Understanding and choosing the right wait time metrics is one of the most important operational decisions a Contact Centre Manager can make.
This article is part of our Contact Center Management Series — a collection of articles that bring together practical guidance and insights to help Contact Centers run better and deliver stronger results.
Many Contact Centre Managers track multiple wait time metrics without fully understanding the role each one plays.
Service Level. Average Speed of Answer. Longest Wait Time. Abandonment Rate.
All of these measures provide valuable operational insights, but they are not equally important, and they should not all be managed in the same way.
Understanding which metrics drive operational decisions — and which are simply outcomes of those decisions — is an important part of effective Contact Centre Management.
In this article, I’ll explain the purpose of the most common Contact Centre wait time metrics, how they relate to one another, and where managers should focus their attention.
Why Wait Time Metrics Matter
For customer contacts that are expected to be handled within 60 minutes, Service Level is the appropriate wait time metric.
For customer contacts that are expected to be handled after 60 minutes, Response Time is generally the more appropriate measure.
Although both metrics measure timeliness, they support very different operational decisions.
Because Service Level and its related wait time metrics are often misunderstood, we’ll focus on those in this article and leave Response Time measurements for a future discussion.
With that said, effective Contact Centre Managers understand that Service Level and Response Time require different planning approaches, different operational assumptions, and different performance measures.
Treating them as though they are the same creates confusion rather than clarity.
If you’d like to test your general understanding of Contact Centre Operations, you may also enjoy these two quizzes:
Service Level
Before you can measure wait time performance, you first need to decide on your Service Level objective.
Without a Service Level objective, you don’t have a meaningful basis for planning, forecasting, or staffing your Contact Centre.
If you’re using an ACD (Automatic Call Distributor), Service Level should be one of your primary operational measures.
One of the biggest misconceptions in our industry is that there is a universal Service Level standard.
There isn’t.
What works well for one organisation may be entirely inappropriate for another.
Even within the same Contact Centre, different customer queues may have different Service Level objectives depending on the nature of the customers and contacts being handled.
First-class and business-class passengers generally enjoy a faster speed of answer than those flying in economy, for example.
Because Service Level has a significant impact on staffing requirements and thus operating costs, it should not be changed frequently.
Most organisations review their Service Level objectives as part of their annual planning or budgeting process.
With the right stakeholders involved and a strong understanding of how to link the Service Level objective to budgets, an annual review is usually sufficient.
Choose the Measurement Interval
Service Level performance should always be measured at the interval level.
For most Contact Centres, a 30-minute interval provides the right balance between operational visibility and practical management.
If your customer contacts are typically longer, a 60-minute interval may be more appropriate.
If you operate a very small Contact Centre or queue with only a handful of agents, measuring performance hourly — or even by shift — may provide sufficient insight.
Larger Contact Centres generally measure Service Level at 30-minute intervals, while very large operations or those pursuing a highly cost-efficient staffing strategy often measure at 15-minute intervals.
The goal is to have exactly the right number of people in the right place at the right time — using labour as efficiently as possible.
Daily, weekly, or monthly averages may have their place for management reporting, but they should never replace interval reporting for those who run the Centre.
That’s because the customer wait time experience, agent occupancy, and opportunities to improve staffing efficiency all exist at the interval level — not within daily or weekly averages.
Using a Traffic Light Approach
Some Contact Centres use a simple green, amber, and red system to display Service Level performance across each interval of the day. 
For example, a 24-hour Contact Centre measuring at 30-minute intervals has 48 reporting intervals each day.
You might define a green interval as achieving a Service Level of 90% or above, with amber and red representing progressively lower levels of performance.
When displayed visually, interval performance quickly reveals patterns:
- Where are the problems occurring?
- Are there recurring periods of under-performance or over-performance?
- Where should management attention be focused?
After all, you can only improve what you can see. Averages can easily distort that clarity.
Service Level performance should never be a secret. Display the results throughout the Contact Centre.
That’s because everyone in the Centre contributes to Service Level performance in some meaningful way.
Choose the Service Level Calculation Formula
Many people are surprised to learn that there isn’t just one way to calculate Service Level.
Most ACD platforms support multiple Service Level calculation formulas, and the formula configured within your system directly affects the Service Level results you report.
That makes choosing the formula an important management decision — not simply a technical configuration.
Ask yourself:
- Which Service Level calculation formula is currently configured in our ACD?
- Is it the formula we intentionally want to use?
- Is the same formula used consistently across the organisation?
- If we compare performance between sites or business units, are we making a true like-for-like comparison?
Understanding your Service Level calculation methodology is just as important as understanding the Service Level target itself.
A well-defined and consistently applied formula helps ensure that Service Level reporting is meaningful and comparable.
Average Speed of Answer
If you’re using an ACD (Automatic Call Distributor), ask yourself an important question.
Why are you using Average Speed of Answer (ASA) as a wait time metric instead of relying on Service Level?
For most Contact Centres, Service Level is the best and primary measure of the customer wait time experience.
ASA is different and not as effective as Service Level.
