Benchmarking has been popular for at least twenty years. However, if the wrong items are benchmarked or the result is inaccurate, bad data is actually worse then no data because it leads the organization to pursue the wrong goals, move in the wrong direction or at minimum, wastes resources.

Examples of Bad Benchmarking

There are some obvious examples of benchmarking errors but some are more subtle. While the following examples draw heavily from the customer contact environment, the lessons apply to all benchmarking.
A company decided to focus on the best (lowest) metrics for average speed of answer (ASA) and talk time. It ended up devoting headcount to answering quickly but then rushing people off the phone. Further, the mechanistic responses resulted in incomplete answers, frustrated employees and higher turnover that caused even more demand to throw partially trained employees into the breech which resulted in even worse answers.
Closer scrutiny of the data found that the companies that were benchmarked had less complex calls due to a different mix of products and a different approach to welcoming new customers.

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