Most organizations use the average or the mean for their metrics. This is common, convenient, and easy. But, the average doesn’t describe the experience of the individual customer.
PS: Go here if you’re interested in other articles on Queueing Theory.
Suppose you run a call center or contact center. Assume the following measures for Average Speed of Answer (ASA), which Â is a common call center metric that is supposed to measure how long a customer has to wait on the telephone before a customer service representative answer the customer’s phone call:
- Target: 60 seconds
- Average ASA: 57 seconds
Most managers would say that this call center is doing just fine. But is it?
Here are the other numbers:
- Shortest Wait or Fastest ASA: 31 seconds
- Longest Wait or Slowest ASA: 85 seconds
- Standard Deviation: 11 seconds
Given the above measures, we know the following according to the axioms of the normal distribution:
- 68.3% of calls will be answered within 57 seconds (+/-) 11 seconds
- 95.5% of calls will be answered within 57 seconds (+/-) 22 seconds
- 99.7% of calls will be answered within 57 seconds (+/-) 33 seconds
Metrics, The Mean: Applications
Beyond the call center, where else might customers wait for service or for product? Think about the specific processes that you are involved in, whether they be software engineering, project management, in a hospital – wherever there are queues or waiting, the example above can be applied.
What The Customer will Feel and Remember
We must keep in mind that the customer will not remember “an average experience”; the customer will remember usually the BEST and the WORST experiences he or she has had with a company, product, or a service provider. The average or the mean, as a measure of customer experience, isÂ inadequateÂ by itself. We must also include the standard deviation, for that will give us a better picture for what the individual customer might be feeling.