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Control charts

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  • #52959

    ABC
    Participant

    Hi,I’m doing a CSAT project for a bpo. I’m little
    confused with the result of my control chart and the
    process capability of our process.
    I took the weekly CSAT score(average score for the
    week) for 25weeks(Number of surveys in each week
    fluctaute). I used Xbar chart, the UCL = 1.114 and
    lCL = -0.222(as per minitab).The mean is 0.446.The
    process capability is 1.10. Does this mean my
    process is stable? Although we have missed the
    target of 52% many times in the 25 week sample. Am I doing something wrong? Can someone suggest if
    Xbar chart is the right option in this case.
    Please help me with the LCL and UCL calcualtion as
    im confused with the formula used in minitab.

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    #187007

    newbie
    Participant

    Process capability has no relationship to process stability.  Stable processes are those that contain common-cause only variation. This is evidenced by a control chart that depicts all data points randomly dispersed around the mean and within the control limits.  If you are using continuous data, you should be using a Variability Chart with your Xbar Chart (ie R or S chart).  You would want to confirm the variaility within your subgroups (ie R or S Chart) is in control before you can reliably assess the variability between your subgroups (X Chart).  In terms of using a non-standard subgroup size, you want to check into how that might effect your chart.  Good luck.

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    #187008

    StuW
    Member

    abc,
    Don’t confuse control and capability concepts as they are distinct concepts!  
    Control charts assess stability and whether, in this case, your 25 weekly CSAT readings represent a consistent process, with a mean of about 0.446.  Check the chart.  Does it show trending, either up or down, or any other evidence of non-stable behavior?  Are there any outliers, obvious points above or below the control limits?   If I assume correctly, and these CSAT values have a min of zero and a max of 1, then there is enough variation in these weekly readings to encompass your entire range.  It sounds to me like you should be using an Individual X-MR type chart based upon the inputs provided, so use that with the average weekly results, and see if the chart changes.
    Capability refers to the ability of a process to meet limits which are typically imposed from outside, usually by a customer.   In this case, that probably does not exist, and the capability indices are potentially meaningless.   If artificial goals are applied, such as having a reading of 0.52, or higher, than the result should be phrased something like, “the data show X% of weekly readings were above the goal”.   The analysis should then focus on what drives these readings to be higher, or lower, and assessing the reasons for low CSAT scores from customers.     
     

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    #187091

    Jonathon Andell
    Participant

    What is CSAT? Your sampling and subgrouping schemes may warrant further consideration – if you have significant sources of variation within your subgroups, the chosen chart may be hiding crucial information. Can you tell us a little more about your data?

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    #187095

    Darth
    Participant

    Customer Satisfaction. Have a good one Jonathon.

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    #187099

    Jonathon Andell
    Participant

    Thanks for the acronym tutelage. I hope you are having a good year. It’s been a long time since I enjoyed working with you.Your response makes me wonder about the sub-grouping scheme even more. Questions for the original poster to this discussion board:1. How many surveys per week?
    2. What subgroup size do you use to compute control limits?
    3. How did you establish a specification limit?Using continuous-data statistics with survey responses is a little tricky. I am not convinced that X-Bar is the best choice, but I am willing to be convinced.

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    #187100

    Ashok
    Participant

    ABC – (I wish you could be a little more open than that, if only, with a surrogate name).I think you have over-simplified the development of your control charts and the conclusion. I also don’t understand how your center line will not be in the middle of UCL and LCL.
    First, the number of observations you used to take average over each week should be the same. Not only the sample size should be the same, even the future test samples should be of the same size. If your sample is 3-10, you can choose the value of A2 from statistical control chart constants and set the limits at grand average + and – A2*Rbar, where Rbar is the range average. if n >10, you can use use std devn of the individual /sqrt(n) and then set the limits at + and – 3 std devns if you like. You should also develop range charts using statistical constants D3 and D4. For the chart average line and limits to be meaningful, you need at least 25-30 weeks data – otherwise Normal distribution will not hold even for averages. In that case, you will need to use t distribution limits which are lot looser. These limits should also be subjected to process of reiteration until all-out of control points are gone. If the process is unstable, i ahve found that many times we do not get the final limits at all as the process of iteration keeps removing new points either from the xbar chart or the range chart.10, you can use use std devn of the individual /sqrt(n) and then set the limits at + and – 3 std devns if you like. You should also develop range charts using statistical constants D3 and D4. For the chart average line and limits to be meaningful, you need at least 25-30 weeks data – otherwise Normal distribution will not hold even for averages. In that case, you will need to use t distribution limits which are lot looser. These limits should also be subjected to process of reiteration until all-out of control points are gone. If the process is unstable, i ahve found that many times we do not get the final limits at all as the process of iteration keeps removing new points either from the xbar chart or the range chart.10, you can use use std devn of the individual /sqrt(n) and then set the limits at + and – 3 std devns if you like. You should also develop range charts using statistical constants D3 and D4. For the chart average line and limits to be meaningful, you need at least 25-30 weeks data – otherwise Normal distribution will not hold even for averages. In that case, you will need to use t distribution limits which are lot looser. These limits should also be subjected to process of reiteration until all-out of control points are gone. If the process is unstable, i ahve found that many times we do not get the final limits at all as the process of iteration keeps removing new points either from the xbar chart or the range chart.Once the limits are set, you should use both (Xbar and R) charts to establish process stability over 8 weeks. You should not only watch for outliers but their are at least 6 other rules (e.g., 8 consecutive points on the same side of central line) that need to be observed. Finally, you also need to rule out trend, oscillation, and population mix ups – for 8 weeks (rule of Student’s t distribution) – to conclude process stability. Process capability is a different thing altogether which just establishes that the process is capable of delivering the specs/requirement.
    Hope this helps.

