A guide to contact center benchmarking

Creating best practices in a vacuum. During a benchmarking exercise, contact center A, which devotes 10% of its contact center agents’ time to ongoing training, determines that a leader in the same industry, contact center B, devotes 5% of its contact center agents’ time to ongoing training. Since ongoing agent training undoubtedly factors into cost per call, contact center A decides to also establish 5% as a target. But just because that 5% number works for contact center B does not mean it will also work for contact center A.

A deeper analysis indicates that contact center B recently implemented a new desktop system that had automated process management features, which streamlined processes. It also had an extensive knowledge database in place, which put key information about products and support at agents’ fingertips. Both technologies reduced the need for agent training.

Training can influence virtually every common KPI, including first call resolution and average handle time, but so can systems such as the one contact center B implemented. So if contact center A creates a new training “best practice” in a silo and doesn’t have an equivalent desktop system, measures of customer experience are likely to be negatively affected. A more informed response contact center A could take would be to consider implementing an improved desktop system that in turn might also reduce the time required for ongoing agent training, thus making a number closer to the 5% ongoing training rate more realistic.

The takeaway: Consider how support systems and other variables in the contact center influence what determines a best practice.

Contact center leaders need to understand that some best practices that bring success to one organization may not qualify as a best practice for another.

Cherry-picking key metrics. During a benchmarking exercise, contact center A, which has an agent average handle time of four minutes and an interactive voice response (IVR) completion rate of 10%, used two other company’s contact centers in the same industry to determine the best standalone targets for these two contact center metrics. Contact center A found these results:

• Contact center B’s agents have average handle times of three minutes and an IVR completion rate of 5%.
• Contact center C’s agents have average handle times of five minutes and an IVR completion rate of 50%.

Contact center A then used these numbers to establish KPIs that called for an average handle time of three minutes and an IVR completion rate of 50%, because it considered these numbers “best practices.” Deeper analysis reveals a more complex picture. Assuming a total of 1,000 calls go into the IVR at both companies and that the goal of each company is to minimize labor expense, Contact center C has better overall results as measured by the number of minutes that agents require to interact with customers. Contact center B requires 2,850 minutes of total handle time (950 agent calls at three minutes each) to interact with customers, while contact center C requires 2,500 minutes of total handle time (500 agent calls at five minutes each) to interact with customers. 

While setting aggressive goals of three minutes average handle time and a 50% IVR completion rate might seem beneficial, are they realistic?  For most organizations, having a higher IVR completion rate results in higher average handle time because agents often handle more complex calls.

The takeaway: Examine relationships between key contact center metrics and other data points.

Overlooking differences in measurement practices. During a benchmarking exercise, contact center A, which has a 6% call abandonment rate, determined that contact center B, part of a company in the same industry, has a 3% abandonment rate and therefore establishes 3% target as a KPI because it is a “best practice.”

A deeper analysis identifies a key difference in the calculation of abandon rates. Contact center A factors into its abandon rate calculation of all abandoned calls, regardless of when they occur. In contrast, contact center B does not factor in calls that are abandoned in less than five seconds (a common practice). This difference accounts for contact center A’s additional 3% of abandoned calls, and subsequently, its 6% abandon rate.

The takeaway: Understand the differences in how various items are measured.

Contact center benchmarking allows companies to determine how to improve processes and results by analyzing how other organizations perform similar functions and processes. But benchmarking cannot be performed blindly with the assumption that a best practice at one organization will have the same results at another. Instead, contact center benchmarking must be executed with acute awareness of the complexities that influence any given metric.