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Call Center Process Sigma Calculation

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  • #23810

    Gadgil
    Member

    Hello,
    I need help in deriving the process sigma. We have several processes, most have more than 1 CTQCs. For example, a)our e-mail processes have Fatal error accuracy which has LSL 95%, b)SLA, that says 80% of e-mails received should be answered within 4 hours c) Staffed hrs, which is the most crucial since we bill our clinet on staffed hrs. so we need it to be as close to 100% as possible.
    Based on the performance on all the above attributes, how can I derive process sigma? Any help will be welcome.

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    #57007

    Szentannai
    Member

    Hi Vinayak,
    there’s a method of calculating one sigma value for these processes, but I’d say that there is no real advantage in rolling the three separate sigma values into one.
    Anyway, the idea is to calculate the DPUs for each process, add them together and divide them by the sum of the  number of defect opportunities  for all the  processes to get a sort of average DPU. Then calculate a DPMO from this and calculate the sigma from the DPMO.
    But again, this will probably only obfuscate any knowledge you have of your processes rather then clarify it.
    Regards
    Sandor

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    #57024

    Norbert
    Participant

    Hi Vinayak,
    if I understood your case correctly, i see 2 processes involvolved: email processing (correctly and timely) and logging of staffed hours (accurate). Thus I recommend using at least 2 sigma calculations, if not setting up 2 distinct six sigma projects.
    In the first case, the unit would be an email with 2 defect opportunities: non-accuracy (to be defined) and response time > 4hrs. If you want to take the LSL for accuracy  into account you could use for example weekly ratios and define a week below 95% error accuracy an error. This however reduces the granularity of you information.
    The second one is a bit more challenging. You will need a measurement to compare your data with in order to define a defect and calculate sigma. I think a sort of valitating or benchmark measurement would be helping. Like comparing billed hours with time card entries or time stamps in the call center system and to set “alarm thresholds” to identify defects. Another possible way might be to conduct an ongoing gage R&R study to gather data. Just an idea.
    I hope that I could help
    Norbert

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