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Rick,
I think that this is a good discussion and while there may still be some disagreement in regards to terms and measurement methods, we are very much in agreement in regards to the fallacy in managing purely by statistics, as reflected in your last paragraph meeting (arbitrary) performance targets such as answer rates doesnt tell much, if anything, about the quality of service and about customer satisfaction. As you state in your previous post is your current SLA meeting your customers expectations?
The reason why there is a relationship between service level and answer rate is simple. The formulae proposed in previous discussions were:
Answer Rate (AR) = Call Answered (CA)/Calls Offered (CO)
Service level (SL) = Call Answered Within Service Level Window (CSL)/Calls Offered (CO)
By definition, total call answered is the sum of calls answered with in the service level window and those answered later (CX): CA=CSL+CX. Therefore:
AR = (CSL+CX) / CO
SL = CSL / CO
And the ratio between the two is CSL / (CSL+CX)
The point is merely that within a *single* call center there will be (an average) fixed relationship between answer rate and service level. Intuitively, because both answer rate and service level deal with sub-groups within the answered calls, there will be a relationship between the two, determined by the number of calls answered within the service level window (and abandoned calls, if you decide to factor them in). Again, this is for a given call center if you meant to suggest that one cannot generalize this behavior and induce one metric from the other I agree.
I am not sure that I agree with the use of standard deviation as a correlation coefficient. Standard deviation measures the variance in sample or population data, and while it is a very important statistical tool, it doesnt imply correlation (or lack thereof) between sets of data.
Finally, if I read your reply correctly, you compare STDEV in answer rate, which is expressed as a percentage, and STEV in ASA, which is expressed in time units (presumably seconds). This is not a valid comparison (STDEV measures the level of spread around the mean and is always expressed using the same units of the sample data).
You said:
the amount of time your customer will hold has a direct correlative relationship to the amount of time they have to hold and or the severity of their issue this sounds like plain tautology although I think I understand what you meant
This discussion may be going into a level of detail that might make it less useful for many. In summary, however, it does demonstrate that call center metrics, if taken seriously, can be fairly involved and that back of an envelope calculations may be risky if one doesnt fully understand the alternatives and subtleties. The, lack of standards and common analysis methods only worsen the situation. I hope that this discussion helped others in seeing it.
Thanks for your thoughtful comments and good discussion points!
Joe
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