Calculating Agent Productivity in Complex Call Center

Six Sigma – iSixSigma Forums Operations Call Centers Calculating Agent Productivity in Complex Call Center

Viewing 4 posts - 1 through 4 (of 4 total)
  • Author
  • #55459

    Rik Webb

    Good evening.

    Great forum you all have here. Lot’s of good info. I did try looking through previous posts to get an answer but could not find what I’m looking for.

    I’m now managing a call center with hardly any agent productivity measurements or guidelines in place. Our historical reporting tool gives a very basic occupancy measurement, but the issue is there is much more going on in this center than just taking inbound calls. It also factors in ACW time which I’m just not comfortable with at the moment.

    Inbound is a big piece of the puzzle, but there is lots of manual outbound calling, a manned dialer that runs daily, and quite a few random projects that take people off of the phones. Which is part of the issue. People can go into random AUX codes like project and it’s hard to tell exactly how ‘productive’ they were during that time. I’m new but I’m assuming a revamping of how/when AUX codes are used is going to be one piece to the puzzle.

    I know some places count ACW and/or certain AUX time in their productivity numbers and maybe we will at some point, but since it’s the AUX/ACW wild wild west at the moment, I started looking at what I feel is maybe a good baseline to being with:

    ACD Talk Time + Outbound Talk Time + Dialer CONNECT Time + Ring Time / staffed hours. I’m also good with including Available Time as well if that makes more sense. My thought with this was to identify what percent of each day each agent is actually on the phone speaking with a customer, and ignoring all the other noise going on. Any thoughts on that?

    Then at some point real soon I would think we need to get our AUX codes reworked and management on all the teams on the same page on when to use them, how to observe and follow up to properly monitor. When comfortable with that, somehow factor in certain AUX time into the final productivity number? Some ACW time is necessary, but is there a way to factor in an average benchmark amount of time into final productivity numbers, rather than actual numbers?

    Sorry this turned out so long. Any thoughts on all of this or even just certain portions of it?

    Rik W.



    Beware of composite metrics. They tend to confirm that there’s a problem but give little or no insight into the causes. I would identify and isolate the critical variables, work on improving the one that’s agreed is most critical, then move on to the next. You won’t tame the wild wild west by trying to address everything at once.


    Rik Webb

    Thank you, good feedback. I’d love to come up with and implement the magic formula right off the bat, but yes it is complicated especially with different departments doing different tasks. Your suggestion may be the much more practical way to go about this, for now at least, so thank you I’m going to give that serious consideration.


    Jeff Marth

    Sounds like you have a few issues; one of those annoying “other” categories, and a no defined list of what deliverables the staff produces.

    Sounds like the problem you are trying to address is lack of clear information on what is happening with the staff, in order to make good allocation decisions. That sound about right?

    A little more granularity can be good, but can also overwhelm people with options, resulting in them picking the wrong one and leaving you in no better of a situation. Perhaps break down the codes by groups or teams to make them more specific to the area, without causing a data nightmare for you.

    Could also be worth investing in some discussions to list out what each team produces as a quantifiable deliverable. You can then use the time for each time to determine how productive they are at their deliverables.

    Starting in an area where there are no good metrics is always tough, but I commend you for recognizing the need to have good data in order to make good decisions!

Viewing 4 posts - 1 through 4 (of 4 total)

You must be logged in to reply to this topic.