance metrics: Help analyze the relationship between service time, waiting time, and agent occupancy.
Combining these metrics helps reveal hidden differences in aggregated data and supports more accurate decisions about service capacity.
How Does Handling Time Analysis Affect Workforce Planning?
Workforce planning depends not only on the volume of incoming calls but also on the time required to handle them, which affects the capacity needed to meet demand.
If a call center makes decisions based solely on average handling time, it may overlook the differences between short and long calls. By contrast, examining the distribution of handling times, request types, and queue conditions can help identify periods of high demand and assess agent capacity more effectively.
For practical application, handling time data should be analyzed across different time periods and by service type. It is also important to clarify whether the recorded time includes only the conversation itself or also the work performed after the call ends.
Conclusion
Average call handling time is a useful metric, but it is not sufficient for managing overall call center performance. Variations in call duration can affect agent occupancy, queue formation, and workforce planning.
By examining the distribution of handling times, percentiles, variability, and queue performance metrics, managers can develop a more accurate understanding of actual call center performance and make operational decisions based on more comprehensive data.
Author: Zahra Shirband – International Relations Expert ISQI
Reference:
Brown, L., Gans, N., Mandelbaum, A., et al. (2005). Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective. Journal of the American Statistical Association, 100(469), 36–50.
