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How to measure
contact center
operational
efficiency
and productivity

Author: Mike Elgan

The goal of a contact center is to keep customers happy while keeping costs down. Measuring contact center operational efficiency to determine if goals are being met is easier said than done.

Contact center operational efficiency is all about solving customer problems, addressing concerns and answering questions—and doing so quickly. The contact center is a critical part of business success, and decision-makers need to be sure it is not a drain on time and resources. The contact center has the potential to transform customers into brand loyalists. A contact center might be a customer's only point of human interaction with your company. It is an inflection point that can thrill a customer—or disappoint them.

Timing is everything. Short waits and quick resolutions boost customer happiness and cut costs. The SQM Group found that every one percent increase in first-call resolution rates nets a one percent increase in customer satisfaction rates.

An efficient contact center all but ensures consistently quick, personable and satisfying customer interactions. And it all starts with data.

Establishing contact center operational efficiency metrics

Call center operational efficiency requires regular improvement, but you cannot track improvement if you do not know what to measure. What are the metrics of success?

  • Response time: The average time it takes to respond to a customer call.
  • Engagements per resolution: The number of touchpoints it takes for a customer concern to be resolved.
  • Service level: The percentage of calls answered within a specific time frame.
  • Average call abandonment rate: The percentage of customers who hang up before talking to an agent.
  • Average queue time: The average time customers spend waiting to speak with an agent.
  • First-call resolution: The percentage of customer problems solved in one interaction.
  • Percentage of calls blocked: How often customers encounter a busy signal.
  • Average speed of answer: The average time it takes between when a hold is ended and an agent picks up the call.

Some metrics are straightforward and can be interpreted at face value. But some require nuanced or subjective interpretation.

  • Average handle time. This metric tracks how long it takes for an agent to resolve a customer issue. Contact centers should establish a range for this metric—if calls are too long, the calls might burden the customer. If they are too short, the customer might feel rushed and unheard.
  • Average after-call work time. This metric tracks the average time agents spend completing necessary post-call work. If it gets too high, it could indicate a problem in the availability of tools or resources, or it could indicate inefficient or burdensome paperwork.
  • Occupancy rate. Occupancy rate measures the time contact center agents spend on calls or completing related follow-up work. If the occupancy rate is low compared to the agent's total logged hours, it could mean that there is too much to do outside of providing customer service.
  • Customer satisfaction. Based on surveys, call recordings and evaluations, this metric measures and tracks the percentage of customers who are satisfied with their experience. Your customers are often the best source of information about their satisfaction.

Creating a quality assurance framework for call center operational efficiency and productivity

Once your organization has set its metrics, you will have the data that forms the foundation for improvement. But even when you know what to measure and how to measure it, you still need a method for analyzing and calculating call center operational efficiency.

This starts with choosing a quality assurance team. Members should come from across the organization and represent leadership, managers and call center agents. The team should create a quality assurance framework that defines quality for different operational outcomes and decide which group—customers, regulators or advisers, for example—judges that quality. A quality assurance framework should also address other factors that affect quality, who improves quality, how quality should be improved and how the organization defines success.

Optimizing contact and call center operational efficiency

With your metrics and quality assurance framework in place, the entire system can come together.

Efficiency metrics do not work in a vacuum. If excessively long hold times are sinking your customer satisfaction scores, that data point should affect average time-in-queue targets. Bring down the average time-in-queue figure, and your customer satisfaction scores might perk back up.

If agents need to boost productivity, they might need new tools, like updated infrastructure and better search and collaboration tools. Target contact center technology that supports customer engagement and breaks down silos that prevent or slow issue resolution.

Contact center success also goes well beyond numbers and analytics. Burnout and turnover are major barriers to productivity, and they feed into each other. Offload needless work from agents by generating the resources for customer self-service wherever possible.

Do not micromanage employees; look for ways to increase their decision-making authority, and track job performance metrics after the fact. Learning management systems, which automatically track and manage goals, can help train agents.

And even with a wealth of data to collect and analyze, it is important to remember the power of soft skills. Empathy, tone and active listening are hard to measure or quantify, but they are essential to a great customer experience.

Your customers are potentially your company's greatest advocates. Ensuring contact center operational efficiency and productivity is a key step toward improving their experience and ensuring your success.

Discover how Verizon's contact center solutions can unlock agility, efficiency and innovation.