First, any metric calculated as an average introduces a degree of bias into its interpretation.
When someone says our ASA was 90 seconds today, it creates the impression that most callers were answered in about 90 seconds — which mathematically isn’t the case.
ASA Is an Outcome — Not a Driver
Even though Service Level and ASA are related and calculated from the same underlying variables, they serve very different purposes.
ASA is also not a driver of performance — it is an outcome of your Service Level performance.
Here is the relationship:
- When Service Level falls, ASA rises.
- When Service Level improves, ASA falls.
One of the most important principles in Contact Centre Management is to manage the drivers rather than the outcomes.
Improve the driver (Service Level in this case) and the outcome (ASA) usually improves automatically.
So where does ASA still have value?
ASA forms part of the Erlang B calculation used to determine the number of trunk lines required for your Contact Centre.
I also use ASA at times in charts or graphs because it is easier for the audience to understand than Service Level.
Though of course those ASA figures are linked to a certain Service Level objective.
If you’ve modelled your operation using Erlang C, you can identify the ASA that corresponds to your chosen Service Level target — for example, 12.7 seconds — and use that figure for trend reporting if you wish.
So if you’re still using ASA as your primary measure of customer wait time, it’s worth asking yourself why.
Longest Wait Time
Even when your Contact Centre consistently achieves its Service Level objective, one customer will always experience the Longest Wait Time.
Understanding the Longest Wait Time is important.
Within any 30-minute interval, customers can experience very different waiting times.
While many customers may be answered quickly, others may wait considerably longer.
This becomes particularly relevant when reviewing customer feedback or survey results relating to wait times.
A customer who was answered in 3 seconds is likely to respond very differently to a wait time survey than one who waited 250 seconds.
Longest Wait Time is also one of the most useful metrics available to supervisors and operational leaders making real-time decisions.
Anyone monitoring the readerboard or wallboard should understand the current Longest Wait Time for the interval, as it provides valuable context when deciding whether Service Level recovery actions are needed.
Fortunately, Erlang C allows us to estimate the expected Longest Wait Time for each interval, making it a useful planning and operational measure.
Like Average Speed of Answer, Longest Wait Time is an outcome rather than a driver.
- When Service Level declines, Longest Wait Time increases.
- When Service Level improves, Longest Wait Time falls.
Rather than chasing the outcome, focus your attention on the driver — in this case, Service Level rather than Longest Wait Time.
Abandonment Rate
Abandonment Rate is one of the most misunderstood metrics in Contact Centre Management.
For Contact Centres that generate revenue directly — such as food ordering, travel reservations, or hotel bookings — Abandonment Rate is understandably important.
Every abandoned call may represent lost revenue, which can be easily calculated.
Rather than managing Abandonment Rate directly, however, these organisations typically achieve low abandonment by setting and consistently delivering on a very high Service Level objective — for example, 95/5.
When customers are answered quickly, there tends to be less abandonment.
For Non-Revenue Generating Centres or Queues
For most non-revenue-generating Contact Centres, Abandonment Rate is best viewed as an outcome of Service Level performance.
- When Service Level declines, Abandonment Rate will generally — but not always — increase.
- Likewise, when Service Level improves, Abandonment Rate will generally decrease.
The important point is that Abandonment Rate reflects customer-chosen behaviour, not just operational mathematics.
Customers abandon for many different reasons, each unique to their own situation.
Some lose patience or move to self-service, while others may not have time to continue waiting. Others simply decide not to wait.
That’s why effective Contact Centres analyse Abandonment Rate rather than manage to it.
They ask questions such as:
- At what point in the wait are customers most likely to abandon?
- Which intervals experience consistently higher abandonment?
- Are our delay announcements helping or discouraging customers?
- Would changing the timing or wording of those announcements improve the customer wait time experience?
Ultimately, your greatest influence over Abandonment Rate comes from consistently achieving your Service Level objective.
When you deliver the customer wait time you’ve promised and operate consistently throughout the day, Abandonment Rate will generally look after itself.
It’s an outcome of Service Level, not a driver.
For a deeper discussion of this topic, you may also enjoy our article Getting a Handle on Abandonment Rate in the Contact Centre.
Bringing It All Together
Service Level is the metric with the driving licence.
Average Speed of Answer, Longest Wait Time, and — generally — Abandonment Rate are the passengers.
When Service Level changes, ASA, Longest Wait Time, and — generally — Abandonment Rate follow in predictable ways.
That’s why effective Contact Centre Managers focus first on the driver — in this case Service Level — and work to achieve it consistently, interval after interval, rather than chasing individual outcome metrics.
Understanding the relationship between these measures doesn’t just improve reporting — it leads to a more consistent customer wait time experience and a more effectively managed Contact Centre.
Thank You for Reading
I regularly share stories, strategies, and insights from our work across Contact Centers, Customer Service, and Customer Experience. If this resonates, I’d love to stay connected.
You can drop me a line anytime, or subscribe via our website.
Daniel Ord
[email protected]
www.omnitouchinternational.com
*Banner image by Donald Wu on Unsplash