Contact Center Economics 101: First Call Resolution – It’s Not Only a Quality Metric


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BenchmarkPortal, The Source For Call Centers

I consider First Call Resolution (FCR) the “magic metric” for call centers, because it has impact on both quality and costs.

Most managers concentrate on the quality side of FCR, and for good reason. Our statistical studies show that FCR correlates with customer satisfaction. It is very easy to understand, intuitively, why customers are happier when they can resolve their issue with their first call.

Call Center EconomicsOften ignored, however, is the impact on contact center economics. Relatively few managers do the math to understand how improving their FCR can help the bottom line, and help them justify needed investments. While an in-depth analysis of a particular center requires considerable customization, the following is a short primer for inbound customer service/tech support centers that will help you to begin wrapping your mind around this issue.

First, calculate your average cost per call. As an initial cut, simply take your entire budget (include all direct costs) and divide by the number of calls taken; let’s say the cost is $8.00 per call.

Benchmark your FCR against that of your industry. If your FCR is 65% and your industry’s average is 75%, then you know your window of opportunity for improvement is, at least, 10%, to be on par with the average for your industry.

Next, determine how many calls, on average, are needed to resolve issues that are not resolved on that first call. Our studies show that 1.5 is a reasonable estimate.

Pulling things together, here is a sample situation:

A center handling 1 million calls per year with a First Call Resolution rate that is 10% below industry average is overspending on calls as follows:

  • 1,000,000 – calls per year
  • 10% – below industry average FCR
  • = 100,000 – calls unresolved the first time
  • 1.5x – multiplier (1.5 additional calls needed to resolve the issue)
  • 150,000 – extra calls per year
  • $8.00 – cost per call
  • = $1,200,000 – potential excess costs for the center

This is a powerful starting point for discussions about how to fix the problem. It also can become a numerator for calculations of ROI. Let’s say, for example, that your analysis indicates that an agent desktop Knowledge Management upgrade could eliminate the 10% negative gap. If that upgrade costs $400,000, the ROI on the investment would pencil out at 300% ($1,200,000 / $400,000). Similar calculations could be made for investments in training, technology, or process initiatives that will improve FCR. These will help convince your CFO that granting your investment requests will positively impact shareholder value. (Note of practical advice: You may want to cultivate a friend over in the bean counter department to work with you in this exercise).

Analytical calculations of this type are very important elements for inbound call centers, which are the focus of this particular article. Naturally, other departments, and centers of other types (sales, collections, etc.), will love improved FCR for other financial reasons that I will discuss in a future article. Do the math, then let the numbers do the talking. You will improve the economic outlook for your center while getting approval for the things you need to build a world-class operation.

Contact Center Economics 101” articles are written by Bruce Belfiore (Harvard MBA) to spotlight practical opportunities for financial improvement of contact center operations. If you are interested in discussing how to launch an FCR improvement initiative of the sort indicated above, contact Bruce at [email protected]

Copyright BenchmarkPortal 2014


  1. Walking past the downstream behavioral impact of unregistered problems and complaints, which is enormous, I’d respectfully suggest that, even more than FCR, it’s HOW the complaint was resolved that may be even more important. That is, is the degree of resolution (as perceived by customers), which can be positive, neutral, or negative. That’s a further financial analysis opportunity which can be easily layered onto FCR.

    In my presentations on customer-centric service, and reflecting similar client data from organizations such as TARP, I often cite the complaint management experience of a major bank. There was a profound difference on prospective behavior depending on how the customer saw their issue being resolved:

    – Positive Resolution (55%) – Future likelihood to do business with the bank, 87%; future likelihood to recommend, 91%
    – Neutral Resolution (25%) – Future likelihood to do business with the bank, 53%; future likelihood to recommend, 54%.
    – Negative Resolution (20%) – Future likelihood to do business with the bank, 21%; future likelihood to recommend, 17&.

    So, in addition to expedited call handling, the clear guidance for service training and operations is to, as much as possible, avoid negative and neutral issue resolution.


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