Thursday, October 13, 2011

Quick & Easy Lessons from the Consumer Call Center Data Book - by Jay Cremins & Sarah Outslay

Recently, one of our benchmark participants was asked: “Why were you interested in participating in this benchmark?” Their reply was superb: “So that we can move toward more common definitions” … and answer “where we are weak or best.”

The reply was superb because improving continuously, as required to stay relevant in today’s business environment, is impossible if you fail to discover best in class practices, ideas, and processes to implement. In this particular case, the benchmark was consumer call center oriented.

Using examples from the consumer call center benchmark as a model, the remainder of this document will dissect two key facets of the reply: “common definitions” and “weak or best.”

Common Definitions

Industries are different … companies are different … business units are different … call centers are definitely different. Complexities include managing consumer-facing call centers, dealer-facing call centers, mixed-purpose call centers, a combination of two, or a combination of three. There is only one way to appropriately compare practices. Collaborating among peers to develop and agree upon common definitions.

In our recent consumer call center study, the OEM participants had highly variable consumer-facing Average Handling Time (AHT). This data was misleading.

It was not the AHT that was widely variable; rather, it was each firm’s definition of AHT that was widely variable. Collectively agreeing on a common definition allowed valid comparisons and meaningful analysis, such as the correlation between overall satisfaction and phone AHT:

Based on the data reported by participants, the correlation between reducing AHT and increasing satisfaction is tenuous. Lesson learned: AHT matters; but, it is not a primary driver of consumer-facing satisfaction.

Weak or Best

Prior to this benchmark, OEM B believed that they managed attrition at a best in class rate:

Because they chose to be subjected to outside comparison, they are now aware of opportunities to improve – and have a peer from whom they may learn how.

OEM B also discovered opportunities to improve a high level corporate goal: consumer-facing satisfaction.

Based on the study data, consumer-facing satisfaction does not correlate with:
  • AHT (see above)
  • ASA – Average Speed to Answer
However, analysis of the benchmark data indicates that consumer-facing satisfaction does correlate with:
  • Case load per agent
  • “Quality Performance” metrics
Lesson learned: AHT and ASA matter; but, case load per agent and quality performance metrics correlate with consumer-facing satisfaction.

These examples, all from the call center benchmark data book, highlight how we all use benchmarking as a fundamental strategic process “so that we can move toward more common definitions” … and answer “where we are weak or best.”

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