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About AnishMohandas

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  • Name
    Anish Mohandas
  • Company
    Commercial Bank International
  • Designation
    Business Excellence/ Lean Specialist


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  1. Hi, I am planning to implement lean six sigma project to reduce TAT in complaint management but i am bit confused on my data collection part. Should i collect data to see how many times we have not met the TAT i.e. defectives or should i consider the complete TAT details for the project. My only question here is 1. Should i go with continuous data or discrete? which one will give me a clear picture of the problem Regards Anish
  2. Hi all, What is box - cox transfromation ? Why are we converting the non-normal data to normal data when we are having non -parametric tests to perform analysis. Please let me know if it necessary to convert my data to normal when it is non normal. Regards Anish Mohandas
  3. Sir, I have attached the sample data for reference. I want to know if i should use No: of calls escalated( count of calls that did not meet the FCR - No: of defects / day) or FCR % for my data analysis. Is there any possibility of using MSA here, the data is collected from the online tool.If yes, then how should i proceed. Can i use 2 sample t test here to see if there is a significant difference in the FCR during week days and week ends( by taking count of FCR as continuous data) or should i use chi square by considering my defects as discrete. Thanks in advance Regards Anish Mo
  4. Hi , We are planning to implement a six sigma project on improving first call resolution. This is one of our primary metric for help desk performance.Now, my question is about data type. Currently , we are calculating FCR as no: of calls escalated to level 2 support for resolution which means my data wil be ( 3, 7, 8, 11,2 ,1,0).Should i convert this in to percentage( 78%, 38%, 24%, 36%) by considering my defects as no: of calls escalated to level 2 support and my opportunity is no: of calls i.e. FCR % = (No: of calls escalated to level 2 support / total no: of calls ) * 100 Which one is mo
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