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    #187106

    ABC
    Participant

    Hi everyone,Thanks so much for your help.
    We have five kinds of rating in our CSAT. Excellent,
    very good, good, below average and poor. These
    rating carries 2,1,0,-1 and -2 points respetively.
    To calculate the CSAT we multiply the survey with
    its corresponding value and divide by total survey.
    EX in a week we may get the following surveys: 5
    Excellent, 7 Very good, 6 good, 2 below average and
    2 poor.the CSAT is calculated as:
    (5*2)+(7*1)+(6*0)+(2*-1)+(2*-2)/22. The average
    score for the week would be 50%.We have surveys varying between 20 -40 per week.My aim is to reduce the variation in CSAT score, my
    findings sugest that its the SCR(single contact
    resolution) that drives CSAT so i’ve suggested
    measures to increase that which is related to the
    process. I also want to know is there any hidden
    factor that impact these scores, any trend that im
    not able to notice. Im pretty new to this six sigma
    concept so I’m wondering if Im using the right
    tool(control chart) here.As far as the control limits are concerned I
    calculated it using minitab and im still not
    convinced as to how these valuse are calculated.
    Would be great if any one of you can help me out
    with that too.Thanks again for all your inputs.Abc.

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    #187109

    Ted
    Member

    greetings abc.i suggest that you have a one on one with your six sigma coach/es to better understand this concept. there’s a plethora of available materials with great content about control charts. but in my observation,
    reading is not as much informative, interactive and fun when compared to a live discussion. the responses of the professionals here are helpful. but a forum has its limit – it’s like talking to
    someone on a one way radio. to better help you with your data preparation, minitab has a pdf download that tells you what particular
    control chart is applicable to your data. you can download it here.
    http://www.minitab.com/en-US/training/tutorials/method-chooser.aspx

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    #187111

    bbusa
    Participant

    I don’t think the Xbar Chart is the right tool to monitor CSAT scores . YOu need to study the subgrouping carefully. You may like to use the XmR chart . Process Capability and stability are entirely different . Also pl check your data for normality – of late there’s been a war on this subject , thoughBBUSA

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    #187114

    Darth
    Participant

    ABC,
    We have done this before in many applications. The easiest way is to define what you consider to be the best…that is, what would constitute a satisfactory score. We usually used “top two box” and then plotted a simple p chart using the number of surveys which received the top two ratings and divide that by total surveys. You are dealing with discrete data so taking averages, standard deviations and any other calculation based on continuous data is not right. In your case, I would have defined Excellent/Very Good as the top two box and thus had 12/22 or .545 as your proportion. Since the denominator will be varying week to week you can now simply plot a p chart. But, be real careful about reacting week to week. There are many variables contributing to CSAT so week to week variation is really meaningless.

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    #187117

    Jonathon Andell
    Participant

    abc, I am concerned whether this data fits with an X-Bar chart. There are a number of mis-matches: – Your “range” can be only an integer from 0 to 4. There really should be more “shades of gray” available.- Your “n” for subgroups makes me wonder whether you are using R-bar or S for setting control limits.- Using this kind of scale to track variation (instead of mean responses) can be dicey at best.You may want to consider an I-MR chart for the weekly averages. And as others have stated, don’t respond to a single week’s fluctuation unless the chart clearly indicates special cause variation. You may be unhappy with the wide limits an I-MR chart will give you. However, the narrow limits of an R-Bar chart with “n” between 20 and 40 could be causing loads of false alarms.

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