reducing variance in AHT

Six Sigma – iSixSigma Forums Old Forums General reducing variance in AHT

Viewing 8 posts - 1 through 8 (of 8 total)
  • Author
  • #52030


     I want to do a six sigma (green belt) project on reducing the variation of AHT (Average Handling Time) between agents.
    I havecollected base line data
    I have no idea how to start off with..
    Please suggest
    Thanks in advance



    If AHT is the response variable, what is it a function of?  Start their and understand the controllng or explanatory varialbes.  Then collect more data on how those explanatory variables are impacting the response variables.
    Hope this helps….gt


    Ken Feldman

    As Helper suggested, you need to identify the variables impacting variation. Is it the experience of the agent? Is it the type of call? Is it the type of customer calling in? Is it affected by geographic or demographic variables. What are the ones with low variability doing differently than the ones with more variation?



    Here are a few things you should be looking for
    1)Co-Relate the KPI scores for Service reps with high aht & low aht , I would probably look at Quality Scores & FCR Scores 2) If you are a Tech Support Queue you need to ensure for any given customer query all the reps are following the same Fix 3) For that you need to ensure that all your support personnel are calibrated on what needs to be done in case of Issue Type A or Steps to be followed & Any deviation on the same needs to be trackedLet me know in case you need any help



    We had a similar issue with our semi tech process.
    We did a NVA analysis and were able to reduce the
    AHT by 20%.



    Forgive me if I seem a little contrary to the other responses (all of them good responses) but are you sure average handling time is your problem? The other responses presume that you have done the prerequisite gathering of voice of customer to find out what your customer is concerned about. Maybe your cusomers are fine with the amount of time it takes to fulfill their requests, but they are mad at the number of mistakes made (just an example).
    I always start with the “practical” question first. What is broken about your process? Hopefully you have already done that and your findings point to AHT as an area of concern. If so, you have been given some good advice so far to get you started. (One more thing, maybe the average is fine but there is a lot of variation between agents and that’s the real problem. Just another thought to illustrate my point.)
    I just didn’t want to overlook the obvious questions first.



    I agree with the other replies, but still wonder why you’d focus on AHT.  As previously indicated, it can be influenced by so many factors, which in and of themselves are difficult to measure. 
    In my experience, AHT is a better metric for staffing, but not for performance.  FCR seems to be the best for performance measurement.  For example, if a customer calls twice about a single issue and spends 60 sec per call, then the AHT looks good at 60 sec.  But the customer may be upset for having to call a 2nd time.  Had it been resolved correctly the first time, the call may have been 90 sec. – Higher AHT, but better FCR, customer sat, and lower costs by reducing the overall call volume. 
    In fact, I believe AHT is not only misleading, but can be dangerous if it’s used to measure performance.  Making call agents accountable to an AHT standard encourages bad behavior like transfers, hang-ups, and not fully resolving their issue.  AHT is easier to measure on every call so it generally considers population data; however, FCR is usually only on sample data so the risk is in the agent’s favor to not resolve the call since it will have more impact on improving their AHT then it will on hurting their FCR.
    Finally, every repeat call for an unresolved issue requires standard info like routing thru the IVR, authentication, etc.  However, I believe if we spend just a little more time resolving their issue properly on the first call (which increases AHT), you’re avoiding those repeat processes (like authentication) and will increase your FCR, reduce your call volume, and ultimately reduce your agent staffing (which AHT was designed to help measure anyway).



    What did your data tell you? Are the average times between agents different?
    If you have collected data on handling time for several agents, you can start with a one-way ANOVA to test your hypothesis. This will give you insight as to whether your AHTs are different or not. Test for equal variances as well.
    I agree with another poster that you should be concerned with more than just the mean time for agents.

Viewing 8 posts - 1 through 8 (of 8 total)

The forum ‘General’ is closed to new topics and replies.