How to Calculate & Improve Average Speed of Answer in Call Centers

Did you know that 20 seconds is the gold standard for Average Speed of Answer (ASA) in modern call centers, with top-performing teams maintaining this benchmark to balance efficiency and customer satisfaction?

Understanding the calculation and strategizing for improvement of ASA is detrimental for all businesses, regardless of their size.

This blog looks at How to Calculate & Improve Average Speed of Answer in Call Centers so that all of your queries are answered properly.

Understanding Average Speed of Answer (ASA)

Definition of ASA

ASA is the average amount of time a call has to wait in a queue before being picked up by an agent.

It does not account for the time spent on automated systems but gives an idea of customer wait time before reaching a representative.

A lower ASA means calls are handled more efficiently, which reduces caller frustration. Implementing a power dialer can reduce waiting time and improve the speed of answer.

Importance of ASA

Altering ASA directly impacts customer satisfaction, service efficiency, and overall call center performance.

Understandably, a long ASA frustrates customers and contributes to higher rates of call abandonment. Monitoring call volumes is key to understanding response times in your phone system.

Globally, the industry benchmark for ASA is approximately 28 seconds, but high-achieving call centers work toward even shorter times to elevate the customer experience and improve operational efficiency.

How to Calculate Average Speed of Answer?

The Average Speed of Answer (ASA) is a very important metric. Call center operations use this metric to measure the average time customers wait before an agent answers tier calls. Efficient call routing helps minimize missed calls and optimize inbound calls.

Businesses use this factor to evaluate their response efficiency and optimize customer service.

Formula for ASA Calculation

The formula for ASA is:

ASA =Total Number of Answered Calls / Total Waiting Time for Answered Calls

Where: 

• Total Waiting Time for Answered Calls is the total time of wait times for all calls that were successfully attended to.
• The Total Number of Answered Calls is the number of calls that agents picked up.

Step-by-Step Example Calculation

Let’s go through a detailed example to understand how to compute ASA.

Step 1: Identify the Given Data

Assume the following call center statistics for a specific time period:

• Total waiting time for answered calls = 7,200 seconds
• Total number of answered calls = 300

Step 2: Apply the ASA Formula

ASA = 7200 seconds / 300 calls

Step 3: Perform the Division

ASA = 24 seconds

This means that, on average, customers waited 24 seconds before their calls were answered.

How to Interpret the Result of ASA?

After you calculate the Average Speed of the Answer, you need to be able to interpret it correctly to ensure that you can improve on it.

Here is how you can appropriately interpret the result of ASA:

• A lower ASA (e.g., under 20 seconds) will mean that you have efficient customer service and need to work on maintaining the current efficiency.
• A higher ASA(e.g., over 60 seconds) may suggest that you have some issues waiting to be fixed, such as staff shortages, high call volume, or inefficient call routing.

With regular tracking of this very important metric, businesses, small or large, can make sure that they have data-driven decisions to improve customer service and minimize wait times.

Common Mistakes in ASA Calculation and How to Avoid Them

The Average Speed of Answer (ASA) is an essential call center performance metric that assesses how long a customer typically waits before their call is answered.

But, if not properly calculated, insights can be misleading and thus negatively affect customer service strategy. Here are some of the commonest errors in ASA calculations – and the ways to avoid them.

1. Including Abandoned Calls in Calculation

One of the major mistakes is adding the waiting time or the number of calls that are hung up without being answered. ASA only measures answered calls.

🔴 Mistake:

Including the wait time of calls that are abandoned before talking to an agent distorts the calculation, causing ASA to be artificially inflated.

✅ How to Avoid:

Make sure the formula only counts answered calls:

ASA= Total Number of Answered Calls / Total Waiting Time for Answered Calls

2. Ignoring Calls Answered by IVR or Automated Systems

Within ASA measurements, certain businesses consider calls answered by IVR systems as “answered calls.”

🔴 Mistake:

Automated systems should not include calls when calculating ASA; these are not true human-to-human interactions. This can cause ASA to look shorter than they really are.

✅ How to Avoid:

Exclude calls managed by IVR systems before performing the calculation. Measure only the calls that a live agent handled.

3. Using the Wrong Units of Time (Seconds Instead of Minutes)

Another common mistake is inconsistency in the time units when adding up the total waiting time.

🔴 Mistake:

For example, if the total waiting time is kept in seconds, but the final ASA is provided in minutes without any conversion, the outcome would be wrong.

✅ How to Avoid:

Repeat the division only after checking the time units. If necessary, convert:

1 minute = 60 seconds

1 hour = 3,600 seconds

Factors Affecting Average Speed of Answer

Set up a business phone system that routes calls efficiently to reduce waiting time. This is especially helpful because missed calls can be minimized by enhancing call center software capabilities.

Here are how metrics such as average handle time, response time, workflow automation, etc., impact ASA and train center agents:

I. Call Volume and Patterns

The timing and volume of calls impact ASA directly. Increased call volumes during peak hours or seasonal surges with not enough resources lead to long call wait times.

