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      I am working as a Team leader in ITES industry in India. We areactually working on a DMAIC(green belt) project to improvize the communication skill of the agents. We are currently running at 85-90%. Our goal statement is to improvize the communication skill to 97% in next 2 months.We have actually a problem in analyzing the Csat data and finding out the root cause.Let me explain how the Csat survey form looks like:Questions asked to the customer:1. Is your problem resolved?2. Was your problem resolved in your first call?3. Technical knowledge of the agent.4. Soft skill of the agent.5. Overall satisfaction.6. Other comments.On the softskill parameter if a customer gives us a rating of 1/2 it isconsidered as good and 3/4 is bad.We have done a agentwise analysis for the last two months and arrived at a which consists of the number of feedbacks received by the agent and the number of Negative feedbacks that he has received on communication skills.Then we have drilled down the communication skill parameter to(based on customer comments):1. Negative on accent2. Negative on pacing3. Negative on sentence structuring4. Negative on active listening5. Negative on clarity of speech6. No reason specifiedMost customers have not specified any reason for marking the agent down for his communication skills and seconly many of the customers have marked down the agent because of the accent problem.So we thought the root cause of the problem is “Accent”.But we did a Pareto chart and found that if we have to reach 97% we have to take care of all the top 5 issues and accent only.Now, the question that I have is:The data what we have is that a continuous data or discrete data?If it is a continuous data will it be possible for us to normalize the data using MinitabAre we proceeding in the correct direction in data collection plan toidentify the root cause?We have also found a correlation that 92% of the customers who have told that his issue is resolved have not marked the agents down for soft skill. About 68% of customers are not satisfied with the communication skil of the agent and their issue remains unresolved.So, here do we have to actaully concentrate on resolution to improvise the communication skills.  And by doing that can we reach 97% ?Thanks for your time.Regards,Kiruba.


    Arne Buthmann

    Hello Kiruba: Before I am in a position to answer your questions I’ve some additional questions: – How do you know that the communication skill is running at 85-90%? Since you write that 68% of your customers are not satisfied with the communication skills of the agent, I don’t understand where the 85-90% come from and how you’ll measure 97%? – Why are you concentrating on communication skills? From a ustomer point of view, it seems to make more sense to focus on better resolving their problems (especially if 68% of your customers say that their issues remain unsolved)? – Do you want to improve the communication skills of your agents or the customer ratings of your agents’ skills? Both might have different root causes. Since you write that you will maybe concentrate on problem resolution to improve the communication skills, it looks more like that you want to improve the ratings rather than the skills. – Why do you want to normalize the data with Minitab? Normalizing data only makes sense, if you want to use a tool or statisitc procedure that requires normally distributed data? (But since “customer ratings (1-4)” and “the number of customers that give a particular comment on the agents’ soft skills” are discrete data normalizing data with Minitab will be impossible, anyway) Maybe you can answer my questions to help me better understand your stuation. My intial comment on your question is that drilling down negative communication skill ratings in order to identify root causes makes much ense. But since most of your customers did not specify their ratings you should ask (maybe a sample of) the customer again why they negatively rate your agents. On the other hand, I don’t think you have to consider all 5 issues since some of those reasons may also be part of the “no reason specified” group. If your’re interested in improving the skills (not only the ratings of the skills) you should think about additional methods to better identify the root causes (like videotaping agent-customer interactions or role-playing plus additonal ratings maybe by colleagues) 
    I’m looking forward to hearing from you!   Arne      



    Hi Arne,Thanks for your time in giving me such a
    elaborate reply.The reason why we are concentrating on
    communication skills is that the expectation
    from the client as of now is a communication
    skill percentege of 97%. i.e., Out of 100
    customers who reply back to the email survey
    form 97 should rate the agent as 1 or 2 in the
    4th question that’s been asked to the customer.As you rightly pointed out we are trying to
    improvise the cutomer ratings by improvising
    the skills of the agents on the floor ( So
    ultimately its about improvising the agents skill
    to improve customer’s experience )As of now we are running at a Communication
    skill percentage of 90 % i.e., Out of 100
    cutomers who reply back to us around 90% of
    the customers give us a good rating on
    Communication skills(1,2).Also the first question that we ask the customer
    is ‘ Is your problem resolved?’ where marking 1
    indiactes resolved and marking 2 indicates
    customers issue is not resolved.So, when we apply a filter in Excel and select 1
    and for which select 1&2 in Question 4 it it
    results in 92%. Similarly, when we select 2 for
    question 1 and see the dissatisfied customers
    in communication skill(3,4) rating it comes to
    68%.Also, out of 10% customers who are not
    satisfied with the communication skill, when we
    analysed th data with a pareto chart 90% are
    because of accent issues. predominat factor
    when compared with pacing, clarity of speech
    etc.,). So, even for the customers who have not
    given us the reason as to why they have rated
    the agent bad we have taken it for granted that it
    should be primarily b’coz of accent issues. Hope this clarifies.Regards,


    Arne Buthmann

    Thanks for clarifying my questions.
    So, I think you’re on a good track with analyzing the data. Some ideas I have in order to improve your agents’ soft skill (ratings) are:
    –         If possible, ask a sample of customers why they rated your agents soft skills down (as well as why they rated them up!): Why is accent a problem for the customer? What can you / your agents do to better satisfy your customer needs. I think, your customer data base (only the responses to your Csat survey) is not enough. Try to clarify the CTQs: When do you and your customer agree that your agents’ accent is good?  etc.).
    –         Maybe use a fishbone diagram or the 5-Whys-technique to deeper analyze why accent is a problem for the customer (One hypothesis I have is that accent is not the ‘real’ cause but rather the most obvious and, thus, rated one.) You might get additional ideas how to solve accent problems, especially if you find out that it is difficult to improve somebody’s accent.
    –         Conduct simulations (role-playing) of different agent-customer situations (especially those where the agent has difficulties to solve the customer’s problem). Have other agents rate and analyze soft skills of the role-playing agent. You should get a better picture of what goes wrong and how to improve.
    –         Finally (as you already mentioned) improve the agents’ problem solving skills. This will actually not improve your agents’ skills themselves but maybe the ratings and – what is most important – customer satisfaction.
    For any questions, don’t hesitate to ask me. Unfortunately, I can’t provide an ITES study.
    Kind regards
    Arne Buthmann



    I had the same question and your answer was very efficient. Thank you very much.

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