• @jashouri – OK. So I gave you 4 sub-process steps that you could form an excercise around. You can make something up (like some new office accessory) that everyone would understand, or use something pertinent to the class – such as breaks (when, how long, how to ensure compliance, how to measure, what makes a good break, etc.). 10 years, 2 months ago

  • @jashouri – what specific aspect are you looking to reinforce? You could be looking at a customer interview guide, the actual data gathering process, data synthesis post interviews, VOC quantification, etc. Your question seems to indicate that you believe that VOC is some simple one step process. 10 years, 2 months ago

  • @jashouri You still seem to be at a very high level. Do you have data on where, when or how they were sent? 10 years, 2 months ago

  • @jashouri – you might also want to Pareto the reason for the return. Your sales people have fewer than expected defects, so they are probably culling out non-productive customers, so find out why. 10 years, 2 months ago

  • @jashouri – This only shows that there is a statistical difference (at 95% CI) that there is a difference in expected levels vs. actual. You will need to figure out why using different tools (5 whys would be good here). If you have other by variables (such as month) then you may want to evaluate those similarly and see if there is anything that…[Read more]

  • @jashouri – what you did was exactly right. If you want to peel the onion further, you could split these up by relevant “by” variables (you indicate that month might be appropriate). 10 years, 2 months ago

  • @jashouri – Do you have just the 2 categories (auto and sales)? How many samples in each and how many defects in each? And you only count defectives, not defects (any return for any reason is a defective)?

    You’re probably good with a Chi-sq if the number of levels is low (2 categories with whole number sample size and whole number defects…[Read more]