Capability Analysis for ordinal data

Capability Analysis is only done for continuous and attribute (defects and defectives) and not on a rating scale like Customer Survey.
Better do the ordinal/nominal regression and determine the scales you want to cover plus the frequency.
 

You dont do Capability  on surveys….you would do it on the process you are surveying…..maybe do paretos on the survey data to find out where or what to improve…..
Does that help…?

Of course you can do capability on an ordinal scale such as a survey.  Find it in Minitab:
Stat > Quality Tools > Attribute Agreement Analysis
Use attribute agreement analysis to assess the agreement of nominal or ordinal ratings given by multiple appraisers. The measurements are subjective ratings by people rather than direct physical measurements. Examples include:
·    Automobile performance ratings
·    Classification of fabric quality as “good” or “bad”
·    Ratings of wine color, aroma, and taste on a 1 to 10 scale
In these situations, quality characteristics are difficult to define and assess. To obtain meaningful classifications, more than one appraiser should classify the response measure. If the appraisers agree, the possibility exists that the ratings are accurate. If the appraisers disagree, rating usefulness is limited.
As an output you can also get Kendall’s coefficient which is used for ordinal data and measures the degree to which people miss.  Check it all out.

Tony,
We used this in a situation where we were having managers evaluate their people on a subjective evaluation scale that was used to judge a portion of the compensation. We did a MSA on the ordinal data which in essence was a capability of the measurement system (managers) to accurately and consistently judge people. Certainly a recipe for disaster. We found out that the system was not capable of adequately evaluating the people. We did a lot of work to improve the repeatability and reproducibility through scenario writing and calibrating the managers as to what each number on the scale means. While not a classic capability study yielding Cpk it was a way of assessing the capability of the measurement system.

Actually, the tests you mention in Minitab are not Process Capability tests for ordinal data, but a revised version of the Attribute MSA that was in previous versions.  The tools are used to tell us if we can rely on the measurement system being used (such as in a survey where you might have ratings such as Bad, Good, Great, or something like that). 
For ordinal data, the best thing to do is to make a determination as to what level in the scale is acceptable to you and your customers, and strive to make improvements in the areas where you are below either on average or on median.  I like to use the median value instead of averages for survey type data.