Predictable patterns of demand — lunchtime rush or holiday spikes, for example — allow call centers to know when they need to ramp up, but those unexpected demand surges can slow things down.

Effective call forecasting and dynamic queue management can help mitigate these spikes by distributing the workload more evenly.

II. Staffing Levels

The ASA is heavily dependent on the availability of customer service agents. Low staffing levels result in call queues for customers as incoming calls compound, with the wait times skyrocketing.

In contrast, bloated personnel incur operational costs without the added likelihood of improved efficiency.

With effective management of the workforce, abandoned calls can be optimized, and center metrics can be improved. By integrating with CRMs, the workflows are simplified for agents, and the handling time is improved for Call center agents. It can also help guide customers through the IVR, decreasing the average speed of within-answer.

III. Technology Utilization

Knowing what ASA is is one thing, but handling it is something else, and that is where modern call center technology comes in.

ACDs and IVR reduce the time spent on each touch point by routing customers to the right department or agent.

Customer Relationship Management (CRM) software allows agents to have instant access to customer history and all relevant information, resulting in lesser handling time and better efficiency.

Tools for workforce management and AI analytics also work to predict call patterns and schedule agents accordingly, paying off with lowered ASA and improved customer experience as a whole.

Strategies to Improve Average Speed of Answer

The Average Speed of Answer (ASA) can be improved by strategic staffing together with intelligent call routing, leveraging technology, and training of agents.

Applying and adopting these techniques could reduce not just the on-hold waiting time of callers but also ensure a better quality of service and a more effective calling program as a whole.

A. Optimize Staffing Levels

Agencies should also align their use with appropriate staffing to maintain low ASA. They shall also look at historical call patterns and analyze the peaks, seasons of traffic, and other unplanned increases and scale staffing accordingly.

Workforce management software will also help you predict the volume of calls and construct an optimized scheduling meeting that does not lead to overstaffing.

Moreover, real-time monitoring tools enable managers to dynamically change staffing according to live call traffic so that they can respond quickly even in case of a sudden spike in call volume.

B. Implement Efficient Call Routing

This facilitates reduced wait times for callers as intelligent call routing systems forward incoming calls to the appropriate agents/departments within the system.

These systems allocate calls based on the availability, skill level, or prioritization of the customer.

Interactive Voice Response (IVR) systems can help customers navigate through self-service options before connecting with an agent, which limits unnecessary call transfers and enhances efficiency.

By introducing skills-based routing, organizations ensure their customers connect with the most suitable agent in relation to the solution they require, reducing typing time, improving resolution time, and enhancing the caller experience.

C. Utilize Technology and Tools

Scaling the right technology is crucial for monitoring and improving ASA. Call center software like Five9, Genesys Cloud, or NICE CXone provides real-time analytics and reporting on the call handling metrics required by managers to spot inefficiencies and bottlenecks.

AI-driven chatbots and virtual assistants handle routine queries, reducing the number of calls human agents need to attend to. Workforce optimization tools help track agent performance and adjust staffing in real time to balance the workload.

D. Training and Development

Well-trained agents are the major contributors towards low ASA, efficient handling of calls, and quick resolution of customer issues.

Training programs should be regularly conducted on call handling techniques, active listening, and problem-solving skills.

Keeping agents up-to-date with product and service knowledge, along with common customer concerns, helps them to resolve inquiries more quickly and, therefore, reduces call durations, improving first-call resolution rates.

This will also allow flexibility in staffing by cross-training agents to handle different types of inquiries and help maintain service levels even during high-demand periods.

Conclusion

In call centers, the Average Speed of Answer (ASA) is a crucial metric influencing customer satisfaction and operational efficiency.

A lower ASA ensures prompt responses, reducing frustration and call abandonment rates. By accurately calculating ASA using the formula (Total Wait Time of Answered Calls ÷ Total Answered Calls) and avoiding common errors, businesses can obtain reliable insights to enhance their service levels.

Improving ASA requires a strategic approach, including optimizing staffing levels, implementing intelligent call routing, leveraging technology like AI-driven analytics, and investing in agent training. Predictive workforce management, real-time monitoring, and automation help balance workloads and minimize waiting times.

By focusing on these strategies, call centers can significantly enhance customer experiences, streamline operations, and maintain a competitive edge in customer service.

Frequently Asked Questions (FAQs)

How is ASA calculated in a call center?

ASA = Total Wait Time of Answered Calls ÷ Total Answered Calls

This formula excludes abandoned calls and automated system navigation time.

What factors increase ASA in a call center?

Here are all the factors that can impact ASA in a call center:

• High call volume during peak hours.
• Inadequate staffing or inefficient scheduling.
• Long agent handling times due to complex queries.
• Poor IVR (Interactive Voice Response) systems, causing delays.

How can AI help reduce ASA?

Does ASA impact call abandonment rates?

Yes, a higher ASA leads to frustrated customers who may hang up before reaching an agent. Reducing ASA improves customer satisfaction and retention.

What’s the best staffing strategy to improve ASA?

• Implement predictive workforce management tools to adjust staffing based on real-time call trends.
• Cross-train agents to handle multiple query types, ensuring flexibility during peak hours.